rail_id run_acc study_acc sample_acc experiment_acc submission_acc submission_center submission_lab study_title study_abstract study_description experiment_title design_description sample_description library_name library_strategy library_source library_selection library_layout paired_nominal_length paired_nominal_stdev library_construction_protocol platform_model sample_attributes experiment_attributes spot_length sample_name sample_title sample_bases sample_spots run_published size run_total_bases run_total_spots num_reads num_spots read_info run_alias run_center_name run_broker_name run_center aligned_reads%.chrm aligned_reads%.chrx aligned_reads%.chry bc_auc.all_reads_all_bases bc_auc.all_reads_annotated_bases bc_auc.unique_reads_all_bases bc_auc.unique_reads_annotated_bases bc_auc.all_% bc_auc.unique_% bc_frag.count bc_frag.kallisto_count bc_frag.kallisto_mean_length bc_frag.mean_length bc_frag.mode_length bc_frag.mode_length_count exon_fc.all_% exon_fc.unique_% exon_fc_count_all.total exon_fc_count_all.assigned exon_fc_count_unique.total exon_fc_count_unique.assigned gene_fc.all_% gene_fc.unique_% gene_fc_count_all.total gene_fc_count_all.assigned gene_fc_count_unique.total gene_fc_count_unique.assigned intron_sum intron_sum_% star.%_of_chimeric_reads star.%_of_chimeric_reads2 star.%_of_reads_mapped_to_multiple_loci star.%_of_reads_mapped_to_multiple_loci2 star.%_of_reads_mapped_to_too_many_loci star.%_of_reads_mapped_to_too_many_loci2 star.%_of_reads_unmapped:_other star.%_of_reads_unmapped:_other2 star.%_of_reads_unmapped:_too_many_mismatches star.%_of_reads_unmapped:_too_many_mismatches2 star.%_of_reads_unmapped:_too_short star.%_of_reads_unmapped:_too_short2 star.all_mapped_reads star.all_mapped_reads2 star.average_input_read_length star.average_input_read_length2 star.average_mapped_length star.average_mapped_length2 star.deletion_average_length star.deletion_average_length2 star.deletion_rate_per_base star.deletion_rate_per_base2 star.insertion_average_length star.insertion_average_length2 star.insertion_rate_per_base star.insertion_rate_per_base2 star.mapping_speed,_million_of_reads_per_hour star.mapping_speed,_million_of_reads_per_hour2 star.mismatch_rate_per_base,_% star.mismatch_rate_per_base,_%2 star.number_of_chimeric_reads star.number_of_chimeric_reads2 star.number_of_input_reads star.number_of_input_reads2 star.number_of_reads_mapped_to_multiple_loci star.number_of_reads_mapped_to_multiple_loci2 star.number_of_reads_mapped_to_too_many_loci star.number_of_reads_mapped_to_too_many_loci2 star.number_of_reads_unmapped:_other star.number_of_reads_unmapped:_other2 star.number_of_reads_unmapped:_too_many_mismatches star.number_of_reads_unmapped:_too_many_mismatches2 star.number_of_reads_unmapped:_too_short star.number_of_reads_unmapped:_too_short2 star.number_of_splices:_at/ac star.number_of_splices:_at/ac2 star.number_of_splices:_annotated_(sjdb) star.number_of_splices:_annotated_(sjdb)2 star.number_of_splices:_gc/ag star.number_of_splices:_gc/ag2 star.number_of_splices:_gt/ag star.number_of_splices:_gt/ag2 star.number_of_splices:_non-canonical star.number_of_splices:_non-canonical2 star.number_of_splices:_total star.number_of_splices:_total2 star.uniquely_mapped_reads_% star.uniquely_mapped_reads_%2 star.uniquely_mapped_reads_number star.uniquely_mapped_reads_number2 junction_count junction_coverage junction_avg_coverage star.number_of_input_reads_both star.all_mapped_reads_both star.number_of_chimeric_reads_both star.number_of_reads_mapped_to_multiple_loci_both star.number_of_reads_mapped_to_too_many_loci_both star.number_of_reads_unmapped:_other_both star.number_of_reads_unmapped:_too_many_mismatches_both star.number_of_reads_unmapped:_too_short_both star.uniquely_mapped_reads_number_both star.%_mapped_reads_both star.%_chimeric_reads_both star.%_reads_mapped_to_multiple_loci_both star.%_reads_mapped_to_too_many_loci_both star.%_reads_unmapped:_other_both star.%_reads_unmapped:_too_many_mismatches_both star.%_reads_unmapped:_too_short_both star.uniquely_mapped_reads_%_both 254486 SRR060885 SRP002915 SRS085364 SRX023877 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565951: SUM159PT_CXCR2_inhibitor GSM565951: SUM159PT_CXCR2_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;SUM159PT|source_name;;cell line SUM159PT|supplier;;Dr. Steve Ethier, University of Michigan|treatment;;CXCR2 inhibitor GEO Accession;;GSM565951 GSM565951 SUM159PT_CXCR2_inhibitor 109304866 6429698 2011-09-08 07:38:24 87626349 109304866 6429698 1 6429698 index:0,count:6429698,average:17,stdev:0 GSM565951_1 GEO 1.4 5.49 0.38 85452678 97344905 27158816 37294888 113.92 137.32 0 0 0 0 0 0 27.08 85.51 14846591 1367106 14846591 1367106 48.35 79.47 14846591 2441025 14846591 1270645 16721914 19.57 0.00 0 53.65 0 14.01 0 7.47 0 0.00 0 0.00 0 5048459 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 462.94 0 0.00 0 0 0 6429698 0 3449619 0 900916 0 480323 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 24.87 0 1598840 0 0 0 0.0 6429698.0 5048459.0 0.0 3449619.0 900916.0 480323.0 0.0 0.0 1598840.0 78.5 0.0 53.7 14.0 7.5 0.0 0.0 24.9 254490 SRR060886 SRP002915 SRS085365 SRX023878 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565952: SUM159PT_PTGIS_inhibitor GSM565952: SUM159PT_PTGIS_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;SUM159PT|source_name;;cell line SUM159PT|supplier;;Dr. Steve Ethier, University of Michigan|treatment;;PTGIS inhibitor GEO Accession;;GSM565952 GSM565952 SUM159PT_PTGIS_inhibitor 174589218 10269954 2011-09-08 07:38:24 138747829 174589218 10269954 1 10269954 index:0,count:10269954,average:17,stdev:0 GSM565952_1 GEO 1.15 5.39 0.38 138102486 158931267 47007778 65569924 115.08 139.49 0 0 0 0 0 0 29.2 86.12 23399295 2383054 23399295 2383054 49.61 80.28 23399295 4048123 23399295 2221517 26415694 19.13 0.00 0 52.51 0 13.65 0 6.90 0 0.00 0 0.00 0 8160021 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 586.85 0 0.00 0 0 0 10269954 0 5392735 0 1401794 0 708139 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 8 0 26.95 0 2767286 0 0 0 0.0 10269954.0 8160021.0 0.0 5392735.0 1401794.0 708139.0 0.0 0.0 2767286.0 79.5 0.0 52.5 13.6 6.9 0.0 0.0 26.9 254494 SRR060887 SRP002915 SRS085366 SRX023879 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565953: SUM159PT_HAS1_inhibitor GSM565953: SUM159PT_HAS1_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;SUM159PT|source_name;;cell line SUM159PT|supplier;;Dr. Steve Ethier, University of Michigan|treatment;;HAS1 inhibitor GEO Accession;;GSM565953 GSM565953 SUM159PT_HAS1_inhibitor 200803966 11811998 2011-09-08 07:38:24 157542511 200803966 11811998 1 11811998 index:0,count:11811998,average:17,stdev:0 GSM565953_1 GEO 1.32 5.32 0.38 158600159 183304022 54469361 76255387 115.58 140.0 0 0 0 0 0 0 29.21 85.37 27012553 2737477 27012553 2737477 49.86 79.26 27012553 4673069 27012553 2541518 29334265 18.50 0.00 0 52.20 0 13.50 0 7.15 0 0.00 0 0.00 0 9372652 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 483.22 0 0.00 0 0 0 11811998 0 6165893 0 1594673 0 844673 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 27.15 0 3206759 0 0 0 0.0 11811998.0 9372652.0 0.0 6165893.0 1594673.0 844673.0 0.0 0.0 3206759.0 79.3 0.0 52.2 13.5 7.2 0.0 0.0 27.1 254498 SRR060888 SRP002915 SRS085367 SRX023880 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565954: SUM159PT_PFKFB3_inhibitor GSM565954: SUM159PT_PFKFB3_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;SUM159PT|source_name;;cell line SUM159PT|supplier;;Dr. Steve Ethier, University of Michigan|treatment;;PFKFB3 inhibitor GEO Accession;;GSM565954 GSM565954 SUM159PT_PFKFB3_inhibitor 197004551 11588503 2011-09-08 07:38:24 154848564 197004551 11588503 1 11588503 index:0,count:11588503,average:17,stdev:0 GSM565954_1 GEO 1.25 5.35 0.37 157381120 182332448 53336424 74362298 115.85 139.42 0 0 0 0 0 0 29.25 86.64 26719366 2720804 26719366 2720804 50.26 80.51 26719366 4674923 26719366 2528251 29197589 18.55 0.00 0 53.17 0 13.30 0 6.43 0 0.00 0 0.00 0 9302030 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 571.49 0 0.00 0 0 0 11588503 0 6161830 0 1541674 0 744799 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 5 0 27.10 0 3140200 0 0 0 0.0 11588503.0 9302030.0 0.0 6161830.0 1541674.0 744799.0 0.0 0.0 3140200.0 80.3 0.0 53.2 13.3 6.4 0.0 0.0 27.1 254502 SRR060889 SRP002915 SRS085368 SRX023881 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565955: SUM159PT_JAK_inhibitor GSM565955: SUM159PT_JAK_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;SUM159PT|source_name;;cell line SUM159PT|supplier;;Dr. Steve Ethier, University of Michigan|treatment;;JAK inhibitor GEO Accession;;GSM565955 GSM565955 SUM159PT_JAK_inhibitor 181068309 10651077 2011-09-08 07:38:24 143123521 181068309 10651077 1 10651077 index:0,count:10651077,average:17,stdev:0 GSM565955_1 GEO 1.55 5.26 0.32 142079309 168637867 47070749 67028719 118.69 142.4 0 0 0 0 0 0 28.6 86.7 24466158 2402946 24466158 2402946 51.02 79.86 24466158 4287312 24466158 2213452 24594032 17.31 0.00 0 52.87 0 13.75 0 7.36 0 0.00 0 0.00 0 8402814 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 412.30 0 0.00 0 0 0 10651077 0 5631312 0 1464292 0 783971 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 5 0 26.02 0 2771502 0 0 0 0.0 10651077.0 8402814.0 0.0 5631312.0 1464292.0 783971.0 0.0 0.0 2771502.0 78.9 0.0 52.9 13.7 7.4 0.0 0.0 26.0 254530 SRR060890 SRP002915 SRS085369 SRX023882 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565956: SUM159PT_NQO1_inhibitor GSM565956: SUM159PT_NQO1_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;SUM159PT|source_name;;cell line SUM159PT|supplier;;Dr. Steve Ethier, University of Michigan|treatment;;NQO1 inhibitor GEO Accession;;GSM565956 GSM565956 SUM159PT_NQO1_inhibitor 210623744 12389632 2011-09-08 07:38:24 161893382 210623744 12389632 1 12389632 index:0,count:12389632,average:17,stdev:0 GSM565956_1 GEO 1.67 5.14 0.3 173902187 211213120 62551415 89837900 121.46 143.62 0 0 0 0 0 0 31.51 88.01 28413593 3241500 28413593 3241500 54.04 80.94 28413593 5559608 28413593 2981106 28446116 16.36 0.00 0 53.31 0 10.98 0 5.97 0 0.00 0 0.00 0 10288776 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 524.74 0 0.00 0 0 0 12389632 0 6605487 0 1360802 0 740054 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 5 0 29.73 0 3683289 0 0 0 0.0 12389632.0 10288776.0 0.0 6605487.0 1360802.0 740054.0 0.0 0.0 3683289.0 83.0 0.0 53.3 11.0 6.0 0.0 0.0 29.7 254535 SRR060891 SRP002915 SRS085370 SRX023883 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565957: SUM159PT_DMSO_only GSM565957: SUM159PT_DMSO_only RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;SUM159PT|source_name;;cell line SUM159PT|supplier;;Dr. Steve Ethier, University of Michigan|treatment;;DMSO only GEO Accession;;GSM565957 GSM565957 SUM159PT_DMSO_only 222977763 13116339 2011-09-08 07:38:24 167792963 222977763 13116339 1 13116339 index:0,count:13116339,average:17,stdev:0 GSM565957_1 GEO 1.55 4.93 0.27 187693885 233494548 70679521 102700723 124.4 145.3 0 0 0 0 0 0 33.17 88.59 29965261 3687983 29965261 3687983 56.22 80.86 29965261 6251433 29965261 3366569 28890170 15.39 0.00 0 53.03 0 9.16 0 6.06 0 0.00 0 0.00 0 11119174 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 491.86 0 0.00 0 0 0 13116339 0 6955961 0 1202041 0 795124 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 10 0 31.74 0 4163213 0 0 0 0.0 13116339.0 11119174.0 0.0 6955961.0 1202041.0 795124.0 0.0 0.0 4163213.0 84.8 0.0 53.0 9.2 6.1 0.0 0.0 31.7 254538 SRR060892 SRP002915 SRS085371 SRX023884 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565958: Hs_578T_CXCR2_inhibitor GSM565958: Hs_578T_CXCR2_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;Hs 578T|source_name;;cell line Hs 578T|supplier;;ATCC|treatment;;CXCR2 inhibitor GEO Accession;;GSM565958 GSM565958 Hs_578T_CXCR2_inhibitor 225808518 13282854 2011-09-08 07:38:24 169055530 225808518 13282854 1 13282854 index:0,count:13282854,average:17,stdev:0 GSM565958_1 GEO 1.22 4.31 0.31 188046047 225535569 66945643 96587136 119.94 144.28 0 0 0 0 0 0 31.48 88.85 31107789 3502711 31107789 3502711 53.13 81.43 31107789 5912173 31107789 3210133 31200381 16.59 0.00 0 54.09 0 9.76 0 6.47 0 0.00 0 0.00 0 11126751 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 583.15 0 0.00 0 0 0 13282854 0 7184681 0 1296494 0 859609 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 8 0 29.68 0 3942070 0 0 0 0.0 13282854.0 11126751.0 0.0 7184681.0 1296494.0 859609.0 0.0 0.0 3942070.0 83.8 0.0 54.1 9.8 6.5 0.0 0.0 29.7 254542 SRR060893 SRP002915 SRS085372 SRX023885 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565959: Hs_578T_PTGIS_inhibitor GSM565959: Hs_578T_PTGIS_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;Hs 578T|source_name;;cell line Hs 578T|supplier;;ATCC|treatment;;PTGIS inhibitor GEO Accession;;GSM565959 GSM565959 Hs_578T_PTGIS_inhibitor 236035939 13884467 2011-09-08 07:38:24 172410331 236035939 13884467 1 13884467 index:0,count:13884467,average:17,stdev:0 GSM565959_1 GEO 1.59 4.05 0.26 192718837 240349123 72709308 107124598 124.71 147.33 0 0 0 0 0 0 33.49 89.28 30832694 3823238 30832694 3823238 56.67 81.06 30832694 6470402 30832694 3471241 29257076 15.18 0.00 0 51.39 0 9.36 0 8.40 0 0.00 0 0.00 0 11417753 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 349.54 0 0.00 0 0 0 13884467 0 7135582 0 1300189 0 1166525 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 13 0 30.84 0 4282171 0 0 0 0.0 13884467.0 11417753.0 0.0 7135582.0 1300189.0 1166525.0 0.0 0.0 4282171.0 82.2 0.0 51.4 9.4 8.4 0.0 0.0 30.8 254546 SRR060894 SRP002915 SRS085373 SRX023886 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565960: Hs_578T_HAS1_inhibitor GSM565960: Hs_578T_HAS1_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;Hs 578T|source_name;;cell line Hs 578T|supplier;;ATCC|treatment;;HAS1 inhibitor GEO Accession;;GSM565960 GSM565960 Hs_578T_HAS1_inhibitor 123256732 7250396 2011-09-08 07:38:24 98603000 123256732 7250396 1 7250396 index:0,count:7250396,average:17,stdev:0 GSM565960_1 GEO 1.71 4.06 0.32 104010206 124603828 37140919 53152493 119.8 143.11 0 0 0 0 0 0 31.26 87.86 17168593 1920796 17168593 1920796 52.98 81.52 17168593 3255708 17168593 1782334 17483254 16.81 0.00 0 54.61 0 10.54 0 4.71 0 0.00 0 0.00 0 6145413 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 492.48 0 0.00 0 0 0 7250396 0 3959138 0 763840 0 341143 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 4 0 30.15 0 2186275 0 0 0 0.0 7250396.0 6145413.0 0.0 3959138.0 763840.0 341143.0 0.0 0.0 2186275.0 84.8 0.0 54.6 10.5 4.7 0.0 0.0 30.2 254550 SRR060895 SRP002915 SRS085374 SRX023887 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565961: Hs_578T_PFKFB3_inhibitor GSM565961: Hs_578T_PFKFB3_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;Hs 578T|source_name;;cell line Hs 578T|supplier;;ATCC|treatment;;PFKFB3 inhibitor GEO Accession;;GSM565961 GSM565961 Hs_578T_PFKFB3_inhibitor 159516525 9383325 2011-09-08 07:38:24 126519405 159516525 9383325 1 9383325 index:0,count:9383325,average:17,stdev:0 GSM565961_1 GEO 1.28 4.24 0.31 135369010 165440528 48536121 70267925 122.21 144.77 0 0 0 0 0 0 32.1 89.86 21863538 2567377 21863538 2567377 55.29 82.77 21863538 4422206 21863538 2364759 21569917 15.93 0.00 0 54.80 0 9.78 0 4.98 0 0.00 0 0.00 0 7998799 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 469.17 0 0.00 0 0 0 9383325 0 5141611 0 917238 0 467288 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 30.45 0 2857188 0 0 0 0.0 9383325.0 7998799.0 0.0 5141611.0 917238.0 467288.0 0.0 0.0 2857188.0 85.2 0.0 54.8 9.8 5.0 0.0 0.0 30.4 254554 SRR060896 SRP002915 SRS085375 SRX023888 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565962: Hs_578T_JAK_inhibitor GSM565962: Hs_578T_JAK_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;Hs 578T|source_name;;cell line Hs 578T|supplier;;ATCC|treatment;;JAK inhibitor GEO Accession;;GSM565962 GSM565962 Hs_578T_JAK_inhibitor 167731469 9866557 2011-09-08 07:38:24 131326440 167731469 9866557 1 9866557 index:0,count:9866557,average:17,stdev:0 GSM565962_1 GEO 1.31 4.28 0.35 140304403 167168421 48596949 68843387 119.15 141.66 0 0 0 0 0 0 30.16 87.46 23364315 2502660 23364315 2502660 52.83 80.96 23364315 4383466 23364315 2316541 23527188 16.77 0.00 0 55.10 0 10.84 0 5.06 0 0.00 0 0.00 0 8297629 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 522.35 0 0.00 0 0 0 9866557 0 5436267 0 1069423 0 499505 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 29.00 0 2861362 0 0 0 0.0 9866557.0 8297629.0 0.0 5436267.0 1069423.0 499505.0 0.0 0.0 2861362.0 84.1 0.0 55.1 10.8 5.1 0.0 0.0 29.0 254559 SRR060897 SRP002915 SRS085376 SRX023889 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565963: Hs_578T_NQO1_inhibitor GSM565963: Hs_578T_NQO1_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;Hs 578T|source_name;;cell line Hs 578T|supplier;;ATCC|treatment;;NQO1 inhibitor GEO Accession;;GSM565963 GSM565963 Hs_578T_NQO1_inhibitor 147345426 8667378 2011-09-08 07:38:24 117037857 147345426 8667378 1 8667378 index:0,count:8667378,average:17,stdev:0 GSM565963_1 GEO 0.99 4.47 0.36 121665991 144651564 41438882 59250204 118.89 142.98 0 0 0 0 0 0 30.3 89.26 20269122 2177217 20269122 2177217 52.61 82.94 20269122 3779889 20269122 2023093 21055268 17.31 0.00 0 54.75 0 11.54 0 5.57 0 0.00 0 0.00 0 7184623 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 537.98 0 0.00 0 0 0 8667378 0 4745487 0 1000001 0 482754 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 4 0 28.14 0 2439136 0 0 0 0.0 8667378.0 7184623.0 0.0 4745487.0 1000001.0 482754.0 0.0 0.0 2439136.0 82.9 0.0 54.8 11.5 5.6 0.0 0.0 28.1 254562 SRR060898 SRP002915 SRS085377 SRX023890 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565964: Hs_578T_DMSO_only GSM565964: Hs_578T_DMSO_only RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;Hs 578T|source_name;;cell line Hs 578T|supplier;;ATCC|treatment;;DMSO only GEO Accession;;GSM565964 GSM565964 Hs_578T_DMSO_only 207767931 12221643 2011-09-08 07:38:24 161664888 207767931 12221643 1 12221643 index:0,count:12221643,average:17,stdev:0 GSM565964_1 GEO 1.1 4.22 0.3 177526169 217943621 65796546 95525352 122.77 145.18 0 0 0 0 0 0 33.24 90.05 28394198 3488072 28394198 3488072 55.72 82.52 28394198 5846541 28394198 3196517 27915747 15.72 0.00 0 54.16 0 9.49 0 4.66 0 0.00 0 0.00 0 10492746 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 549.97 0 0.00 0 0 0 12221643 0 6619273 0 1159505 0 569392 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 4 0 31.69 0 3873473 0 0 0 0.0 12221643.0 10492746.0 0.0 6619273.0 1159505.0 569392.0 0.0 0.0 3873473.0 85.9 0.0 54.2 9.5 4.7 0.0 0.0 31.7 254567 SRR060899 SRP002915 SRS085378 SRX023891 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565965: MCF7_CXCR2_inhibitor GSM565965: MCF7_CXCR2_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;MCF7|source_name;;cell line MCF7|supplier;;ATCC|treatment;;CXCR2 inhibitor GEO Accession;;GSM565965 GSM565965 MCF7_CXCR2_inhibitor 232705962 13688586 2011-09-08 07:38:24 177473880 232705962 13688586 1 13688586 index:0,count:13688586,average:17,stdev:0 GSM565965_1 GEO 2.7 3.96 0.31 194734165 245711161 69242673 99886370 126.18 144.26 0 0 0 0 0 0 30.89 87.39 32849386 3563701 32849386 3563701 56.0 79.87 32849386 6459814 32849386 3257309 29106653 14.95 0.00 0 54.49 0 9.76 0 5.96 0 0.00 0 0.00 0 11536406 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 483.13 0 0.00 0 0 0 13688586 0 7458381 0 1336010 0 816170 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 9 0 29.79 0 4078025 0 0 0 0.0 13688586.0 11536406.0 0.0 7458381.0 1336010.0 816170.0 0.0 0.0 4078025.0 84.3 0.0 54.5 9.8 6.0 0.0 0.0 29.8 254979 SRR060900 SRP002915 SRS085379 SRX023892 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565966: MCF7_PTGIS_inhibitor GSM565966: MCF7_PTGIS_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;MCF7|source_name;;cell line MCF7|supplier;;ATCC|treatment;;PTGIS inhibitor GEO Accession;;GSM565966 GSM565966 MCF7_PTGIS_inhibitor 232541096 13678888 2011-09-08 07:38:24 176860062 232541096 13678888 1 13678888 index:0,count:13678888,average:17,stdev:0 GSM565966_1 GEO 2.4 4.11 0.32 194185811 242823328 68333848 99618456 125.05 145.78 0 0 0 0 0 0 31.2 89.04 33102921 3582054 33102921 3582054 54.95 81.55 33102921 6309110 33102921 3281007 28608415 14.73 0.00 0 54.52 0 10.58 0 5.49 0 0.00 0 0.00 0 11480791 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 341.97 0 0.00 0 0 0 13678888 0 7457636 0 1446807 0 751290 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 8 0 29.41 0 4023155 0 0 0 0.0 13678888.0 11480791.0 0.0 7457636.0 1446807.0 751290.0 0.0 0.0 4023155.0 83.9 0.0 54.5 10.6 5.5 0.0 0.0 29.4 254983 SRR060901 SRP002915 SRS085380 SRX023893 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565967: MCF7_HAS1_inhibitor GSM565967: MCF7_HAS1_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;MCF7|source_name;;cell line MCF7|supplier;;ATCC|treatment;;HAS1 inhibitor GEO Accession;;GSM565967 GSM565967 MCF7_HAS1_inhibitor 235281020 13840060 2011-09-08 07:38:24 178579670 235281020 13840060 1 13840060 index:0,count:13840060,average:17,stdev:0 GSM565967_1 GEO 3.13 4.07 0.3 197218067 249055529 68057089 99237876 126.28 145.82 0 0 0 0 0 0 30.73 89.43 33973342 3583294 33973342 3583294 56.47 81.65 33973342 6584170 33973342 3271789 27076322 13.73 0.00 0 55.30 0 10.67 0 5.07 0 0.00 0 0.00 0 11660577 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 425.85 0 0.00 0 0 0 13840060 0 7653663 0 1477138 0 702345 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 5 0 28.95 0 4006914 0 0 0 0.0 13840060.0 11660577.0 0.0 7653663.0 1477138.0 702345.0 0.0 0.0 4006914.0 84.3 0.0 55.3 10.7 5.1 0.0 0.0 29.0 509972 SRR060902 SRP002915 SRS085381 SRX023894 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565968: MCF7_PFKFB3_inhibitor GSM565968: MCF7_PFKFB3_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;MCF7|source_name;;cell line MCF7|supplier;;ATCC|treatment;;PFKFB3 inhibitor GEO Accession;;GSM565968 GSM565968 MCF7_PFKFB3_inhibitor 238489821 14028813 2011-09-08 07:38:24 180388706 238489821 14028813 1 14028813 index:0,count:14028813,average:17,stdev:0 GSM565968_1 GEO 2.44 4.17 0.31 195928386 243463310 67526215 98055217 124.26 145.21 0 0 0 0 0 0 30.52 88.88 33632658 3533425 33632658 3533425 53.97 81.58 33632658 6248782 33632658 3242985 29906922 15.26 0.00 0 54.20 0 11.48 0 5.98 0 0.00 0 0.00 0 11578876 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 515.34 0 0.00 0 0 0 14028813 0 7603530 0 1610630 0 839307 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 28.34 0 3975346 0 0 0 0.0 14028813.0 11578876.0 0.0 7603530.0 1610630.0 839307.0 0.0 0.0 3975346.0 82.5 0.0 54.2 11.5 6.0 0.0 0.0 28.3 509980 SRR060903 SRP002915 SRS085382 SRX023895 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565969: MCF7_JAK_inhibitor GSM565969: MCF7_JAK_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;MCF7|source_name;;cell line MCF7|supplier;;ATCC|treatment;;JAK inhibitor GEO Accession;;GSM565969 GSM565969 MCF7_JAK_inhibitor 232055542 13650326 2011-09-08 07:38:24 172140593 232055542 13650326 1 13650326 index:0,count:13650326,average:17,stdev:0 GSM565969_1 GEO 2.66 4.23 0.3 193126657 244691351 67136633 97991091 126.7 145.96 0 0 0 0 0 0 30.93 89.34 32933153 3531241 32933153 3531241 56.08 81.84 32933153 6402570 32933153 3234616 27619973 14.30 0.00 0 54.68 0 10.79 0 5.58 0 0.00 0 0.00 0 11416581 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 491.41 0 0.00 0 0 0 13650326 0 7464205 0 1472503 0 761242 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 7 0 28.95 0 3952376 0 0 0 0.0 13650326.0 11416581.0 0.0 7464205.0 1472503.0 761242.0 0.0 0.0 3952376.0 83.6 0.0 54.7 10.8 5.6 0.0 0.0 29.0 509988 SRR060904 SRP002915 SRS085383 SRX023896 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565970: MCF7_NQO1_inhibitor GSM565970: MCF7_NQO1_inhibitor RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;MCF7|source_name;;cell line MCF7|supplier;;ATCC|treatment;;NQO1 inhibitor GEO Accession;;GSM565970 GSM565970 MCF7_NQO1_inhibitor 243596196 14329188 2011-09-08 07:38:24 182504711 243596196 14329188 1 14329188 index:0,count:14329188,average:17,stdev:0 GSM565970_1 GEO 2.52 4.28 0.32 197758809 242786688 66400029 95571700 122.77 143.93 0 0 0 0 0 0 29.2 87.35 34345325 3415055 34345325 3415055 52.5 80.4 34345325 6139152 34345325 3143362 32135773 16.25 0.00 0 54.33 0 11.63 0 6.76 0 0.00 0 0.00 0 11694074 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 452.50 0 0.00 0 0 0 14329188 0 7784339 0 1667160 0 967954 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 6 0 27.29 0 3909735 0 0 0 0.0 14329188.0 11694074.0 0.0 7784339.0 1667160.0 967954.0 0.0 0.0 3909735.0 81.6 0.0 54.3 11.6 6.8 0.0 0.0 27.3 509996 SRR060905 SRP002915 SRS085384 SRX023897 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565971: MCF7_DMSO_only GSM565971: MCF7_DMSO_only RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;MCF7|source_name;;cell line MCF7|supplier;;ATCC|treatment;;DMSO only GEO Accession;;GSM565971 GSM565971 MCF7_DMSO_only 224817435 13224555 2011-09-08 07:38:24 173940916 224817435 13224555 1 13224555 index:0,count:13224555,average:17,stdev:0 GSM565971_1 GEO 2.35 4.37 0.36 181032195 217520356 59310961 84648978 120.16 142.72 0 0 0 0 0 0 28.48 87.27 31818180 3047738 31818180 3047738 51.38 80.66 31818180 5498183 31818180 2816890 30408633 16.80 0.00 0 54.51 0 12.60 0 6.49 0 0.00 0 0.00 0 10700583 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 602.64 0 0.00 0 0 0 13224555 0 7208436 0 1665764 0 858208 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 26.41 0 3492147 0 0 0 0.0 13224555.0 10700583.0 0.0 7208436.0 1665764.0 858208.0 0.0 0.0 3492147.0 80.9 0.0 54.5 12.6 6.5 0.0 0.0 26.4 510004 SRR060906 SRP002915 SRS085385 SRX023898 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565972: SUM159PT_non-targeting_siRNAs GSM565972: SUM159PT_non-targeting_siRNAs RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;SUM159PT|source_name;;cell line SUM159PT|supplier;;Dr. Steve Ethier, University of Michigan|treatment;;non-targeting siRNAs GEO Accession;;GSM565972 GSM565972 SUM159PT_non-targeting_siRNAs 217523007 12795471 2011-09-08 07:38:24 156849308 217523007 12795471 1 12795471 index:0,count:12795471,average:17,stdev:0 GSM565972_1 GEO 1.54 5.38 0.4 174383341 203840385 58123785 82192751 116.89 141.41 0 0 0 0 0 0 29.37 88.42 29903495 3025581 29903495 3025581 51.06 81.61 29903495 5260597 29903495 2792725 31225837 17.91 0.00 0 53.77 0 12.64 0 6.84 0 0.00 0 0.00 0 10302658 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 500.69 0 0.00 0 0 0 12795471 0 6880758 0 1617067 0 875746 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 10 0 26.74 0 3421900 0 0 0 0.0 12795471.0 10302658.0 0.0 6880758.0 1617067.0 875746.0 0.0 0.0 3421900.0 80.5 0.0 53.8 12.6 6.8 0.0 0.0 26.7 510012 SRR060907 SRP002915 SRS085386 SRX023899 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565973: SUM159PT_STAT3_siRNAs GSM565973: SUM159PT_STAT3_siRNAs RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;SUM159PT|source_name;;cell line SUM159PT|supplier;;Dr. Steve Ethier, University of Michigan|treatment;;STAT3 siRNAs GEO Accession;;GSM565973 GSM565973 SUM159PT_STAT3_siRNAs 235532620 13854860 2011-09-08 07:38:24 178268251 235532620 13854860 1 13854860 index:0,count:13854860,average:17,stdev:0 GSM565973_1 GEO 1.57 5.57 0.38 185094565 214539988 59141326 83236651 115.91 140.74 0 0 0 0 0 0 27.75 87.15 32293260 3034338 32293260 3034338 49.12 80.38 32293260 5372414 32293260 2798863 34875499 18.84 0.00 0 53.80 0 13.92 0 7.14 0 0.00 0 0.00 0 10936441 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 665.03 0 0.00 0 0 0 13854860 0 7454606 0 1928961 0 989458 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 5 0 25.13 0 3481835 0 0 0 0.0 13854860.0 10936441.0 0.0 7454606.0 1928961.0 989458.0 0.0 0.0 3481835.0 78.9 0.0 53.8 13.9 7.1 0.0 0.0 25.1 510020 SRR060908 SRP002915 SRS085387 SRX023900 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565974: Hs_578T_non-targeting_siRNAs GSM565974: Hs_578T_non-targeting_siRNAs RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;Hs 578T|source_name;;cell line Hs 578T|supplier;;ATCC|treatment;;non-targeting siRNAs GEO Accession;;GSM565974 GSM565974 Hs_578T_non-targeting_siRNAs 238804559 14047327 2011-09-08 07:38:24 180662703 238804559 14047327 1 14047327 index:0,count:14047327,average:17,stdev:0 GSM565974_1 GEO 1.36 4.27 0.37 199654105 238426895 71564296 102586789 119.42 143.35 0 0 0 0 0 0 31.98 89.6 32592604 3775189 32592604 3775189 53.2 82.44 32592604 6279601 32592604 3473736 33491827 16.77 0.00 0 54.04 0 9.93 0 6.04 0 0.00 0 0.00 0 11804784 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 549.68 0 0.00 0 0 0 14047327 0 7591336 0 1394473 0 848070 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 7 0 29.99 0 4213448 0 0 0 0.0 14047327.0 11804784.0 0.0 7591336.0 1394473.0 848070.0 0.0 0.0 4213448.0 84.0 0.0 54.0 9.9 6.0 0.0 0.0 30.0 255015 SRR060909 SRP002915 SRS085388 SRX023901 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565975: Hs_578T_STAT3_siRNAs GSM565975: Hs_578T_STAT3_siRNAs RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;Hs 578T|source_name;;cell line Hs 578T|supplier;;ATCC|treatment;;STAT3 siRNAs GEO Accession;;GSM565975 GSM565975 Hs_578T_STAT3_siRNAs 243089562 14299386 2011-09-08 07:38:24 177893795 243089562 14299386 1 14299386 index:0,count:14299386,average:17,stdev:0 GSM565975_1 GEO 1.4 4.2 0.32 201954098 242522835 69794921 100240468 120.09 143.62 0 0 0 0 0 0 30.68 89.18 33606435 3664826 33606435 3664826 53.26 81.59 33606435 6360852 33606435 3352675 33407542 16.54 0.00 0 54.79 0 10.44 0 6.04 0 0.00 0 0.00 0 11943678 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 627.78 0 0.00 0 0 0 14299386 0 7834280 0 1492437 0 863271 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 6 0 28.74 0 4109398 0 0 0 0.0 14299386.0 11943678.0 0.0 7834280.0 1492437.0 863271.0 0.0 0.0 4109398.0 83.5 0.0 54.8 10.4 6.0 0.0 0.0 28.7 127521 SRR060910 SRP002915 SRS085389 SRX023902 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565976: MCF7_non-targeting_siRNAs GSM565976: MCF7_non-targeting_siRNAs RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;MCF7|source_name;;cell line MCF7|supplier;;ATCC|treatment;;non-targeting siRNAs GEO Accession;;GSM565976 GSM565976 MCF7_non-targeting_siRNAs 219569535 12915855 2011-09-08 07:38:24 156288227 219569535 12915855 1 12915855 index:0,count:12915855,average:17,stdev:0 GSM565976_1 GEO 2.0 4.44 0.38 170516959 202912574 54571046 77938065 119.0 142.82 0 0 0 0 0 0 27.7 86.93 30689565 2793732 30689565 2793732 49.68 80.03 30689565 5010339 30689565 2572012 29803246 17.48 0.00 0 53.20 0 13.19 0 8.73 0 0.00 0 0.00 0 10085193 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 534.45 0 0.00 0 0 0 12915855 0 6871378 0 1703607 0 1127055 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 13 0 24.88 0 3213815 0 0 0 0.0 12915855.0 10085193.0 0.0 6871378.0 1703607.0 1127055.0 0.0 0.0 3213815.0 78.1 0.0 53.2 13.2 8.7 0.0 0.0 24.9 127523 SRR060911 SRP002915 SRS085390 SRX023903 SRA021045 GEO SAGE-Seq gene expression profiles of Hs578T, MCF7, and SUM159PT cells treated with STAT3 or non-targeting siRNAs, DMSO, or CXCR2, PTGIS, HAS1, PFKFB3, JAK, or NQO1 inhibitor To investigate potential links between Stat3 transcriptional activity and other signaling pathways in breast cancer, we determined the gene expression profiles of three breast cancer cell lines treated with JAK, PTGIS, PFKFB3, CXCR2, HAS1, or NQO1 inhibitor (all of which decreased Stat3 transcriptional activity in Hs 578T cells except for the NQO1 inhibitor), inhibitor treatment vehicle alone (DMSO), STAT3 siRNAs, or non-targeting siRNAs. Using the resulting data, we identified a gene signature that was significantly regulated by STAT3 siRNAs and similarly affected by the JAK and at least 3 other inhibitors (or by 4 other inhibitors) but not by the NQO1 inhibitor in Hs 578T cells that was enriched in genes involved in development and correlated with shorter distant metastasis-free survival in primary lymph-node-negative invasive breast tumors. These results emphasize the central importance of Stat3 in CD44+/CD24- stem-cell-like breast cancer cells. Overall design: This study includes SAGE-Seq libraries obtained using 27 samples that each underwent individual protocols. There are nine samples of each of three cell lines - Hs 578T, MCF7, and SUM159PT. The samples in each group were treated with either one of the six inhibitors, DMSO only (the background control for inhibitor-treated cells), STAT3 siRNAs, or non-targeting siRNAs (the background control for STAT3 siRNAs). GSM565977: MCF7_STAT3_siRNAs GSM565977: MCF7_STAT3_siRNAs RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell line;;MCF7|source_name;;cell line MCF7|supplier;;ATCC|treatment;;STAT3 siRNAs GEO Accession;;GSM565977 GSM565977 MCF7_STAT3_siRNAs 226149487 13302911 2011-09-08 07:38:24 166246451 226149487 13302911 1 13302911 index:0,count:13302911,average:17,stdev:0 GSM565977_1 GEO 2.37 4.27 0.35 181639766 221987010 59240369 85102400 122.21 143.66 0 0 0 0 0 0 28.59 88.03 32246279 3071055 32246279 3071055 52.27 80.57 32246279 5614450 32246279 2810651 29723869 16.36 0.00 0 54.52 0 12.03 0 7.22 0 0.00 0 0.00 0 10741887 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 576.99 0 0.00 0 0 0 13302911 0 7253237 0 1600466 0 960558 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 10 0 26.22 0 3488650 0 0 0 0.0 13302911.0 10741887.0 0.0 7253237.0 1600466.0 960558.0 0.0 0.0 3488650.0 80.7 0.0 54.5 12.0 7.2 0.0 0.0 26.2 1083673 SRR067891 SRP003726 SRS116524 SRX027808 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603077: epitheliumbreast-normal-N1 GSM603077: epitheliumbreast-normal-N1 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD24|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM603077 17 GSM603077 epitheliumbreast-normal-N1 88290384 5193552 2010-10-07 13:42:37 44590078 88290384 5193552 1 5193552 index:0,count:5193552,average:17,stdev:0 GSM603077_1 GEO 3.16 3.24 0.13 77402041 102792205 32638484 48963489 132.8 150.02 0 0 0 0 0 0 37.29 88.79 11582538 1705788 11582538 1705788 62.42 80.94 11582538 2855203 11582538 1554957 9331828 12.06 0.00 0 51.09 0 4.31 0 7.61 0 0.00 0 0.00 0 4574402 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 296.77 0 0.00 0 0 0 5193552 0 2653216 0 224045 0 395105 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 11 0 36.99 0 1921186 0 0 0 0.0 5193552.0 4574402.0 0.0 2653216.0 224045.0 395105.0 0.0 0.0 1921186.0 88.1 0.0 51.1 4.3 7.6 0.0 0.0 37.0 1083688 SRR067892 SRP003726 SRS116525 SRX027809 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603078: epitheliumbreast-normal-N2 GSM603078: epitheliumbreast-normal-N2 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD24|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM603078 17 GSM603078 epitheliumbreast-normal-N2 84393134 4964302 2010-10-07 13:40:33 39488371 84393134 4964302 1 4964302 index:0,count:4964302,average:17,stdev:0 GSM603078_1 GEO 4.73 2.82 0.13 74418294 102759051 29829335 46767554 138.08 156.78 0 0 0 0 0 0 36.68 91.85 11499249 1612775 11499249 1612775 64.36 84.34 11499249 2829651 11499249 1480787 8160975 10.97 0.00 0 53.20 0 4.63 0 6.80 0 0.00 0 0.00 0 4396852 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 248.22 0 0.00 0 0 0 4964302 0 2641024 0 229700 0 337750 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 13 0 35.37 0 1755828 0 0 0 0.0 4964302.0 4396852.0 0.0 2641024.0 229700.0 337750.0 0.0 0.0 1755828.0 88.6 0.0 53.2 4.6 6.8 0.0 0.0 35.4 1083704 SRR067893 SRP003726 SRS116526 SRX027810 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603079: epitheliumbreast-normal-N3 GSM603079: epitheliumbreast-normal-N3 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD24|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM603079 18 GSM603079 epitheliumbreast-normal-N3 63883386 3549077 2010-10-19 16:18:48 47661155 63883386 3549077 1 3549077 index:0,count:3549077,average:18,stdev:0 GSM603079_1 GEO 5.53 3.63 0.24 53536390 71197640 21519191 30182169 132.99 140.26 0 0 0 0 0 0 30.46 77.26 8377459 933494 8377459 933494 61.4 72.85 8377459 1881531 8377459 880182 6900804 12.89 0.00 0 52.31 0 6.00 0 7.65 0 0.00 0 0.00 0 3064614 0 18 0 17.81 0 0.00 0 0.00 0 0.00 0 0.00 0 399.27 0 0.02 0 0 0 3549077 0 1856387 0 212966 0 271497 0 0 0 0 0 0 0 0 0 0 0 69 0 0 0 69 0 34.04 0 1208227 0 0 0 0.0 3549077.0 3064614.0 0.0 1856387.0 212966.0 271497.0 0.0 0.0 1208227.0 86.3 0.0 52.3 6.0 7.6 0.0 0.0 34.0 1083720 SRR067894 SRP003726 SRS116527 SRX027811 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603080: epitheliumbreast-normal-N4 GSM603080: epitheliumbreast-normal-N4 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD24|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM603080 18 GSM603080 epitheliumbreast-normal-N4 33960024 1886668 2010-10-19 16:14:45 19814460 33960024 1886668 1 1886668 index:0,count:1886668,average:18,stdev:0 GSM603080_1 GEO 3.41 3.51 0.2 28957253 38900665 12261983 17170384 134.34 140.03 0 0 0 0 0 0 32.79 78.59 4378701 540108 4378701 540108 62.32 73.44 4378701 1026604 4378701 504713 3379139 11.67 0.00 0 50.89 0 5.64 0 7.04 0 0.00 0 0.00 0 1647321 0 18 0 17.84 0 0.00 0 0.00 0 0.00 0 0.00 0 251.56 0 0.01 0 0 0 1886668 0 960079 0 106435 0 132912 0 0 0 0 0 0 0 0 0 0 0 37 0 0 0 37 0 36.43 0 687242 0 0 0 0.0 1886668.0 1647321.0 0.0 960079.0 106435.0 132912.0 0.0 0.0 687242.0 87.3 0.0 50.9 5.6 7.0 0.0 0.0 36.4 1083737 SRR067895 SRP003726 SRS116528 SRX027812 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603081: epitheliumbreast-normal-N5 GSM603081: epitheliumbreast-normal-N5 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD44|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM603081 18 GSM603081 epitheliumbreast-normal-N5 38878668 2159926 2010-10-19 16:16:24 21296183 38878668 2159926 1 2159926 index:0,count:2159926,average:18,stdev:0 GSM603081_1 GEO 4.32 3.51 0.21 31826536 41718314 13283162 18232316 131.08 137.26 0 0 0 0 0 0 31.81 77.7 4929569 579652 4929569 579652 61.4 73.48 4929569 1118861 4929569 548176 4033390 12.67 0.00 0 49.83 0 5.23 0 10.40 0 0.00 0 0.00 0 1822268 0 18 0 17.81 0 0.00 0 0.00 0 0.00 0 0.00 0 259.19 0 0.02 0 0 0 2159926 0 1076245 0 112920 0 224738 0 0 0 0 0 0 0 0 0 0 0 97 0 0 0 97 0 34.54 0 746023 0 0 0 0.0 2159926.0 1822268.0 0.0 1076245.0 112920.0 224738.0 0.0 0.0 746023.0 84.4 0.0 49.8 5.2 10.4 0.0 0.0 34.5 1083753 SRR067896 SRP003726 SRS116529 SRX027813 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603082: epitheliumbreast-normal-N6 GSM603082: epitheliumbreast-normal-N6 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD44|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM603082 18 GSM603082 epitheliumbreast-normal-N6 19401426 1077857 2010-10-19 16:14:59 11048152 19401426 1077857 1 1077857 index:0,count:1077857,average:18,stdev:0 GSM603082_1 GEO 3.22 3.34 0.18 17000029 22948258 8449532 12016977 134.99 142.22 0 0 0 0 0 0 41.03 83.74 2291584 396511 2291584 396511 67.44 79.03 2291584 651824 2291584 374217 1725209 10.15 0.00 0 45.73 0 3.94 0 6.39 0 0.00 0 0.00 0 966483 0 18 0 17.84 0 0.00 0 0.00 0 0.00 0 0.00 0 184.78 0 0.01 0 0 0 1077857 0 492954 0 42489 0 68885 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 17 0 43.93 0 473529 0 0 0 0.0 1077857.0 966483.0 0.0 492954.0 42489.0 68885.0 0.0 0.0 473529.0 89.7 0.0 45.7 3.9 6.4 0.0 0.0 43.9 1083771 SRR067897 SRP003726 SRS116530 SRX027814 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603083: epitheliumbreast-normal-N7 GSM603083: epitheliumbreast-normal-N7 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD44|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM603083 17 GSM603083 epitheliumbreast-normal-N7 189502281 11147193 2010-10-07 14:13:02 148837762 189502281 11147193 1 11147193 index:0,count:11147193,average:17,stdev:0 GSM603083_1 GEO 2.97 3.72 0.28 161981157 202875173 62856313 93423190 125.25 148.63 0 0 0 0 0 0 34.71 89.84 25214201 3324478 25214201 3324478 57.34 84.04 25214201 5491614 25214201 3109640 25516570 15.75 0.00 0 52.72 0 6.76 0 7.32 0 0.00 0 0.00 0 9577617 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 401.30 0 0.00 0 0 0 11147193 0 5877343 0 753279 0 816297 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 33.19 0 3700274 0 0 0 0.0 11147193.0 9577617.0 0.0 5877343.0 753279.0 816297.0 0.0 0.0 3700274.0 85.9 0.0 52.7 6.8 7.3 0.0 0.0 33.2 1083785 SRR067898 SRP003726 SRS116531 SRX027815 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603084: epitheliumbreast-cancer-C1 GSM603084: epitheliumbreast-cancer-C1 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD24|cell type;;epithelial cell|disease state;;cancer|source_name;;biopsy and surgery|tissue;;breast GEO Accession;;GSM603084 17 GSM603084 epitheliumbreast-cancer-C1 73715808 4336224 2010-10-07 13:50:00 38395778 73715808 4336224 1 4336224 index:0,count:4336224,average:17,stdev:0 GSM603084_1 GEO 2.29 4.85 0.45 64290428 74450381 21233196 29531381 115.8 139.08 0 0 0 0 0 0 27.83 84.67 10923746 1058988 10923746 1058988 51.14 78.14 10923746 1946121 10923746 977367 12349142 19.21 0.00 0 58.91 0 8.68 0 3.56 0 0.00 0 0.00 0 3805299 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 433.62 0 0.00 0 0 0 4336224 0 2554524 0 376477 0 154448 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 28.84 0 1250775 0 0 0 0.0 4336224.0 3805299.0 0.0 2554524.0 376477.0 154448.0 0.0 0.0 1250775.0 87.8 0.0 58.9 8.7 3.6 0.0 0.0 28.8 1083802 SRR067899 SRP003726 SRS116532 SRX027816 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603085: epitheliumbreast-cancer-C2 GSM603085: epitheliumbreast-cancer-C2 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD24|cell type;;epithelial cell|disease state;;cancer|source_name;;biopsy and surgery|tissue;;breast GEO Accession;;GSM603085 17 GSM603085 epitheliumbreast-cancer-C2 80271076 4721828 2010-10-07 13:59:39 55547443 80271076 4721828 1 4721828 index:0,count:4721828,average:17,stdev:0 GSM603085_1 GEO 3.61 4.23 0.43 65227386 72925854 20681983 27923382 111.8 135.01 0 0 0 0 0 0 25.1 79.55 11320153 968641 11320153 968641 46.1 72.33 11320153 1779237 11320153 880827 13463697 20.64 0.00 0 55.96 0 10.72 0 7.53 0 0.00 0 0.00 0 3859892 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 424.96 0 0.00 0 0 0 4721828 0 2642172 0 506154 0 355782 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 25.79 0 1217720 0 0 0 0.0 4721828.0 3859892.0 0.0 2642172.0 506154.0 355782.0 0.0 0.0 1217720.0 81.7 0.0 56.0 10.7 7.5 0.0 0.0 25.8 1085449 SRR067900 SRP003726 SRS116533 SRX027817 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603086: epitheliumbreast-cancer-C3 GSM603086: epitheliumbreast-cancer-C3 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD24|cell type;;epithelial cell|disease state;;cancer|source_name;;biopsy and surgery|tissue;;breast GEO Accession;;GSM603086 17 GSM603086 epitheliumbreast-cancer-C3 70003314 4117842 2010-10-07 13:59:31 52444168 70003314 4117842 1 4117842 index:0,count:4117842,average:17,stdev:0 GSM603086_1 GEO 3.82 3.91 1.19 60596879 71735874 19379306 27494214 118.38 141.87 0 0 0 0 0 0 26.82 84.26 10180222 961309 10180222 961309 50.52 77.63 10180222 1810891 10180222 885670 10682315 17.63 0.00 0 59.34 0 8.52 0 4.44 0 0.00 0 0.00 0 3584301 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 436.01 0 0.00 0 0 0 4117842 0 2443452 0 350898 0 182643 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 27.71 0 1140849 0 0 0 0.0 4117842.0 3584301.0 0.0 2443452.0 350898.0 182643.0 0.0 0.0 1140849.0 87.0 0.0 59.3 8.5 4.4 0.0 0.0 27.7 1085464 SRR067901 SRP003726 SRS116534 SRX027818 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603087: epitheliumbreast-cancer-C4 GSM603087: epitheliumbreast-cancer-C4 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;CD24|cell type;;epithelial cell|disease state;;cancer|source_name;;biopsy and surgery|tissue;;breast GEO Accession;;GSM603087 17 GSM603087 epitheliumbreast-cancer-C4 60713222 3571366 2010-10-07 13:59:51 43075100 60713222 3571366 1 3571366 index:0,count:3571366,average:17,stdev:0 GSM603087_1 GEO 3.33 4.49 0.42 46285267 53369123 13457278 18685179 115.3 138.85 0 0 0 0 0 0 23.23 80.27 8424168 635948 8424168 635948 46.6 74.94 8424168 1275593 8424168 593711 8672867 18.74 0.00 0 54.47 0 14.87 0 8.48 0 0.00 0 0.00 0 2737442 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 401.78 0 0.00 0 0 0 3571366 0 1945164 0 531091 0 302833 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 22.18 0 792278 0 0 0 0.0 3571366.0 2737442.0 0.0 1945164.0 531091.0 302833.0 0.0 0.0 792278.0 76.6 0.0 54.5 14.9 8.5 0.0 0.0 22.2 1085480 SRR067902 SRP003726 SRS116535 SRX027819 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603088: epitheliumbreast-cancer-C5 GSM603088: epitheliumbreast-cancer-C5 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;EPCR|cell type;;epithelial cell|disease state;;cancer|source_name;;biopsy and surgery|tissue;;breast GEO Accession;;GSM603088 17 GSM603088 epitheliumbreast-cancer-C5 65479597 3851741 2010-10-07 13:54:40 29190565 65479597 3851741 1 3851741 index:0,count:3851741,average:17,stdev:0 GSM603088_1 GEO 1.57 4.78 0.37 57304773 66340275 18863877 25995334 115.77 137.8 0 0 0 0 0 0 27.96 85.35 9727969 948234 9727969 948234 51.92 79.89 9727969 1761085 9727969 887563 11166451 19.49 0.00 0 59.22 0 8.71 0 3.23 0 0.00 0 0.00 0 3391855 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 385.17 0 0.00 0 0 0 3851741 0 2280835 0 335602 0 124284 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 28.84 0 1111020 0 0 0 0.0 3851741.0 3391855.0 0.0 2280835.0 335602.0 124284.0 0.0 0.0 1111020.0 88.1 0.0 59.2 8.7 3.2 0.0 0.0 28.8 1085496 SRR067903 SRP003726 SRS116536 SRX027820 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603089: epitheliumbreast-cancer-C6 GSM603089: epitheliumbreast-cancer-C6 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;EPCR|cell type;;epithelial cell|disease state;;cancer|source_name;;biopsy and surgery|tissue;;breast GEO Accession;;GSM603089 17 GSM603089 epitheliumbreast-cancer-C6 72516543 4265679 2010-10-07 13:56:15 35257107 72516543 4265679 1 4265679 index:0,count:4265679,average:17,stdev:0 GSM603089_1 GEO 1.62 5.06 0.36 63134048 72542028 21308038 29958050 114.9 140.6 0 0 0 0 0 0 28.57 85.05 10564692 1067577 10564692 1067577 50.34 78.75 10564692 1881241 10564692 988458 12405194 19.65 0.00 0 58.18 0 8.66 0 3.73 0 0.00 0 0.00 0 3736939 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 529.53 0 0.00 0 0 0 4265679 0 2481724 0 369569 0 159171 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 29.43 0 1255215 0 0 0 0.0 4265679.0 3736939.0 0.0 2481724.0 369569.0 159171.0 0.0 0.0 1255215.0 87.6 0.0 58.2 8.7 3.7 0.0 0.0 29.4 542759 SRR067904 SRP003726 SRS116537 SRX027821 SRA024462 GEO Gene expression profiling of human tissue samples using SAGE-Seq We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Overall design: Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq GSM603090: epitheliumbreast-cancer-C7 GSM603090: epitheliumbreast-cancer-C7 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell marker;;SSEA4|cell type;;epithelial cell|disease state;;cancer|source_name;;biopsy and surgery|tissue;;breast GEO Accession;;GSM603090 17 GSM603090 epitheliumbreast-cancer-C7 57487846 3381638 2010-10-07 14:03:23 42484477 57487846 3381638 1 3381638 index:0,count:3381638,average:17,stdev:0 GSM603090_1 GEO 1.34 4.38 0.43 47677882 53078792 16081245 22274280 111.33 138.51 0 0 0 0 0 0 27.66 82.37 8017309 779702 8017309 779702 47.97 78.36 8017309 1352395 8017309 741704 8948192 18.77 0.00 0 55.38 0 11.01 0 5.62 0 0.00 0 0.00 0 2819263 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 380.43 0 0.00 0 0 0 3381638 0 1872692 0 372366 0 190009 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 27.99 0 946571 0 0 0 0.0 3381638.0 2819263.0 0.0 1872692.0 372366.0 190009.0 0.0 0.0 946571.0 83.4 0.0 55.4 11.0 5.6 0.0 0.0 28.0 792074 SRR071160 SRP004042 SRS118733 SRX030065 SRA025891 GEO Identification of stromally expressed molecules in the prostate by Tag profiling of cancer-associated fibroblasts, normal fibroblasts and fetal prostate The stromal microenvironment plays key roles in prostate development and cancer. Cancer associated fibroblasts (CAFs) and other stromal cells stimulate tumourigenesis via several mechanisms including the expression of pro-tumourigenic factors. Mesenchyme (embryonic stroma) controls prostate organogenesis, and in some circumstances can re-differentiate prostate tumours. Epithelia are regulated by powerful paracrine signalling from the stroma in both development and disease, and identification of these stromal signals is important. We have applied next-generation Tag profiling to fetal human prostate, normal human prostate fibroblasts (NPFs) and CAFs to identify molecules expressed in prostatic stroma Overall design: Each sample was used for Tag library construction, by Solexa Inc GSM614543: Cancer-associated fibroblasts (CAF) GSM614543: Cancer-associated fibroblasts (CAF) RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell type;;Fibroblasts|developmental stage;;Adult|source_name;;Cancer-associated fibroblasts (CAF)|tissue;;Prostate GEO Accession;;GSM614543 16 GSM614543 Cancer-associated fibroblasts (CAF) 39299504 2456219 2011-10-24 09:22:16 25140025 39299504 2456219 1 2456219 index:0,count:2456219,average:16,stdev:0 GSM614543_1 GEO 2.06 4.91 0.62 28891073 31241869 5014340 7179077 108.14 143.17 0 0 0 0 0 0 14.75 85.2 7895104 267226 7895104 267226 44.57 78.95 7895104 807397 7895104 247623 7266756 25.15 0.00 0 60.98 0 18.76 0 7.49 0 0.00 0 0.00 0 1811518 0 16 0 15.99 0 0.00 0 0.00 0 0.00 0 0.00 0 340.09 0 0.00 0 0 0 2456219 0 1497871 0 460809 0 183892 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12.77 0 313647 0 0 0 0.0 2456219.0 1811518.0 0.0 1497871.0 460809.0 183892.0 0.0 0.0 313647.0 73.8 0.0 61.0 18.8 7.5 0.0 0.0 12.8 792090 SRR071161 SRP004042 SRS118734 SRX030066 SRA025891 GEO Identification of stromally expressed molecules in the prostate by Tag profiling of cancer-associated fibroblasts, normal fibroblasts and fetal prostate The stromal microenvironment plays key roles in prostate development and cancer. Cancer associated fibroblasts (CAFs) and other stromal cells stimulate tumourigenesis via several mechanisms including the expression of pro-tumourigenic factors. Mesenchyme (embryonic stroma) controls prostate organogenesis, and in some circumstances can re-differentiate prostate tumours. Epithelia are regulated by powerful paracrine signalling from the stroma in both development and disease, and identification of these stromal signals is important. We have applied next-generation Tag profiling to fetal human prostate, normal human prostate fibroblasts (NPFs) and CAFs to identify molecules expressed in prostatic stroma Overall design: Each sample was used for Tag library construction, by Solexa Inc GSM614544: Normal prostate fibroblasts (NPF) GSM614544: Normal prostate fibroblasts (NPF) RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell type;;Fibroblasts|development stage;;Adult|source_name;;Normal prostate fibroblasts (NPF)|tissue;;Prostate GEO Accession;;GSM614544 16 GSM614544 Normal prostate fibroblasts (NPF) 39342256 2458891 2011-10-24 09:22:16 25736887 39342256 2458891 1 2458891 index:0,count:2458891,average:16,stdev:0 GSM614544_1 GEO 1.58 4.93 0.68 28493439 30765578 4846737 6865175 107.97 141.65 0 0 0 0 0 0 14.34 84.47 7752457 256040 7752457 256040 43.1 77.2 7752457 769776 7752457 233984 7193740 25.25 0.00 0 60.30 0 19.16 0 8.21 0 0.00 0 0.00 0 1785828 0 16 0 15.99 0 0.00 0 0.00 0 0.00 0 0.00 0 491.78 0 0.00 0 0 0 2458891 0 1482724 0 471141 0 201922 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12.33 0 303104 0 0 0 0.0 2458891.0 1785828.0 0.0 1482724.0 471141.0 201922.0 0.0 0.0 303104.0 72.6 0.0 60.3 19.2 8.2 0.0 0.0 12.3 792107 SRR071162 SRP004042 SRS118735 SRX030067 SRA025891 GEO Identification of stromally expressed molecules in the prostate by Tag profiling of cancer-associated fibroblasts, normal fibroblasts and fetal prostate The stromal microenvironment plays key roles in prostate development and cancer. Cancer associated fibroblasts (CAFs) and other stromal cells stimulate tumourigenesis via several mechanisms including the expression of pro-tumourigenic factors. Mesenchyme (embryonic stroma) controls prostate organogenesis, and in some circumstances can re-differentiate prostate tumours. Epithelia are regulated by powerful paracrine signalling from the stroma in both development and disease, and identification of these stromal signals is important. We have applied next-generation Tag profiling to fetal human prostate, normal human prostate fibroblasts (NPFs) and CAFs to identify molecules expressed in prostatic stroma Overall design: Each sample was used for Tag library construction, by Solexa Inc GSM614545: Fetal prostate (EMB) GSM614545: Fetal prostate (EMB) RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer cell type;;Fibroblasts and Epithelia|development stage;;Fetal|source_name;;Fetal prostate (EMB)|tissue;;Prostate GEO Accession;;GSM614545 16 GSM614545 Fetal prostate (EMB) 58371040 3648190 2011-10-24 09:22:16 34529919 58371040 3648190 1 3648190 index:0,count:3648190,average:16,stdev:0 GSM614545_1 GEO 1.26 4.63 0.41 39983615 42453034 7516356 10778547 106.18 143.4 0 0 0 0 0 0 16.21 86.36 10439387 405866 10439387 405866 43.44 78.53 10439387 1087876 10439387 369052 10031396 25.09 0.00 0 55.77 0 19.51 0 11.84 0 0.00 0 0.00 0 2504474 0 16 0 15.99 0 0.00 0 0.00 0 0.00 0 0.00 0 505.13 0 0.00 0 0 0 3648190 0 2034530 0 711737 0 431979 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12.88 0 469944 0 0 0 0.0 3648190.0 2504474.0 0.0 2034530.0 711737.0 431979.0 0.0 0.0 469944.0 68.6 0.0 55.8 19.5 11.8 0.0 0.0 12.9 564158 SRR079377 SRP004847 SRS150252 SRX033283 SRA027222 GEO Altered antisense-to-sense transcript ratios in breast cancer: Sage-Seq Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Overall design: Global transcriptome profilings of 12 samples in normal and 9 samples in cancer from clinical breast tissue using Sage-Seq. GSM622192: breast_epithelium_normal_CD24_P1 GSM622192: breast_epithelium_normal_CD24_P1 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD24+|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM622192 17 GSM622192 breast_epithelium_normal_CD24_P1 96147410 5655730 2010-12-20 10:15:20 55463777 96147410 5655730 1 5655730 index:0,count:5655730,average:17,stdev:0 GSM622192_1 GEO 4.03 2.88 0.16 80286465 109240543 34492201 53577293 136.06 155.33 0 0 0 0 0 0 38.25 89.35 11529678 1814328 11529678 1814328 62.38 82.96 11529678 2958439 11529678 1684442 9542781 11.89 0.00 0 47.96 0 5.25 0 10.89 0 0.00 0 0.00 0 4742931 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 407.21 0 0.00 0 0 0 5655730 0 2712442 0 297093 0 615706 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 4 0 35.90 0 2030489 0 0 0 0.0 5655730.0 4742931.0 0.0 2712442.0 297093.0 615706.0 0.0 0.0 2030489.0 83.9 0.0 48.0 5.3 10.9 0.0 0.0 35.9 564164 SRR079378 SRP004847 SRS150253 SRX033284 SRA027222 GEO Altered antisense-to-sense transcript ratios in breast cancer: Sage-Seq Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Overall design: Global transcriptome profilings of 12 samples in normal and 9 samples in cancer from clinical breast tissue using Sage-Seq. GSM622193: breast_epithelium_normal_CD44_P1 GSM622193: breast_epithelium_normal_CD44_P1 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD44+|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM622193 17 GSM622193 breast_epithelium_normal_CD44_P1 78985043 4646179 2010-12-20 10:15:20 42427370 78985043 4646179 1 4646179 index:0,count:4646179,average:17,stdev:0 GSM622193_1 GEO 1.64 3.22 0.16 66216897 86773721 30859017 46592493 131.04 150.99 0 0 0 0 0 0 41.2 88.75 9127835 1612180 9127835 1612180 61.39 82.84 9127835 2402050 9127835 1504895 8805005 13.30 0.00 0 45.12 0 5.12 0 10.66 0 0.00 0 0.00 0 3913007 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 278.77 0 0.00 0 0 0 4646179 0 2096485 0 238070 0 495102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 39.10 0 1816522 0 0 0 0.0 4646179.0 3913007.0 0.0 2096485.0 238070.0 495102.0 0.0 0.0 1816522.0 84.2 0.0 45.1 5.1 10.7 0.0 0.0 39.1 564173 SRR079379 SRP004847 SRS150254 SRX033285 SRA027222 GEO Altered antisense-to-sense transcript ratios in breast cancer: Sage-Seq Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Overall design: Global transcriptome profilings of 12 samples in normal and 9 samples in cancer from clinical breast tissue using Sage-Seq. GSM622194: breast_epithelium_normal_CD24_P2 GSM622194: breast_epithelium_normal_CD24_P2 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD24+|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM622194 18 GSM622194 breast_epithelium_normal_CD24_P2 96393492 5355194 2010-12-20 10:15:20 75754220 96393492 5355194 1 5355194 index:0,count:5355194,average:18,stdev:0 GSM622194_1 GEO 3.2 3.36 0.16 82335526 112886483 35529322 51724297 137.11 145.58 0 0 0 0 0 0 35.34 83.13 11428933 1657404 11428933 1657404 65.26 77.15 11428933 3060743 11428933 1538345 8126003 9.87 0.00 0 50.35 0 5.33 0 7.09 0 0.00 0 0.00 0 4690037 0 18 0 17.82 0 0.00 0 0.00 0 0.00 0 0.00 0 292.10 0 0.01 0 0 0 5355194 0 2696177 0 285430 0 379727 0 0 0 0 0 0 0 0 0 0 0 62 0 0 0 62 0 37.23 0 1993860 0 0 0 0.0 5355194.0 4690037.0 0.0 2696177.0 285430.0 379727.0 0.0 0.0 1993860.0 87.6 0.0 50.3 5.3 7.1 0.0 0.0 37.2 564229 SRR079380 SRP004847 SRS150255 SRX033286 SRA027222 GEO Altered antisense-to-sense transcript ratios in breast cancer: Sage-Seq Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Overall design: Global transcriptome profilings of 12 samples in normal and 9 samples in cancer from clinical breast tissue using Sage-Seq. GSM622195: breast_epithelium_normal_CD44_P2 GSM622195: breast_epithelium_normal_CD44_P2 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD44+|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM622195 18 GSM622195 breast_epithelium_normal_CD44_P2 101228940 5623830 2010-12-20 10:15:20 85484327 101228940 5623830 1 5623830 index:0,count:5623830,average:18,stdev:0 GSM622195_1 GEO 2.65 3.25 0.14 85908686 115942059 38744399 55310569 134.96 142.76 0 0 0 0 0 0 36.89 83.03 11566553 1805525 11566553 1805525 66.14 77.56 11566553 3237217 11566553 1686577 8693507 10.12 0.00 0 48.37 0 4.99 0 7.97 0 0.00 0 0.00 0 4894775 0 18 0 17.82 0 0.00 0 0.00 0 0.00 0 0.00 0 396.98 0 0.01 0 0 0 5623830 0 2720117 0 280846 0 448209 0 0 0 0 0 0 0 0 0 0 0 80 0 0 0 80 0 38.67 0 2174658 0 0 0 0.0 5623830.0 4894775.0 0.0 2720117.0 280846.0 448209.0 0.0 0.0 2174658.0 87.0 0.0 48.4 5.0 8.0 0.0 0.0 38.7 564238 SRR079381 SRP004847 SRS150256 SRX033287 SRA027222 GEO Altered antisense-to-sense transcript ratios in breast cancer: Sage-Seq Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Overall design: Global transcriptome profilings of 12 samples in normal and 9 samples in cancer from clinical breast tissue using Sage-Seq. GSM622196: breast_epithelium_normal_CD24_P3 GSM622196: breast_epithelium_normal_CD24_P3 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD24+|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM622196 17 GSM622196 breast_epithelium_normal_CD24_P3 67630352 3978256 2010-12-20 10:15:20 36073210 67630352 3978256 1 3978256 index:0,count:3978256,average:17,stdev:0 GSM622196_1 GEO 4.92 2.84 0.15 58404963 75443068 24841822 34054282 129.17 137.08 0 0 0 0 0 0 33.24 78.43 8512422 1146962 8512422 1146962 58.44 72.91 8512422 2016404 8512422 1066163 6312668 10.81 0.00 0 49.97 0 5.56 0 7.71 0 0.00 0 0.00 0 3450361 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 333.06 0 0.00 0 0 0 3978256 0 1987967 0 221122 0 306773 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 5 0 36.76 0 1462394 0 0 0 0.0 3978256.0 3450361.0 0.0 1987967.0 221122.0 306773.0 0.0 0.0 1462394.0 86.7 0.0 50.0 5.6 7.7 0.0 0.0 36.8 564245 SRR079382 SRP004847 SRS150257 SRX033288 SRA027222 GEO Altered antisense-to-sense transcript ratios in breast cancer: Sage-Seq Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Overall design: Global transcriptome profilings of 12 samples in normal and 9 samples in cancer from clinical breast tissue using Sage-Seq. GSM622197: breast_epithelium_normal_CD44_P3 GSM622197: breast_epithelium_normal_CD44_P3 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD44+|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM622197 17 GSM622197 breast_epithelium_normal_CD44_P3 73998212 4352836 2010-12-20 10:15:20 38062910 73998212 4352836 1 4352836 index:0,count:4352836,average:17,stdev:0 GSM622197_1 GEO 3.34 3.3 0.15 63061136 82857518 31225440 45130084 131.39 144.53 0 0 0 0 0 0 41.08 83.22 8384268 1529557 8384268 1529557 62.54 78.61 8384268 2328616 8384268 1444745 7330488 11.62 0.00 0 43.32 0 4.59 0 9.87 0 0.00 0 0.00 0 3723304 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 265.60 0 0.00 0 0 0 4352836 0 1885435 0 199910 0 429622 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 5 0 42.22 0 1837869 0 0 0 0.0 4352836.0 3723304.0 0.0 1885435.0 199910.0 429622.0 0.0 0.0 1837869.0 85.5 0.0 43.3 4.6 9.9 0.0 0.0 42.2 564253 SRR079383 SRP004847 SRS150258 SRX033289 SRA027222 GEO Altered antisense-to-sense transcript ratios in breast cancer: Sage-Seq Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Overall design: Global transcriptome profilings of 12 samples in normal and 9 samples in cancer from clinical breast tissue using Sage-Seq. GSM622198: breast_epithelium_cancer_CD24_IDC36 GSM622198: breast_epithelium_cancer_CD24_IDC36 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD24+|cell type;;epithelial cell|disease state;;cancer|source_name;;biopsy and surgery|tissue;;breast GEO Accession;;GSM622198 17 GSM622198 breast_epithelium_cancer_CD24_IDC36 96388861 5669933 2010-12-20 10:15:20 64262954 96388861 5669933 1 5669933 index:0,count:5669933,average:17,stdev:0 GSM622198_1 GEO 5.57 3.77 0.26 81380859 103472863 30508972 43619094 127.15 142.97 0 0 0 0 0 0 31.42 84.33 12906900 1515180 12906900 1515180 57.23 76.97 12906900 2760315 12906900 1382894 13158988 16.17 0.00 0 53.37 0 6.73 0 8.21 0 0.00 0 0.00 0 4823087 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 295.82 0 0.00 0 0 0 5669933 0 3026318 0 381571 0 465275 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 14 0 31.69 0 1796769 0 0 0 0.0 5669933.0 4823087.0 0.0 3026318.0 381571.0 465275.0 0.0 0.0 1796769.0 85.1 0.0 53.4 6.7 8.2 0.0 0.0 31.7 564261 SRR079384 SRP004847 SRS150259 SRX033290 SRA027222 GEO Altered antisense-to-sense transcript ratios in breast cancer: Sage-Seq Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Overall design: Global transcriptome profilings of 12 samples in normal and 9 samples in cancer from clinical breast tissue using Sage-Seq. GSM622199: breast_epithelium_cancer_SSEA4_IDC38 GSM622199: breast_epithelium_cancer_SSEA4_IDC38 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;R&D Systems|cell marker;;SSEA4+|cell type;;epithelial cell|disease state;;cancer|source_name;;biopsy and surgery|tissue;;breast GEO Accession;;GSM622199 17 GSM622199 breast_epithelium_cancer_SSEA4_IDC38 54389290 3199370 2010-12-20 10:15:20 43254814 54389290 3199370 1 3199370 index:0,count:3199370,average:17,stdev:0 GSM622199_1 GEO 1.89 4.16 0.6 47145460 53723923 15494679 21433689 113.95 138.33 0 0 0 0 0 0 27.7 84.63 7820161 771883 7820161 771883 51.19 79.74 7820161 1426591 7820161 727207 8800313 18.67 0.00 0 58.60 0 8.72 0 4.18 0 0.00 0 0.00 0 2786731 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 500.77 0 0.00 0 0 0 3199370 0 1874702 0 278993 0 133646 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 28.51 0 912029 0 0 0 0.0 3199370.0 2786731.0 0.0 1874702.0 278993.0 133646.0 0.0 0.0 912029.0 87.1 0.0 58.6 8.7 4.2 0.0 0.0 28.5 254350 SRR088863 SRP004965 SRS150670 SRX036725 SRA027371 GEO Epigenetic regulation of cell type-specific expression patterns in the human mammary epithelium [SAGE-Seq] Here we describe the application of high-throughput sequencing technology for profiling histone and DNA methylation, and gene expression patterns of normal human mammary progenitor-enriched and luminal lineage-committed cells. We observed significant differences in histone H3 lysine 27 tri-methylation (H3K27me3) enrichment and DNA methylation of genes expressed in a cell type-specific manner, suggesting their regulation by epigenetic mechanisms and a dynamic interplay between the two processes that together define developmental potential. The technologies we developed and the epigenetically regulated genes we identified will accelerate the characterization of primary cell epigenomes and the dissection of human mammary epithelial lineage-commitment and luminal differentiation. Overall design: Global transcriptome profilings of 15 samples in normal breast tissue using Sage-Seq. GSM643913: N34_CD44+_SAGESeq GSM643913: N34_CD44+_SAGESeq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD44+|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM643913 17 GSM643913 N34_CD44+_SAGESeq 87365312 5139136 2011-03-01 13:29:00 48213804 87365312 5139136 1 5139136 index:0,count:5139136,average:17,stdev:0 GSM643913_1 GEO 2.11 3.49 0.13 77134037 102015210 35554892 54755577 132.26 154.0 0 0 0 0 0 0 41.41 90.19 10693901 1887909 10693901 1887909 65.42 84.96 10693901 2982607 10693901 1778382 9777610 12.68 0.00 0 47.99 0 3.55 0 7.73 0 0.00 0 0.00 0 4559407 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 355.79 0 0.00 0 0 0 5139136 0 2466100 0 182562 0 397167 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 40.73 0 2093307 0 0 0 0.0 5139136.0 4559407.0 0.0 2466100.0 182562.0 397167.0 0.0 0.0 2093307.0 88.7 0.0 48.0 3.6 7.7 0.0 0.0 40.7 127177 SRR088864 SRP004965 SRS150670 SRX036725 SRA027371 GEO Epigenetic regulation of cell type-specific expression patterns in the human mammary epithelium [SAGE-Seq] Here we describe the application of high-throughput sequencing technology for profiling histone and DNA methylation, and gene expression patterns of normal human mammary progenitor-enriched and luminal lineage-committed cells. We observed significant differences in histone H3 lysine 27 tri-methylation (H3K27me3) enrichment and DNA methylation of genes expressed in a cell type-specific manner, suggesting their regulation by epigenetic mechanisms and a dynamic interplay between the two processes that together define developmental potential. The technologies we developed and the epigenetically regulated genes we identified will accelerate the characterization of primary cell epigenomes and the dissection of human mammary epithelial lineage-commitment and luminal differentiation. Overall design: Global transcriptome profilings of 15 samples in normal breast tissue using Sage-Seq. GSM643913: N34_CD44+_SAGESeq GSM643913: N34_CD44+_SAGESeq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD44+|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM643913 17 GSM643913 N34_CD44+_SAGESeq 85811053 5047709 2011-03-01 13:29:00 46803961 85811053 5047709 1 5047709 index:0,count:5047709,average:17,stdev:0 GSM643913_2 GEO 2.1 3.49 0.13 75887720 100353555 35009580 53905290 132.24 153.97 0 0 0 0 0 0 41.44 90.19 10518477 1858975 10518477 1858975 65.4 84.94 10518477 2933560 10518477 1750789 9657416 12.73 0.00 0 48.03 0 3.54 0 7.60 0 0.00 0 0.00 0 4485720 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 279.57 0 0.00 0 0 0 5047709 0 2424508 0 178543 0 383446 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 11 0 40.83 0 2061212 0 0 0 0.0 5047709.0 4485720.0 0.0 2424508.0 178543.0 383446.0 0.0 0.0 2061212.0 88.9 0.0 48.0 3.5 7.6 0.0 0.0 40.8 127179 SRR088865 SRP004965 SRS150671 SRX036726 SRA027371 GEO Epigenetic regulation of cell type-specific expression patterns in the human mammary epithelium [SAGE-Seq] Here we describe the application of high-throughput sequencing technology for profiling histone and DNA methylation, and gene expression patterns of normal human mammary progenitor-enriched and luminal lineage-committed cells. We observed significant differences in histone H3 lysine 27 tri-methylation (H3K27me3) enrichment and DNA methylation of genes expressed in a cell type-specific manner, suggesting their regulation by epigenetic mechanisms and a dynamic interplay between the two processes that together define developmental potential. The technologies we developed and the epigenetically regulated genes we identified will accelerate the characterization of primary cell epigenomes and the dissection of human mammary epithelial lineage-commitment and luminal differentiation. Overall design: Global transcriptome profilings of 15 samples in normal breast tissue using Sage-Seq. GSM643914: N58_CD24+_SAGESeq GSM643914: N58_CD24+_SAGESeq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer antibody vender;;BD-Pharmingen|cell marker;;CD24+|cell type;;epithelial cell|disease state;;normal|source_name;;reduction mammoplasty|tissue;;breast GEO Accession;;GSM643914 17 GSM643914 N58_CD24+_SAGESeq 167381184 9845952 2011-03-01 13:29:00 132952969 167381184 9845952 1 9845952 index:0,count:9845952,average:17,stdev:0 GSM643914_1 GEO 3.37 3.4 0.2 141246214 185325850 61505855 91257651 131.21 148.37 0 0 0 0 0 0 39.18 90.26 20455270 3267668 20455270 3267668 62.0 83.71 20455270 5170878 20455270 3030274 18357423 13.00 0.00 0 47.94 0 5.20 0 10.09 0 0.00 0 0.00 0 8340667 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 337.58 0 0.00 0 0 0 9845952 0 4720529 0 511750 0 993535 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 36.77 0 3620138 0 0 0 0.0 9845952.0 8340667.0 0.0 4720529.0 511750.0 993535.0 0.0 0.0 3620138.0 84.7 0.0 47.9 5.2 10.1 0.0 0.0 36.8 317771 SRR091652 SRP005279 SRS152391 SRX037913 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652276: DGE_dic9-20_1 GSM652276: DGE_dic9-20_1 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;dic(9;20)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652276 18 GSM652276 DGE_dic9-20_1 238646808 13258156 2011-12-21 09:09:34 171041592 238646808 13258156 1 13258156 index:0,count:13258156,average:18,stdev:0 GSM652276_1 GEO 3.23 4.16 0.26 216831569 275043475 97713972 131295568 126.85 134.37 0 0 0 0 0 0 36.31 81.94 31171089 4486464 31171089 4486464 65.15 75.46 31171089 8050092 31171089 4131745 26844002 12.38 0.00 0 51.90 0 4.30 0 2.50 0 0.00 0 0.00 0 12356660 0 18 0 17.85 0 0.00 0 0.00 0 0.00 0 0.00 0 463.39 0 0.01 0 0 0 13258156 0 6881153 0 570244 0 331252 0 0 0 0 0 0 0 0 0 0 0 216 0 0 0 216 0 41.30 0 5475507 0 0 0 0.0 13258156.0 12356660.0 0.0 6881153.0 570244.0 331252.0 0.0 0.0 5475507.0 93.2 0.0 51.9 4.3 2.5 0.0 0.0 41.3 317775 SRR091653 SRP005279 SRS152392 SRX037914 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652277: DGE_dic9-20_2 GSM652277: DGE_dic9-20_2 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;dic(9;20)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652277 17 GSM652277 DGE_dic9-20_2 425410074 25024122 2011-12-21 09:09:34 210337086 425410074 25024122 1 25024122 index:0,count:25024122,average:17,stdev:0 GSM652277_1 GEO 4.74 4.06 0.39 366942208 468217034 145892904 213802575 127.6 146.55 0 0 0 0 0 0 35.78 90.44 55164532 7767260 55164532 7767260 62.4 83.04 55164532 13548328 55164532 7132081 47923525 13.06 0.00 0 52.44 0 10.62 0 2.62 0 0.00 0 0.00 0 21711195 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 692.98 0 0.00 0 0 0 25024122 0 13122437 0 2658112 0 654815 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 10 0 34.32 0 8588758 0 0 0 0.0 25024122.0 21711195.0 0.0 13122437.0 2658112.0 654815.0 0.0 0.0 8588758.0 86.8 0.0 52.4 10.6 2.6 0.0 0.0 34.3 317779 SRR091654 SRP005279 SRS152393 SRX037915 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652278: DGE_dic9-20_3 GSM652278: DGE_dic9-20_3 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;dic(9;20)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652278 18 GSM652278 DGE_dic9-20_3 252775962 14043109 2011-12-21 09:09:34 177508188 252775962 14043109 1 14043109 index:0,count:14043109,average:18,stdev:0 GSM652278_1 GEO 4.07 4.11 0.33 228944631 300143309 102781184 140448911 131.1 136.65 0 0 0 0 0 0 36.9 83.57 32620589 4805495 32620589 4805495 68.08 77.55 32620589 8866751 32620589 4459269 25636840 11.20 0.00 0 51.80 0 4.45 0 2.80 0 0.00 0 0.00 0 13023959 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 417.81 0 0.01 0 0 0 14043109 0 7273860 0 625294 0 393855 0 0 0 1 0 0 0 0 0 0 0 102 0 0 0 102 0 40.95 0 5750099 0 0 0 0.0 14043109.0 13023959.0 0.0 7273860.0 625294.0 393855.0 0.0 1.0 5750099.0 92.7 0.0 51.8 4.5 2.8 0.0 0.0 40.9 317783 SRR091655 SRP005279 SRS152394 SRX037916 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652279: DGE_HeH_1 GSM652279: DGE_HeH_1 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;High Hyperploidy (HeH)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652279 18 GSM652279 DGE_HeH_1 138673728 7704096 2011-12-21 09:09:34 112885820 138673728 7704096 1 7704096 index:0,count:7704096,average:18,stdev:0 GSM652279_1 GEO 2.08 4.69 0.3 118726713 143519241 48171718 65296594 120.88 135.55 0 0 0 0 0 0 32.7 81.92 18386967 2224028 18386967 2224028 55.72 77.21 18386967 3790046 18386967 2096407 17682227 14.89 0.00 0 53.05 0 7.55 0 4.16 0 0.00 0 0.00 0 6801753 0 18 0 17.74 0 0.00 0 0.00 0 0.00 0 0.00 0 616.33 0 0.01 0 0 0 7704096 0 4086719 0 581508 0 320835 0 0 0 0 0 0 0 0 0 0 0 28 0 0 0 28 0 35.24 0 2715034 0 0 0 0.0 7704096.0 6801753.0 0.0 4086719.0 581508.0 320835.0 0.0 0.0 2715034.0 88.3 0.0 53.0 7.5 4.2 0.0 0.0 35.2 635572 SRR091656 SRP005279 SRS152395 SRX037917 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652280: DGE_HeH_2a GSM652280: DGE_HeH_2a RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;High Hyperploidy (HeH)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652280 17 GSM652280 DGE_HeH_2a 397534103 23384359 2011-12-21 09:09:34 194384922 397534103 23384359 1 23384359 index:0,count:23384359,average:17,stdev:0 GSM652280_1 GEO 2.43 4.8 0.45 340810469 412805550 119710984 172735445 121.12 144.29 0 0 0 0 0 0 31.51 90.0 56443397 6341883 56443397 6341883 57.79 83.27 56443397 11631109 56443397 5867159 50740329 14.89 0.00 0 55.93 0 10.48 0 3.46 0 0.00 0 0.00 0 20125338 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 584.61 0 0.00 0 0 0 23384359 0 13079184 0 2449693 0 809328 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 7 0 30.13 0 7046154 0 0 0 0.0 23384359.0 20125338.0 0.0 13079184.0 2449693.0 809328.0 0.0 0.0 7046154.0 86.1 0.0 55.9 10.5 3.5 0.0 0.0 30.1 635580 SRR091657 SRP005279 SRS152396 SRX037918 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652281: DGE_HeH_2b GSM652281: DGE_HeH_2b RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;High Hyperploidy (HeH)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652281 18 GSM652281 DGE_HeH_2b 285025896 15834772 2011-12-21 09:09:34 210279389 285025896 15834772 1 15834772 index:0,count:15834772,average:18,stdev:0 GSM652281_1 GEO 3.42 4.6 0.38 254612758 318556983 107277291 142311081 125.11 132.66 0 0 0 0 0 0 33.09 79.8 38797178 4786589 38797178 4786589 63.06 73.8 38797178 9121584 38797178 4426377 32061317 12.59 0.00 0 53.48 0 5.82 0 2.82 0 0.00 0 0.00 0 14465788 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 475.04 0 0.01 0 0 0 15834772 0 8467913 0 921726 0 447258 0 0 0 0 0 0 0 0 0 0 0 113 0 0 0 113 0 37.88 0 5997875 0 0 0 0.0 15834772.0 14465788.0 0.0 8467913.0 921726.0 447258.0 0.0 0.0 5997875.0 91.4 0.0 53.5 5.8 2.8 0.0 0.0 37.9 317795 SRR091658 SRP005279 SRS152397 SRX037919 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652282: DGE_HeH_3 GSM652282: DGE_HeH_3 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;High Hyperploidy (HeH)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652282 18 GSM652282 DGE_HeH_3 176921172 9828954 2011-12-21 09:09:34 128890228 176921172 9828954 1 9828954 index:0,count:9828954,average:18,stdev:0 GSM652282_1 GEO 2.93 5.09 0.31 157780256 204902267 65725584 92952218 129.87 141.42 0 0 0 0 0 0 34.18 83.4 23915991 3076088 23915991 3076088 67.01 75.74 23915991 6031117 23915991 2793607 15779045 10.00 0.00 0 54.04 0 5.82 0 2.61 0 0.00 0 0.00 0 9000264 0 18 0 17.82 0 0.00 0 0.00 0 0.00 0 0.00 0 426.32 0 0.02 0 0 0 9828954 0 5311795 0 572109 0 256581 0 0 0 0 0 0 0 0 0 0 0 130 0 0 0 130 0 37.53 0 3688469 0 0 0 0.0 9828954.0 9000264.0 0.0 5311795.0 572109.0 256581.0 0.0 0.0 3688469.0 91.6 0.0 54.0 5.8 2.6 0.0 0.0 37.5 635596 SRR091659 SRP005279 SRS152398 SRX037920 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652283: DGE_HeH_4 GSM652283: DGE_HeH_4 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;High Hyperploidy (HeH)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652283 18 GSM652283 DGE_HeH_4 201765708 11209206 2011-12-21 09:09:34 146023149 201765708 11209206 1 11209206 index:0,count:11209206,average:18,stdev:0 GSM652283_1 GEO 2.99 5.12 0.36 182246139 234465525 77427535 105898231 128.65 136.77 0 0 0 0 0 0 34.52 82.62 26408676 3582649 26408676 3582649 67.24 75.64 26408676 6977661 26408676 3280208 18501927 10.15 0.00 0 53.89 0 5.26 0 2.16 0 0.00 0 0.00 0 10377298 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 388.01 0 0.01 0 0 0 11209206 0 6040952 0 589743 0 242164 0 0 0 1 0 0 0 0 0 0 0 195 0 0 0 195 0 38.69 0 4336346 0 0 0 0.0 11209206.0 10377298.0 0.0 6040952.0 589743.0 242164.0 0.0 1.0 4336346.0 92.6 0.0 53.9 5.3 2.2 0.0 0.0 38.7 635652 SRR091660 SRP005279 SRS152399 SRX037921 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652284: DGE_HeH_5 GSM652284: DGE_HeH_5 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;High Hyperploidy (HeH)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652284 18 GSM652284 DGE_HeH_5 170524224 9473568 2011-12-21 09:09:34 136032412 170524224 9473568 1 9473568 index:0,count:9473568,average:18,stdev:0 GSM652284_1 GEO 1.65 5.06 0.39 151466244 181359314 66666469 87379402 119.74 131.07 0 0 0 0 0 0 34.33 79.29 21627412 2957179 21627412 2957179 59.21 73.09 21627412 5100017 21627412 2725666 21137647 13.96 0.00 0 51.55 0 5.75 0 3.34 0 0.00 0 0.00 0 8613216 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 598.33 0 0.01 0 0 0 9473568 0 4883854 0 544377 0 315975 0 0 0 0 0 0 0 0 0 0 0 54 0 0 0 54 0 39.37 0 3729362 0 0 0 0.0 9473568.0 8613216.0 0.0 4883854.0 544377.0 315975.0 0.0 0.0 3729362.0 90.9 0.0 51.6 5.7 3.3 0.0 0.0 39.4 635660 SRR091661 SRP005279 SRS152400 SRX037922 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652285: DGE_HeH_6 GSM652285: DGE_HeH_6 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;High Hyperploidy (HeH)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652285 18 GSM652285 DGE_HeH_6 225018522 12501029 2011-12-21 09:09:34 180340437 225018522 12501029 1 12501029 index:0,count:12501029,average:18,stdev:0 GSM652285_1 GEO 3.27 4.65 0.32 194328452 240493083 80351431 112445370 123.76 139.94 0 0 0 0 0 0 32.09 78.64 29981839 3546975 29981839 3546975 58.47 74.53 29981839 6462935 29981839 3361461 25154531 12.94 0.00 0 52.34 0 7.83 0 3.74 0 0.00 0 0.00 0 11053567 0 18 0 17.82 0 0.00 0 0.00 0 0.00 0 0.00 0 463.96 0 0.01 0 0 0 12501029 0 6543425 0 979372 0 468090 0 0 0 0 0 0 0 0 0 0 0 28 0 0 0 28 0 36.08 0 4510142 0 0 0 0.0 12501029.0 11053567.0 0.0 6543425.0 979372.0 468090.0 0.0 0.0 4510142.0 88.4 0.0 52.3 7.8 3.7 0.0 0.0 36.1 635668 SRR091662 SRP005279 SRS152401 SRX037923 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652286: DGE_HeH_7 GSM652286: DGE_HeH_7 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;High Hyperploidy (HeH)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652286 18 GSM652286 DGE_HeH_7 258571152 14365064 2011-12-21 09:09:34 188584037 258571152 14365064 1 14365064 index:0,count:14365064,average:18,stdev:0 GSM652286_1 GEO 1.88 5.29 0.48 227699542 276629191 93227463 122756798 121.49 131.67 0 0 0 0 0 0 32.15 79.62 34455406 4150042 34455406 4150042 59.89 73.42 34455406 7731546 34455406 3826541 29535627 12.97 0.00 0 53.58 0 7.66 0 2.47 0 0.00 0 0.00 0 12909523 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 423.89 0 0.01 0 0 0 14365064 0 7697396 0 1100438 0 355103 0 0 0 0 0 0 0 0 0 0 0 77 0 0 0 77 0 36.28 0 5212127 0 0 0 0.0 14365064.0 12909523.0 0.0 7697396.0 1100438.0 355103.0 0.0 0.0 5212127.0 89.9 0.0 53.6 7.7 2.5 0.0 0.0 36.3 635676 SRR091663 SRP005279 SRS152402 SRX037924 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652287: DGE_HeH_8 GSM652287: DGE_HeH_8 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;High Hyperploidy (HeH)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652287 18 GSM652287 DGE_HeH_8 113331204 6296178 2011-12-21 09:09:34 81848472 113331204 6296178 1 6296178 index:0,count:6296178,average:18,stdev:0 GSM652287_1 GEO 3.35 4.67 0.33 101408750 133389678 44184759 63006526 131.54 142.6 0 0 0 0 0 0 36.18 84.54 14485437 2099576 14485437 2099576 67.75 78.38 14485437 3931813 14485437 1946642 9825000 9.69 0.00 0 52.73 0 4.32 0 3.51 0 0.00 0 0.00 0 5803441 0 18 0 17.79 0 0.00 0 0.00 0 0.00 0 0.00 0 453.32 0 0.02 0 0 0 6296178 0 3319897 0 271802 0 220934 0 0 0 1 0 0 0 0 0 0 0 285 0 0 0 285 0 39.45 0 2483544 0 0 0 0.0 6296178.0 5803441.0 0.0 3319897.0 271802.0 220934.0 0.0 1.0 2483544.0 92.2 0.0 52.7 4.3 3.5 0.0 0.0 39.4 635685 SRR091664 SRP005279 SRS152403 SRX037925 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652288: DGE_t12-21_1 GSM652288: DGE_t12-21_1 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;t(12;21) ETV6-RUNX1|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652288 18 GSM652288 DGE_t12-21_1 286924392 15940244 2011-12-21 09:09:34 213441551 286924392 15940244 1 15940244 index:0,count:15940244,average:18,stdev:0 GSM652288_1 GEO 5.87 3.42 0.21 255981841 343583301 112882952 166382284 134.22 147.39 0 0 0 0 0 0 35.3 81.11 38124939 5151404 38124939 5151404 65.77 77.94 38124939 9598387 38124939 4950589 28156283 11.00 0.00 0 51.70 0 6.04 0 2.41 0 0.00 0 0.00 0 14592872 0 18 0 17.77 0 0.00 0 0.00 0 0.00 0 0.00 0 526.47 0 0.01 0 0 0 15940244 0 8241432 0 963451 0 383913 0 0 0 8 0 0 0 0 0 0 0 127 0 0 0 127 0 39.85 0 6351440 0 0 0 0.0 15940244.0 14592872.0 0.0 8241432.0 963451.0 383913.0 0.0 8.0 6351440.0 91.5 0.0 51.7 6.0 2.4 0.0 0.0 39.8 635692 SRR091665 SRP005279 SRS152404 SRX037926 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652289: DGE_t12-21_2 GSM652289: DGE_t12-21_2 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;t(12;21) ETV6-RUNX1|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652289 17 GSM652289 DGE_t12-21_2 397975865 23410345 2011-12-21 09:09:34 189673052 397975865 23410345 1 23410345 index:0,count:23410345,average:17,stdev:0 GSM652289_1 GEO 1.26 4.45 0.43 350136166 424070819 142698292 201553524 121.12 141.24 0 0 0 0 0 0 37.35 91.92 52900948 7720499 52900948 7720499 61.43 86.06 52900948 12698118 52900948 7228184 44873468 12.82 0.00 0 52.42 0 9.07 0 2.63 0 0.00 0 0.00 0 20670824 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 501.65 0 0.00 0 0 0 23410345 0 12271518 0 2123748 0 615773 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 14 0 35.88 0 8399306 0 0 0 0.0 23410345.0 20670824.0 0.0 12271518.0 2123748.0 615773.0 0.0 0.0 8399306.0 88.3 0.0 52.4 9.1 2.6 0.0 0.0 35.9 635700 SRR091666 SRP005279 SRS152405 SRX037927 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652290: DGE_t12-21_3 GSM652290: DGE_t12-21_3 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;t(12;21) ETV6-RUNX1|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652290 18 GSM652290 DGE_t12-21_3 227532186 12640677 2011-12-21 09:09:34 166412603 227532186 12640677 1 12640677 index:0,count:12640677,average:18,stdev:0 GSM652290_1 GEO 1.94 4.42 0.35 203195590 248985397 90718975 121789890 122.53 134.25 0 0 0 0 0 0 34.17 77.63 29012405 3941427 29012405 3941427 60.54 72.53 29012405 6982271 29012405 3682661 26919124 13.25 0.00 0 51.07 0 5.69 0 3.07 0 0.00 0 0.00 0 11533432 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 479.02 0 0.01 0 0 0 12640677 0 6455947 0 718686 0 388559 0 0 0 0 0 0 0 0 0 0 0 88 0 0 0 88 0 40.17 0 5077485 0 0 0 0.0 12640677.0 11533432.0 0.0 6455947.0 718686.0 388559.0 0.0 0.0 5077485.0 91.2 0.0 51.1 5.7 3.1 0.0 0.0 40.2 635708 SRR091667 SRP005279 SRS152406 SRX037928 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652291: DGE_t9-22_1 GSM652291: DGE_t9-22_1 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;t(9;22) BCR-ABL1|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652291 18 GSM652291 DGE_t9-22_1 290481300 16137850 2011-12-21 09:09:34 210015364 290481300 16137850 1 16137850 index:0,count:16137850,average:18,stdev:0 GSM652291_1 GEO 3.16 3.89 0.34 256193657 323691220 122861688 165673407 126.35 134.85 0 0 0 0 0 0 37.07 78.56 35183148 5401167 35183148 5401167 62.78 72.02 35183148 9146890 35183148 4951207 32188299 12.56 0.00 0 47.69 0 4.43 0 5.29 0 0.00 0 0.00 0 14570543 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 514.13 0 0.02 0 0 0 16137850 0 7695667 0 714186 0 853121 0 0 0 0 0 0 0 0 0 0 0 352 0 0 0 352 0 42.60 0 6874876 0 0 0 0.0 16137850.0 14570543.0 0.0 7695667.0 714186.0 853121.0 0.0 0.0 6874876.0 90.3 0.0 47.7 4.4 5.3 0.0 0.0 42.6 635716 SRR091668 SRP005279 SRS152407 SRX037929 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652292: DGE_t9-22_2 GSM652292: DGE_t9-22_2 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;t(9;22) BCR-ABL1|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652292 17 GSM652292 DGE_t9-22_2 346389841 20375873 2011-12-21 09:09:34 163164269 346389841 20375873 1 20375873 index:0,count:20375873,average:17,stdev:0 GSM652292_1 GEO 1.12 3.7 0.52 307181497 378719688 123816631 176582074 123.29 142.62 0 0 0 0 0 0 36.03 89.76 48608541 6541406 48608541 6541406 61.37 83.55 48608541 11140992 48608541 6089036 40700242 13.25 0.00 0 53.33 0 8.37 0 2.53 0 0.00 0 0.00 0 18154168 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 444.56 0 0.00 0 0 0 20375873 0 10866323 0 1705751 0 515954 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 7 0 35.77 0 7287845 0 0 0 0.0 20375873.0 18154168.0 0.0 10866323.0 1705751.0 515954.0 0.0 0.0 7287845.0 89.1 0.0 53.3 8.4 2.5 0.0 0.0 35.8 635724 SRR091669 SRP005279 SRS152408 SRX037930 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652293: DGE_t9-22_3 GSM652293: DGE_t9-22_3 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;B-cell precursor (BCP) ALL|bcp all subtype;;t(9;22) BCR-ABL1|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652293 18 GSM652293 DGE_t9-22_3 201537198 11196511 2011-12-21 09:09:34 149498627 201537198 11196511 1 11196511 index:0,count:11196511,average:18,stdev:0 GSM652293_1 GEO 8.66 3.24 0.28 180720721 242402779 62720703 85770094 134.13 136.75 0 0 0 0 0 0 25.95 76.19 29858682 2673184 29858682 2673184 62.41 70.19 29858682 6428500 29858682 2462803 25584684 14.16 0.00 0 60.66 0 5.48 0 2.53 0 0.00 0 0.00 0 10300211 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 463.30 0 0.02 0 0 0 11196511 0 6791500 0 613148 0 283150 0 0 0 2 0 0 0 0 0 0 0 87 0 0 0 87 0 31.34 0 3508711 0 0 0 0.0 11196511.0 10300211.0 0.0 6791500.0 613148.0 283150.0 0.0 2.0 3508711.0 92.0 0.0 60.7 5.5 2.5 0.0 0.0 31.3 635781 SRR091670 SRP005279 SRS152409 SRX037931 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652294: DGE_TALL_1 GSM652294: DGE_TALL_1 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;T-cell lineage ALL (T-ALL)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652294 18 GSM652294 DGE_TALL_1 183564396 10198022 2011-12-21 09:09:34 138584274 183564396 10198022 1 10198022 index:0,count:10198022,average:18,stdev:0 GSM652294_1 GEO 4.77 3.82 0.29 160821871 204147830 59587067 78377043 126.94 131.53 0 0 0 0 0 0 26.93 74.09 26468888 2479616 26468888 2479616 60.17 67.17 26468888 5540577 26468888 2248154 22525546 14.01 0.00 0 57.48 0 6.47 0 3.23 0 0.00 0 0.00 0 9208322 0 18 0 17.80 0 0.00 0 0.00 0 0.00 0 0.00 0 483.06 0 0.03 0 0 0 10198022 0 5861404 0 659829 0 329871 0 0 0 0 0 0 0 0 0 0 0 148 0 0 0 148 0 32.82 0 3346918 0 0 0 0.0 10198022.0 9208322.0 0.0 5861404.0 659829.0 329871.0 0.0 0.0 3346918.0 90.3 0.0 57.5 6.5 3.2 0.0 0.0 32.8 635788 SRR091671 SRP005279 SRS152410 SRX037932 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652295: DGE_TALL_2 GSM652295: DGE_TALL_2 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;T-cell lineage ALL (T-ALL)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652295 18 GSM652295 DGE_TALL_2 192171294 10676183 2011-12-21 09:09:34 155431179 192171294 10676183 1 10676183 index:0,count:10676183,average:18,stdev:0 GSM652295_1 GEO 1.69 4.7 0.4 164205232 193683448 64888846 82982039 117.95 127.88 0 0 0 0 0 0 29.57 75.99 24986545 2760320 24986545 2760320 57.74 66.99 24986545 5390028 24986545 2433493 24091594 14.67 0.00 0 53.42 0 7.68 0 4.87 0 0.00 0 0.00 0 9335754 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 768.69 0 0.01 0 0 0 10676183 0 5703356 0 820205 0 520224 0 0 0 0 0 0 0 0 0 0 0 31 0 0 0 31 0 34.02 0 3632398 0 0 0 0.0 10676183.0 9335754.0 0.0 5703356.0 820205.0 520224.0 0.0 0.0 3632398.0 87.4 0.0 53.4 7.7 4.9 0.0 0.0 34.0 635796 SRR091672 SRP005279 SRS152411 SRX037933 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652296: DGE_TALL_3 GSM652296: DGE_TALL_3 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;T-cell lineage ALL (T-ALL)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow|tissue;;Bone marrow GEO Accession;;GSM652296 17 GSM652296 DGE_TALL_3 245365369 14433257 2011-12-21 09:09:34 110299593 245365369 14433257 1 14433257 index:0,count:14433257,average:17,stdev:0 GSM652296_1 GEO 1.83 4.02 0.36 218581020 283701636 90690187 132525322 129.79 146.13 0 0 0 0 0 0 38.8 93.96 32531039 5015459 32531039 5015459 67.61 86.45 32531039 8738279 32531039 4614634 24808868 11.35 0.00 0 52.57 0 8.14 0 2.31 0 0.00 0 0.00 0 12924932 0 17 0 16.99 0 0.00 0 0.00 0 0.00 0 0.00 0 355.89 0 0.00 0 0 0 14433257 0 7586956 0 1174830 0 333495 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 36.98 0 5337976 0 0 0 0.0 14433257.0 12924932.0 0.0 7586956.0 1174830.0 333495.0 0.0 0.0 5337976.0 89.5 0.0 52.6 8.1 2.3 0.0 0.0 37.0 635804 SRR091673 SRP005279 SRS152412 SRX037934 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM652297: DGE_TALL_4 GSM652297: DGE_TALL_4 RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;T-cell lineage ALL (T-ALL)|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Peripheral blood|tissue;;Peripheral blood GEO Accession;;GSM652297 18 GSM652297 DGE_TALL_4 240400782 13355599 2011-12-21 09:09:34 187683057 240400782 13355599 1 13355599 index:0,count:13355599,average:18,stdev:0 GSM652297_1 GEO 2.49 4.49 0.38 208364026 255041550 85777003 114072402 122.4 132.99 0 0 0 0 0 0 31.86 78.63 31502261 3770880 31502261 3770880 59.44 73.24 31502261 7034779 31502261 3512453 28177549 13.52 0.00 0 52.70 0 7.23 0 4.16 0 0.00 0 0.00 0 11834731 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 546.37 0 0.01 0 0 0 13355599 0 7038933 0 965849 0 555019 0 0 0 0 0 0 0 0 0 0 0 84 0 0 0 84 0 35.91 0 4795798 0 0 0 0.0 13355599.0 11834731.0 0.0 7038933.0 965849.0 555019.0 0.0 0.0 4795798.0 88.6 0.0 52.7 7.2 4.2 0.0 0.0 35.9 124013 SRR10200236 SRP223635 SRS5451545 SRX6920378 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100784: HeLa rep-1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HeLa|source_name;;Cell line GEO Accession;;GSM4100784 GSM4100784 HeLa rep-1 551023849 2164823 2019-10-01 16:55:05 262912140 551023849 2164823 2 2164823 index:0,count:2164823,average:126.96,stdev:9.90|index:1,count:2164823,average:127.57,stdev:10.46 GSM4100784_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 254 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 36.42 0 0 0 0 0 2164823 0 0 0 0 0 3 0 0 0 2164820 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 2164823.0 0.0 0.0 0.0 0.0 3.0 0.0 2164820.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 124015 SRR10200237 SRP223635 SRS5451546 SRX6920379 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100785: HeLa rep-2; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HeLa|source_name;;Cell line GEO Accession;;GSM4100785 GSM4100785 HeLa rep-2 156052026 591508 2019-10-01 16:55:05 75582627 156052026 591508 2 591508 index:0,count:591508,average:131.59,stdev:12.74|index:1,count:591508,average:132.23,stdev:13.00 GSM4100785_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 263 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 32.26 0 0 0 0 0 591508 0 0 0 0 0 6 0 0 0 591502 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 591508.0 0.0 0.0 0.0 0.0 6.0 0.0 591502.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 124017 SRR10200238 SRP223635 SRS5451547 SRX6920380 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100786: HeLa rep-3; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HeLa|source_name;;Cell line GEO Accession;;GSM4100786 GSM4100786 HeLa rep-3 823051836 3232081 2019-10-01 16:55:05 391181712 823051836 3232081 2 3232081 index:0,count:3232081,average:127.05,stdev:10.06|index:1,count:3232081,average:127.61,stdev:10.56 GSM4100786_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 254 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 34.32 0 0 0 0 0 3232081 0 0 0 0 0 3 0 0 0 3232078 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 3232081.0 0.0 0.0 0.0 0.0 3.0 0.0 3232078.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 248038 SRR10200239 SRP223635 SRS5451548 SRX6920381 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100787: HeLa rep-4; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HeLa|source_name;;Cell line GEO Accession;;GSM4100787 GSM4100787 HeLa rep-4 649681430 2542255 2019-10-01 16:55:05 308390580 649681430 2542255 2 2542255 index:0,count:2542255,average:127.49,stdev:10.42|index:1,count:2542255,average:128.06,stdev:10.89 GSM4100787_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 255 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 17.27 0 0 0 0 0 2542255 0 0 0 0 0 2 0 0 0 2542253 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 2542255.0 0.0 0.0 0.0 0.0 2.0 0.0 2542253.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 124033 SRR10200240 SRP223635 SRS5451549 SRX6920382 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100788: HeLa rep-5; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HeLa|source_name;;Cell line GEO Accession;;GSM4100788 GSM4100788 HeLa rep-5 284699223 1112808 2019-10-01 16:55:05 135603817 284699223 1112808 2 1112808 index:0,count:1112808,average:127.63,stdev:10.31|index:1,count:1112808,average:128.21,stdev:10.80 GSM4100788_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 255 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 39.28 0 0 0 0 0 1112808 0 0 0 0 0 2 0 0 0 1112806 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 1112808.0 0.0 0.0 0.0 0.0 2.0 0.0 1112806.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 124035 SRR10200241 SRP223635 SRS5451550 SRX6920383 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100789: HEK293 rep-1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HEK293|source_name;;Cell line GEO Accession;;GSM4100789 GSM4100789 HEK293 rep-1 1051493716 4161178 2019-10-01 16:55:05 496835663 1051493716 4161178 2 4161178 index:0,count:4161178,average:126.08,stdev:8.46|index:1,count:4161178,average:126.61,stdev:9.09 GSM4100789_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 252 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 30.51 0 0 0 0 0 4161178 0 0 0 0 0 1 0 0 0 4161177 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 4161178.0 0.0 0.0 0.0 0.0 1.0 0.0 4161177.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 124037 SRR10200242 SRP223635 SRS5451551 SRX6920384 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100790: HEK293 rep-2; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HEK293|source_name;;Cell line GEO Accession;;GSM4100790 GSM4100790 HEK293 rep-2 1219354661 4820308 2019-10-01 16:55:05 575701779 1219354661 4820308 2 4820308 index:0,count:4820308,average:126.26,stdev:8.84|index:1,count:4820308,average:126.70,stdev:9.33 GSM4100790_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 252 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 24.48 0 0 0 0 0 4820308 0 0 0 0 0 6 0 0 0 4820302 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 4820308.0 0.0 0.0 0.0 0.0 6.0 0.0 4820302.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 248078 SRR10200243 SRP223635 SRS5451552 SRX6920385 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100791: HEK293 rep-3; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HEK293|source_name;;Cell line GEO Accession;;GSM4100791 GSM4100791 HEK293 rep-3 1383895516 5469427 2019-10-01 16:55:05 649465628 1383895516 5469427 2 5469427 index:0,count:5469427,average:126.21,stdev:8.62|index:1,count:5469427,average:126.81,stdev:9.31 GSM4100791_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 253 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 22.32 0 0 0 0 0 5469427 0 0 0 0 0 0 0 0 0 5469427 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 5469427.0 0.0 0.0 0.0 0.0 0.0 0.0 5469427.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 248082 SRR10200244 SRP223635 SRS5451553 SRX6920386 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100792: HEK293 rep-4; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HEK293|source_name;;Cell line GEO Accession;;GSM4100792 GSM4100792 HEK293 rep-4 880464256 3475296 2019-10-01 16:55:05 414050967 880464256 3475296 2 3475296 index:0,count:3475296,average:126.41,stdev:8.79|index:1,count:3475296,average:126.94,stdev:9.38 GSM4100792_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 253 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 45.00 0 0 0 0 0 3475296 0 0 0 0 0 4 0 0 0 3475292 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 3475296.0 0.0 0.0 0.0 0.0 4.0 0.0 3475292.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 248086 SRR10200245 SRP223635 SRS5451554 SRX6920387 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100793: HEK293 rep-5; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HEK293|source_name;;Cell line GEO Accession;;GSM4100793 GSM4100793 HEK293 rep-5 1772878643 7022042 2019-10-01 16:55:05 836974249 1772878643 7022042 2 7022042 index:0,count:7022042,average:125.92,stdev:8.33|index:1,count:7022042,average:126.55,stdev:9.09 GSM4100793_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 252 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 46.99 0 0 0 0 0 7022042 0 0 0 0 0 3 0 0 0 7022039 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 7022042.0 0.0 0.0 0.0 0.0 3.0 0.0 7022039.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 248090 SRR10200246 SRP223635 SRS5451555 SRX6920388 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100794: HepG2 rep-1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HepG2|source_name;;Cell line GEO Accession;;GSM4100794 GSM4100794 HepG2 rep-1 142483080 523812 2019-10-01 16:55:05 69486431 142483080 523812 2 523812 index:0,count:523812,average:135.82,stdev:13.98|index:1,count:523812,average:136.19,stdev:13.99 GSM4100794_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 272 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 29.46 0 0 0 0 0 523812 0 0 0 0 0 1 0 0 0 523811 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 523812.0 0.0 0.0 0.0 0.0 1.0 0.0 523811.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 248094 SRR10200247 SRP223635 SRS5451556 SRX6920389 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100795: HepG2 rep-2; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HepG2|source_name;;Cell line GEO Accession;;GSM4100795 GSM4100795 HepG2 rep-2 1650290765 6498083 2019-10-01 16:55:05 777625556 1650290765 6498083 2 6498083 index:0,count:6498083,average:126.70,stdev:9.60|index:1,count:6498083,average:127.27,stdev:10.16 GSM4100795_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 253 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 37.67 0 0 0 0 0 6498083 0 0 0 0 0 1 0 0 0 6498082 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 6498083.0 0.0 0.0 0.0 0.0 1.0 0.0 6498082.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 248098 SRR10200248 SRP223635 SRS5451557 SRX6920390 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100796: HepG2 rep-3; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HepG2|source_name;;Cell line GEO Accession;;GSM4100796 GSM4100796 HepG2 rep-3 1409238765 5572832 2019-10-01 16:55:05 660514091 1409238765 5572832 2 5572832 index:0,count:5572832,average:126.16,stdev:9.18|index:1,count:5572832,average:126.71,stdev:9.76 GSM4100796_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 252 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 42.33 0 0 0 0 0 5572832 0 0 0 0 0 4 0 0 0 5572828 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 5572832.0 0.0 0.0 0.0 0.0 4.0 0.0 5572828.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 248102 SRR10200249 SRP223635 SRS5451558 SRX6920391 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100797: HepG2 rep-4; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HepG2|source_name;;Cell line GEO Accession;;GSM4100797 GSM4100797 HepG2 rep-4 1564580939 6179404 2019-10-01 16:55:05 736753244 1564580939 6179404 2 6179404 index:0,count:6179404,average:126.31,stdev:9.40|index:1,count:6179404,average:126.88,stdev:9.99 GSM4100797_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 253 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 45.12 0 0 0 0 0 6179404 0 0 0 0 0 9 0 0 0 6179395 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 6179404.0 0.0 0.0 0.0 0.0 9.0 0.0 6179395.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 248130 SRR10200250 SRP223635 SRS5451559 SRX6920392 SRA969727 GEO RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. RegSNPs-intron shows excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of regSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. Overall design: Sequencing of RNA products (amplified using PCR) generated from an Exontrap plasmid loaded with a fragment containing a part of real exon and intron harboring the reference or alternative allele of an intronic variant. Counts of spliced products with respect to a set of test variants were documented, in five replicates for each of three cell lines. GSM4100798: HepG2 rep-5; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA paired Cells were lysed in situ 48 hours after transfection and total RNA was isolated using miRNeasy mini kit with the optional DNase digestion step (Qiagen, Germantown MD) following the manufacturer's protocol. Using 285-400 ng RNA, cDNA was synthesized with QuantiTect Reverse Transcription kit (Qiagen, Germantown MD) following the manufacturer's protocol. cDNA was PCR amplified using barcoded primers. 2 μL cDNA were amplified in a 50 μL volume containing 2X Invitrogen Platinum SuperFi PCR Master Mix (Thermo Fisher Scientific, Waltham MA) using 1 μM (final concentration) barcoded primers. The sequencing library was created by end-polishing the barcoded PCR products, followed by adapter ligation and amplification, according to instructions of Illumina (Illumina, Inc., San Diego, CA). NextSeq 500 cell line;;HepG2|source_name;;Cell line GEO Accession;;GSM4100798 GSM4100798 HepG2 rep-5 1463904988 5771951 2019-10-01 16:55:05 687891295 1463904988 5771951 2 5771951 index:0,count:5771951,average:126.51,stdev:9.53|index:1,count:5771951,average:127.12,stdev:10.13 GSM4100798_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 253 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 28.08 0 0 0 0 0 5771951 0 0 0 0 0 5 0 0 0 5771946 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 5771951.0 0.0 0.0 0.0 0.0 5.0 0.0 5771946.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 870666 SRR1818490 SRP055513 SRS857345 SRX890431 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619134: CJ1 eye_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;eye|trimester;;1 GEO Accession;;GSM1619134 GSM1619134 CJ1 eye_9 207338886 11518827 2015-05-28 18:06:17 162303358 207338886 11518827 1 11518827 index:0,count:11518827,average:18,stdev:0 GSM1619134_r1 GEO 2.4 4.26 0.32 181132957 227659622 72433693 96948785 125.69 133.84 0 0 0 0 0 0 31.64 80.11 27967323 3245767 27967323 3245767 61.33 72.22 27967323 6292289 27967323 2926122 21421700 11.83 0.00 0 53.90 0 8.51 0 2.43 0 0.00 0 0.00 0 10259705 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 455.69 0 0.00 0 0 0 11518827 0 6208103 0 979691 0 279431 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 20 0 35.17 0 4051602 0 0 0 0.0 11518827.0 10259705.0 0.0 6208103.0 979691.0 279431.0 0.0 0.0 4051602.0 89.1 0.0 53.9 8.5 2.4 0.0 0.0 35.2 870682 SRR1818491 SRP055513 SRS857344 SRX890432 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619135: CC2 pancreas_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;pancreas|trimester;;2 GEO Accession;;GSM1619135 GSM1619135 CC2 pancreas_18 172685772 9593654 2015-05-28 18:06:17 138061022 172685772 9593654 1 9593654 index:0,count:9593654,average:18,stdev:0 GSM1619135_r1 GEO 2.35 3.98 0.26 156533445 199289704 74148181 100996127 127.31 136.21 0 0 0 0 0 0 37.71 80.61 21877098 3340912 21877098 3340912 63.24 73.33 21877098 5603099 21877098 3039124 15693870 10.03 0.00 0 49.15 0 4.99 0 2.65 0 0.00 0 0.00 0 8859844 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 392.47 0 0.00 0 0 0 9593654 0 4715302 0 479200 0 254610 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 11 0 43.20 0 4144542 0 0 0 0.0 9593654.0 8859844.0 0.0 4715302.0 479200.0 254610.0 0.0 0.0 4144542.0 92.4 0.0 49.2 5.0 2.7 0.0 0.0 43.2 870698 SRR1818492 SRP055513 SRS857343 SRX890433 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619136: CI1 skin_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;skin|trimester;;2 GEO Accession;;GSM1619136 GSM1619136 CI1 skin_16 203781978 11321221 2015-05-28 18:06:17 163737551 203781978 11321221 1 11321221 index:0,count:11321221,average:18,stdev:0 GSM1619136_r1 GEO 1.74 4.31 0.3 181906842 224275847 78455954 106309739 123.29 135.5 0 0 0 0 0 0 34.87 81.74 26337363 3592841 26337363 3592841 60.05 71.03 26337363 6186658 26337363 3121829 21373873 11.75 0.00 0 52.18 0 6.42 0 2.57 0 0.00 0 0.00 0 10303313 0 18 0 17.85 0 0.00 0 0.00 0 0.00 0 0.00 0 443.00 0 0.00 0 0 0 11321221 0 5907951 0 726478 0 291430 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 21 0 38.82 0 4395362 0 0 0 0.0 11321221.0 10303313.0 0.0 5907951.0 726478.0 291430.0 0.0 0.0 4395362.0 91.0 0.0 52.2 6.4 2.6 0.0 0.0 38.8 870714 SRR1818493 SRP055513 SRS857342 SRX890434 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619137: CJ1 maternal endometrium_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;female|source_name;;Maternal endometrium|tissue;;endometrium|trimester;;1 GEO Accession;;GSM1619137 GSM1619137 CJ1 maternal endometrium_9 188434962 10468609 2015-05-28 18:06:17 150805062 188434962 10468609 1 10468609 index:0,count:10468609,average:18,stdev:0 GSM1619137_r1 GEO 3.27 3.68 0.23 170788391 213815855 74025956 101743842 125.19 137.44 0 0 0 0 0 0 35.47 82.81 24530686 3429630 24530686 3429630 61.3 76.16 24530686 5928158 24530686 3154384 19720340 11.55 0.00 0 52.81 0 4.88 0 2.74 0 0.00 0 0.00 0 9670198 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 136.05 0 0.00 0 0 0 10468609 0 5528668 0 511309 0 287102 0 0 0 0 0 0 0 0 0 0 0 116 0 0 0 116 0 39.56 0 4141530 0 0 0 0.0 10468609.0 9670198.0 0.0 5528668.0 511309.0 287102.0 0.0 0.0 4141530.0 92.4 0.0 52.8 4.9 2.7 0.0 0.0 39.6 870730 SRR1818494 SRP055513 SRS857340 SRX890435 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619138: CI1 lung_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;lung|trimester;;2 GEO Accession;;GSM1619138 GSM1619138 CI1 lung_16 216399024 12022168 2015-05-28 18:06:17 174711870 216399024 12022168 1 12022168 index:0,count:12022168,average:18,stdev:0 GSM1619138_r1 GEO 1.26 4.62 0.32 187540716 229881707 77675435 102561204 122.58 132.04 0 0 0 0 0 0 32.36 79.08 28337913 3433427 28337913 3433427 59.33 72.31 28337913 6295621 28337913 3139268 24387432 13.00 0.00 0 52.15 0 8.08 0 3.66 0 0.00 0 0.00 0 10611175 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 424.31 0 0.00 0 0 0 12022168 0 6269592 0 971300 0 439693 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 12 0 36.11 0 4341583 0 0 0 0.0 12022168.0 10611175.0 0.0 6269592.0 971300.0 439693.0 0.0 0.0 4341583.0 88.3 0.0 52.2 8.1 3.7 0.0 0.0 36.1 870745 SRR1818495 SRP055513 SRS857341 SRX890436 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619139: CC2 skin_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;skin|trimester;;2 GEO Accession;;GSM1619139 GSM1619139 CC2 skin_18 205357212 11408734 2015-05-28 18:06:17 165792872 205357212 11408734 1 11408734 index:0,count:11408734,average:18,stdev:0 GSM1619139_r1 GEO 2.36 4.08 0.36 174746271 202120734 72840274 90248144 115.67 123.9 0 0 0 0 0 0 28.87 70.15 25501190 2851667 25501190 2851667 52.87 65.63 25501190 5222871 25501190 2667728 30107113 17.23 0.00 0 50.95 0 7.54 0 5.87 0 0.00 0 0.00 0 9878146 0 18 0 17.92 0 0.00 0 0.00 0 0.00 0 0.00 0 500.87 0 0.00 0 0 0 11408734 0 5813084 0 860779 0 669809 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 13 0 35.63 0 4065062 0 0 0 0.0 11408734.0 9878146.0 0.0 5813084.0 860779.0 669809.0 0.0 0.0 4065062.0 86.6 0.0 51.0 7.5 5.9 0.0 0.0 35.6 870760 SRR1818496 SRP055513 SRS857339 SRX890437 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619140: CC2 spleen_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;spleen|trimester;;2 GEO Accession;;GSM1619140 GSM1619140 CC2 spleen_18 184517622 10250979 2015-05-28 18:06:17 147410564 184517622 10250979 1 10250979 index:0,count:10250979,average:18,stdev:0 GSM1619140_r1 GEO 2.0 3.42 0.2 167989608 199858426 68088164 90261363 118.97 132.57 0 0 0 0 0 0 33.44 83.88 22785298 3197948 22785298 3197948 67.26 76.11 22785298 6431727 22785298 2901562 15843040 9.43 0.00 0 56.10 0 4.25 0 2.46 0 0.00 0 0.00 0 9563100 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 113.20 0 0.00 0 0 0 10250979 0 5750705 0 435996 0 251883 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 6 0 37.19 0 3812395 0 0 0 0.0 10250979.0 9563100.0 0.0 5750705.0 435996.0 251883.0 0.0 0.0 3812395.0 93.3 0.0 56.1 4.3 2.5 0.0 0.0 37.2 870778 SRR1818497 SRP055513 SRS857235 SRX890438 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619141: CI1 spleen_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;spleen|trimester;;2 GEO Accession;;GSM1619141 GSM1619141 CI1 spleen_16 320688324 17816018 2015-05-28 18:06:17 251982376 320688324 17816018 1 17816018 index:0,count:17816018,average:18,stdev:0 GSM1619141_r1 GEO 1.28 3.54 0.25 290893643 339106139 123010889 164345200 116.57 133.6 0 0 0 0 0 0 35.95 86.44 39813833 5942168 39813833 5942168 65.38 80.32 39813833 10806329 39813833 5521621 27388521 9.42 0.00 0 54.18 0 5.08 0 2.15 0 0.00 0 0.00 0 16527651 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 485.89 0 0.00 0 0 0 17816018 0 9653242 0 905234 0 383133 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 14 0 38.59 0 6874409 0 0 0 0.0 17816018.0 16527651.0 0.0 9653242.0 905234.0 383133.0 0.0 0.0 6874409.0 92.8 0.0 54.2 5.1 2.2 0.0 0.0 38.6 870792 SRR1818498 SRP055513 SRS857335 SRX890439 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619142: CC2 placenta_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;placenta|trimester;;2 GEO Accession;;GSM1619142 GSM1619142 CC2 placenta_18 273052728 15169596 2015-05-28 18:06:17 219894390 273052728 15169596 1 15169596 index:0,count:15169596,average:18,stdev:0 GSM1619142_r1 GEO 2.56 3.27 0.21 245620343 290431738 96820364 123417456 118.24 127.47 0 0 0 0 0 0 30.6 78.89 38255848 4267087 38255848 4267087 64.24 74.08 38255848 8958906 38255848 4006945 29335205 11.94 0.00 0 56.28 0 5.31 0 2.75 0 0.00 0 0.00 0 13946413 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 455.09 0 0.00 0 0 0 15169596 0 8537732 0 805594 0 417589 0 0 0 0 0 0 0 0 0 0 0 29 0 0 0 29 0 35.65 0 5408681 0 0 0 0.0 15169596.0 13946413.0 0.0 8537732.0 805594.0 417589.0 0.0 0.0 5408681.0 91.9 0.0 56.3 5.3 2.8 0.0 0.0 35.7 870808 SRR1818499 SRP055513 SRS857338 SRX890440 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619143: CJ1 stomach_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;stomach|trimester;;1 GEO Accession;;GSM1619143 GSM1619143 CJ1 stomach_9 128136726 7118707 2015-05-28 18:06:17 101651100 128136726 7118707 1 7118707 index:0,count:7118707,average:18,stdev:0 GSM1619143_r1 GEO 2.99 4.19 0.28 113016413 144815458 43298944 58211159 128.14 134.44 0 0 0 0 0 0 30.68 81.16 17671426 1966651 17671426 1966651 63.0 72.68 17671426 4038204 17671426 1761100 11877674 10.51 0.00 0 56.01 0 7.21 0 2.74 0 0.00 0 0.00 0 6410262 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 457.63 0 0.00 0 0 0 7118707 0 3987137 0 513552 0 194893 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 15 0 34.04 0 2423125 0 0 0 0.0 7118707.0 6410262.0 0.0 3987137.0 513552.0 194893.0 0.0 0.0 2423125.0 90.0 0.0 56.0 7.2 2.7 0.0 0.0 34.0 872456 SRR1818500 SRP055513 SRS857336 SRX890441 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619144: CC2 adrenal_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;adrenal|trimester;;2 GEO Accession;;GSM1619144 GSM1619144 CC2 adrenal_18 160880814 8937823 2015-05-28 18:06:17 126154379 160880814 8937823 1 8937823 index:0,count:8937823,average:18,stdev:0 GSM1619144_r1 GEO 8.14 3.93 0.21 148057150 196087237 58248229 73780715 132.44 126.67 0 0 0 0 0 0 29.42 75.87 21566675 2467936 21566675 2467936 65.64 70.3 21566675 5506803 21566675 2286672 16659944 11.25 0.00 0 57.47 0 3.38 0 2.76 0 0.00 0 0.00 0 8389086 0 18 0 17.91 0 0.00 0 0.00 0 0.00 0 0.00 0 378.54 0 0.00 0 0 0 8937823 0 5136372 0 302200 0 246537 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 7 0 36.39 0 3252714 0 0 0 0.0 8937823.0 8389086.0 0.0 5136372.0 302200.0 246537.0 0.0 0.0 3252714.0 93.9 0.0 57.5 3.4 2.8 0.0 0.0 36.4 872472 SRR1818501 SRP055513 SRS857337 SRX890442 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619145: CJ1 spinal cord_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;cord|trimester;;1 GEO Accession;;GSM1619145 GSM1619145 CJ1 spinal cord_9 197565048 10975836 2015-05-28 18:06:17 155863460 197565048 10975836 1 10975836 index:0,count:10975836,average:18,stdev:0 GSM1619145_r1 GEO 2.17 4.35 0.35 178163016 228224017 83036640 115998055 128.1 139.7 0 0 0 0 0 0 38.5 83.6 24199993 3887604 24199993 3887604 63.44 75.23 24199993 6405728 24199993 3498446 20561246 11.54 0.00 0 49.63 0 4.59 0 3.41 0 0.00 0 0.00 0 10097880 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 500.16 0 0.01 0 0 0 10975836 0 5447590 0 503805 0 374151 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 18 0 42.37 0 4650290 0 0 0 0.0 10975836.0 10097880.0 0.0 5447590.0 503805.0 374151.0 0.0 0.0 4650290.0 92.0 0.0 49.6 4.6 3.4 0.0 0.0 42.4 436247 SRR1818502 SRP055513 SRS857334 SRX890443 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619146: CC2 lung_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;lung|trimester;;2 GEO Accession;;GSM1619146 GSM1619146 CC2 lung_18 214695054 11927503 2015-05-28 18:06:17 172000555 214695054 11927503 1 11927503 index:0,count:11927503,average:18,stdev:0 GSM1619146_r1 GEO 2.04 4.5 0.3 183878894 226818366 79164364 105463689 123.35 133.22 0 0 0 0 0 0 32.71 76.94 27066773 3402327 27066773 3402327 57.88 71.16 27066773 6019962 27066773 3146940 25800833 14.03 0.00 0 50.12 0 7.32 0 5.48 0 0.00 0 0.00 0 10400651 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 145.56 0 0.00 0 0 0 11927503 0 5978400 0 872647 0 654205 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 16 0 37.08 0 4422251 0 0 0 0.0 11927503.0 10400651.0 0.0 5978400.0 872647.0 654205.0 0.0 0.0 4422251.0 87.2 0.0 50.1 7.3 5.5 0.0 0.0 37.1 436255 SRR1818503 SRP055513 SRS857332 SRX890444 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619147: CI1 kidney_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;kidney|trimester;;2 GEO Accession;;GSM1619147 GSM1619147 CI1 kidney_16 206741808 11485656 2015-05-28 18:06:17 166468176 206741808 11485656 1 11485656 index:0,count:11485656,average:18,stdev:0 GSM1619147_r1 GEO 2.5 4.4 0.39 180994599 225909951 76155760 102452903 124.82 134.53 0 0 0 0 0 0 32.91 79.22 26557545 3371979 26557545 3371979 59.66 72.58 26557545 6112793 26557545 3089287 23724946 13.11 0.00 0 52.15 0 6.97 0 3.82 0 0.00 0 0.00 0 10245997 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 449.44 0 0.00 0 0 0 11485656 0 5989782 0 801061 0 438598 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 22 0 37.06 0 4256215 0 0 0 0.0 11485656.0 10245997.0 0.0 5989782.0 801061.0 438598.0 0.0 0.0 4256215.0 89.2 0.0 52.2 7.0 3.8 0.0 0.0 37.1 872520 SRR1818504 SRP055513 SRS857333 SRX890445 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619148: CC2 kidney_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;kidney|trimester;;2 GEO Accession;;GSM1619148 GSM1619148 CC2 kidney_18 184350240 10241680 2015-05-28 18:06:17 146812751 184350240 10241680 1 10241680 index:0,count:10241680,average:18,stdev:0 GSM1619148_r1 GEO 17.05 1.73 0.17 161668227 255018191 48557406 72439709 157.74 149.18 0 0 0 0 0 0 22.21 75.13 27632336 2045379 27632336 2045379 73.72 71.55 27632336 6788307 27632336 1948171 17795282 11.01 0.00 0 63.33 0 4.39 0 5.70 0 0.00 0 0.00 0 9208368 0 18 0 17.83 0 0.00 0 0.00 0 0.00 0 0.00 0 158.92 0 0.00 0 0 0 10241680 0 6485734 0 449618 0 583694 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 11 0 26.58 0 2722634 0 0 0 0.0 10241680.0 9208368.0 0.0 6485734.0 449618.0 583694.0 0.0 0.0 2722634.0 89.9 0.0 63.3 4.4 5.7 0.0 0.0 26.6 436271 SRR1818505 SRP055513 SRS857331 SRX890446 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619149: CI1 pancreas_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;pancreas|trimester;;2 GEO Accession;;GSM1619149 GSM1619149 CI1 pancreas_16 123008310 6833795 2015-05-28 18:06:17 100230261 123008310 6833795 1 6833795 index:0,count:6833795,average:18,stdev:0 GSM1619149_r1 GEO 1.97 4.29 0.34 111046702 140027279 49680989 70088497 126.1 141.08 0 0 0 0 0 0 37.51 84.83 16034877 2355957 16034877 2355957 62.14 75.9 16034877 3903188 16034877 2108127 12431868 11.20 0.00 0 51.27 0 5.89 0 2.19 0 0.00 0 0.00 0 6281245 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 128.13 0 0.00 0 0 0 6833795 0 3503890 0 402806 0 149744 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 40.64 0 2777355 0 0 0 0.0 6833795.0 6281245.0 0.0 3503890.0 402806.0 149744.0 0.0 0.0 2777355.0 91.9 0.0 51.3 5.9 2.2 0.0 0.0 40.6 436279 SRR1818506 SRP055513 SRS857330 SRX890447 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619150: CJ1 tongue_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;tongue|trimester;;1 GEO Accession;;GSM1619150 GSM1619150 CJ1 tongue_9 8006238 444791 2015-05-28 18:06:17 6631632 8006238 444791 1 444791 index:0,count:444791,average:18,stdev:0 GSM1619150_r1 GEO 1.85 4.35 0.35 7045702 8649027 2941608 3941081 122.76 133.98 0 0 0 0 0 0 32.78 79.5 1048297 130759 1048297 130759 58.96 72.16 1048297 235167 1048297 118673 888341 12.61 0.00 0 52.70 0 7.17 0 3.16 0 0.00 0 0.00 0 398860 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 123.17 0 0.00 0 0 0 444791 0 234393 0 31870 0 14061 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 36.98 0 164467 0 0 0 0.0 444791.0 398860.0 0.0 234393.0 31870.0 14061.0 0.0 0.0 164467.0 89.7 0.0 52.7 7.2 3.2 0.0 0.0 37.0 436287 SRR1818507 SRP055513 SRS857329 SRX890448 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619151: CC2 tongue_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;tongue|trimester;;2 GEO Accession;;GSM1619151 GSM1619151 CC2 tongue_18 212024214 11779123 2015-05-28 18:06:17 168754724 212024214 11779123 1 11779123 index:0,count:11779123,average:18,stdev:0 GSM1619151_r1 GEO 5.22 3.74 0.25 191182142 243517855 75912470 99600411 127.37 131.2 0 0 0 0 0 0 30.18 77.05 28917430 3271525 28917430 3271525 60.82 70.6 28917430 6592487 28917430 2997515 24892839 13.02 0.00 0 55.98 0 5.87 0 2.10 0 0.00 0 0.00 0 10840150 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 565.40 0 0.00 0 0 0 11779123 0 6594442 0 691408 0 247565 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 10 0 36.04 0 4245708 0 0 0 0.0 11779123.0 10840150.0 0.0 6594442.0 691408.0 247565.0 0.0 0.0 4245708.0 92.0 0.0 56.0 5.9 2.1 0.0 0.0 36.0 436295 SRR1818508 SRP055513 SRS857327 SRX890449 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619152: CI1 intestine_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;intestine|trimester;;2 GEO Accession;;GSM1619152 GSM1619152 CI1 intestine_16 204680304 11371128 2015-05-28 18:06:17 161812468 204680304 11371128 1 11371128 index:0,count:11371128,average:18,stdev:0 GSM1619152_r1 GEO 2.67 4.31 0.29 182007883 228474345 74685702 101690817 125.53 136.16 0 0 0 0 0 0 33.48 82.62 27163004 3451076 27163004 3451076 60.87 74.36 27163004 6273682 27163004 3105888 22293459 12.25 0.00 0 53.91 0 6.32 0 3.03 0 0.00 0 0.00 0 10307474 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 553.19 0 0.00 0 0 0 11371128 0 6130621 0 718771 0 344883 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 16 0 36.73 0 4176853 0 0 0 0.0 11371128.0 10307474.0 0.0 6130621.0 718771.0 344883.0 0.0 0.0 4176853.0 90.6 0.0 53.9 6.3 3.0 0.0 0.0 36.7 436303 SRR1818509 SRP055513 SRS857328 SRX890450 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619153: CC2 amnion_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;amnion|trimester;;2 GEO Accession;;GSM1619153 GSM1619153 CC2 amnion_18 167535180 9307510 2015-05-28 18:06:17 135187674 167535180 9307510 1 9307510 index:0,count:9307510,average:18,stdev:0 GSM1619153_r1 GEO 1.44 4.59 0.28 151237105 177637338 68909656 81463597 117.46 118.22 0 0 0 0 0 0 32.55 72.33 21271091 2782503 21271091 2782503 55.0 66.15 21271091 4701162 21271091 2544615 18675223 12.35 0.00 0 50.50 0 5.99 0 2.18 0 0.00 0 0.00 0 8547517 0 18 0 17.91 0 0.00 0 0.00 0 0.00 0 0.00 0 465.38 0 0.00 0 0 0 9307510 0 4700511 0 557544 0 202449 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 8 0 41.33 0 3847006 0 0 0 0.0 9307510.0 8547517.0 0.0 4700511.0 557544.0 202449.0 0.0 0.0 3847006.0 91.8 0.0 50.5 6.0 2.2 0.0 0.0 41.3 436358 SRR1818510 SRP055513 SRS857325 SRX890451 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619154: CI1 placenta_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;placenta|trimester;;2 GEO Accession;;GSM1619154 GSM1619154 CI1 placenta_16 124086258 6893681 2015-05-28 18:06:17 98770321 124086258 6893681 1 6893681 index:0,count:6893681,average:18,stdev:0 GSM1619154_r1 GEO 1.92 4.39 0.28 111300100 137285552 47748727 64231120 123.35 134.52 0 0 0 0 0 0 35.04 82.65 16168480 2206684 16168480 2206684 61.53 76.37 16168480 3875438 16168480 2039129 12750075 11.46 0.00 0 52.63 0 6.22 0 2.42 0 0.00 0 0.00 0 6298431 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 406.84 0 0.00 0 0 0 6893681 0 3628382 0 428653 0 166597 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 15 0 38.73 0 2670049 0 0 0 0.0 6893681.0 6298431.0 0.0 3628382.0 428653.0 166597.0 0.0 0.0 2670049.0 91.4 0.0 52.6 6.2 2.4 0.0 0.0 38.7 436367 SRR1818511 SRP055513 SRS857326 SRX890452 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619155: CJ1 amnion_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;amnion|trimester;;1 GEO Accession;;GSM1619155 GSM1619155 CJ1 amnion_9 139236678 7735371 2015-05-28 18:06:17 110179251 139236678 7735371 1 7735371 index:0,count:7735371,average:18,stdev:0 GSM1619155_r1 GEO 3.38 4.16 0.26 124442638 158756057 51426847 70084195 127.57 136.28 0 0 0 0 0 0 33.85 82.96 18671530 2385600 18671530 2385600 64.01 76.74 18671530 4511260 18671530 2206594 13671794 10.99 0.00 0 53.93 0 6.65 0 2.24 0 0.00 0 0.00 0 7047428 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 488.55 0 0.00 0 0 0 7735371 0 4171901 0 514295 0 173648 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 8 0 37.17 0 2875527 0 0 0 0.0 7735371.0 7047428.0 0.0 4171901.0 514295.0 173648.0 0.0 0.0 2875527.0 91.1 0.0 53.9 6.6 2.2 0.0 0.0 37.2 436375 SRR1818512 SRP055513 SRS857324 SRX890453 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619156: CI1 liver_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;liver|trimester;;2 GEO Accession;;GSM1619156 GSM1619156 CI1 liver_16 153488052 8527114 2015-05-28 18:06:17 122358367 153488052 8527114 1 8527114 index:0,count:8527114,average:18,stdev:0 GSM1619156_r1 GEO 1.57 2.58 0.22 142832734 151531296 56457129 72743927 106.09 128.85 0 0 0 0 0 0 33.98 87.42 18694041 2753706 18694041 2753706 64.76 83.3 18694041 5247307 18694041 2623942 10519471 7.36 0.00 0 58.09 0 3.75 0 1.22 0 0.00 0 0.00 0 8103149 0 18 0 17.92 0 0.00 0 0.00 0 0.00 0 0.00 0 444.89 0 0.00 0 0 0 8527114 0 4953238 0 320074 0 103891 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 11 0 36.94 0 3149911 0 0 0 0.0 8527114.0 8103149.0 0.0 4953238.0 320074.0 103891.0 0.0 0.0 3149911.0 95.0 0.0 58.1 3.8 1.2 0.0 0.0 36.9 436383 SRR1818513 SRP055513 SRS857323 SRX890454 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619157: CI1 chorion_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;chorion|trimester;;2 GEO Accession;;GSM1619157 GSM1619157 CI1 chorion_16 165017286 9167627 2015-05-28 18:06:17 133167794 165017286 9167627 1 9167627 index:0,count:9167627,average:18,stdev:0 GSM1619157_r1 GEO 1.82 4.4 0.29 147579539 181645630 63687820 85615347 123.08 134.43 0 0 0 0 0 0 35.22 82.56 21360853 2939880 21360853 2939880 59.0 75.26 21360853 4924703 21360853 2680085 17213308 11.66 0.00 0 52.21 0 6.07 0 2.88 0 0.00 0 0.00 0 8346921 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 492.59 0 0.01 0 0 0 9167627 0 4785972 0 556924 0 263782 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 12 0 38.84 0 3560949 0 0 0 0.0 9167627.0 8346921.0 0.0 4785972.0 556924.0 263782.0 0.0 0.0 3560949.0 91.0 0.0 52.2 6.1 2.9 0.0 0.0 38.8 872776 SRR1818514 SRP055513 SRS857322 SRX890455 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619158: CC2 liver_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;liver|trimester;;2 GEO Accession;;GSM1619158 GSM1619158 CC2 liver_18 170745876 9485882 2015-05-28 18:06:17 135810989 170745876 9485882 1 9485882 index:0,count:9485882,average:18,stdev:0 GSM1619158_r1 GEO 1.68 2.71 0.21 157698818 165964079 66395732 82425954 105.24 124.14 0 0 0 0 0 0 35.18 84.94 20561666 3144970 20561666 3144970 62.7 81.12 20561666 5605370 20561666 3003642 13389505 8.49 0.00 0 55.22 0 4.03 0 1.72 0 0.00 0 0.00 0 8940526 0 18 0 17.93 0 0.00 0 0.00 0 0.00 0 0.00 0 449.33 0 0.00 0 0 0 9485882 0 5237753 0 382001 0 163355 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 11 0 39.03 0 3702773 0 0 0 0.0 9485882.0 8940526.0 0.0 5237753.0 382001.0 163355.0 0.0 0.0 3702773.0 94.3 0.0 55.2 4.0 1.7 0.0 0.0 39.0 436398 SRR1818515 SRP055513 SRS857321 SRX890456 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619159: CI1 muscle_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;muscle|trimester;;2 GEO Accession;;GSM1619159 GSM1619159 CI1 muscle_16 37980270 2110015 2015-05-28 18:06:17 30968137 37980270 2110015 1 2110015 index:0,count:2110015,average:18,stdev:0 GSM1619159_r1 GEO 2.76 4.34 0.29 33819529 43040526 14037816 19517285 127.27 139.03 0 0 0 0 0 0 34.0 82.96 5033005 653987 5033005 653987 61.9 70.91 5033005 1190572 5033005 559001 3612501 10.68 0.00 0 53.79 0 6.23 0 2.61 0 0.00 0 0.00 0 1923370 0 18 0 17.81 0 0.00 0 0.00 0 0.00 0 0.00 0 237.38 0 0.01 0 0 0 2110015 0 1135029 0 131486 0 55159 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 37.36 0 788341 0 0 0 0.0 2110015.0 1923370.0 0.0 1135029.0 131486.0 55159.0 0.0 0.0 788341.0 91.2 0.0 53.8 6.2 2.6 0.0 0.0 37.4 436406 SRR1818516 SRP055513 SRS857320 SRX890457 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619160: CC2 brain_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;brain|trimester;;2 GEO Accession;;GSM1619160 GSM1619160 CC2 brain_18 136796850 7599825 2015-05-28 18:06:17 107624336 136796850 7599825 1 7599825 index:0,count:7599825,average:18,stdev:0 GSM1619160_r1 GEO 3.76 4.38 0.39 121123975 153033211 52955470 72010390 126.34 135.98 0 0 0 0 0 0 33.5 77.66 17163025 2299511 17163025 2299511 59.63 71.76 17163025 4093372 17163025 2124969 17969329 14.84 0.00 0 51.36 0 4.69 0 4.99 0 0.00 0 0.00 0 6864212 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 396.51 0 0.01 0 0 0 7599825 0 3903191 0 356296 0 379317 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 11 0 38.96 0 2961021 0 0 0 0.0 7599825.0 6864212.0 0.0 3903191.0 356296.0 379317.0 0.0 0.0 2961021.0 90.3 0.0 51.4 4.7 5.0 0.0 0.0 39.0 436414 SRR1818517 SRP055513 SRS857319 SRX890458 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619161: CI1 amnion_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;amnion|trimester;;2 GEO Accession;;GSM1619161 GSM1619161 CI1 amnion_16 175428234 9746013 2015-05-28 18:06:17 138416752 175428234 9746013 1 9746013 index:0,count:9746013,average:18,stdev:0 GSM1619161_r1 GEO 1.62 4.75 0.29 157061268 192334583 65530527 88492919 122.46 135.04 0 0 0 0 0 0 33.98 82.41 23172980 3019265 23172980 3019265 58.78 73.83 23172980 5222931 23172980 2705066 17435586 11.10 0.00 0 53.57 0 6.69 0 2.14 0 0.00 0 0.00 0 8884817 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 417.69 0 0.00 0 0 0 9746013 0 5221104 0 652311 0 208885 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 7 0 37.59 0 3663713 0 0 0 0.0 9746013.0 8884817.0 0.0 5221104.0 652311.0 208885.0 0.0 0.0 3663713.0 91.2 0.0 53.6 6.7 2.1 0.0 0.0 37.6 436422 SRR1818518 SRP055513 SRS857317 SRX890459 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619162: CJ1 intestine_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;intestine|trimester;;1 GEO Accession;;GSM1619162 GSM1619162 CJ1 intestine_9 107898048 5994336 2015-05-28 18:06:17 85935880 107898048 5994336 1 5994336 index:0,count:5994336,average:18,stdev:0 GSM1619162_r1 GEO 1.3 4.78 0.33 95129316 116722575 39675425 53411454 122.7 134.62 0 0 0 0 0 0 33.69 81.71 14188299 1814836 14188299 1814836 59.58 72.39 14188299 3209828 14188299 1607732 11801204 12.41 0.00 0 52.82 0 7.65 0 2.48 0 0.00 0 0.00 0 5387415 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 449.58 0 0.01 0 0 0 5994336 0 3166434 0 458488 0 148433 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 9 0 37.05 0 2220981 0 0 0 0.0 5994336.0 5387415.0 0.0 3166434.0 458488.0 148433.0 0.0 0.0 2220981.0 89.9 0.0 52.8 7.6 2.5 0.0 0.0 37.1 436430 SRR1818519 SRP055513 SRS857318 SRX890460 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619163: CC2 tongue.2_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;tongue.2|trimester;;2 GEO Accession;;GSM1619163 GSM1619163 CC2 tongue.2_18 133470882 7415049 2015-05-28 18:06:17 105547536 133470882 7415049 1 7415049 index:0,count:7415049,average:18,stdev:0 GSM1619163_r1 GEO 1.8 3.87 0.32 117659840 140507566 50083716 65862713 119.42 131.51 0 0 0 0 0 0 32.12 76.43 17402195 2137704 17402195 2137704 54.63 71.17 17402195 3635549 17402195 1990443 19542585 16.61 0.00 0 52.03 0 7.16 0 3.09 0 0.00 0 0.00 0 6654913 0 18 0 17.91 0 0.00 0 0.00 0 0.00 0 0.00 0 513.35 0 0.00 0 0 0 7415049 0 3858112 0 531257 0 228879 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 7 0 37.72 0 2796801 0 0 0 0.0 7415049.0 6654913.0 0.0 3858112.0 531257.0 228879.0 0.0 0.0 2796801.0 89.7 0.0 52.0 7.2 3.1 0.0 0.0 37.7 436486 SRR1818520 SRP055513 SRS857316 SRX890461 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619164: CJ1 placenta_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;placenta|trimester;;1 GEO Accession;;GSM1619164 GSM1619164 CJ1 placenta_9 143970984 7998388 2015-05-28 18:06:17 114085583 143970984 7998388 1 7998388 index:0,count:7998388,average:18,stdev:0 GSM1619164_r1 GEO 2.21 3.95 0.25 128526806 149260077 60012916 73756839 116.13 122.9 0 0 0 0 0 0 37.56 81.46 17929702 2729911 17929702 2729911 59.69 77.63 17929702 4338220 17929702 2601620 19554909 15.21 0.00 0 48.97 0 7.03 0 2.11 0 0.00 0 0.00 0 7267963 0 18 0 17.91 0 0.00 0 0.00 0 0.00 0 0.00 0 457.05 0 0.00 0 0 0 7998388 0 3916794 0 561989 0 168436 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 12 0 41.90 0 3351169 0 0 0 0.0 7998388.0 7267963.0 0.0 3916794.0 561989.0 168436.0 0.0 0.0 3351169.0 90.9 0.0 49.0 7.0 2.1 0.0 0.0 41.9 436494 SRR1818521 SRP055513 SRS857315 SRX890462 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619165: CI1 maternal endometrium_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;female|source_name;;Maternal endometrium|tissue;;endometrium|trimester;;2 GEO Accession;;GSM1619165 GSM1619165 CI1 maternal endometrium_16 139808844 7767158 2015-05-28 18:06:17 110596838 139808844 7767158 1 7767158 index:0,count:7767158,average:18,stdev:0 GSM1619165_r1 GEO 2.06 3.99 0.22 128355730 168115352 63199989 89661711 130.98 141.87 0 0 0 0 0 0 40.88 84.0 17613304 2970968 17613304 2970968 63.7 76.09 17613304 4628870 17613304 2691067 14722589 11.47 0.00 0 48.03 0 4.23 0 2.20 0 0.00 0 0.00 0 7267171 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 499.32 0 0.00 0 0 0 7767158 0 3730259 0 328902 0 171085 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 9 0 45.54 0 3536912 0 0 0 0.0 7767158.0 7267171.0 0.0 3730259.0 328902.0 171085.0 0.0 0.0 3536912.0 93.6 0.0 48.0 4.2 2.2 0.0 0.0 45.5 436502 SRR1818522 SRP055513 SRS857314 SRX890463 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619166: CJ1 umbilical cord_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;cord|trimester;;1 GEO Accession;;GSM1619166 GSM1619166 CJ1 umbilical cord_9 33945660 1885870 2015-05-28 18:06:17 27542299 33945660 1885870 1 1885870 index:0,count:1885870,average:18,stdev:0 GSM1619166_r1 GEO 1.37 4.31 0.29 30494183 38488553 13611561 18968845 126.22 139.36 0 0 0 0 0 0 36.95 83.72 4406481 638726 4406481 638726 61.52 74.24 4406481 1063548 4406481 566352 3360748 11.02 0.00 0 51.21 0 6.26 0 2.07 0 0.00 0 0.00 0 1728698 0 18 0 17.84 0 0.00 0 0.00 0 0.00 0 0.00 0 399.36 0 0.00 0 0 0 1885870 0 965788 0 118092 0 39080 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 40.45 0 762910 0 0 0 0.0 1885870.0 1728698.0 0.0 965788.0 118092.0 39080.0 0.0 0.0 762910.0 91.7 0.0 51.2 6.3 2.1 0.0 0.0 40.5 436510 SRR1818523 SRP055513 SRS857312 SRX890464 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619167: CI1 brain_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;brain|trimester;;2 GEO Accession;;GSM1619167 GSM1619167 CI1 brain_16 152634780 8479710 2015-05-28 18:06:17 121776034 152634780 8479710 1 8479710 index:0,count:8479710,average:18,stdev:0 GSM1619167_r1 GEO 3.47 4.32 0.36 138991401 180631799 63062197 87473826 129.96 138.71 0 0 0 0 0 0 37.13 82.96 19218460 2928017 19218460 2928017 64.57 76.73 19218460 5091614 19218460 2708135 16674486 12.00 0.00 0 51.37 0 3.97 0 3.04 0 0.00 0 0.00 0 7885166 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 127.73 0 0.01 0 0 0 8479710 0 4355702 0 336777 0 257767 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 9 0 41.62 0 3529464 0 0 0 0.0 8479710.0 7885166.0 0.0 4355702.0 336777.0 257767.0 0.0 0.0 3529464.0 93.0 0.0 51.4 4.0 3.0 0.0 0.0 41.6 436518 SRR1818524 SRP055513 SRS857313 SRX890465 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619168: CJ1 heart V_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;V|trimester;;1 GEO Accession;;GSM1619168 GSM1619168 CJ1 heart V_9 15363882 853549 2015-05-28 18:06:17 12682992 15363882 853549 1 853549 index:0,count:853549,average:18,stdev:0 GSM1619168_r1 GEO 4.39 4.01 0.31 13906370 18120379 5735302 7966215 130.3 138.9 0 0 0 0 0 0 34.27 84.33 2044944 270841 2044944 270841 63.57 75.98 2044944 502382 2044944 244039 1466607 10.55 0.00 0 54.96 0 5.44 0 1.97 0 0.00 0 0.00 0 790323 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 42.68 0 0.01 0 0 0 853549 0 469140 0 46438 0 16788 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 37.63 0 321183 0 0 0 0.0 853549.0 790323.0 0.0 469140.0 46438.0 16788.0 0.0 0.0 321183.0 92.6 0.0 55.0 5.4 2.0 0.0 0.0 37.6 436526 SRR1818525 SRP055513 SRS857311 SRX890466 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619169: CC2 intestine_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;intestine|trimester;;2 GEO Accession;;GSM1619169 GSM1619169 CC2 intestine_18 28247130 1569285 2015-05-28 18:06:17 23204720 28247130 1569285 1 1569285 index:0,count:1569285,average:18,stdev:0 GSM1619169_r1 GEO 3.25 3.84 0.23 25095853 31110962 10694927 13868498 123.97 129.67 0 0 0 0 0 0 32.49 77.3 3586616 462160 3586616 462160 61.25 69.51 3586616 871104 3586616 415552 2912978 11.61 0.00 0 52.54 0 5.50 0 3.87 0 0.00 0 0.00 0 1422310 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 332.32 0 0.00 0 0 0 1569285 0 824439 0 86262 0 60713 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 38.10 0 597871 0 0 0 0.0 1569285.0 1422310.0 0.0 824439.0 86262.0 60713.0 0.0 0.0 597871.0 90.6 0.0 52.5 5.5 3.9 0.0 0.0 38.1 436534 SRR1818526 SRP055513 SRS857310 SRX890467 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619170: CI1 tongue_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;male|source_name;;Fetal tissue|tissue;;tongue|trimester;;2 GEO Accession;;GSM1619170 GSM1619170 CI1 tongue_16 71618976 3978832 2015-05-28 18:06:17 56671129 71618976 3978832 1 3978832 index:0,count:3978832,average:18,stdev:0 GSM1619170_r1 GEO 2.2 3.93 0.27 64353159 81056812 27340409 37602616 125.96 137.53 0 0 0 0 0 0 34.91 83.29 9185758 1275713 9185758 1275713 64.53 75.45 9185758 2357970 9185758 1155519 6894977 10.71 0.00 0 53.35 0 6.13 0 2.02 0 0.00 0 0.00 0 3654288 0 18 0 17.85 0 0.00 0 0.00 0 0.00 0 0.00 0 318.31 0 0.01 0 0 0 3978832 0 2122705 0 244070 0 80474 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 38.49 0 1531583 0 0 0 0.0 3978832.0 3654288.0 0.0 2122705.0 244070.0 80474.0 0.0 0.0 1531583.0 91.8 0.0 53.3 6.1 2.0 0.0 0.0 38.5 436542 SRR1818527 SRP055513 SRS857309 SRX890468 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619171: CC2 stomach_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18|Sex;;female|source_name;;Fetal tissue|tissue;;stomach|trimester;;2 GEO Accession;;GSM1619171 GSM1619171 CC2 stomach_18 131394222 7299679 2015-05-28 18:06:17 104156710 131394222 7299679 1 7299679 index:0,count:7299679,average:18,stdev:0 GSM1619171_r1 GEO 3.82 4.08 0.25 116821796 151720788 49401789 67016546 129.87 135.66 0 0 0 0 0 0 33.71 80.82 17419949 2232496 17419949 2232496 64.02 73.61 17419949 4239302 17419949 2033323 13340640 11.42 0.00 0 52.87 0 6.36 0 2.93 0 0.00 0 0.00 0 6621805 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 495.83 0 0.01 0 0 0 7299679 0 3859633 0 464056 0 213818 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 11 0 37.84 0 2762172 0 0 0 0.0 7299679.0 6621805.0 0.0 3859633.0 464056.0 213818.0 0.0 0.0 2762172.0 90.7 0.0 52.9 6.4 2.9 0.0 0.0 37.8 436550 SRR1818528 SRP055513 SRS857308 SRX890469 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619172: CJ1 pancreas_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9|Sex;;male|source_name;;Fetal tissue|tissue;;pancreas|trimester;;1 GEO Accession;;GSM1619172 GSM1619172 CJ1 pancreas_9 18930222 1051679 2015-05-28 18:06:17 15689413 18930222 1051679 1 1051679 index:0,count:1051679,average:18,stdev:0 GSM1619172_r1 GEO 3.82 3.93 0.32 16760902 21329707 6733303 9136502 127.26 135.69 0 0 0 0 0 0 31.63 79.79 2541723 300410 2541723 300410 61.46 72.57 2541723 583849 2541723 273246 1943458 11.60 0.00 0 54.52 0 7.19 0 2.48 0 0.00 0 0.00 0 949910 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 222.71 0 0.01 0 0 0 1051679 0 573395 0 75652 0 26117 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 35.80 0 376515 0 0 0 0.0 1051679.0 949910.0 0.0 573395.0 75652.0 26117.0 0.0 0.0 376515.0 90.3 0.0 54.5 7.2 2.5 0.0 0.0 35.8 436558 SRR1818529 SRP055513 SRS857307 SRX890470 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619173: CF2 spleen_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;spleen|trimester;;1 GEO Accession;;GSM1619173 GSM1619173 CF2 spleen_22 365188050 20288225 2015-05-28 18:06:17 282848243 365188050 20288225 1 20288225 index:0,count:20288225,average:18,stdev:0 GSM1619173_r1 GEO 1.2 4.08 0.24 324636526 395904418 139488314 191858812 121.95 137.54 0 0 0 0 0 0 35.62 84.06 45246744 6562840 45246744 6562840 63.03 76.25 45246744 11614887 45246744 5952540 34140483 10.52 0.00 0 52.34 0 6.02 0 3.16 0 0.00 0 0.00 0 18426209 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 450.85 0 0.01 0 0 0 20288225 0 10619154 0 1221835 0 640181 0 0 0 0 0 0 0 0 0 0 0 36 0 0 0 36 0 38.48 0 7807055 0 0 0 0.0 20288225.0 18426209.0 0.0 10619154.0 1221835.0 640181.0 0.0 0.0 7807055.0 90.8 0.0 52.3 6.0 3.2 0.0 0.0 38.5 436614 SRR1818530 SRP055513 SRS857306 SRX890471 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619174: DA2 liver_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;8.3|Sex;;female|source_name;;Fetal tissue|tissue;;liver|trimester;;2 GEO Accession;;GSM1619174 GSM1619174 DA2 liver_9 310550256 17252792 2015-05-28 18:06:17 229247118 310550256 17252792 1 17252792 index:0,count:17252792,average:18,stdev:0 GSM1619174_r1 GEO 1.94 3.08 0.24 285667936 315813508 109053517 141011095 110.55 129.3 0 0 0 0 0 0 31.97 84.94 39848885 5171722 39848885 5171722 62.49 78.86 39848885 10108817 39848885 4801700 25984501 9.10 0.00 0 58.47 0 4.83 0 1.41 0 0.00 0 0.00 0 16177402 0 18 0 17.91 0 0.00 0 0.00 0 0.00 0 0.00 0 540.09 0 0.00 0 0 0 17252792 0 10088451 0 832502 0 242888 0 0 0 0 0 0 0 0 0 0 0 43 0 0 0 43 0 35.29 0 6088951 0 0 0 0.0 17252792.0 16177402.0 0.0 10088451.0 832502.0 242888.0 0.0 0.0 6088951.0 93.8 0.0 58.5 4.8 1.4 0.0 0.0 35.3 436623 SRR1818531 SRP055513 SRS857305 SRX890472 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619175: CP1 intestine_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;intestine|trimester;;2 GEO Accession;;GSM1619175 GSM1619175 CP1 intestine_22 37512702 2084039 2015-05-28 18:06:17 28302253 37512702 2084039 1 2084039 index:0,count:2084039,average:18,stdev:0 GSM1619175_r1 GEO 2.56 4.11 0.25 33244407 42194497 14491761 19942402 126.92 137.61 0 0 0 0 0 0 35.66 82.83 4824627 671810 4824627 671810 62.45 75.84 4824627 1176512 4824627 615099 3744814 11.26 0.00 0 51.47 0 6.36 0 3.25 0 0.00 0 0.00 0 1883776 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 300.10 0 0.01 0 0 0 2084039 0 1072695 0 132518 0 67745 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 38.92 0 811081 0 0 0 0.0 2084039.0 1883776.0 0.0 1072695.0 132518.0 67745.0 0.0 0.0 811081.0 90.4 0.0 51.5 6.4 3.3 0.0 0.0 38.9 436631 SRR1818532 SRP055513 SRS857304 SRX890473 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619176: DF1 skin_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;skin|trimester;;1 GEO Accession;;GSM1619176 GSM1619176 DF1 skin_9 255737340 14207630 2015-05-28 18:06:17 196638658 255737340 14207630 1 14207630 index:0,count:14207630,average:18,stdev:0 GSM1619176_r1 GEO 1.0 4.44 0.37 224811846 266624490 100328617 131144966 118.6 130.72 0 0 0 0 0 0 34.87 79.04 32641205 4434501 32641205 4434501 57.87 71.02 32641205 7359380 32641205 3984590 29784318 13.25 0.00 0 50.02 0 7.18 0 3.31 0 0.00 0 0.00 0 12716970 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 516.64 0 0.00 0 0 0 14207630 0 7106733 0 1020707 0 469953 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 8 0 39.49 0 5610237 0 0 0 0.0 14207630.0 12716970.0 0.0 7106733.0 1020707.0 469953.0 0.0 0.0 5610237.0 89.5 0.0 50.0 7.2 3.3 0.0 0.0 39.5 873272 SRR1818533 SRP055513 SRS857303 SRX890474 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619177: CF2 lung_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;lung|trimester;;2 GEO Accession;;GSM1619177 GSM1619177 CF2 lung_22 295661196 16425622 2015-05-28 18:06:17 226168494 295661196 16425622 1 16425622 index:0,count:16425622,average:18,stdev:0 GSM1619177_r1 GEO 1.02 4.76 0.33 249791584 296936657 105159286 138027319 118.87 131.26 0 0 0 0 0 0 32.39 77.8 37415957 4571147 37415957 4571147 55.87 71.49 37415957 7886241 37415957 4200450 37802336 15.13 0.00 0 50.16 0 8.55 0 5.52 0 0.00 0 0.00 0 14114959 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 542.50 0 0.00 0 0 0 16425622 0 8239618 0 1403890 0 906773 0 0 0 0 0 0 0 0 0 0 0 65 0 0 0 65 0 35.77 0 5875341 0 0 0 0.0 16425622.0 14114959.0 0.0 8239618.0 1403890.0 906773.0 0.0 0.0 5875341.0 85.9 0.0 50.2 8.5 5.5 0.0 0.0 35.8 873288 SRR1818534 SRP055513 SRS857300 SRX890475 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619178: CV1 heart V_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;female|source_name;;Fetal tissue|tissue;;heart|trimester;;2 GEO Accession;;GSM1619178 GSM1619178 CV1 heart V_16 494751870 27486215 2015-05-28 18:06:17 386694348 494751870 27486215 1 27486215 index:0,count:27486215,average:18,stdev:0 GSM1619178_r1 GEO 3.84 4.43 0.3 438671290 535826476 181529957 241780258 122.15 133.19 0 0 0 0 0 0 33.92 83.17 65023331 8434183 65023331 8434183 60.03 76.88 65023331 14924640 65023331 7796332 60096855 13.70 0.00 0 53.56 0 6.33 0 3.21 0 0.00 0 0.00 0 24863015 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 152.70 0 0.00 0 0 0 27486215 0 14721626 0 1739825 0 883375 0 0 0 0 0 0 0 0 0 0 0 30 0 0 0 30 0 36.90 0 10141389 0 0 0 0.0 27486215.0 24863015.0 0.0 14721626.0 1739825.0 883375.0 0.0 0.0 10141389.0 90.5 0.0 53.6 6.3 3.2 0.0 0.0 36.9 436655 SRR1818535 SRP055513 SRS857299 SRX890476 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619179: CH1 adrenal_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.4|Sex;;female|source_name;;Fetal tissue|tissue;;adrenal|trimester;;1 GEO Accession;;GSM1619179 GSM1619179 CH1 adrenal_9 22401648 1244536 2015-05-28 18:06:17 19030436 22401648 1244536 1 1244536 index:0,count:1244536,average:18,stdev:0 GSM1619179_r1 GEO 4.72 4.27 0.37 19629731 23958788 7359283 9618692 122.05 130.7 0 0 0 0 0 0 28.05 76.0 3017765 312687 3017765 312687 56.96 69.81 3017765 634920 3017765 287212 3020812 15.39 0.00 0 56.51 0 7.10 0 3.33 0 0.00 0 0.00 0 1114763 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 235.81 0 0.01 0 0 0 1244536 0 703347 0 88382 0 41391 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 33.06 0 411416 0 0 0 0.0 1244536.0 1114763.0 0.0 703347.0 88382.0 41391.0 0.0 0.0 411416.0 89.6 0.0 56.5 7.1 3.3 0.0 0.0 33.1 436663 SRR1818536 SRP055513 SRS857298 SRX890477 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619180: DF1 eye_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;eye|trimester;;1 GEO Accession;;GSM1619180 GSM1619180 DF1 eye_9 207702990 11539055 2015-05-28 18:06:17 161055682 207702990 11539055 1 11539055 index:0,count:11539055,average:18,stdev:0 GSM1619180_r1 GEO 1.24 4.06 0.31 185865731 240310624 82385962 112621331 129.29 136.7 0 0 0 0 0 0 36.72 83.93 26741031 3872457 26741031 3872457 63.86 75.9 26741031 6734157 26741031 3501938 20528226 11.04 0.00 0 51.40 0 6.14 0 2.48 0 0.00 0 0.00 0 10544842 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 437.27 0 0.00 0 0 0 11539055 0 5930999 0 708183 0 286030 0 0 0 0 0 0 0 0 0 0 0 32 0 0 0 32 0 39.98 0 4613843 0 0 0 0.0 11539055.0 10544842.0 0.0 5930999.0 708183.0 286030.0 0.0 0.0 4613843.0 91.4 0.0 51.4 6.1 2.5 0.0 0.0 40.0 436671 SRR1818537 SRP055513 SRS857302 SRX890478 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619181: CR1 kidney_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;kidney|trimester;;2 GEO Accession;;GSM1619181 GSM1619181 CR1 kidney_22 233008092 12944894 2015-05-28 18:06:17 180983407 233008092 12944894 1 12944894 index:0,count:12944894,average:18,stdev:0 GSM1619181_r1 GEO 2.09 4.34 0.35 201301445 253634587 90593997 123347969 126.0 136.15 0 0 0 0 0 0 35.87 80.72 28266545 4088715 28266545 4088715 61.02 73.65 28266545 6956806 28266545 3730477 25611795 12.72 0.00 0 48.94 0 6.43 0 5.50 0 0.00 0 0.00 0 11400275 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 416.09 0 0.00 0 0 0 12944894 0 6335085 0 832937 0 711682 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 15 0 39.13 0 5065190 0 0 0 0.0 12944894.0 11400275.0 0.0 6335085.0 832937.0 711682.0 0.0 0.0 5065190.0 88.1 0.0 48.9 6.4 5.5 0.0 0.0 39.1 436679 SRR1818538 SRP055513 SRS857301 SRX890479 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619182: CV1 amnion_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;female|source_name;;Fetal tissue|tissue;;amnion|trimester;;2 GEO Accession;;GSM1619182 GSM1619182 CV1 amnion_16 197549280 10974960 2015-05-28 18:06:17 146639356 197549280 10974960 1 10974960 index:0,count:10974960,average:18,stdev:0 GSM1619182_r1 GEO 1.44 4.18 0.26 177132277 225302732 78190299 109561140 127.19 140.12 0 0 0 0 0 0 37.13 85.22 24731268 3727051 24731268 3727051 61.96 78.11 24731268 6219534 24731268 3416258 17833155 10.07 0.00 0 51.62 0 5.97 0 2.56 0 0.00 0 0.00 0 10038638 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 500.12 0 0.00 0 0 0 10974960 0 5665204 0 654984 0 281338 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 12 0 39.85 0 4373434 0 0 0 0.0 10974960.0 10038638.0 0.0 5665204.0 654984.0 281338.0 0.0 0.0 4373434.0 91.5 0.0 51.6 6.0 2.6 0.0 0.0 39.8 873369 SRR1818539 SRP055513 SRS857296 SRX890480 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619183: BP1 lung_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.1|Sex;;male|source_name;;Fetal tissue|tissue;;lung|trimester;;1 GEO Accession;;GSM1619183 GSM1619183 BP1 lung_9 259933734 14440763 2015-05-28 18:06:17 191179865 259933734 14440763 1 14440763 index:0,count:14440763,average:18,stdev:0 GSM1619183_r1 GEO 1.07 4.46 0.33 229615145 281162157 97581768 131011666 122.45 134.26 0 0 0 0 0 0 34.61 82.41 33882045 4499564 33882045 4499564 60.38 74.31 33882045 7850442 33882045 4057165 27543413 12.00 0.00 0 52.23 0 7.57 0 2.39 0 0.00 0 0.00 0 13001922 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 504.73 0 0.00 0 0 0 14440763 0 7542243 0 1093593 0 345248 0 0 0 0 0 0 0 0 0 0 0 41 0 0 0 41 0 37.81 0 5459679 0 0 0 0.0 14440763.0 13001922.0 0.0 7542243.0 1093593.0 345248.0 0.0 0.0 5459679.0 90.0 0.0 52.2 7.6 2.4 0.0 0.0 37.8 873481 SRR1818540 SRP055513 SRS857297 SRX890481 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619184: CP1 chorion_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;chorion|trimester;;2 GEO Accession;;GSM1619184 GSM1619184 CP1 chorion_22 182022786 10112377 2015-05-28 18:06:17 134871748 182022786 10112377 1 10112377 index:0,count:10112377,average:18,stdev:0 GSM1619184_r1 GEO 3.43 4.03 0.3 155987996 187077345 67119556 84946096 119.93 126.56 0 0 0 0 0 0 32.46 76.35 22826202 2862968 22826202 2862968 56.9 70.32 22826202 5018905 22826202 2636757 21901567 14.04 0.00 0 50.15 0 6.63 0 6.14 0 0.00 0 0.00 0 8821074 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 322.16 0 0.00 0 0 0 10112377 0 5071478 0 670202 0 621101 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 17 0 37.08 0 3749596 0 0 0 0.0 10112377.0 8821074.0 0.0 5071478.0 670202.0 621101.0 0.0 0.0 3749596.0 87.2 0.0 50.2 6.6 6.1 0.0 0.0 37.1 436751 SRR1818541 SRP055513 SRS857295 SRX890482 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619185: CF2 kidney_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;kidney|trimester;;2 GEO Accession;;GSM1619185 GSM1619185 CF2 kidney_22 353885724 19660318 2015-05-28 18:06:17 269894553 353885724 19660318 1 19660318 index:0,count:19660318,average:18,stdev:0 GSM1619185_r1 GEO 2.07 4.41 0.42 274384804 317235522 114784693 146752740 115.62 127.85 0 0 0 0 0 0 27.69 66.97 40709968 4294394 40709968 4294394 48.25 61.58 40709968 7483686 40709968 3948576 57430763 20.93 0.00 0 46.28 0 8.35 0 12.75 0 0.00 0 0.00 0 15511054 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 604.93 0 0.00 0 0 0 19660318 0 9098471 0 1642366 0 2506898 0 0 0 0 0 0 0 0 0 0 0 62 0 0 0 62 0 32.62 0 6412583 0 0 0 0.0 19660318.0 15511054.0 0.0 9098471.0 1642366.0 2506898.0 0.0 0.0 6412583.0 78.9 0.0 46.3 8.4 12.8 0.0 0.0 32.6 436759 SRR1818542 SRP055513 SRS857293 SRX890483 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619186: CR1 spleen_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;spleen|trimester;;2 GEO Accession;;GSM1619186 GSM1619186 CR1 spleen_22 263636784 14646488 2015-05-28 18:06:17 202337150 263636784 14646488 1 14646488 index:0,count:14646488,average:18,stdev:0 GSM1619186_r1 GEO 0.91 3.98 0.3 228612559 259341811 95201666 124074906 113.44 130.33 0 0 0 0 0 0 33.48 81.56 33054567 4338108 33054567 4338108 58.13 75.4 33054567 7531049 33054567 4010498 31319747 13.70 0.00 0 52.14 0 6.68 0 4.87 0 0.00 0 0.00 0 12955698 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 488.22 0 0.00 0 0 0 14646488 0 7636909 0 977768 0 713022 0 0 0 0 0 0 0 0 0 0 0 36 0 0 0 36 0 36.31 0 5318789 0 0 0 0.0 14646488.0 12955698.0 0.0 7636909.0 977768.0 713022.0 0.0 0.0 5318789.0 88.5 0.0 52.1 6.7 4.9 0.0 0.0 36.3 436766 SRR1818543 SRP055513 SRS857292 SRX890484 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619187: DA2 pancreas_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;8.3|Sex;;female|source_name;;Fetal tissue|tissue;;pancreas|trimester;;1 GEO Accession;;GSM1619187 GSM1619187 DA2 pancreas_9 800559576 44475532 2015-05-28 18:06:17 649395945 800559576 44475532 1 44475532 index:0,count:44475532,average:18,stdev:0 GSM1619187_r1 GEO 1.65 4.38 0.28 706492870 872673135 300270675 404974436 123.52 134.87 0 0 0 0 0 0 34.05 81.19 102967372 13652948 102967372 13652948 61.91 73.31 102967372 24824733 102967372 12327074 81510274 11.54 0.00 0 52.35 0 7.16 0 2.68 0 0.00 0 0.00 0 40099573 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 426.97 0 0.01 0 0 0 44475532 0 23284508 0 3186215 0 1189744 0 0 0 0 0 0 0 0 0 0 0 162 0 0 0 162 0 37.81 0 16815065 0 0 0 0.0 44475532.0 40099573.0 0.0 23284508.0 3186215.0 1189744.0 0.0 0.0 16815065.0 90.2 0.0 52.4 7.2 2.7 0.0 0.0 37.8 436774 SRR1818544 SRP055513 SRS857291 SRX890485 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619188: BO1 pancreas_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;21|Sex;;male|source_name;;Fetal tissue|tissue;;pancreas|trimester;;2 GEO Accession;;GSM1619188 GSM1619188 BO1 pancreas_22 118988802 6610489 2015-05-28 18:06:17 93261195 118988802 6610489 1 6610489 index:0,count:6610489,average:18,stdev:0 GSM1619188_r1 GEO 1.38 4.08 0.37 105484754 126419407 45602701 60740067 119.85 133.19 0 0 0 0 0 0 33.0 77.67 15884156 1981817 15884156 1981817 55.3 69.21 15884156 3321350 15884156 1765994 14986080 14.21 0.00 0 52.25 0 6.59 0 2.56 0 0.00 0 0.00 0 6005591 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 390.13 0 0.01 0 0 0 6610489 0 3453916 0 435433 0 169465 0 0 0 0 0 0 0 0 0 0 0 52 0 0 0 52 0 38.60 0 2551675 0 0 0 0.0 6610489.0 6005591.0 0.0 3453916.0 435433.0 169465.0 0.0 0.0 2551675.0 90.8 0.0 52.2 6.6 2.6 0.0 0.0 38.6 873560 SRR1818545 SRP055513 SRS857294 SRX890486 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619189: CV1 skin_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;female|source_name;;Fetal tissue|tissue;;skin|trimester;;2 GEO Accession;;GSM1619189 GSM1619189 CV1 skin_16 276848352 15380464 2015-05-28 18:06:17 214724921 276848352 15380464 1 15380464 index:0,count:15380464,average:18,stdev:0 GSM1619189_r1 GEO 1.22 4.36 0.27 244662707 303906592 106010426 145033450 124.21 136.81 0 0 0 0 0 0 35.0 81.82 35161339 4856285 35161339 4856285 60.55 72.97 35161339 8400996 35161339 4330985 28025076 11.45 0.00 0 51.62 0 7.16 0 2.64 0 0.00 0 0.00 0 13874278 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 128.77 0 0.00 0 0 0 15380464 0 7939239 0 1100736 0 405450 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 15 0 38.59 0 5935039 0 0 0 0.0 15380464.0 13874278.0 0.0 7939239.0 1100736.0 405450.0 0.0 0.0 5935039.0 90.2 0.0 51.6 7.2 2.6 0.0 0.0 38.6 873576 SRR1818546 SRP055513 SRS857289 SRX890487 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619190: CF2 liver_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;liver|trimester;;2 GEO Accession;;GSM1619190 GSM1619190 CF2 liver_22 147096000 8172000 2015-05-28 18:06:17 115043681 147096000 8172000 1 8172000 index:0,count:8172000,average:18,stdev:0 GSM1619190_r1 GEO 1.45 2.89 0.21 134993947 149104338 51379097 67472881 110.45 131.32 0 0 0 0 0 0 31.53 84.19 18270182 2418478 18270182 2418478 62.73 78.51 18270182 4811387 18270182 2255154 11953888 8.86 0.00 0 58.70 0 4.18 0 1.97 0 0.00 0 0.00 0 7669488 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 439.09 0 0.00 0 0 0 8172000 0 4796951 0 341717 0 160795 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 10 0 35.15 0 2872537 0 0 0 0.0 8172000.0 7669488.0 0.0 4796951.0 341717.0 160795.0 0.0 0.0 2872537.0 93.9 0.0 58.7 4.2 2.0 0.0 0.0 35.2 436799 SRR1818547 SRP055513 SRS857290 SRX890488 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619191: CR1 tongue_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;tongue|trimester;;2 GEO Accession;;GSM1619191 GSM1619191 CR1 tongue_22 201214692 11178594 2015-05-28 18:06:17 149468438 201214692 11178594 1 11178594 index:0,count:11178594,average:18,stdev:0 GSM1619191_r1 GEO 1.53 3.89 0.27 180193012 224198738 78634926 108112312 124.42 137.49 0 0 0 0 0 0 36.23 84.07 25589192 3700632 25589192 3700632 61.64 76.97 25589192 6296187 25589192 3387826 22800681 12.65 0.00 0 52.00 0 6.40 0 2.22 0 0.00 0 0.00 0 10214436 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 376.10 0 0.00 0 0 0 11178594 0 5812761 0 715436 0 248722 0 0 0 0 0 0 0 0 0 0 0 29 0 0 0 29 0 39.38 0 4401675 0 0 0 0.0 11178594.0 10214436.0 0.0 5812761.0 715436.0 248722.0 0.0 0.0 4401675.0 91.4 0.0 52.0 6.4 2.2 0.0 0.0 39.4 436807 SRR1818548 SRP055513 SRS857288 SRX890489 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619192: CF2 heart A_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;heart|trimester;;2 GEO Accession;;GSM1619192 GSM1619192 CF2 heart A_22 170185734 9454763 2015-05-28 18:06:17 126231109 170185734 9454763 1 9454763 index:0,count:9454763,average:18,stdev:0 GSM1619192_r1 GEO 4.66 4.01 0.27 153851663 199159209 65949990 91451112 129.45 138.67 0 0 0 0 0 0 35.25 83.3 22357781 3071571 22357781 3071571 63.8 77.17 22357781 5559771 22357781 2845763 17855875 11.61 0.00 0 53.17 0 5.46 0 2.37 0 0.00 0 0.00 0 8714524 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 391.23 0 0.00 0 0 0 9454763 0 5027063 0 515892 0 224347 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 25 0 39.00 0 3687461 0 0 0 0.0 9454763.0 8714524.0 0.0 5027063.0 515892.0 224347.0 0.0 0.0 3687461.0 92.2 0.0 53.2 5.5 2.4 0.0 0.0 39.0 436815 SRR1818549 SRP055513 SRS857287 SRX890490 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619193: DJ1 muscle_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.6|Sex;;male|source_name;;Fetal tissue|tissue;;muscle|trimester;;1 GEO Accession;;GSM1619193 GSM1619193 DJ1 muscle_9 170189604 9454978 2015-05-28 18:06:17 126700825 170189604 9454978 1 9454978 index:0,count:9454978,average:18,stdev:0 GSM1619193_r1 GEO 1.2 4.35 0.33 151448529 189073889 67907527 93096480 124.84 137.09 0 0 0 0 0 0 36.77 82.97 21898196 3155083 21898196 3155083 61.65 74.52 21898196 5290240 21898196 2833554 16520707 10.91 0.00 0 50.53 0 6.74 0 2.51 0 0.00 0 0.00 0 8580547 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 430.86 0 0.01 0 0 0 9454978 0 4777901 0 637444 0 236987 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 22 0 40.22 0 3802646 0 0 0 0.0 9454978.0 8580547.0 0.0 4777901.0 637444.0 236987.0 0.0 0.0 3802646.0 90.8 0.0 50.5 6.7 2.5 0.0 0.0 40.2 873736 SRR1818550 SRP055513 SRS857285 SRX890491 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619194: CR1 skin_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;skin|trimester;;2 GEO Accession;;GSM1619194 GSM1619194 CR1 skin_22 77271768 4292876 2015-05-28 18:06:17 57339293 77271768 4292876 1 4292876 index:0,count:4292876,average:18,stdev:0 GSM1619194_r1 GEO 1.37 4.18 0.31 68655392 84307968 30093946 40197956 122.8 133.57 0 0 0 0 0 0 35.08 81.01 9863137 1363883 9863137 1363883 60.87 73.9 9863137 2366702 9863137 1244172 8268801 12.04 0.00 0 51.36 0 6.68 0 2.74 0 0.00 0 0.00 0 3888324 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 335.96 0 0.00 0 0 0 4292876 0 2204742 0 286741 0 117811 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 9 0 39.22 0 1683582 0 0 0 0.0 4292876.0 3888324.0 0.0 2204742.0 286741.0 117811.0 0.0 0.0 1683582.0 90.6 0.0 51.4 6.7 2.7 0.0 0.0 39.2 873753 SRR1818551 SRP055513 SRS857284 SRX890492 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619195: DF1 umbilical cord_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;cord|trimester;;1 GEO Accession;;GSM1619195 GSM1619195 DF1 umbilical cord_9 308964258 17164681 2015-05-28 18:06:17 243397639 308964258 17164681 1 17164681 index:0,count:17164681,average:18,stdev:0 GSM1619195_r1 GEO 1.14 4.33 0.35 269526348 320757183 122963612 160250202 119.01 130.32 0 0 0 0 0 0 35.82 79.46 39079211 5457479 39079211 5457479 58.23 72.99 39079211 8870991 39079211 5013046 35857339 13.30 0.00 0 48.74 0 7.16 0 4.08 0 0.00 0 0.00 0 15234900 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 514.94 0 0.00 0 0 0 17164681 0 8366345 0 1228964 0 700817 0 0 0 0 0 0 0 0 0 0 0 48 0 0 0 48 0 40.02 0 6868555 0 0 0 0.0 17164681.0 15234900.0 0.0 8366345.0 1228964.0 700817.0 0.0 0.0 6868555.0 88.8 0.0 48.7 7.2 4.1 0.0 0.0 40.0 873768 SRR1818552 SRP055513 SRS857283 SRX890493 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619196: CR1 amnion_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;amnion|trimester;;2 GEO Accession;;GSM1619196 GSM1619196 CR1 amnion_22 341731152 18985064 2015-05-28 18:06:17 269349596 341731152 18985064 1 18985064 index:0,count:18985064,average:18,stdev:0 GSM1619196_r1 GEO 0.73 4.75 0.35 293960484 343007851 123936585 160040781 116.69 129.13 0 0 0 0 0 0 32.26 77.37 42682527 5352874 42682527 5352874 52.87 70.71 42682527 8771107 42682527 4892075 41303545 14.05 0.00 0 50.95 0 7.68 0 4.93 0 0.00 0 0.00 0 16590883 0 18 0 17.91 0 0.00 0 0.00 0 0.00 0 0.00 0 443.81 0 0.00 0 0 0 18985064 0 9672459 0 1458711 0 935470 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 16 0 36.44 0 6918424 0 0 0 0.0 18985064.0 16590883.0 0.0 9672459.0 1458711.0 935470.0 0.0 0.0 6918424.0 87.4 0.0 50.9 7.7 4.9 0.0 0.0 36.4 436894 SRR1818553 SRP055513 SRS857282 SRX890494 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619197: CH1 muscle_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.4|Sex;;female|source_name;;Fetal tissue|tissue;;muscle|trimester;;1 GEO Accession;;GSM1619197 GSM1619197 CH1 muscle_9 30350610 1686145 2015-05-28 18:06:17 25830228 30350610 1686145 1 1686145 index:0,count:1686145,average:18,stdev:0 GSM1619197_r1 GEO 2.29 4.47 0.33 26286564 31754176 10712342 14039545 120.8 131.06 0 0 0 0 0 0 31.27 77.8 3960535 466295 3960535 466295 57.78 70.4 3960535 861551 3960535 421943 3623938 13.79 0.00 0 52.88 0 8.22 0 3.35 0 0.00 0 0.00 0 1491081 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 289.05 0 0.01 0 0 0 1686145 0 891707 0 138580 0 56484 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 9 0 35.55 0 599374 0 0 0 0.0 1686145.0 1491081.0 0.0 891707.0 138580.0 56484.0 0.0 0.0 599374.0 88.4 0.0 52.9 8.2 3.3 0.0 0.0 35.5 436902 SRR1818554 SRP055513 SRS857286 SRX890495 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619198: CF2 muscle_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;muscle|trimester;;2 GEO Accession;;GSM1619198 GSM1619198 CF2 muscle_22 216989694 12054983 2015-05-28 18:06:17 168551021 216989694 12054983 1 12054983 index:0,count:12054983,average:18,stdev:0 GSM1619198_r1 GEO 1.35 4.19 0.24 192542983 246976229 88831976 126750166 128.27 142.69 0 0 0 0 0 0 39.25 86.01 27223913 4284183 27223913 4284183 63.06 77.4 27223913 6882617 27223913 3855379 19224524 9.98 0.00 0 49.22 0 7.31 0 2.15 0 0.00 0 0.00 0 10914157 0 18 0 17.83 0 0.00 0 0.00 0 0.00 0 0.00 0 429.68 0 0.01 0 0 0 12054983 0 5933298 0 881607 0 259219 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 20 0 41.32 0 4980859 0 0 0 0.0 12054983.0 10914157.0 0.0 5933298.0 881607.0 259219.0 0.0 0.0 4980859.0 90.5 0.0 49.2 7.3 2.2 0.0 0.0 41.3 436909 SRR1818555 SRP055513 SRS857281 SRX890496 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619199: CV1 placenta_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;female|source_name;;Fetal tissue|tissue;;placenta|trimester;;2 GEO Accession;;GSM1619199 GSM1619199 CV1 placenta_16 250663284 13925738 2015-05-28 18:06:17 185762166 250663284 13925738 1 13925738 index:0,count:13925738,average:18,stdev:0 GSM1619199_r1 GEO 1.65 3.16 0.18 226546220 274233469 91880498 121984769 121.05 132.76 0 0 0 0 0 0 33.28 83.52 36136253 4291779 36136253 4291779 68.96 77.97 36136253 8893615 36136253 4006247 22798962 10.06 0.00 0 55.71 0 4.74 0 2.65 0 0.00 0 0.00 0 12896435 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 424.85 0 0.00 0 0 0 13925738 0 7758085 0 660037 0 369266 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 22 0 36.90 0 5138350 0 0 0 0.0 13925738.0 12896435.0 0.0 7758085.0 660037.0 369266.0 0.0 0.0 5138350.0 92.6 0.0 55.7 4.7 2.7 0.0 0.0 36.9 436917 SRR1818556 SRP055513 SRS857279 SRX890497 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619200: DF1 stomach_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;stomach|trimester;;1 GEO Accession;;GSM1619200 GSM1619200 DF1 stomach_9 225332460 12518470 2015-05-28 18:06:17 166911127 225332460 12518470 1 12518470 index:0,count:12518470,average:18,stdev:0 GSM1619200_r1 GEO 1.26 4.68 0.34 198496850 244842004 85307815 115081736 123.35 134.9 0 0 0 0 0 0 34.4 81.1 29575697 3870366 29575697 3870366 60.11 73.79 29575697 6763134 29575697 3521471 25152990 12.67 0.00 0 51.75 0 7.52 0 2.61 0 0.00 0 0.00 0 11250518 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 306.57 0 0.00 0 0 0 12518470 0 6478466 0 941145 0 326806 0 0 0 1 0 0 0 0 0 0 0 25 0 0 0 25 0 38.12 0 4772052 0 0 0 0.0 12518470.0 11250518.0 0.0 6478466.0 941145.0 326806.0 0.0 1.0 4772052.0 89.9 0.0 51.8 7.5 2.6 0.0 0.0 38.1 436925 SRR1818557 SRP055513 SRS857280 SRX890498 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619201: DF1 heart V_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;heart|trimester;;1 GEO Accession;;GSM1619201 GSM1619201 DF1 heart V_9 409967622 22775979 2015-05-28 18:06:17 298348653 409967622 22775979 1 22775979 index:0,count:22775979,average:18,stdev:0 GSM1619201_r1 GEO 3.55 4.36 0.33 370042599 468259952 159722324 219379222 126.54 137.35 0 0 0 0 0 0 36.21 84.95 53204978 7585019 53204978 7585019 62.63 77.51 53204978 13120100 53204978 6920704 43072150 11.64 0.00 0 52.77 0 5.96 0 2.06 0 0.00 0 0.00 0 20947461 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 490.98 0 0.00 0 0 0 22775979 0 12018863 0 1358287 0 470231 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 25 0 39.20 0 8928598 0 0 0 0.0 22775979.0 20947461.0 0.0 12018863.0 1358287.0 470231.0 0.0 0.0 8928598.0 92.0 0.0 52.8 6.0 2.1 0.0 0.0 39.2 436934 SRR1818558 SRP055513 SRS857278 SRX890499 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619202: CF2 stomach_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;stomach|trimester;;2 GEO Accession;;GSM1619202 GSM1619202 CF2 stomach_22 368846388 20491466 2015-05-28 18:06:17 282138629 368846388 20491466 1 20491466 index:0,count:20491466,average:18,stdev:0 GSM1619202_r1 GEO 3.14 4.26 0.32 319233656 387974562 129004482 170169264 121.53 131.91 0 0 0 0 0 0 30.92 77.44 48110612 5580318 48110612 5580318 57.04 71.49 48110612 10294590 48110612 5151219 50811972 15.92 0.00 0 52.91 0 7.57 0 4.36 0 0.00 0 0.00 0 18047753 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 515.87 0 0.00 0 0 0 20491466 0 10841745 0 1550428 0 893285 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 25 0 35.17 0 7206008 0 0 0 0.0 20491466.0 18047753.0 0.0 10841745.0 1550428.0 893285.0 0.0 0.0 7206008.0 88.1 0.0 52.9 7.6 4.4 0.0 0.0 35.2 436943 SRR1818559 SRP055513 SRS857276 SRX890500 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619203: CV2 heart V_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16.5|Sex;;male|source_name;;Fetal tissue|tissue;;heart|trimester;;2 GEO Accession;;GSM1619203 GSM1619203 CV2 heart V_16 452710692 25150594 2015-05-28 18:06:17 355212230 452710692 25150594 1 25150594 index:0,count:25150594,average:18,stdev:0 GSM1619203_r1 GEO 3.44 4.33 0.35 398818347 480570617 165159657 218932520 120.5 132.56 0 0 0 0 0 0 33.63 82.31 59059872 7616958 59059872 7616958 58.92 76.07 59059872 13344535 59059872 7039655 53797624 13.49 0.00 0 53.26 0 6.66 0 3.29 0 0.00 0 0.00 0 22649086 0 18 0 17.85 0 0.00 0 0.00 0 0.00 0 0.00 0 167.36 0 0.01 0 0 0 25150594 0 13395064 0 1674406 0 827102 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 100 0 36.79 0 9254022 0 0 0 0.0 25150594.0 22649086.0 0.0 13395064.0 1674406.0 827102.0 0.0 0.0 9254022.0 90.1 0.0 53.3 6.7 3.3 0.0 0.0 36.8 436999 SRR1818560 SRP055513 SRS857275 SRX890501 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619204: BP1 pancreas_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.1|Sex;;male|source_name;;Fetal tissue|tissue;;pancreas|trimester;;1 GEO Accession;;GSM1619204 GSM1619204 BP1 pancreas_9 21573324 1198518 2015-05-28 18:06:17 18120103 21573324 1198518 1 1198518 index:0,count:1198518,average:18,stdev:0 GSM1619204_r1 GEO 1.02 4.63 0.44 18671492 21088648 7278237 9137525 112.95 125.55 0 0 0 0 0 0 27.5 71.89 2961405 293268 2961405 293268 50.24 65.21 2961405 535809 2961405 266001 3271706 17.52 0.00 0 54.95 0 8.14 0 2.88 0 0.00 0 0.00 0 1066481 0 18 0 17.84 0 0.00 0 0.00 0 0.00 0 0.00 0 269.67 0 0.02 0 0 0 1198518 0 658537 0 97531 0 34506 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 9 0 34.04 0 407944 0 0 0 0.0 1198518.0 1066481.0 0.0 658537.0 97531.0 34506.0 0.0 0.0 407944.0 89.0 0.0 54.9 8.1 2.9 0.0 0.0 34.0 437007 SRR1818561 SRP055513 SRS857274 SRX890502 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619205: CR1 brain_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;brain|trimester;;2 GEO Accession;;GSM1619205 GSM1619205 CR1 brain_22 1538639496 85479972 2015-05-28 18:06:17 1149662927 1538639496 85479972 1 85479972 index:0,count:85479972,average:18,stdev:0 GSM1619205_r1 GEO 1.02 4.7 0.41 1367814079 1669057547 626998951 842816391 122.02 134.42 0 0 0 0 0 0 36.59 80.77 191935220 28306074 191935220 28306074 60.72 75.16 191935220 46971332 191935220 26338032 187194389 13.69 0.00 0 49.51 0 5.71 0 3.79 0 0.00 0 0.00 0 77361039 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 506.13 0 0.01 0 0 0 85479972 0 42317156 0 4877056 0 3241877 0 0 0 0 0 0 0 0 0 0 0 162 0 0 0 162 0 41.00 0 35043883 0 0 0 0.0 85479972.0 77361039.0 0.0 42317156.0 4877056.0 3241877.0 0.0 0.0 35043883.0 90.5 0.0 49.5 5.7 3.8 0.0 0.0 41.0 874024 SRR1818562 SRP055513 SRS857277 SRX890503 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619206: DF1 amnion_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;amnion|trimester;;1 GEO Accession;;GSM1619206 GSM1619206 DF1 amnion_9 301948920 16774940 2015-05-28 18:06:17 222197824 301948920 16774940 1 16774940 index:0,count:16774940,average:18,stdev:0 GSM1619206_r1 GEO 1.12 4.05 0.26 267594168 323175317 119043453 150889338 120.77 126.75 0 0 0 0 0 0 33.63 76.6 38640181 5098898 38640181 5098898 58.97 69.81 38640181 8940484 38640181 4646879 31060796 11.61 0.00 0 50.70 0 7.71 0 1.90 0 0.00 0 0.00 0 15161964 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 447.33 0 0.00 0 0 0 16774940 0 8505548 0 1293593 0 319383 0 0 0 0 0 0 0 0 0 0 0 37 0 0 0 37 0 39.68 0 6656416 0 0 0 0.0 16774940.0 15161964.0 0.0 8505548.0 1293593.0 319383.0 0.0 0.0 6656416.0 90.4 0.0 50.7 7.7 1.9 0.0 0.0 39.7 874040 SRR1818563 SRP055513 SRS857273 SRX890504 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619207: CF2 skin_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;skin|trimester;;2 GEO Accession;;GSM1619207 GSM1619207 CF2 skin_22 194070258 10781681 2015-05-28 18:06:17 143816276 194070258 10781681 1 10781681 index:0,count:10781681,average:18,stdev:0 GSM1619207_r1 GEO 1.91 4.37 0.26 172453404 215067094 75864984 103749867 124.71 136.76 0 0 0 0 0 0 36.03 82.89 24826480 3519173 24826480 3519173 62.03 75.78 24826480 6057968 24826480 3217496 20368591 11.81 0.00 0 51.21 0 6.96 0 2.45 0 0.00 0 0.00 0 9766581 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 510.71 0 0.00 0 0 0 10781681 0 5520948 0 750441 0 264659 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 21 0 39.38 0 4245633 0 0 0 0.0 10781681.0 9766581.0 0.0 5520948.0 750441.0 264659.0 0.0 0.0 4245633.0 90.6 0.0 51.2 7.0 2.5 0.0 0.0 39.4 437031 SRR1818564 SRP055513 SRS857272 SRX890505 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619208: DJ1 kidney_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.6|Sex;;male|source_name;;Fetal tissue|tissue;;kidney|trimester;;1 GEO Accession;;GSM1619208 GSM1619208 DJ1 kidney_9 228443958 12691331 2015-05-28 18:06:17 168435575 228443958 12691331 1 12691331 index:0,count:12691331,average:18,stdev:0 GSM1619208_r1 GEO 1.1 4.72 0.37 201337184 246540305 85033108 113845495 122.45 133.88 0 0 0 0 0 0 33.91 81.23 29661524 3862454 29661524 3862454 59.13 73.36 29661524 6735494 29661524 3488290 26205968 13.02 0.00 0 52.29 0 7.71 0 2.54 0 0.00 0 0.00 0 11391338 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 117.75 0 0.00 0 0 0 12691331 0 6636515 0 978062 0 321931 0 0 0 0 0 0 0 0 0 0 0 30 0 0 0 30 0 37.47 0 4754823 0 0 0 0.0 12691331.0 11391338.0 0.0 6636515.0 978062.0 321931.0 0.0 0.0 4754823.0 89.8 0.0 52.3 7.7 2.5 0.0 0.0 37.5 437038 SRR1818565 SRP055513 SRS857271 SRX890506 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619209: DF1 brain_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;brain|trimester;;1 GEO Accession;;GSM1619209 GSM1619209 DF1 brain_9 357509340 19861630 2015-05-28 18:06:17 262742706 357509340 19861630 1 19861630 index:0,count:19861630,average:18,stdev:0 GSM1619209_r1 GEO 1.42 4.82 0.47 318606204 387571528 141727645 190309223 121.65 134.28 0 0 0 0 0 0 34.79 79.12 45092013 6266841 45092013 6266841 58.87 73.12 45092013 10604710 45092013 5791633 46014296 14.44 0.00 0 50.83 0 5.63 0 3.67 0 0.00 0 0.00 0 18015302 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 162.87 0 0.00 0 0 0 19861630 0 10094727 0 1117876 0 728452 0 0 0 0 0 0 0 0 0 0 0 26 0 0 0 26 0 39.88 0 7920575 0 0 0 0.0 19861630.0 18015302.0 0.0 10094727.0 1117876.0 728452.0 0.0 0.0 7920575.0 90.7 0.0 50.8 5.6 3.7 0.0 0.0 39.9 437046 SRR1818566 SRP055513 SRS857269 SRX890507 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619210: DJ1 brain_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.6|Sex;;male|source_name;;Fetal tissue|tissue;;brain|trimester;;1 GEO Accession;;GSM1619210 GSM1619210 DJ1 brain_9 8331192 462844 2015-05-28 18:06:17 6434675 8331192 462844 1 462844 index:0,count:462844,average:18,stdev:0 GSM1619210_r1 GEO 0.93 4.78 0.41 7429385 9300193 3453441 4728843 125.18 136.93 0 0 0 0 0 0 37.15 80.94 1030436 156464 1030436 156464 61.55 74.64 1030436 259245 1030436 144282 950334 12.79 0.00 0 49.24 0 5.32 0 3.68 0 0.00 0 0.00 0 421188 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 104.14 0 0.01 0 0 0 462844 0 227887 0 24627 0 17029 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 41.76 0 193301 0 0 0 0.0 462844.0 421188.0 0.0 227887.0 24627.0 17029.0 0.0 0.0 193301.0 91.0 0.0 49.2 5.3 3.7 0.0 0.0 41.8 437054 SRR1818567 SRP055513 SRS857268 SRX890508 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619211: CR1 chorion_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;chorion|trimester;;2 GEO Accession;;GSM1619211 GSM1619211 CR1 chorion_22 347864868 19325826 2015-05-28 18:06:17 266523730 347864868 19325826 1 19325826 index:0,count:19325826,average:18,stdev:0 GSM1619211_r1 GEO 1.24 4.03 0.29 308893849 372162201 143082216 190454734 120.48 133.11 0 0 0 0 0 0 37.08 80.99 43759343 6473078 43759343 6473078 58.2 74.84 43759343 10161652 43759343 5981212 44799201 14.50 0.00 0 48.99 0 5.77 0 3.89 0 0.00 0 0.00 0 17458972 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 552.17 0 0.00 0 0 0 19325826 0 9466860 0 1114899 0 751955 0 0 0 0 0 0 0 0 0 0 0 61 0 0 0 61 0 41.35 0 7992112 0 0 0 0.0 19325826.0 17458972.0 0.0 9466860.0 1114899.0 751955.0 0.0 0.0 7992112.0 90.3 0.0 49.0 5.8 3.9 0.0 0.0 41.4 437062 SRR1818568 SRP055513 SRS857267 SRX890509 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619212: CF2 eye_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;eye|trimester;;2 GEO Accession;;GSM1619212 GSM1619212 CF2 eye_22 369903942 20550219 2015-05-28 18:06:17 290566255 369903942 20550219 1 20550219 index:0,count:20550219,average:18,stdev:0 GSM1619212_r1 GEO 1.63 4.39 0.32 318848017 378024296 142338072 185181120 118.56 130.1 0 0 0 0 0 0 35.59 80.62 46407481 6410416 46407481 6410416 58.89 74.03 46407481 10609076 46407481 5886446 42615045 13.37 0.00 0 48.96 0 7.21 0 5.13 0 0.00 0 0.00 0 18013908 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 596.62 0 0.00 0 0 0 20550219 0 10062247 0 1481402 0 1054909 0 0 0 0 0 0 0 0 0 0 0 24 0 0 0 24 0 38.69 0 7951661 0 0 0 0.0 20550219.0 18013908.0 0.0 10062247.0 1481402.0 1054909.0 0.0 0.0 7951661.0 87.7 0.0 49.0 7.2 5.1 0.0 0.0 38.7 437070 SRR1818569 SRP055513 SRS857270 SRX890510 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619213: CR1 liver_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;liver|trimester;;2 GEO Accession;;GSM1619213 GSM1619213 CR1 liver_22 191764062 10653559 2015-05-28 18:06:17 151889762 191764062 10653559 1 10653559 index:0,count:10653559,average:18,stdev:0 GSM1619213_r1 GEO 1.27 3.17 0.26 171647932 178344823 63863780 81862588 103.9 128.18 0 0 0 0 0 0 30.8 83.98 24179299 2993696 24179299 2993696 57.49 78.34 24179299 5588353 24179299 2792905 18785824 10.94 0.00 0 57.79 0 5.85 0 2.90 0 0.00 0 0.00 0 9721188 0 18 0 17.91 0 0.00 0 0.00 0 0.00 0 0.00 0 485.48 0 0.00 0 0 0 10653559 0 6156279 0 622995 0 309376 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 8 0 33.46 0 3564909 0 0 0 0.0 10653559.0 9721188.0 0.0 6156279.0 622995.0 309376.0 0.0 0.0 3564909.0 91.2 0.0 57.8 5.8 2.9 0.0 0.0 33.5 437127 SRR1818570 SRP055513 SRS857266 SRX890511 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619214: CL3 gonad_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;8.2|Sex;;female|source_name;;Fetal tissue|tissue;;gonad|trimester;;1 GEO Accession;;GSM1619214 GSM1619214 CL3 gonad_9 23096016 1283112 2015-05-28 18:06:17 19394514 23096016 1283112 1 1283112 index:0,count:1283112,average:18,stdev:0 GSM1619214_r1 GEO 1.1 4.89 0.42 19972792 22570389 7975127 9877441 113.01 123.85 0 0 0 0 0 0 28.55 72.67 3087690 324181 3087690 324181 51.5 66.74 3087690 584747 3087690 297746 3371256 16.88 0.00 0 53.73 0 8.58 0 2.92 0 0.00 0 0.00 0 1135491 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 271.72 0 0.02 0 0 0 1283112 0 689388 0 110115 0 37506 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 10 0 34.77 0 446103 0 0 0 0.0 1283112.0 1135491.0 0.0 689388.0 110115.0 37506.0 0.0 0.0 446103.0 88.5 0.0 53.7 8.6 2.9 0.0 0.0 34.8 437134 SRR1818571 SRP055513 SRS857265 SRX890512 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619215: DF1 tongue_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;tongue|trimester;;1 GEO Accession;;GSM1619215 GSM1619215 DF1 tongue_9 267601536 14866752 2015-05-28 18:06:17 207659872 267601536 14866752 1 14866752 index:0,count:14866752,average:18,stdev:0 GSM1619215_r1 GEO 0.89 4.78 0.34 235764838 290357711 104580028 139871222 123.16 133.75 0 0 0 0 0 0 35.27 80.47 33999800 4709243 33999800 4709243 60.02 72.05 33999800 8012963 33999800 4216470 28739531 12.19 0.00 0 50.44 0 7.47 0 2.73 0 0.00 0 0.00 0 13350536 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 438.69 0 0.01 0 0 0 14866752 0 7498435 0 1110743 0 405473 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 23 0 39.36 0 5852101 0 0 0 0.0 14866752.0 13350536.0 0.0 7498435.0 1110743.0 405473.0 0.0 0.0 5852101.0 89.8 0.0 50.4 7.5 2.7 0.0 0.0 39.4 437143 SRR1818572 SRP055513 SRS857264 SRX890513 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619216: CR1 intestine_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;intestine|trimester;;2 GEO Accession;;GSM1619216 GSM1619216 CR1 intestine_22 323539182 17974399 2015-05-28 18:06:17 238774900 323539182 17974399 1 17974399 index:0,count:17974399,average:18,stdev:0 GSM1619216_r1 GEO 1.9 4.39 0.31 285321400 361523367 124506379 173396726 126.71 139.27 0 0 0 0 0 0 36.18 83.98 41832505 5844336 41832505 5844336 63.29 77.85 41832505 10223057 41832505 5418136 32133378 11.26 0.00 0 51.15 0 7.15 0 2.98 0 0.00 0 0.00 0 16152853 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 425.71 0 0.00 0 0 0 17974399 0 9193534 0 1286067 0 535479 0 0 0 0 0 0 0 0 0 0 0 33 0 0 0 33 0 38.72 0 6959319 0 0 0 0.0 17974399.0 16152853.0 0.0 9193534.0 1286067.0 535479.0 0.0 0.0 6959319.0 89.9 0.0 51.1 7.2 3.0 0.0 0.0 38.7 437150 SRR1818573 SRP055513 SRS857263 SRX890514 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619217: CV1 heart A_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;female|source_name;;Fetal tissue|tissue;;heart|trimester;;2 GEO Accession;;GSM1619217 GSM1619217 CV1 heart A_16 243581688 13532316 2015-05-28 18:06:17 180508521 243581688 13532316 1 13532316 index:0,count:13532316,average:18,stdev:0 GSM1619217_r1 GEO 3.57 4.44 0.28 219656310 281030145 94825429 131968158 127.94 139.17 0 0 0 0 0 0 36.08 84.7 31832076 4491457 31832076 4491457 63.77 77.98 31832076 7938877 31832076 4135129 25552081 11.63 0.00 0 52.81 0 5.92 0 2.08 0 0.00 0 0.00 0 12449222 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 451.08 0 0.00 0 0 0 13532316 0 7146721 0 801227 0 281867 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 21 0 39.18 0 5302501 0 0 0 0.0 13532316.0 12449222.0 0.0 7146721.0 801227.0 281867.0 0.0 0.0 5302501.0 92.0 0.0 52.8 5.9 2.1 0.0 0.0 39.2 437158 SRR1818574 SRP055513 SRS857261 SRX890515 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619218: CV1 eye_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;female|source_name;;Fetal tissue|tissue;;eye|trimester;;2 GEO Accession;;GSM1619218 GSM1619218 CV1 eye_16 257021532 14278974 2015-05-28 18:06:17 189777023 257021532 14278974 1 14278974 index:0,count:14278974,average:18,stdev:0 GSM1619218_r1 GEO 1.05 4.67 0.35 228046272 281666147 103697169 140813569 123.51 135.79 0 0 0 0 0 0 36.37 80.94 32191423 4696728 32191423 4696728 60.14 73.54 32191423 7765046 32191423 4267222 28966618 12.70 0.00 0 49.79 0 6.09 0 3.48 0 0.00 0 0.00 0 12912251 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 508.95 0 0.00 0 0 0 14278974 0 7109820 0 870078 0 496645 0 0 0 0 0 0 0 0 0 0 0 33 0 0 0 33 0 40.64 0 5802431 0 0 0 0.0 14278974.0 12912251.0 0.0 7109820.0 870078.0 496645.0 0.0 0.0 5802431.0 90.4 0.0 49.8 6.1 3.5 0.0 0.0 40.6 437166 SRR1818575 SRP055513 SRS857260 SRX890516 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619219: CV2 eye_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16.5|Sex;;male|source_name;;Fetal tissue|tissue;;eye|trimester;;2 GEO Accession;;GSM1619219 GSM1619219 CV2 eye_16 377145198 20952511 2015-05-28 18:06:17 277497056 377145198 20952511 1 20952511 index:0,count:20952511,average:18,stdev:0 GSM1619219_r1 GEO 1.31 4.26 0.34 335702067 394583725 149185731 193238316 117.54 129.53 0 0 0 0 0 0 35.12 79.96 48034042 6662643 48034042 6662643 58.91 73.73 48034042 11175658 48034042 6143607 44144254 13.15 0.00 0 50.77 0 6.41 0 3.04 0 0.00 0 0.00 0 18971270 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 777.62 0 0.00 0 0 0 20952511 0 10638506 0 1343846 0 637395 0 0 0 0 0 0 0 0 0 0 0 39 0 0 0 39 0 39.77 0 8332764 0 0 0 0.0 20952511.0 18971270.0 0.0 10638506.0 1343846.0 637395.0 0.0 0.0 8332764.0 90.5 0.0 50.8 6.4 3.0 0.0 0.0 39.8 437173 SRR1818576 SRP055513 SRS857262 SRX890517 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619220: DF1 kidney_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;kidney|trimester;;1 GEO Accession;;GSM1619220 GSM1619220 DF1 kidney_9 431388072 23966004 2015-05-28 18:06:17 327343624 431388072 23966004 1 23966004 index:0,count:23966004,average:18,stdev:0 GSM1619220_r1 GEO 1.08 4.78 0.41 377717242 449009149 160044172 207445492 118.87 129.62 0 0 0 0 0 0 33.0 78.8 55808933 7046017 55808933 7046017 57.35 71.55 55808933 12246637 55808933 6397789 52935488 14.01 0.00 0 51.80 0 7.68 0 3.22 0 0.00 0 0.00 0 21354708 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 595.02 0 0.01 0 0 0 23966004 0 12413221 0 1839698 0 771598 0 0 0 0 0 0 0 0 0 0 0 40 0 0 0 40 0 37.31 0 8941487 0 0 0 0.0 23966004.0 21354708.0 0.0 12413221.0 1839698.0 771598.0 0.0 0.0 8941487.0 89.1 0.0 51.8 7.7 3.2 0.0 0.0 37.3 437181 SRR1818577 SRP055513 SRS857258 SRX890518 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619221: CR1 maternal endometrium_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Maternal endometrium|tissue;;endometrium|trimester;;2 GEO Accession;;GSM1619221 GSM1619221 CR1 maternal endometrium_22 227764026 12653557 2015-05-28 18:06:17 180019575 227764026 12653557 1 12653557 index:0,count:12653557,average:18,stdev:0 GSM1619221_r1 GEO 1.52 4.18 0.28 187769880 230088980 86419725 117498517 122.54 135.96 0 0 0 0 0 0 35.64 78.29 27235371 3778746 27235371 3778746 56.08 72.47 27235371 5945790 27235371 3497784 31955867 17.02 0.00 0 45.65 0 6.78 0 9.42 0 0.00 0 0.00 0 10603019 0 18 0 17.91 0 0.00 0 0.00 0 0.00 0 0.00 0 624.01 0 0.00 0 0 0 12653557 0 5776697 0 858543 0 1191995 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 18 0 38.14 0 4826322 0 0 0 0.0 12653557.0 10603019.0 0.0 5776697.0 858543.0 1191995.0 0.0 0.0 4826322.0 83.8 0.0 45.7 6.8 9.4 0.0 0.0 38.1 437189 SRR1818578 SRP055513 SRS857257 SRX890519 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619222: CF2 adrenal_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;adrenal|trimester;;2 GEO Accession;;GSM1619222 GSM1619222 CF2 adrenal_22 459187830 25510435 2015-05-28 18:06:17 359204611 459187830 25510435 1 25510435 index:0,count:25510435,average:18,stdev:0 GSM1619222_r1 GEO 4.82 4.13 0.29 407549789 515800697 154363294 208342191 126.56 134.97 0 0 0 0 0 0 30.07 80.4 62169715 6934445 62169715 6934445 59.72 73.07 62169715 13770814 62169715 6301589 59632569 14.63 0.00 0 56.58 0 5.41 0 4.21 0 0.00 0 0.00 0 23057670 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 507.39 0 0.01 0 0 0 25510435 0 14433244 0 1379370 0 1073395 0 0 0 0 0 0 0 0 0 0 0 27 0 0 0 27 0 33.81 0 8624426 0 0 0 0.0 25510435.0 23057670.0 0.0 14433244.0 1379370.0 1073395.0 0.0 0.0 8624426.0 90.4 0.0 56.6 5.4 4.2 0.0 0.0 33.8 437197 SRR1818579 SRP055513 SRS857256 SRX890520 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619223: CV1 stomach_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;female|source_name;;Fetal tissue|tissue;;stomach|trimester;;2 GEO Accession;;GSM1619223 GSM1619223 CV1 stomach_16 196286400 10904800 2015-05-28 18:06:17 152595349 196286400 10904800 1 10904800 index:0,count:10904800,average:18,stdev:0 GSM1619223_r1 GEO 2.42 4.52 0.27 172130159 217605335 73291414 100384530 126.42 136.97 0 0 0 0 0 0 34.29 81.56 25401767 3342282 25401767 3342282 60.59 74.21 25401767 5906443 25401767 3041163 21472666 12.47 0.00 0 51.81 0 7.56 0 3.05 0 0.00 0 0.00 0 9747811 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 530.50 0 0.00 0 0 0 10904800 0 5649727 0 824649 0 332340 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 17 0 37.58 0 4098084 0 0 0 0.0 10904800.0 9747811.0 0.0 5649727.0 824649.0 332340.0 0.0 0.0 4098084.0 89.4 0.0 51.8 7.6 3.0 0.0 0.0 37.6 437253 SRR1818580 SRP055513 SRS857259 SRX890521 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619224: CF2 pancreas_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;pancreas|trimester;;2 GEO Accession;;GSM1619224 GSM1619224 CF2 pancreas_22 201434616 11190812 2015-05-28 18:06:17 149973469 201434616 11190812 1 11190812 index:0,count:11190812,average:18,stdev:0 GSM1619224_r1 GEO 1.82 3.84 0.25 183092482 236581656 90629617 129081341 129.21 142.43 0 0 0 0 0 0 42.98 87.83 23574602 4447637 23574602 4447637 67.14 79.07 23574602 6947849 23574602 4003896 15997632 8.74 0.00 0 47.22 0 4.95 0 2.58 0 0.00 0 0.00 0 10347983 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 110.07 0 0.00 0 0 0 11190812 0 5284062 0 553984 0 288845 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 20 0 45.25 0 5063921 0 0 0 0.0 11190812.0 10347983.0 0.0 5284062.0 553984.0 288845.0 0.0 0.0 5063921.0 92.5 0.0 47.2 5.0 2.6 0.0 0.0 45.3 437262 SRR1818581 SRP055513 SRS857255 SRX890522 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619225: CR1 placenta_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;placenta|trimester;;2 GEO Accession;;GSM1619225 GSM1619225 CR1 placenta_22 196362882 10909049 2015-05-28 18:06:17 144587145 196362882 10909049 1 10909049 index:0,count:10909049,average:18,stdev:0 GSM1619225_r1 GEO 1.19 3.01 0.2 177364420 211844801 69412648 92455309 119.44 133.2 0 0 0 0 0 0 32.25 83.97 28871659 3258779 28871659 3258779 68.93 78.1 28871659 6963701 28871659 3030906 18560127 10.46 0.00 0 57.04 0 4.97 0 2.42 0 0.00 0 0.00 0 10103290 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 553.13 0 0.01 0 0 0 10909049 0 6222322 0 541911 0 263848 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 14 0 35.58 0 3880968 0 0 0 0.0 10909049.0 10103290.0 0.0 6222322.0 541911.0 263848.0 0.0 0.0 3880968.0 92.6 0.0 57.0 5.0 2.4 0.0 0.0 35.6 437270 SRR1818582 SRP055513 SRS857254 SRX890523 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619226: CV2 heart A_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16.5|Sex;;male|source_name;;Fetal tissue|tissue;;heart|trimester;;2 GEO Accession;;GSM1619226 GSM1619226 CV2 heart A_16 183779334 10209963 2015-05-28 18:06:17 135914997 183779334 10209963 1 10209963 index:0,count:10209963,average:18,stdev:0 GSM1619226_r1 GEO 3.25 4.24 0.36 164769095 203216628 70590986 94777079 123.33 134.26 0 0 0 0 0 0 34.41 81.38 24210288 3209894 24210288 3209894 59.92 75.19 24210288 5589952 24210288 2965804 21926721 13.31 0.00 0 52.75 0 6.07 0 2.55 0 0.00 0 0.00 0 9329601 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 622.98 0 0.00 0 0 0 10209963 0 5385327 0 619721 0 260641 0 0 0 0 0 0 0 0 0 0 0 38 0 0 0 38 0 38.63 0 3944274 0 0 0 0.0 10209963.0 9329601.0 0.0 5385327.0 619721.0 260641.0 0.0 0.0 3944274.0 91.4 0.0 52.7 6.1 2.6 0.0 0.0 38.6 437278 SRR1818583 SRP055513 SRS857252 SRX890524 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619227: DJ2 gonad_18; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;18-|Sex;;female|source_name;;Fetal tissue|tissue;;gonad|trimester;;2 GEO Accession;;GSM1619227 GSM1619227 DJ2 gonad_18 219912318 12217351 2015-05-28 18:06:17 163203630 219912318 12217351 1 12217351 index:0,count:12217351,average:18,stdev:0 GSM1619227_r1 GEO 1.22 4.78 0.38 192745102 224210683 81437665 103595395 116.32 127.21 0 0 0 0 0 0 31.59 75.74 28503594 3446393 28503594 3446393 54.88 69.63 28503594 5987569 28503594 3168302 30998259 16.08 0.00 0 52.06 0 7.09 0 3.61 0 0.00 0 0.00 0 10910722 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 549.78 0 0.01 0 0 0 12217351 0 6360533 0 865919 0 440709 0 0 0 1 0 0 0 0 0 0 0 44 0 0 0 44 0 37.24 0 4550189 0 0 0 0.0 12217351.0 10910722.0 0.0 6360533.0 865919.0 440709.0 0.0 1.0 4550189.0 89.3 0.0 52.1 7.1 3.6 0.0 0.0 37.2 437286 SRR1818584 SRP055513 SRS857251 SRX890525 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619228: CF2 intestine_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;intestine|trimester;;2 GEO Accession;;GSM1619228 GSM1619228 CF2 intestine_22 275721300 15317850 2015-05-28 18:06:17 212352061 275721300 15317850 1 15317850 index:0,count:15317850,average:18,stdev:0 GSM1619228_r1 GEO 2.68 4.11 0.27 243891599 311297633 105170556 145196416 127.64 138.06 0 0 0 0 0 0 35.24 82.77 35319697 4874174 35319697 4874174 62.57 75.72 35319697 8655698 35319697 4458800 27421041 11.24 0.00 0 51.86 0 6.60 0 3.09 0 0.00 0 0.00 0 13833231 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 417.76 0 0.00 0 0 0 15317850 0 7944585 0 1010546 0 474073 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 25 0 38.44 0 5888646 0 0 0 0.0 15317850.0 13833231.0 0.0 7944585.0 1010546.0 474073.0 0.0 0.0 5888646.0 90.3 0.0 51.9 6.6 3.1 0.0 0.0 38.4 874584 SRR1818585 SRP055513 SRS857250 SRX890526 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619229: DJ1 liver_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.6|Sex;;male|source_name;;Fetal tissue|tissue;;liver|trimester;;1 GEO Accession;;GSM1619229 GSM1619229 DJ1 liver_9 277358346 15408797 2015-05-28 18:06:17 212698244 277358346 15408797 1 15408797 index:0,count:15408797,average:18,stdev:0 GSM1619229_r1 GEO 1.95 3.29 0.3 250067087 274848746 92353710 120293614 109.91 130.25 0 0 0 0 0 0 30.34 83.25 35882809 4292031 35882809 4292031 60.53 77.3 35882809 8563741 35882809 3985003 25032945 10.01 0.00 0 58.35 0 6.01 0 2.18 0 0.00 0 0.00 0 14147084 0 18 0 17.91 0 0.00 0 0.00 0 0.00 0 0.00 0 711.18 0 0.00 0 0 0 15408797 0 8991511 0 925749 0 335964 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 21 0 33.46 0 5155573 0 0 0 0.0 15408797.0 14147084.0 0.0 8991511.0 925749.0 335964.0 0.0 0.0 5155573.0 91.8 0.0 58.4 6.0 2.2 0.0 0.0 33.5 874600 SRR1818586 SRP055513 SRS857249 SRX890527 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619230: DF1 placenta_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;placenta|trimester;;1 GEO Accession;;GSM1619230 GSM1619230 DF1 placenta_9 235216494 13067583 2015-05-28 18:06:17 186257861 235216494 13067583 1 13067583 index:0,count:13067583,average:18,stdev:0 GSM1619230_r1 GEO 2.52 4.12 0.33 199951783 233927996 80540105 101400441 116.99 125.9 0 0 0 0 0 0 29.9 75.16 30601371 3382961 30601371 3382961 54.55 69.83 30601371 6170628 30601371 3142793 33900667 16.95 0.00 0 52.13 0 7.64 0 5.78 0 0.00 0 0.00 0 11312860 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 691.81 0 0.00 0 0 0 13067583 0 6812086 0 998872 0 755851 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 12 0 34.44 0 4500774 0 0 0 0.0 13067583.0 11312860.0 0.0 6812086.0 998872.0 755851.0 0.0 0.0 4500774.0 86.6 0.0 52.1 7.6 5.8 0.0 0.0 34.4 437311 SRR1818587 SRP055513 SRS857248 SRX890528 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619231: CP1 eye_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;eye|trimester;;2 GEO Accession;;GSM1619231 GSM1619231 CP1 eye_22 16350228 908346 2015-05-28 18:06:17 13791187 16350228 908346 1 908346 index:0,count:908346,average:18,stdev:0 GSM1619231_r1 GEO 1.54 4.16 0.32 14225928 16232229 6477490 7962684 114.1 122.93 0 0 0 0 0 0 34.36 76.35 2037564 275823 2037564 275823 57.59 71.7 2037564 462333 2037564 259038 1919060 13.49 0.00 0 48.60 0 6.98 0 4.64 0 0.00 0 0.00 0 802754 0 18 0 17.93 0 0.00 0 0.00 0 0.00 0 0.00 0 233.57 0 0.00 0 0 0 908346 0 441487 0 63411 0 42181 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 4 0 39.77 0 361267 0 0 0 0.0 908346.0 802754.0 0.0 441487.0 63411.0 42181.0 0.0 0.0 361267.0 88.4 0.0 48.6 7.0 4.6 0.0 0.0 39.8 437318 SRR1818588 SRP055513 SRS857253 SRX890529 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619232: DJ1 skin_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.6|Sex;;male|source_name;;Fetal tissue|tissue;;skin|trimester;;1 GEO Accession;;GSM1619232 GSM1619232 DJ1 skin_9 33329862 1851659 2015-05-28 18:06:17 27939299 33329862 1851659 1 1851659 index:0,count:1851659,average:18,stdev:0 GSM1619232_r1 GEO 1.18 4.51 0.4 28577096 32743830 11409879 14619464 114.58 128.13 0 0 0 0 0 0 29.31 74.61 4465977 476716 4465977 476716 52.09 67.07 4465977 847268 4465977 428547 4496886 15.74 0.00 0 53.33 0 9.00 0 3.16 0 0.00 0 0.00 0 1626518 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 350.84 0 0.01 0 0 0 1851659 0 987567 0 166700 0 58441 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 19 0 34.51 0 638951 0 0 0 0.0 1851659.0 1626518.0 0.0 987567.0 166700.0 58441.0 0.0 0.0 638951.0 87.8 0.0 53.3 9.0 3.2 0.0 0.0 34.5 437327 SRR1818589 SRP055513 SRS857247 SRX890530 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619233: CV1 muscle_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16|Sex;;female|source_name;;Fetal tissue|tissue;;muscle|trimester;;2 GEO Accession;;GSM1619233 GSM1619233 CV1 muscle_16 112206294 6233683 2015-05-28 18:06:17 83235805 112206294 6233683 1 6233683 index:0,count:6233683,average:18,stdev:0 GSM1619233_r1 GEO 1.45 4.58 0.26 99737096 126950457 44872070 63406452 127.29 141.3 0 0 0 0 0 0 37.87 85.18 14461834 2140670 14461834 2140670 63.07 76.34 14461834 3565368 14461834 1918363 10702235 10.73 0.00 0 50.37 0 7.23 0 2.08 0 0.00 0 0.00 0 5653148 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 448.83 0 0.00 0 0 0 6233683 0 3140134 0 450666 0 129869 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 13 0 40.31 0 2513014 0 0 0 0.0 6233683.0 5653148.0 0.0 3140134.0 450666.0 129869.0 0.0 0.0 2513014.0 90.7 0.0 50.4 7.2 2.1 0.0 0.0 40.3 437382 SRR1818590 SRP055513 SRS857246 SRX890531 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619234: CF2 amnion_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;amnion|trimester;;2 GEO Accession;;GSM1619234 GSM1619234 CF2 amnion_22 238318002 13239889 2015-05-28 18:06:17 176661688 238318002 13239889 1 13239889 index:0,count:13239889,average:18,stdev:0 GSM1619234_r1 GEO 0.94 4.29 0.27 213545984 261318213 91713830 126617069 122.37 138.06 0 0 0 0 0 0 35.63 83.87 30554872 4303519 30554872 4303519 58.53 74.99 30554872 7069118 30554872 3848050 22280325 10.43 0.00 0 52.46 0 6.80 0 1.99 0 0.00 0 0.00 0 12076759 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 441.33 0 0.00 0 0 0 13239889 0 6945484 0 900017 0 263113 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 20 0 38.76 0 5131275 0 0 0 0.0 13239889.0 12076759.0 0.0 6945484.0 900017.0 263113.0 0.0 0.0 5131275.0 91.2 0.0 52.5 6.8 2.0 0.0 0.0 38.8 437390 SRR1818591 SRP055513 SRS857245 SRX890532 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619235: CF2 placenta_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;female|source_name;;Fetal tissue|tissue;;placenta|trimester;;2 GEO Accession;;GSM1619235 GSM1619235 CF2 placenta_22 250162146 13897897 2015-05-28 18:06:17 185617528 250162146 13897897 1 13897897 index:0,count:13897897,average:18,stdev:0 GSM1619235_r1 GEO 3.33 4.56 0.26 224615800 287663718 99526545 135761810 128.07 136.41 0 0 0 0 0 0 37.35 85.28 31914807 4753872 31914807 4753872 64.87 79.15 31914807 8255220 31914807 4411831 22568597 10.05 0.00 0 51.46 0 5.64 0 2.79 0 0.00 0 0.00 0 12726422 0 18 0 17.85 0 0.00 0 0.00 0 0.00 0 0.00 0 113.71 0 0.00 0 0 0 13897897 0 7152194 0 783277 0 388198 0 0 0 0 0 0 0 0 0 0 0 37 0 0 0 37 0 40.11 0 5574228 0 0 0 0.0 13897897.0 12726422.0 0.0 7152194.0 783277.0 388198.0 0.0 0.0 5574228.0 91.6 0.0 51.5 5.6 2.8 0.0 0.0 40.1 437399 SRR1818592 SRP055513 SRS857244 SRX890533 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619236: CC3 heart A_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;21|Sex;;female|source_name;;Fetal tissue|tissue;;heart|trimester;;2 GEO Accession;;GSM1619236 GSM1619236 CC3 heart A_22 269422866 14967937 2015-05-28 18:06:17 197979520 269422866 14967937 1 14967937 index:0,count:14967937,average:18,stdev:0 GSM1619236_r1 GEO 3.45 4.26 0.3 238402050 292271182 100469309 135053163 122.6 134.42 0 0 0 0 0 0 32.94 79.24 34905507 4447899 34905507 4447899 58.06 73.33 34905507 7838998 34905507 4116204 34461013 14.45 0.00 0 52.70 0 6.26 0 3.53 0 0.00 0 0.00 0 13502132 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 431.08 0 0.00 0 0 0 14967937 0 7888588 0 937735 0 528070 0 0 0 0 0 0 0 0 0 0 0 31 0 0 0 31 0 37.50 0 5613544 0 0 0 0.0 14967937.0 13502132.0 0.0 7888588.0 937735.0 528070.0 0.0 0.0 5613544.0 90.2 0.0 52.7 6.3 3.5 0.0 0.0 37.5 437407 SRR1818593 SRP055513 SRS857243 SRX890534 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619237: CR1 muscle_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;muscle|trimester;;2 GEO Accession;;GSM1619237 GSM1619237 CR1 muscle_22 304176078 16898671 2015-05-28 18:06:17 233099936 304176078 16898671 1 16898671 index:0,count:16898671,average:18,stdev:0 GSM1619237_r1 GEO 1.21 4.38 0.3 270083144 343452143 122647170 173605740 127.17 141.55 0 0 0 0 0 0 37.93 84.54 38581763 5802569 38581763 5802569 62.42 76.5 38581763 9549436 38581763 5250887 29735434 11.01 0.00 0 49.92 0 7.41 0 2.05 0 0.00 0 0.00 0 15299074 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 553.05 0 0.00 0 0 0 16898671 0 8435191 0 1252485 0 347112 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 23 0 40.62 0 6863883 0 0 0 0.0 16898671.0 15299074.0 0.0 8435191.0 1252485.0 347112.0 0.0 0.0 6863883.0 90.5 0.0 49.9 7.4 2.1 0.0 0.0 40.6 437415 SRR1818594 SRP055513 SRS857242 SRX890535 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619238: CV2 gonad_16; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;16.5|Sex;;male|source_name;;Fetal tissue|tissue;;gonad|trimester;;2 GEO Accession;;GSM1619238 GSM1619238 CV2 gonad_16 130027320 7223740 2015-05-28 18:06:17 100203084 130027320 7223740 1 7223740 index:0,count:7223740,average:18,stdev:0 GSM1619238_r1 GEO 1.73 4.7 0.41 112271408 134138925 46538623 61535149 119.48 132.22 0 0 0 0 0 0 32.4 79.08 16776427 2056531 16776427 2056531 56.11 72.42 16776427 3561309 16776427 1883426 17716824 15.78 0.00 0 51.87 0 7.26 0 4.87 0 0.00 0 0.00 0 6347448 0 18 0 17.90 0 0.00 0 0.00 0 0.00 0 0.00 0 440.77 0 0.01 0 0 0 7223740 0 3746893 0 524638 0 351654 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 3 0 36.00 0 2600555 0 0 0 0.0 7223740.0 6347448.0 0.0 3746893.0 524638.0 351654.0 0.0 0.0 2600555.0 87.9 0.0 51.9 7.3 4.9 0.0 0.0 36.0 437423 SRR1818595 SRP055513 SRS857241 SRX890536 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619239: DJ1 lung_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.6|Sex;;male|source_name;;Fetal tissue|tissue;;lung|trimester;;1 GEO Accession;;GSM1619239 GSM1619239 DJ1 lung_9 278232660 15457370 2015-05-28 18:06:17 219429268 278232660 15457370 1 15457370 index:0,count:15457370,average:18,stdev:0 GSM1619239_r1 GEO 0.87 4.91 0.38 236114443 279089696 97750033 127980538 118.2 130.93 0 0 0 0 0 0 31.82 77.74 35722251 4247358 35722251 4247358 56.09 70.38 35722251 7488040 35722251 3845256 33275933 14.09 0.00 0 51.01 0 9.20 0 4.44 0 0.00 0 0.00 0 13349135 0 18 0 17.89 0 0.00 0 0.00 0 0.00 0 0.00 0 141.23 0 0.01 0 0 0 15457370 0 7885428 0 1421361 0 686874 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 12 0 35.35 0 5463707 0 0 0 0.0 15457370.0 13349135.0 0.0 7885428.0 1421361.0 686874.0 0.0 0.0 5463707.0 86.4 0.0 51.0 9.2 4.4 0.0 0.0 35.3 437431 SRR1818596 SRP055513 SRS857240 SRX890537 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619240: CC3 heart V_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;21|Sex;;female|source_name;;Fetal tissue|tissue;;heart|trimester;;2 GEO Accession;;GSM1619240 GSM1619240 CC3 heart V_22 26147412 1452634 2015-05-28 18:06:17 22013770 26147412 1452634 1 1452634 index:0,count:1452634,average:18,stdev:0 GSM1619240_r1 GEO 3.31 4.42 0.34 22629598 26418598 9618646 12608662 116.74 131.09 0 0 0 0 0 0 33.03 78.82 3316086 423168 3316086 423168 55.95 73.55 3316086 716850 3316086 394893 3321652 14.68 0.00 0 51.24 0 6.59 0 5.21 0 0.00 0 0.00 0 1281266 0 18 0 17.92 0 0.00 0 0.00 0 0.00 0 0.00 0 348.63 0 0.00 0 0 0 1452634 0 744375 0 95668 0 75700 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 4 0 36.96 0 536891 0 0 0 0.0 1452634.0 1281266.0 0.0 744375.0 95668.0 75700.0 0.0 0.0 536891.0 88.2 0.0 51.2 6.6 5.2 0.0 0.0 37.0 437439 SRR1818597 SRP055513 SRS857239 SRX890538 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619241: CH1 gonad_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.4|Sex;;female|source_name;;Fetal tissue|tissue;;gonad|trimester;;1 GEO Accession;;GSM1619241 GSM1619241 CH1 gonad_9 12264462 681359 2015-05-28 18:06:17 10602467 12264462 681359 1 681359 index:0,count:681359,average:18,stdev:0 GSM1619241_r1 GEO 1.31 4.81 0.43 10554920 11762418 4007058 4960865 111.44 123.8 0 0 0 0 0 0 26.19 70.3 1688701 157728 1688701 157728 48.76 64.54 1688701 293614 1688701 144786 1947468 18.45 0.00 0 55.45 0 8.71 0 2.91 0 0.00 0 0.00 0 602172 0 18 0 17.86 0 0.00 0 0.00 0 0.00 0 0.00 0 188.68 0 0.02 0 0 0 681359 0 377821 0 59337 0 19850 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 4 0 32.93 0 224351 0 0 0 0.0 681359.0 602172.0 0.0 377821.0 59337.0 19850.0 0.0 0.0 224351.0 88.4 0.0 55.5 8.7 2.9 0.0 0.0 32.9 874888 SRR1818598 SRP055513 SRS857238 SRX890539 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619242: CR1 lung_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;lung|trimester;;2 GEO Accession;;GSM1619242 GSM1619242 CR1 lung_22 175563774 9753543 2015-05-28 18:06:17 136527780 175563774 9753543 1 9753543 index:0,count:9753543,average:18,stdev:0 GSM1619242_r1 GEO 1.2 4.65 0.31 153680838 192958755 68906861 93701178 125.56 135.98 0 0 0 0 0 0 36.58 82.62 21928049 3184128 21928049 3184128 62.16 75.19 21928049 5411037 21928049 2897659 17680734 11.50 0.00 0 49.74 0 7.05 0 3.69 0 0.00 0 0.00 0 8705364 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 438.91 0 0.00 0 0 0 9753543 0 4851591 0 687822 0 360357 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 21 0 39.51 0 3853773 0 0 0 0.0 9753543.0 8705364.0 0.0 4851591.0 687822.0 360357.0 0.0 0.0 3853773.0 89.3 0.0 49.7 7.1 3.7 0.0 0.0 39.5 874904 SRR1818599 SRP055513 SRS857237 SRX890540 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619243: DF1 spinal cord_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;9.3|Sex;;male|source_name;;Fetal tissue|tissue;;cord|trimester;;1 GEO Accession;;GSM1619243 GSM1619243 DF1 spinal cord_9 214289910 11904995 2015-05-28 18:06:17 158538901 214289910 11904995 1 11904995 index:0,count:11904995,average:18,stdev:0 GSM1619243_r1 GEO 1.45 4.74 0.36 192971017 243991121 91948083 126962862 126.44 138.08 0 0 0 0 0 0 39.38 83.63 26169416 4300490 26169416 4300490 63.21 76.01 26169416 6903063 26169416 3908826 22960046 11.90 0.00 0 48.53 0 5.14 0 3.13 0 0.00 0 0.00 0 10920019 0 18 0 17.88 0 0.00 0 0.00 0 0.00 0 0.00 0 131.47 0 0.00 0 0 0 11904995 0 5777459 0 612061 0 372915 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 17 0 43.20 0 5142560 0 0 0 0.0 11904995.0 10920019.0 0.0 5777459.0 612061.0 372915.0 0.0 0.0 5142560.0 91.7 0.0 48.5 5.1 3.1 0.0 0.0 43.2 876553 SRR1818600 SRP055513 SRS857236 SRX890541 SRA244533 GEO A human fetal transcriptional atlas Gene expression is highly dynamic during fetal development and determines tissue specification and function. In humans, the transcriptional profile of different organs during development has not been systematically studied. However, understanding how a particular tissue acquires its tissue identity will give insight into the development and maturation of tissues from a developmental biology perspective. Overall design: Next-generation sequencing (DeepSAGE) dataset of 111 RNA samples representing 21 different human fetal organs and the maternal endometrium at three timepoints (gestational ages) during first and second trimester development (W9, W16-18, W22) GSM1619244: CR1 stomach_22; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single After washing with 0.9% NaCl (Fresenius Kabi, France), the organs and tissues were snap-frozen in buffer RLT (Qiagen, Germany) and stored at -80°C until further use. The organs and tissues were homogenized using a pestle or a syringe needle followed by the QIAshredder homogenizer (Qiagen, Germany). Total RNA was isolated with the RNeasy Kit (Qiagen, Germany) including on-column DNase digestion. The DeepSAGE libraries were generated as previously described (Mastrokolias et al., 2012; GSE33701). Each library (8 pM) was loaded on a v3 flowcell and sequenced on an Illumina HiSeq2000 sequencer (Illumina, USA). Illumina HiSeq 2000 gestational age;;22|Sex;;male|source_name;;Fetal tissue|tissue;;stomach|trimester;;2 GEO Accession;;GSM1619244 GSM1619244 CR1 stomach_22 215764524 11986918 2015-05-28 18:06:17 160057990 215764524 11986918 1 11986918 index:0,count:11986918,average:18,stdev:0 GSM1619244_r1 GEO 4.31 4.08 0.28 190836299 248257198 81240804 112729623 130.09 138.76 0 0 0 0 0 0 34.62 82.48 27975420 3748746 27975420 3748746 63.46 75.47 27975420 6871183 27975420 3430077 22684219 11.89 0.00 0 52.41 0 6.38 0 3.30 0 0.00 0 0.00 0 10827193 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 469.05 0 0.01 0 0 0 11986918 0 6282139 0 764487 0 395235 0 0 0 3 0 0 0 0 0 0 0 23 0 0 0 23 0 37.92 0 4545054 0 0 0 0.0 11986918.0 10827193.0 0.0 6282139.0 764487.0 395235.0 0.0 3.0 4545054.0 90.3 0.0 52.4 6.4 3.3 0.0 0.0 37.9 342078 SRR2099707 SRP040110 SRS572281 SRX488750 SRA145703 University of Colorado - Denver Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts These are RNAseq reads from human cell culture (neurons and fibroblasts) infected with VZV. Thus the reads are a mixture of human and viral. The study was designed to assess whether VZV was in true latency, or whether is was simply an aborted infection. Comparison of Vericella-Zoster Virus RNA sequences in human neurons and fibroblasts Illumina TruSeq stranded-mRNA library, iCell human-iPS differentiated to a neuronal cell type Infected with VZV NEURON-1 RNA-Seq TRANSCRIPTOMIC RANDOM paired 0.0E0 Illumina HiSeq 2000 age;;14 days|biomaterial provider;;Don Gilden, University of Colorado - Denver|BioSampleModel;;Human|cell line;;iCell human iPC differentiated neuron|disease;;infected with VZV|isolate;;iCell human iPC and vOka VZV|sex;;not determined|tissue;;Neuron 202 NEURON-1 Human neuron infected with Varicella-Zoster Virus 280634024 1392338 2015-07-14 11:32:12 56906344 280634024 1392338 2 1392338 index:0,count:1392338,average:100.81,stdev:1.54|index:1,count:1392338,average:100.75,stdev:1.81 Neuron-1 0.0 0.0 0.0 317 317 134 134 100.0 100.0 2 2 147.500 147.500 161 1 50.0 100.0 3 1 3 1 100.0 100.0 3 2 3 1 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 2 0 201 0 182.00 0 0.00 0 0.00 0 0.00 0 0.00 0 50.63 0 4.95 0 0 0 1392338 0 1 0 0 0 18 0 0 0 1392318 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 1 0 0 0 0.0 1392338.0 2.0 0.0 1.0 0.0 18.0 0.0 1392318.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 684681 SRR2099728 SRP040110 SRS572352 SRX488833 SRA145703 University of Colorado - Denver Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts These are RNAseq reads from human cell culture (neurons and fibroblasts) infected with VZV. Thus the reads are a mixture of human and viral. The study was designed to assess whether VZV was in true latency, or whether is was simply an aborted infection. Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts Illumina TruSeq stranded-mRNA library, iCell human-iPS differentiated to a neuronal cell type, Infected with VZV NEURON-2 RNA-Seq TRANSCRIPTOMIC RANDOM paired 0.0E0 Illumina HiSeq 2000 age;;14 days|biomaterial provider;;Don Gilden, University of Colorado - Denver|BioSampleModel;;Human|cell line;;iCell human iPC differentiated neuron|isolate;;iCell human iPC and vOka VZV|sex;;not determined|tissue;;Neuron 202 NEURON-2 Human neuron infected with Varicella-Zoster Virus 388661959 1928409 2015-07-14 11:32:12 79936964 388661959 1928409 2 1928409 index:0,count:1928409,average:100.80,stdev:1.56|index:1,count:1928409,average:100.74,stdev:1.83 Neuron-2 0.0 0.0 0.0 1125 1298 978 1004 115.38 102.66 8 8 140.625 140.625 147 2 75.0 85.71 9 6 9 6 87.5 85.71 9 7 9 6 275 24.44 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 8 0 201 0 191.57 0 2.00 0 0.15 0 0.00 0 0.00 0 49.24 0 0.67 0 0 0 1928409 0 1 0 0 0 41 0 0 0 1928360 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 7 0 0 0 0.0 1928409.0 8.0 0.0 1.0 0.0 41.0 0.0 1928360.0 7.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 342479 SRR2099739 SRP040110 SRS572380 SRX488860 SRA145703 University of Colorado - Denver Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts These are RNAseq reads from human cell culture (neurons and fibroblasts) infected with VZV. Thus the reads are a mixture of human and viral. The study was designed to assess whether VZV was in true latency, or whether is was simply an aborted infection. Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts Illumina TruSeq stranded-mRNA library, iCell human-iPS differentiated to a neuronal cell type, Infected with VZV NEURON-3 RNA-Seq TRANSCRIPTOMIC RANDOM paired 0.0E0 Illumina HiSeq 2000 age;;14 days|biomaterial_provider;;Don Gilden, University of Colorado - Denver|BioSampleModel;;Human|cell_line;;iCell human iPC differentiated neuron|isolate;;iCell human iPC and vOka VZV|sex;;not determined|tissue;;neuron 202 NEURON-3 Human neuron infected with Varicella-Zoster Virus 79300448 393310 2015-07-14 11:33:11 16838197 79300448 393310 2 393310 index:0,count:393310,average:100.82,stdev:1.51|index:1,count:393310,average:100.81,stdev:1.58 Neuron-3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.01 0 0.00 0 99.99 0 0 0 201 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 18.39 0 0 0 0 0 393310 0 0 0 0 0 30 0 0 0 393280 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 393310.0 0.0 0.0 0.0 0.0 30.0 0.0 393280.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 685064 SRR2099740 SRP040110 SRS572381 SRX488861 SRA145703 University of Colorado - Denver Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts These are RNAseq reads from human cell culture (neurons and fibroblasts) infected with VZV. Thus the reads are a mixture of human and viral. The study was designed to assess whether VZV was in true latency, or whether is was simply an aborted infection. Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts Illumina TruSeq stranded-mRNA library, iCell human-iPS differentiated to a neuronal cell type, Infected with VZV HFL-1 RNA-Seq TRANSCRIPTOMIC RANDOM paired 0.0E0 Illumina HiSeq 2000 age;;14 days|biomaterial provider;;Don Gilden, University of Colorado - Denver|BioSampleModel;;Human|cell line;;human fetal lung fibroblast|isolate;;human fetal lung fibroblasts and vOka VZV|sex;;not determined|tissue;;fibroblast 202 HFL-1 Human fibroblast infected with Varicella-Zoster Virus 856009483 4247399 2015-07-14 11:33:11 177532380 856009483 4247399 2 4247399 index:0,count:4247399,average:100.80,stdev:1.55|index:1,count:4247399,average:100.74,stdev:1.86 Fibroblast-1 0.0 0.0 0.0 381 381 218 218 100.0 100.0 3 3 127.000 127.000 60 1 33.33 50.0 4 1 4 1 33.33 50.0 4 1 4 1 179 46.98 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 3 0 201 0 161.00 0 0.00 0 0.00 0 0.00 0 0.00 0 49.17 0 1.86 0 0 0 4247399 0 1 0 0 0 118 0 0 0 4247278 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 2 0 0 0 0.0 4247399.0 3.0 0.0 1.0 0.0 118.0 0.0 4247278.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 342543 SRR2099741 SRP040110 SRS572382 SRX488862 SRA145703 University of Colorado - Denver Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts These are RNAseq reads from human cell culture (neurons and fibroblasts) infected with VZV. Thus the reads are a mixture of human and viral. The study was designed to assess whether VZV was in true latency, or whether is was simply an aborted infection. Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts Illumina TruSeq stranded-mRNA library, iCell human-iPS differentiated to a neuronal cell type, Infected with VZV HFL-2 RNA-Seq TRANSCRIPTOMIC RANDOM paired 0.0E0 Illumina HiSeq 2000 age;;14 days|biomaterial provider;;Don Gilden, University of Colorado - Denver|BioSampleModel;;Human|cell line;;human fetal lung fibroblast|isolate;;Human fetal lung fibroblasts and vOka VZV|sex;;not determined|tissue;;fibroblast 202 HFL-2 Human fibroblast infected with Varicella-Zoster Virus 1925827499 9555972 2015-07-14 11:33:11 402781059 1925827499 9555972 2 9555972 index:0,count:9555972,average:100.80,stdev:1.57|index:1,count:9555972,average:100.73,stdev:1.88 Fibroblast-2 0.0 0.0 0.0 669 666 447 444 99.55 99.33 6 6 111.500 111.500 154 2 50.0 75.0 13 3 13 3 66.67 75.0 13 4 13 3 62 9.27 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 6 0 201 0 166.75 0 0.00 0 0.00 0 2.00 0 0.30 0 51.04 0 1.20 0 0 0 9555972 0 2 0 0 0 172 0 0 0 9555794 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 4 0 0 0 0.0 9555972.0 6.0 0.0 2.0 0.0 172.0 0.0 9555794.0 4.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 685097 SRR2099742 SRP040110 SRS572420 SRX488901 SRA145703 University of Colorado - Denver Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts These are RNAseq reads from human cell culture (neurons and fibroblasts) infected with VZV. Thus the reads are a mixture of human and viral. The study was designed to assess whether VZV was in true latency, or whether is was simply an aborted infection. Comparison of Varicella-Zoster Virus RNA sequences in human neurons and fibroblasts Illumina TruSeq stranded-mRNA library, iCell human-iPS differentiated to a neuronal cell type, Infected with VZV HFL-3 RNA-Seq TRANSCRIPTOMIC RANDOM paired 0.0E0 Illumina HiSeq 2000 age;;14 days|biomaterial provider;;Don Gilden, University of Colorado - Denver|BioSampleModel;;Human|cell line;;Human fetal lung fibroblast|isolate;;Human fetal lung fibroblasts and vOka VZV|sex;;not determined|tissue;;fibroblast 202 HFL-3 Human fibroblast infected with Varicella-Zoster Virus 1137516807 5644166 2015-07-14 11:34:14 235657468 1137516807 5644166 2 5644166 index:0,count:5644166,average:100.80,stdev:1.55|index:1,count:5644166,average:100.73,stdev:1.87 Fibroblast-3 0.0 0.0 5.56 1299 1423 1228 1352 109.55 110.1 11 11 118.091 118.091 71 2 45.45 50.0 18 5 18 5 45.45 40.0 18 5 18 4 212 16.32 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 11 0 201 0 172.20 0 0.00 0 0.00 0 0.00 0 0.00 0 40.48 0 1.05 0 0 0 5644166 0 1 0 0 0 125 0 0 0 5644030 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 10 0 0 0 0.0 5644166.0 11.0 0.0 1.0 0.0 125.0 0.0 5644030.0 10.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 891161 SRR2671991 SRP064863 SRS1115910 SRX1339072 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad6 infected A549 6 hours replicate 1 mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" . 6_10_6.FCC0F05ACXX_L1_R1_ICGATGT RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;6 hours after infection|tissue;;lung carcinoma|Treatment replicate;;1|treatment;;infected with human adenovirus type 6 202 Ad6 infected A549 6 hours replicate 1 294268700 1523159 2015-10-30 15:33:51 150236115 294268700 1523159 2 1523159 index:0,count:1477216,average:100,stdev:0|index:1,count:1465471,average:100,stdev:0 6_10_6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00 100.00 0 0 200 100 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 52.68 15.54 0 0 0 0 1419528 103631 0 0 0 0 32 0 0 0 1419496 103631 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 1523159.0 0.0 0.0 0.0 0.0 32.0 0.0 1523127.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 853097 SRR2672046 SRP064863 SRS1117398 SRX1341869 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad6 infected A549 6 hours replicate 3 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 6-2_10_6.FCD1RRNACXX_L2_IGTGGCC RNA-Seq TRANSCRIPTOMIC PolyA paired Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;6 hours after infection|tissue;;lung carcinoma|Treatment replicate;;3|treatment;;infected with human adenovirus type 6 202 Ad6 infected A549 6 hours replicate 3 110261410 587733 2015-10-30 15:33:51 50273367 110261410 587733 2 587733 index:0,count:567994,average:100,stdev:0|index:1,count:562758,average:95,stdev:0 6-2_10_6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00 100.00 0 0 195 97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 8.35 3.83 0 0 0 0 543019 44714 0 0 0 0 7 0 0 0 543012 44714 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 587733.0 0.0 0.0 0.0 0.0 7.0 0.0 587726.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 856377 SRR2672113 SRP064863 SRS1117472 SRX1341946 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad6 infected A549 12 hours replicate 1 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 6_10_12.FCC0F05ACXX_L1_R1_ITGACCA RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;12 hours after infection|tissue;;lung carcinoma|Treatment replicate;;1|treatment;;infected with human adenovirus type 6 202 Ad6 infected A549 12 hours replicate 1 3661987300 18784489 2015-10-30 15:33:51 1900498781 3661987300 18784489 2 18784489 index:0,count:18373980,average:100,stdev:0|index:1,count:18245893,average:100,stdev:0 6_10_12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00 100.00 0 0 200 100 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 56.67 136.67 0 0 0 0 17835384 949105 0 0 0 0 779 0 0 0 17834605 949105 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 18784489.0 0.0 0.0 0.0 0.0 779.0 0.0 18783710.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 428422 SRR2672130 SRP064863 SRS1117475 SRX1341947 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad6 infected A549 12 hours replicate 2 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 6-1_10_12.FCD1RRNACXX_L2_IGTGAAA RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;12 hours after infection|tissue;;lung carcinoma|Treatment replicate;;2|treatment;;infected with human adenovirus type 6 202 Ad6 infected A549 12 hours replicate 2 1487030225 7896386 2015-10-30 15:33:51 685608550 1487030225 7896386 2 7896386 index:0,count:7632542,average:100,stdev:0|index:1,count:7618695,average:95,stdev:0 6-1_10_12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 99.99 100.00 0 0 195 97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 65.22 64.98 0 0 0 0 7354851 541535 0 0 0 0 677 0 0 0 7354174 541535 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 7896386.0 0.0 0.0 0.0 0.0 677.0 0.0 7895709.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 860314 SRR2672209 SRP064863 SRS1117476 SRX1341949 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad6 infected A549 12 hours replicate 3 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 6-2_10.12.FCD1RRNACXX_L3_IGTTTCG RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;12 hours after infection|tissue;;lung carcinoma|Treatment replicate;;3|treatment;;infected with human adenovirus type 6 202 Ad6 infected A549 12 hours replicate 3 1650835615 8771862 2015-10-30 15:33:51 766341323 1650835615 8771862 2 8771862 index:0,count:8474000,average:100,stdev:0|index:1,count:8457217,average:95,stdev:0 6-2_10_12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 99.99 100.00 0 0 195 97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 63.31 81.67 0 0 0 0 8159355 612507 0 0 0 0 862 0 0 0 8158493 612507 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 8771862.0 0.0 0.0 0.0 0.0 862.0 0.0 8771000.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 860811 SRR2672228 SRP064863 SRS1117483 SRX1341952 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad26 infected A549 6 hours replicate 1 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 26_10_6.FCC0F05ACXX_L2_R1_IACAGTG RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;6 hours after infection|tissue;;lung carcinoma|Treatment replicate;;1|treatment;;infected with human adenovirus type 26 202 Ad26 infected A549 6 hours replicate 1 222665100 1141369 2015-10-30 15:33:51 107506794 222665100 1141369 2 1141369 index:0,count:1118288,average:100,stdev:0|index:1,count:1108363,average:100,stdev:0 26_10_6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 99.99 100.00 0 0 200 100 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 56.62 20.19 0 0 0 0 1085282 56087 0 0 0 0 161 0 0 0 1085121 56087 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 1141369.0 0.0 0.0 0.0 0.0 161.0 0.0 1141208.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 860827 SRR2672229 SRP064863 SRS1117493 SRX1341966 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad26 infected A549 6 hours replicate 2 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 26-1_10_6.FCD1RRNACXX_L3_ICGTACG RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;6 hours after infection|tissue;;lung carcinoma|Treatment replicate;;2|treatment;;infected with human adenovirus type 26 202 Ad26 infected A549 6 hours replicate 2 17552690 92957 2015-10-30 15:33:51 8130166 17552690 92957 2 92957 index:0,count:90804,average:100,stdev:0|index:1,count:89182,average:95,stdev:0 26-1_10_6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 99.99 100.00 0 0 195 98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 11.60 7.11 0 0 0 0 87029 5928 0 0 0 0 9 0 0 0 87020 5928 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 92957.0 0.0 0.0 0.0 0.0 9.0 0.0 92948.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 860940 SRR2672230 SRP064863 SRS1117506 SRX1341971 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad26 infected A549 6 hours replicate 3 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 26-2_10_6.FCD1RRNACXX_L3_IACTCAT RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;6 hours after infection|tissue;;lung carcinoma|Treatment replicate;;3|treatment;;infected with human adenovirus type 26 202 Ad26 infected A549 6 hours replicate 3 13976305 74083 2015-10-30 15:33:51 6450108 13976305 74083 2 74083 index:0,count:72276,average:100,stdev:0|index:1,count:71039,average:95,stdev:0 26-2_10_6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 99.99 100.00 0 0 195 98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10.84 8.73 0 0 0 0 69232 4851 0 0 0 0 5 0 0 0 69227 4851 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 74083.0 0.0 0.0 0.0 0.0 5.0 0.0 74078.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 860957 SRR2672231 SRP064863 SRS1117516 SRX1342001 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad26 infected A549 12 hours replicate 1 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 26_10_12.FCC0F05ACXX_L2_R1_IGCCAAT RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;12 hours after infection|tissue;;lung carcinoma|Treatment replicate;;1|treatment;;infected with human adenovirus type 26 202 Ad26 infected A549 12 hours replicate 1 2585209300 13301857 2015-10-30 15:33:51 1292673626 2585209300 13301857 2 13301857 index:0,count:12974567,average:100,stdev:0|index:1,count:12877526,average:100,stdev:0 26_10_12 0.0 0.0 0.0 75 75 75 75 100.0 100.0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 75 100.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00 100.00 0 1 200 100 0.00 75.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 16.64 18.66 5.33 0 0 0 12550236 751621 0 0 0 0 273 0 0 0 12549963 751620 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 1 0 0 0.0 13301857.0 1.0 0.0 0.0 0.0 273.0 0.0 13301583.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 860974 SRR2672232 SRP064863 SRS1117521 SRX1342025 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad6 infected A549 12 hours replicate 2 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 26-1_10_12.FCD1RRNACXX_L4_IGAGTGG RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;12 hours after infection|tissue;;lung carcinoma|Treatment replicate;;2|treatment;;infected with human adenovirus type 26 202 Ad26 infected A549 12 hours replicate 2 385677420 2038466 2015-10-30 15:33:51 176778391 385677420 2038466 2 2038466 index:0,count:1980756,average:100,stdev:0|index:1,count:1974756,average:95,stdev:0 26-1_10_12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 99.99 100.00 0 0 195 97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 17.97 5.20 0 0 0 0 1917046 121420 0 0 0 0 125 0 0 0 1916921 121420 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 2038466.0 0.0 0.0 0.0 0.0 125.0 0.0 2038341.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 860990 SRR2672233 SRP064863 SRS1117517 SRX1342037 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad26 infected A549 12 hours replicate 3 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 26-2_10_12.FCD1RRNACXX_L4_IATTCCT RNA-Seq TRANSCRIPTOMIC PolyA paired 0.0E0 Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;12 hours after infection|tissue;;lung carcinoma|Treatment replicate;;3|treatment;;infected with human adenovirus type 26 202 Ad26 infected A549 12 hours replicate 3 390592405 2063878 2015-10-30 15:33:51 181357049 390592405 2063878 2 2063878 index:0,count:2006476,average:100,stdev:0|index:1,count:1999419,average:95,stdev:0 26-2_10_12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 99.99 100.00 0 0 195 97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 61.87 18.28 0 0 0 0 1942017 121861 0 0 0 0 136 0 0 0 1941881 121861 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 2063878.0 0.0 0.0 0.0 0.0 136.0 0.0 2063742.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 861005 SRR2672234 SRP064863 SRS1117395 SRX1341866 SRA305258 Mayo Clinic Michael Barry Lab RNA-seq of Human lung cell line A549 infected with Adenovirus RNA-seq of Human lung cell line A549 alone as control, or infected with human adenovirus serotype 6, or infected with human adenovirus serotoype 26 Viral Sequencing Reads: Ad6 infected A549 6 hours replicate 2 As Written in Publication reference: Turner MA et al. 2015 J Virol “ mRNA Library Construction. TruSeq mRNA libraries (Illumina, San Diego, CA) were generated for three treatments (mock, Ad6, Ad26) at two time points (6 and 12 hours). RNA libraries were prepared according to the manufacturer’s instructions for the TruSeq RNA Sample Prep Kit v2 using an Eppendorf EpMotion 5075 robot (Hamburg, Germany). Reverse transcription and adaptor ligation steps were performed manually. Briefly, polyA mRNA was purified from total RNA using oligo dT magnetic beads. The purified mRNA was fragmented at 95°C for 8 minutes, eluted from the beads, and primed for first strand cDNA synthesis. RNA fragments were reverse transcribed into cDNA using SuperScript III reverse transcriptase with random primers (Invitrogen, Carlsbad, CA). Second strand cDNA synthesis was performed using DNA polymerase I and RNase H. Double-stranded cDNA was purified using a single AMPure XP bead (Agencourt, Danvers, MA) clean-up step. cDNA ends were repaired and phosphorylated using Klenow, T4 polymerase, and T4 polynucleotide kinase followed by a single AMPure XP bead clean-up. A single 3’ adenosine was added to these blunt-ended cDNAs with Klenow exo-. Paired-end DNA adaptors (Illumina) with a single “T” base overhang at the 3’ end were immediately ligated to the ‘A tailed’ cDNA population. Unique indexes included in the standard TruSeq Kits (12-Set A and 12-Set B) were incorporated at the adaptor ligation step for multiplex sample loading on the flow cells. The adapter-modified DNA fragments were purified by two rounds of AMPure XP bead clean-up steps and were enriched by 12 cycles of PCR using primers included in the Illumina Sample Prep Kit. The concentration and size distribution of the libraries were determined on an Agilent Bioanalyzer DNA 1000 chip (Santa Clara, CA). A final quantification, using Qubit fluorometry (Invitrogen, Carlsbad, CA), was done to confirm sample concentration. mRNA Library Sequencing. Libraries were loaded onto paired end flow cells at concentrations of 8-10 pM to generate cluster densities of 700,000/mm2 following Illumina’s standard protocol using the Illumina cBot and cBot Paired end cluster kit version 3. Libraries were indexed on the flow cell accommodating 3 or 4 libraries per lane. The flow cells were sequenced as 101 X 2 paired end reads on an Illumina HiSeq 2000 using TruSeq SBS sequencing kit version 3 and HCS v2.0.12 data collection software. Base-calling was performed using Illumina’s RTA version 1.17.21.3. An initial sequencing run was performed on single mock, Ad6, and Ad26 samples followed by a second batch of samples for a final "n" of 3 samples per test group. The triplicate dataset was used for downstream analyses. Next Generation Sequencing (NGS) Data Analysis. Sequenced reads from the instrument were aligned using Bowtie2 aligner to a reference consisting of Ad6 genome (GenBank HQ413315.1) and Ad26 genome (GenBank EF153474.1). In order to quantify the reads mapped to Adenovirus genes, the Bowtie2 aligned SAM (sequence alignment map) files were converted to BAM (Binary Alignment Map) file format. “ 6-1_10_6.FCD1RRNACXX_L2_IGTCCGC RNA-Seq TRANSCRIPTOMIC PolyA paired Illumina HiSeq 2000 age;;58|biomaterial_provider;;ATCC:CCL-185|BioSampleModel;;Human|cell_line;;A549|cell_type;;Lung epithelial|isolate;;ATCC:CCL-185|sex;;male|timepoint;;6 hours after infection|tissue;;lung carcinoma|Treatment replicate;;2|treatment;;infected with human adenovirus type 6 202 Ad6 infected A549 6 hours replicate 2 112229385 597307 2015-10-30 15:33:51 51423195 112229385 597307 2 597307 index:0,count:577561,average:100,stdev:0|index:1,count:573403,average:95,stdev:0 6-1_10_6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00 100.00 0 0 195 97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 37.61 17.46 0 0 0 0 553657 43650 0 0 0 0 11 0 0 0 553646 43650 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0 0 0 0 0.0 597307.0 0.0 0.0 0.0 0.0 11.0 0.0 597296.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 1263903 SRR627491 SRP005279 SRS377784 SRX207879 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046908: CD19_196; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer IIx cell type;;Fractionated CD19+ B-cells|disease state;;healthy donor|source_name;;Peripheral Blood GEO Accession;;GSM1046908 GSM1046908 CD19_196 287301955 16900115 2015-07-22 17:02:28 173539466 287301955 16900115 1 16900115 index:0,count:16900115,average:17,stdev:0 GSM1046908_r1 GEO 2.18 4.44 0.13 250655266 318446797 69532419 101549025 127.05 146.05 0 0 0 0 0 0 23.83 86.77 51727677 3555618 51727677 3555618 57.75 79.86 51727677 8616588 51727677 3272679 36159855 14.43 0.00 0 64.03 0 8.63 0 3.10 0 0.00 0 0.00 0 14919297 0 17 0 16.97 0 0.00 0 0.00 0 0.00 0 0.00 0 411.08 0 0.01 0 0 0 16900115 0 10821447 0 1457742 0 523076 0 0 0 0 0 0 0 0 0 0 0 53 0 0 0 53 0 24.25 0 4097850 0 0 0 0.0 16900115.0 14919297.0 0.0 10821447.0 1457742.0 523076.0 0.0 0.0 4097850.0 88.3 0.0 64.0 8.6 3.1 0.0 0.0 24.2 2527824 SRR627492 SRP005279 SRS377785 SRX207880 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046909: CD19_377; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer IIx cell type;;Fractionated CD19+ B-cells|disease state;;healthy donor|source_name;;Peripheral Blood GEO Accession;;GSM1046909 GSM1046909 CD19_377 250095398 14711494 2015-07-22 17:02:28 144510018 250095398 14711494 1 14711494 index:0,count:14711494,average:17,stdev:0 GSM1046909_r1 GEO 2.42 3.88 0.22 221931766 283407933 78799360 115698009 127.7 146.83 0 0 0 0 0 0 31.37 89.02 38872464 4130886 38872464 4130886 58.24 79.83 38872464 7667694 38872464 3704617 33301063 15.01 0.00 0 57.95 0 6.73 0 3.78 0 0.00 0 0.00 0 13166423 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 353.08 0 0.00 0 0 0 14711494 0 8525922 0 989620 0 555451 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 17 0 31.54 0 4640501 0 0 0 0.0 14711494.0 13166423.0 0.0 8525922.0 989620.0 555451.0 0.0 0.0 4640501.0 89.5 0.0 58.0 6.7 3.8 0.0 0.0 31.5 1263935 SRR627493 SRP005279 SRS377786 SRX207881 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046910: CD19_465; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer IIx cell type;;Fractionated CD19+ B-cells|disease state;;healthy donor|source_name;;Peripheral Blood GEO Accession;;GSM1046910 GSM1046910 CD19_465 393071110 23121830 2015-07-22 17:02:28 236154032 393071110 23121830 1 23121830 index:0,count:23121830,average:17,stdev:0 GSM1046910_r1 GEO 2.25 4.05 0.17 352096631 453079979 116646079 174098479 128.68 149.25 0 0 0 0 0 0 29.84 90.7 64097103 6228958 64097103 6228958 60.19 81.76 64097103 12562205 64097103 5615268 50466341 14.33 0.00 0 60.57 0 6.95 0 2.78 0 0.00 0 0.00 0 20872323 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 291.04 0 0.00 0 0 0 23121830 0 14004649 0 1607129 0 642378 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 21 0 29.70 0 6867674 0 0 0 0.0 23121830.0 20872323.0 0.0 14004649.0 1607129.0 642378.0 0.0 0.0 6867674.0 90.3 0.0 60.6 7.0 2.8 0.0 0.0 29.7 2527889 SRR627494 SRP005279 SRS377787 SRX207882 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046911: CD19_573; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer IIx cell type;;Fractionated CD19+ B-cells|disease state;;healthy donor|source_name;;Peripheral Blood GEO Accession;;GSM1046911 GSM1046911 CD19_573 292449385 17202905 2015-07-22 17:02:28 167306279 292449385 17202905 1 17202905 index:0,count:17202905,average:17,stdev:0 GSM1046911_r1 GEO 1.98 3.8 0.26 253328917 321707489 72215621 107195716 126.99 148.44 0 0 0 0 0 0 25.4 89.6 50546575 3810587 50546575 3810587 56.32 81.81 50546575 8449754 50546575 3479430 40895402 16.14 0.00 0 62.49 0 10.86 0 1.93 0 0.00 0 0.00 0 15002528 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 533.88 0 0.00 0 0 0 17202905 0 10749491 0 1868820 0 331557 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 5 0 24.72 0 4253037 0 0 0 0.0 17202905.0 15002528.0 0.0 10749491.0 1868820.0 331557.0 0.0 0.0 4253037.0 87.2 0.0 62.5 10.9 1.9 0.0 0.0 24.7 1263967 SRR627495 SRP005279 SRS377788 SRX207883 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046912: CD3_539; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer IIx cell type;;Fractionated CD3+ T-cells|disease state;;healthy donor|source_name;;Peripheral Blood GEO Accession;;GSM1046912 GSM1046912 CD3_539 256536171 15090363 2015-07-22 17:02:28 146535226 256536171 15090363 1 15090363 index:0,count:15090363,average:17,stdev:0 GSM1046912_r1 GEO 1.76 4.41 0.11 228057677 295044605 67564886 100830978 129.37 149.24 0 0 0 0 0 0 27.01 91.98 44942722 3660405 44942722 3660405 60.22 81.52 44942722 8159297 44942722 3244401 32441481 14.23 0.00 0 63.42 0 7.88 0 2.33 0 0.00 0 0.00 0 13550175 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 532.60 0 0.00 0 0 0 15090363 0 9570451 0 1188832 0 351356 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 7 0 26.37 0 3979724 0 0 0 0.0 15090363.0 13550175.0 0.0 9570451.0 1188832.0 351356.0 0.0 0.0 3979724.0 89.8 0.0 63.4 7.9 2.3 0.0 0.0 26.4 1263983 SRR627496 SRP005279 SRS377789 SRX207884 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046913: CD3_546; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer IIx cell type;;Fractionated CD3+ T-cells|disease state;;healthy donor|source_name;;Peripheral Blood GEO Accession;;GSM1046913 GSM1046913 CD3_546 323208964 19012292 2015-07-22 17:02:28 187760023 323208964 19012292 1 19012292 index:0,count:19012292,average:17,stdev:0 GSM1046913_r1 GEO 1.7 3.76 0.13 283692843 366209730 86033988 129776179 129.09 150.84 0 0 0 0 0 0 27.94 92.62 55332296 4692208 55332296 4692208 57.57 83.92 55332296 9667539 55332296 4251534 41151747 14.51 0.00 0 61.68 0 9.36 0 2.31 0 0.00 0 0.00 0 16793721 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 492.40 0 0.00 0 0 0 19012292 0 11727444 0 1778671 0 439900 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 12 0 26.65 0 5066277 0 0 0 0.0 19012292.0 16793721.0 0.0 11727444.0 1778671.0 439900.0 0.0 0.0 5066277.0 88.3 0.0 61.7 9.4 2.3 0.0 0.0 26.6 2527987 SRR627497 SRP005279 SRS377790 SRX207885 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046914: CD3_547; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer IIx cell type;;Fractionated CD3+ T-cells|disease state;;healthy donor|source_name;;Peripheral Blood GEO Accession;;GSM1046914 GSM1046914 CD3_547 342191436 20128908 2015-07-22 17:02:28 200496137 342191436 20128908 1 20128908 index:0,count:20128908,average:17,stdev:0 GSM1046914_r1 GEO 1.69 3.81 0.18 301017921 387869126 93061682 141311951 128.85 151.85 0 0 0 0 0 0 28.58 92.89 57477735 5090018 57477735 5090018 57.18 83.69 57477735 10185232 57477735 4586152 46175461 15.34 0.00 0 61.27 0 9.17 0 2.34 0 0.00 0 0.00 0 17811806 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 489.62 0 0.00 0 0 0 20128908 0 12332134 0 1846412 0 470690 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 10 0 27.22 0 5479672 0 0 0 0.0 20128908.0 17811806.0 0.0 12332134.0 1846412.0 470690.0 0.0 0.0 5479672.0 88.5 0.0 61.3 9.2 2.3 0.0 0.0 27.2 2528017 SRR627498 SRP005279 SRS377791 SRX207886 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046915: CD3_549; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer IIx cell type;;Fractionated CD3+ T-cells|disease state;;healthy donor|source_name;;Peripheral Blood GEO Accession;;GSM1046915 GSM1046915 CD3_549 366189605 21540565 2015-07-22 17:02:28 216161226 366189605 21540565 1 21540565 index:0,count:21540565,average:17,stdev:0 GSM1046915_r1 GEO 1.56 3.99 0.16 322300845 414698018 91106307 137581725 128.67 151.01 0 0 0 0 0 0 25.99 92.48 64644895 4961941 64644895 4961941 57.53 83.39 64644895 10982918 64644895 4474314 51316229 15.92 0.00 0 63.73 0 8.37 0 3.00 0 0.00 0 0.00 0 19092201 0 17 0 16.98 0 0.00 0 0.00 0 0.00 0 0.00 0 438.11 0 0.00 0 0 0 21540565 0 13726984 0 1802756 0 645608 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 15 0 24.91 0 5365217 0 0 0 0.0 21540565.0 19092201.0 0.0 13726984.0 1802756.0 645608.0 0.0 0.0 5365217.0 88.6 0.0 63.7 8.4 3.0 0.0 0.0 24.9 2528050 SRR627499 SRP005279 SRS377792 SRX207887 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046916: DGE_HeH_9; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;BCP ALL|cell type;;leukemic cells|cytogenetic background;;High Hyperploidy|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow GEO Accession;;GSM1046916 GSM1046916 DGE_HeH_9 58829994 3268333 2013-01-14 14:57:01 25981116 58829994 3268333 1 3268333 index:0,count:3268333,average:18,stdev:0 GSM1046916_r1 GEO 1.26 3.53 0.36 52373463 67149712 21880715 29579386 128.21 135.18 0 0 0 0 0 0 33.93 82.58 7504458 1015522 7504458 1015522 61.39 72.88 7504458 1837508 7504458 896290 6832720 13.05 0.00 0 53.95 0 3.58 0 4.84 0 0.00 0 0.00 0 2993059 0 18 0 17.79 0 0.00 0 0.00 0 0.00 0 0.00 0 356.55 0 0.01 0 0 0 3268333 0 1763285 0 117108 0 158166 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 18 0 37.63 0 1229774 0 0 0 0.0 3268333.0 2993059.0 0.0 1763285.0 117108.0 158166.0 0.0 0.0 1229774.0 91.6 0.0 54.0 3.6 4.8 0.0 0.0 37.6 2531345 SRR627500 SRP005279 SRS377793 SRX207888 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046917: DGE_undefined_1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;BCP ALL|cell type;;leukemic cells|cytogenetic background;;undefined|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow GEO Accession;;GSM1046917 GSM1046917 DGE_undefined_1 91800936 5100052 2015-07-22 17:02:28 73346793 91800936 5100052 1 5100052 index:0,count:5100052,average:18,stdev:0 GSM1046917_r1 GEO 1.01 5.24 0.44 76436685 85414149 29348654 36917770 111.74 125.79 0 0 0 0 0 0 27.18 71.9 11969435 1181044 11969435 1181044 51.44 65.84 11969435 2235493 11969435 1081386 13438313 17.58 0.00 0 53.00 0 9.67 0 5.13 0 0.00 0 0.00 0 4345458 0 18 0 17.87 0 0.00 0 0.00 0 0.00 0 0.00 0 496.22 0 0.01 0 0 0 5100052 0 2702928 0 492994 0 261600 0 0 0 0 0 0 0 0 0 0 0 31 0 0 0 31 0 32.21 0 1642530 0 0 0 0.0 5100052.0 4345458.0 0.0 2702928.0 492994.0 261600.0 0.0 0.0 1642530.0 85.2 0.0 53.0 9.7 5.1 0.0 0.0 32.2 2531378 SRR627501 SRP005279 SRS377794 SRX207889 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046918: DGE_t1-19_1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;BCP ALL|cell type;;leukemic cells|cytogenetic background;;t(1;19)TCF3-PBX1|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow GEO Accession;;GSM1046918 GSM1046918 DGE_t1-19_1 137528478 7640471 2015-07-22 17:02:28 106593814 137528478 7640471 1 7640471 index:0,count:7640471,average:18,stdev:0 GSM1046918_r1 GEO 5.24 3.62 0.39 122039632 156471276 47474614 65111609 128.21 137.15 0 0 0 0 0 0 29.82 78.17 19056035 2080718 19056035 2080718 59.94 73.03 19056035 4182070 19056035 1943776 16790339 13.76 0.00 0 56.48 0 5.60 0 3.08 0 0.00 0 0.00 0 6977191 0 18 0 17.84 0 0.00 0 0.00 0 0.00 0 0.00 0 429.78 0 0.03 0 0 0 7640471 0 4315530 0 428040 0 235239 0 0 0 1 0 0 0 0 0 0 0 99 0 0 0 99 0 34.84 0 2661661 0 0 0 0.0 7640471.0 6977191.0 0.0 4315530.0 428040.0 235239.0 0.0 1.0 2661661.0 91.3 0.0 56.5 5.6 3.1 0.0 0.0 34.8 2531409 SRR627502 SRP005279 SRS377795 SRX207890 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046919: DGE_MLL-11q23_1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;BCP ALL|cell type;;leukemic cells|cytogenetic background;;MLL/11q23|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow GEO Accession;;GSM1046919 GSM1046919 DGE_MLL-11q23_1 133157376 7397632 2015-07-22 17:02:28 105746524 133157376 7397632 1 7397632 index:0,count:7397632,average:18,stdev:0 GSM1046919_r1 GEO 1.0 5.11 0.28 118061000 133353230 41987230 53007175 112.95 126.25 0 0 0 0 0 0 25.1 72.48 19532798 1710110 19532798 1710110 48.96 64.52 19532798 3335072 19532798 1522247 25451829 21.56 0.00 0 60.19 0 6.79 0 1.13 0 0.00 0 0.00 0 6812007 0 18 0 17.80 0 0.00 0 0.00 0 0.00 0 0.00 0 459.16 0 0.02 0 0 0 7397632 0 4452572 0 502256 0 83369 0 0 0 0 0 0 0 0 0 0 0 154 0 0 0 154 0 31.89 0 2359435 0 0 0 0.0 7397632.0 6812007.0 0.0 4452572.0 502256.0 83369.0 0.0 0.0 2359435.0 92.1 0.0 60.2 6.8 1.1 0.0 0.0 31.9 2531440 SRR627503 SRP005279 SRS377796 SRX207891 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046920: DGE_t12-21_4; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;BCP ALL|cell type;;leukemic cells|cytogenetic background;;t(12;21) ETV6-RUNX1|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow GEO Accession;;GSM1046920 GSM1046920 DGE_t12-21_4 25703424 1427968 2013-01-14 14:56:58 11593540 25703424 1427968 1 1427968 index:0,count:1427968,average:18,stdev:0 GSM1046920_r1 GEO 3.08 3.21 0.25 22048715 29002396 10474899 15354363 131.54 146.58 0 0 0 0 0 0 39.95 85.51 3063403 505945 3063403 505945 64.96 76.27 3063403 822647 3063403 451277 2311473 10.48 0.00 0 47.24 0 3.58 0 7.74 0 0.00 0 0.00 0 1266317 0 18 0 17.70 0 0.00 0 0.00 0 0.00 0 0.00 0 342.71 0 0.01 0 0 0 1427968 0 674619 0 51077 0 110574 0 0 0 0 0 0 0 0 0 0 0 91 0 0 0 91 0 41.44 0 591698 0 0 0 0.0 1427968.0 1266317.0 0.0 674619.0 51077.0 110574.0 0.0 0.0 591698.0 88.7 0.0 47.2 3.6 7.7 0.0 0.0 41.4 2531473 SRR627504 SRP005279 SRS377797 SRX207892 SRA029126 GEO Digital gene expression profiling of primary acute lymphoblastic leukemia cells We determined the genome-wide digital gene expression (DGE) profiles of primary acute lymphoblastic leukemia (ALL) cells from 28 patients and fractionated blood cells from healthy blood donors taking advantage of “second generation” sequencing technology. The patients included in the study represent distinct subtypes of B-cell precursor (BCP) ALL and T-cell lineage ALL (T-ALL) and the controls are fractionated CD19+ and CD3+ cells. Overall design: Gene expression analysis of 28 ALL patient samples with different immunophenotypic backgrounds including T-ALL (n=4) and patients with BCP ALL with diverse cytogenetic backgrounds: High Hyperploidy (HeH) (n=10), t(9;22) BCR-ABL1 (n=3), t(12;21) ETV6-RUNX1 (n=4), dic(9;20) (n=3), t(1;19)TCF3-PBX1, MLL/11q23 (n=1) and undefined/non-recurrent aberrations (n=1). Fractionated b-cells (CD19+) and t-cells (CD3+) isolated from peripheral blood of healthy donors were used as controls. Sequencing libraries were prepared from 1 µg of total RNA using reagents from the NlaIII Digital Gene Expression Tag Profiling kit (Illumina Inc, San Diego, CA, USA). mRNA was captured on magnetic oligo(dT) beads and reverse transcribed into double-stranded cDNA. The cDNA was cleaved using the restriction enzyme NlaIII. An adapter sequence containing the recognition sequence for the restriction enzyme MmeI was ligated to the NlaIII cleavage sites. The adapter-ligated cDNA was digested with MmeI to release the cDNA from the magnetic bead, while leaving 17 base-pairs of sequence in the fragment. The fragments were dephosphorylated and purified by phenol-chloroform. A second adapter was ligated at the MmeI cleavage sites. The adapter-ligated cDNA fragments were amplified by PCR, and the PCR products were purified on a 6% polyacrylamide gel. The ~96 base pair PCR products were excised from the gel and eluted overnight, followed by ethanol precipitation and re-suspension. Purified libraries were quality controlled and quantified on a Bioanalyzer using DNA 1000 series or High Sensitivity chips. The DGE libraries were diluted to a 10 nM concentration and sequenced on one lane of an Illumina GAII or GAIIx for 18 cycles. GSM1046921: DGE_HeH_10; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Illumina Genome Analyzer II all lineage;;BCP ALL|cell type;;leukemic cells|cytogenetic background;;High Hyperploidy|disease state;;acute lymphoblastic leukemia (ALL)|source_name;;Bone marrow GEO Accession;;GSM1046921 GSM1046921 DGE_HeH_10 67384926 3743607 2013-01-14 14:56:51 29591030 67384926 3743607 1 3743607 index:0,count:3743607,average:18,stdev:0 GSM1046921_r1 GEO 2.4 4.21 0.5 60346007 76094118 26711492 36118750 126.1 135.22 0 0 0 0 0 0 36.41 83.52 8664246 1253758 8664246 1253758 62.79 72.21 8664246 2162148 8664246 1083998 6417086 10.63 0.00 0 51.88 0 4.00 0 4.02 0 0.00 0 0.00 0 3443529 0 18 0 17.79 0 0.00 0 0.00 0 0.00 0 0.00 0 313.42 0 0.01 0 0 0 3743607 0 1942360 0 149716 0 150362 0 0 0 0 0 0 0 0 0 0 0 53 0 0 0 53 0 40.10 0 1501169 0 0 0 0.0 3743607.0 3443529.0 0.0 1942360.0 149716.0 150362.0 0.0 0.0 1501169.0 92.0 0.0 51.9 4.0 4.0 0.0 0.0 40.1 2108441 SRR645160 SRP017786 SRS383501 SRX214989 SRA064011 sysu liuq Homo sapiens Transcriptome or Gene expression 6 DGE sequencing human DGE sequencing of Human nomral 2 Normal Sample 2 of Human RNA-Seq TRANSCRIPTOMIC RANDOM single Illumina HiSeq 2000 21 Human_2N normal samle 101530233 4834773 2015-07-22 17:10:41 68292985 101530233 4834773 1 4834773 index:0,count:4834773,average:21,stdev:0 2N_Data sysu 5.66 2.95 0.13 93880197 138995773 71288145 110237875 148.06 154.64 0 0 0 0 0 0 65.31 86.42 7084690 2938635 7084690 2938635 58.59 60.32 7084690 2636449 7084690 2051131 7637253 8.14 0.00 0 22.74 0 2.65 0 4.27 0 0.00 0 0.01 0 4499840 0 21 0 20.96 0 0.00 0 0.00 0 0.00 0 0.00 0 223.14 0 0.03 0 0 0 4834773 0 1099255 0 128267 0 206384 0 0 0 282 0 0 0 0 0 0 0 704 0 0 0 704 0 70.34 0 3400585 0 0 0 0.0 4834773.0 4499840.0 0.0 1099255.0 128267.0 206384.0 0.0 282.0 3400585.0 93.1 0.0 22.7 2.7 4.3 0.0 0.0 70.3 2108471 SRR645161 SRP017786 SRS383502 SRX214990 SRA064011 sysu liuq Homo sapiens Transcriptome or Gene expression 6 DGE sequencing human DGE sequencing of Human tumor 2 Tumor Sample 2 of Human RNA-Seq TRANSCRIPTOMIC RANDOM single Illumina HiSeq 2000 21 Human_2T tumor sample 106586592 5075552 2015-07-22 17:10:41 70900818 106586592 5075552 1 5075552 index:0,count:5075552,average:21,stdev:0 2T_RawData sysu 3.29 3.43 0.19 100492993 137819706 63959972 93025181 137.14 145.44 0 0 0 0 0 0 59.43 93.94 9316586 2871130 9316586 2871130 77.25 86.56 9316586 3732254 9316586 2645309 4955251 4.93 0.00 0 34.97 0 3.55 0 1.26 0 0.00 0 0.00 0 4831253 0 21 0 20.93 0 0.00 0 0.00 0 0.00 0 0.00 0 156.17 0 0.04 0 0 0 5075552 0 1775058 0 180430 0 63799 0 0 0 70 0 0 0 0 0 0 0 1151 0 0 0 1151 0 60.21 0 3056195 0 0 0 0.0 5075552.0 4831253.0 0.0 1775058.0 180430.0 63799.0 0.0 70.0 3056195.0 95.2 0.0 35.0 3.6 1.3 0.0 0.0 60.2 2108503 SRR645162 SRP017786 SRS383505 SRX214993 SRA064011 sysu liuq Homo sapiens Transcriptome or Gene expression 6 DGE sequencing human DGE sequencing of Human normal 23 RNA-Seq TRANSCRIPTOMIC RANDOM single Illumina HiSeq 2000 21 Human_23N DGE sequencing of Human nomral 23 98072289 4670109 2015-07-22 17:10:41 65529370 98072289 4670109 1 4670109 index:0,count:4670109,average:21,stdev:0 23N_RawData sysu 5.44 2.92 0.18 92431409 134857869 62638581 95981478 145.9 153.23 0 0 0 0 0 0 63.02 93.45 7955257 2795122 7955257 2795122 72.69 79.2 7955257 3224131 7955257 2368852 5125163 5.54 0.00 0 30.93 0 3.27 0 1.76 0 0.00 0 0.00 0 4435405 0 21 0 20.94 0 0.00 0 0.00 0 0.00 0 0.00 0 164.83 0 0.03 0 0 0 4670109 0 1444363 0 152595 0 82039 0 0 0 70 0 0 0 0 0 0 0 1207 0 0 0 1207 0 64.05 0 2991042 0 0 0 0.0 4670109.0 4435405.0 0.0 1444363.0 152595.0 82039.0 0.0 70.0 2991042.0 95.0 0.0 30.9 3.3 1.8 0.0 0.0 64.0 2108534 SRR645163 SRP017786 SRS383503 SRX214991 SRA064011 sysu liuq Homo sapiens Transcriptome or Gene expression 6 DGE sequencing human DGE sequencing of Human nomral 3 RNA-Seq TRANSCRIPTOMIC RANDOM single Illumina HiSeq 2000 21 Human_3N normal samle 93968847 4474707 2015-07-22 17:10:41 63034114 93968847 4474707 1 4474707 index:0,count:4474707,average:21,stdev:0 3N_RawData sysu 5.08 2.55 0.19 88601266 135129240 66870459 107019282 152.51 160.04 0 0 0 0 0 0 69.54 92.76 6716198 2959930 6716198 2959930 63.22 66.83 6716198 2691012 6716198 2132539 5492437 6.20 0.00 0 23.81 0 2.20 0 2.68 0 0.00 0 0.00 0 4256341 0 21 0 20.96 0 1.00 0 0.00 0 0.00 0 0.00 0 196.45 0 0.03 0 0 0 4474707 0 1065404 0 98378 0 119868 0 0 0 120 0 0 0 0 0 0 0 704 0 0 0 704 0 71.31 0 3190937 0 0 0 0.0 4474707.0 4256341.0 0.0 1065404.0 98378.0 119868.0 0.0 120.0 3190937.0 95.1 0.0 23.8 2.2 2.7 0.0 0.0 71.3 2125493 SRR645375 SRP017786 SRS383504 SRX214992 SRA064011 sysu liuq Homo sapiens Transcriptome or Gene expression 6 DGE sequencing human DGE sequencing of Human tumor 3 RNA-Seq TRANSCRIPTOMIC RANDOM single Illumina HiSeq 2000 21 Human_3T DGE sequencing of Human tumor 3 92914332 4424492 2015-07-22 17:10:41 62703811 92914332 4424492 1 4424492 index:0,count:4424492,average:21,stdev:0 3T_RawData sysu 3.33 3.61 0.23 87675724 121163364 60328408 87329595 138.19 144.76 0 0 0 0 0 0 63.25 92.37 7643390 2660126 7643390 2660126 73.22 83.87 7643390 3079323 7643390 2415304 4725900 5.39 0.00 0 29.97 0 2.88 0 2.07 0 0.00 0 0.00 0 4205774 0 21 0 20.95 0 0.00 0 0.00 0 0.00 0 0.00 0 150.27 0 0.03 0 0 0 4424492 0 1325993 0 127313 0 91367 0 0 0 38 0 0 0 0 0 0 0 780 0 0 0 780 0 65.09 0 2879781 0 0 0 0.0 4424492.0 4205774.0 0.0 1325993.0 127313.0 91367.0 0.0 38.0 2879781.0 95.1 0.0 30.0 2.9 2.1 0.0 0.0 65.1 2125522 SRR645376 SRP017786 SRS383506 SRX215193 SRA064011 sysu liuq Homo sapiens Transcriptome or Gene expression 6 DGE sequencing human DGE sequencing of Human tumor 23 RNA-Seq TRANSCRIPTOMIC RANDOM single Illumina HiSeq 2000 21 Human_23T DGE sequencing of Human tumor 23 115377570 5494170 2015-07-22 17:10:41 76619264 115377570 5494170 1 5494170 index:0,count:5494170,average:21,stdev:0 23T_RawData sysu 2.57 2.37 0.18 109513415 146329047 60589715 89145909 133.62 147.13 0 0 0 0 0 0 51.65 93.87 11882486 2716671 11882486 2716671 76.56 83.68 11882486 4026729 11882486 2421881 4598315 4.20 0.00 0 43.06 0 2.99 0 1.28 0 0.00 0 0.00 0 5259898 0 21 0 20.94 0 1.00 0 0.00 0 0.00 0 0.00 0 163.46 0 0.04 0 0 0 5494170 0 2365775 0 164019 0 70185 0 0 0 68 0 0 0 0 0 0 0 3264 0 0 0 3264 0 52.68 0 2894123 0 0 0 0.0 5494170.0 5259898.0 0.0 2365775.0 164019.0 70185.0 0.0 68.0 2894123.0 95.7 0.0 43.1 3.0 1.3 0.0 0.0 52.7 729166 SRR6459204 SRP128731 SRS2823421 SRX3549451 SRA645811 novo RNA my data my1 mydata 0001 RNA-Seq TRANSCRIPTOMIC RT-PCR paired HiSeq X Ten age;;60|biomaterial_provider;;hos|BioSampleModel;;Human|isolate;;yes|sex;;male|tissue;;blood A1 3750 25 2018-01-10 17:46:12 81144 3750 25 2 25 index:0,count:25,average:150,stdev:0 A1.fastq.gz 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 100.00 0 0 0 150 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 25.0 0.0 0.0 0.0 0.0 0.0 0.0 25.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 2239549 SRR8176161 SRP168237 SRS4031505 SRX4996439 SRA807556 GEO Regulation of human epidermal progenitor cell function by HNRNPK through transcriptional and post-transcriptional mechanisms Maintenance of high-turnover tissues such as the epidermis requires a tight balance between stem and progenitor cell proliferation and differentiation. The molecular mechanisms governing this process are an area of active investigation. Here we show that HNRNPK, a multifunctional protein, is necessary to prevent premature differentiation and sustains the proliferative capacity of epidermal stem and progenitor cells. To prevent premature differentiation of progenitor cells, HNRNPK recruits DDX6 to a subset of mRNAs that code for transcription factors that induce differentiation. Upon binding, these mRNAs such as GRHL3, KLF4, and ZNF750 are degraded which prevents premature differentiation. To sustain the proliferative capacity of the epidermis, HNRNPK recruits RNA polymerase II to genomic sites of proliferation genes such as MYC, FGFBP1, PTHLH, ITGB4 to promote their expressions. Our study establishes a prominent role for HNRNPK in maintaining adult tissue homeostasis through both transcriptional and post-transcriptional mechanisms. Overall design: HNRNPK RNA-seq in primary keratinocytes. HNRNPK RNA IP-seq in primary keratinocytes. ChIP-seq with HNRNPK and RNA POL II antibodies in primary keratinocytes. GSM3464079: CTLi_RNAseq_rep_1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single RNA was isolated using GeneJET RNA purification kit (Thermo Scientific). RNA-seq libraries were prepared with TruSeq RNA Library Prep Kit (Illumina) then multiplexed Illumina HiSeq 4000 antibody;;n/a|cell type;;primary keratinocytes|genotype;;Control shRNA|source_name;;Human epidermal keratinocyte|tissue;;Neonatal foreskin GEO Accession;;GSM3464079 GSM3464079 CTLi_RNAseq_rep_1 526695648 32918478 2019-07-28 11:43:00 145493680 526695648 32918478 2 32918478 index:0,count:32918478,average:8,stdev:0|index:1,count:32918478,average:8,stdev:0 GSM3464079_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 100.00 0 0.00 0 0.00 0 0 0 16 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 1004.29 0 0 0 0 0 32918478 0 0 0 0 0 32918478 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 32918478.0 0.0 0.0 0.0 0.0 32918478.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 0.0 2239581 SRR8176162 SRP168237 SRS4031506 SRX4996440 SRA807556 GEO Regulation of human epidermal progenitor cell function by HNRNPK through transcriptional and post-transcriptional mechanisms Maintenance of high-turnover tissues such as the epidermis requires a tight balance between stem and progenitor cell proliferation and differentiation. The molecular mechanisms governing this process are an area of active investigation. Here we show that HNRNPK, a multifunctional protein, is necessary to prevent premature differentiation and sustains the proliferative capacity of epidermal stem and progenitor cells. To prevent premature differentiation of progenitor cells, HNRNPK recruits DDX6 to a subset of mRNAs that code for transcription factors that induce differentiation. Upon binding, these mRNAs such as GRHL3, KLF4, and ZNF750 are degraded which prevents premature differentiation. To sustain the proliferative capacity of the epidermis, HNRNPK recruits RNA polymerase II to genomic sites of proliferation genes such as MYC, FGFBP1, PTHLH, ITGB4 to promote their expressions. Our study establishes a prominent role for HNRNPK in maintaining adult tissue homeostasis through both transcriptional and post-transcriptional mechanisms. Overall design: HNRNPK RNA-seq in primary keratinocytes. HNRNPK RNA IP-seq in primary keratinocytes. ChIP-seq with HNRNPK and RNA POL II antibodies in primary keratinocytes. GSM3464080: CTLi_RNAseq_rep_2; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single RNA was isolated using GeneJET RNA purification kit (Thermo Scientific). RNA-seq libraries were prepared with TruSeq RNA Library Prep Kit (Illumina) then multiplexed Illumina HiSeq 4000 antibody;;n/a|cell type;;primary keratinocytes|genotype;;Control shRNA|source_name;;Human epidermal keratinocyte|tissue;;Neonatal foreskin GEO Accession;;GSM3464080 GSM3464080 CTLi_RNAseq_rep_2 520898112 32556132 2019-07-28 11:43:00 144044807 520898112 32556132 2 32556132 index:0,count:32556132,average:8,stdev:0|index:1,count:32556132,average:8,stdev:0 GSM3464080_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 100.00 0 0.00 0 0.00 0 0 0 16 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 1160.42 0 0 0 0 0 32556132 0 0 0 0 0 32556132 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 32556132.0 0.0 0.0 0.0 0.0 32556132.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 0.0 2239612 SRR8176163 SRP168237 SRS4031507 SRX4996441 SRA807556 GEO Regulation of human epidermal progenitor cell function by HNRNPK through transcriptional and post-transcriptional mechanisms Maintenance of high-turnover tissues such as the epidermis requires a tight balance between stem and progenitor cell proliferation and differentiation. The molecular mechanisms governing this process are an area of active investigation. Here we show that HNRNPK, a multifunctional protein, is necessary to prevent premature differentiation and sustains the proliferative capacity of epidermal stem and progenitor cells. To prevent premature differentiation of progenitor cells, HNRNPK recruits DDX6 to a subset of mRNAs that code for transcription factors that induce differentiation. Upon binding, these mRNAs such as GRHL3, KLF4, and ZNF750 are degraded which prevents premature differentiation. To sustain the proliferative capacity of the epidermis, HNRNPK recruits RNA polymerase II to genomic sites of proliferation genes such as MYC, FGFBP1, PTHLH, ITGB4 to promote their expressions. Our study establishes a prominent role for HNRNPK in maintaining adult tissue homeostasis through both transcriptional and post-transcriptional mechanisms. Overall design: HNRNPK RNA-seq in primary keratinocytes. HNRNPK RNA IP-seq in primary keratinocytes. ChIP-seq with HNRNPK and RNA POL II antibodies in primary keratinocytes. GSM3464081: HNRNPKi_RNAseq_rep_1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single RNA was isolated using GeneJET RNA purification kit (Thermo Scientific). RNA-seq libraries were prepared with TruSeq RNA Library Prep Kit (Illumina) then multiplexed Illumina HiSeq 4000 antibody;;n/a|cell type;;primary keratinocytes|genotype;;HNRNPK shRNA knockdown|source_name;;Human epidermal keratinocyte|tissue;;Neonatal foreskin GEO Accession;;GSM3464081 GSM3464081 HNRNPKi_RNAseq_rep_1 497101040 31068815 2019-07-28 11:43:00 146044686 497101040 31068815 2 31068815 index:0,count:31068815,average:8,stdev:0|index:1,count:31068815,average:8,stdev:0 GSM3464081_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 100.00 0 0.00 0 0.00 0 0 0 16 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 1189.87 0 0 0 0 0 31068815 0 0 0 0 0 31068815 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 31068815.0 0.0 0.0 0.0 0.0 31068815.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 0.0 2239643 SRR8176164 SRP168237 SRS4031508 SRX4996442 SRA807556 GEO Regulation of human epidermal progenitor cell function by HNRNPK through transcriptional and post-transcriptional mechanisms Maintenance of high-turnover tissues such as the epidermis requires a tight balance between stem and progenitor cell proliferation and differentiation. The molecular mechanisms governing this process are an area of active investigation. Here we show that HNRNPK, a multifunctional protein, is necessary to prevent premature differentiation and sustains the proliferative capacity of epidermal stem and progenitor cells. To prevent premature differentiation of progenitor cells, HNRNPK recruits DDX6 to a subset of mRNAs that code for transcription factors that induce differentiation. Upon binding, these mRNAs such as GRHL3, KLF4, and ZNF750 are degraded which prevents premature differentiation. To sustain the proliferative capacity of the epidermis, HNRNPK recruits RNA polymerase II to genomic sites of proliferation genes such as MYC, FGFBP1, PTHLH, ITGB4 to promote their expressions. Our study establishes a prominent role for HNRNPK in maintaining adult tissue homeostasis through both transcriptional and post-transcriptional mechanisms. Overall design: HNRNPK RNA-seq in primary keratinocytes. HNRNPK RNA IP-seq in primary keratinocytes. ChIP-seq with HNRNPK and RNA POL II antibodies in primary keratinocytes. GSM3464082: HNRNPKi_RNAseq_rep_2; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single RNA was isolated using GeneJET RNA purification kit (Thermo Scientific). RNA-seq libraries were prepared with TruSeq RNA Library Prep Kit (Illumina) then multiplexed Illumina HiSeq 4000 antibody;;n/a|cell type;;primary keratinocytes|genotype;;HNRNPK shRNA knockdown|source_name;;Human epidermal keratinocyte|tissue;;Neonatal foreskin GEO Accession;;GSM3464082 GSM3464082 HNRNPKi_RNAseq_rep_2 584333600 36520850 2019-07-28 11:43:00 159808281 584333600 36520850 2 36520850 index:0,count:36520850,average:8,stdev:0|index:1,count:36520850,average:8,stdev:0 GSM3464082_r1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0.00 0 0.00 0 100.00 0 0.00 0 0.00 0 0 0 16 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 1753.00 0 0 0 0 0 36520850 0 0 0 0 0 36520850 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0 0.0 36520850.0 0.0 0.0 0.0 0.0 36520850.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 0.0 2507963 SRR976225 SRP029889 SRS479317 SRX348541 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229103: hB1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;67.56|rin;;8.6|sex;;male|source_name;;Holland 3|tissue;;brain GEO Accession;;GSM1229103 GSM1229103 hB1 99527820 4739420 2013-10-17 10:08:32 52275123 99527820 4739420 1 4739420 index:0,count:4739420,average:21,stdev:0 GSM1229103_r1 GEO 7.0 3.98 0.34 95216116 133022567 72582432 104019338 139.71 143.31 0 0 0 0 0 0 69.51 91.69 6941753 3178670 6941753 3178670 78.15 85.94 6941753 3574036 6941753 2979242 4932381 5.18 0.00 0 23.35 0 1.96 0 1.54 0 0.00 0 0.00 0 4573073 0 21 0 20.94 0 1.00 0 0.00 0 0.00 0 0.00 0 179.60 0 0.07 0 0 0 4739420 0 1106437 0 93066 0 73188 0 0 0 93 0 0 0 0 0 1 0 1037 0 0 0 1038 0 73.14 0 3466636 0 0 0 0.0 4739420.0 4573073.0 0.0 1106437.0 93066.0 73188.0 0.0 93.0 3466636.0 96.5 0.0 23.3 2.0 1.5 0.0 0.0 73.1 2507994 SRR976226 SRP029889 SRS479318 SRX348542 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229104: hB1_GAII; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;67.56|rin;;8.6|sex;;male|source_name;;Holland 3|tissue;;brain GEO Accession;;GSM1229104 GSM1229104 hB1_GAII 315579894 15027614 2013-10-17 10:08:32 225009726 315579894 15027614 1 15027614 index:0,count:15027614,average:21,stdev:0 GSM1229104_r1 GEO 3.49 4.6 0.59 287422468 339468955 177504273 235950384 118.11 132.93 0 0 0 0 0 0 47.36 79.85 28811514 6872539 28811514 6872539 54.66 75.19 28811514 7933030 28811514 6471355 45829283 15.94 0.00 0 39.30 0 2.42 0 0.96 0 0.00 0 0.05 0 14512270 0 21 0 20.62 0 1.00 0 0.00 0 0.00 0 0.00 0 228.27 0 0.32 0 0 0 15027614 0 5905903 0 363697 0 144024 0 0 0 7623 0 0 0 0 0 16 0 29413 0 0 0 29429 0 57.27 0 8606367 0 0 0 0.0 15027614.0 14512270.0 0.0 5905903.0 363697.0 144024.0 0.0 7623.0 8606367.0 96.6 0.0 39.3 2.4 1.0 0.0 0.1 57.3 2508025 SRR976227 SRP029889 SRS479319 SRX348543 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229105: hB2; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;45.03|rin;;8.3|sex;;male|source_name;;Finn II|tissue;;brain GEO Accession;;GSM1229105 GSM1229105 hB2 124736409 5939829 2013-10-17 10:08:32 60969283 124736409 5939829 1 5939829 index:0,count:5939829,average:21,stdev:0 GSM1229105_r1 GEO 4.3 4.37 0.42 119176600 164854180 93595141 133796320 138.33 142.95 0 0 0 0 0 0 71.38 91.47 8653583 4088263 8653583 4088263 77.12 84.76 8653583 4417101 8653583 3788359 5918663 4.97 0.00 0 21.19 0 1.88 0 1.69 0 0.00 0 0.00 0 5727664 0 21 0 20.94 0 1.00 0 0.00 0 0.00 0 0.00 0 203.65 0 0.09 0 0 0 5939829 0 1258366 0 111560 0 100464 0 0 0 141 0 0 0 0 0 0 0 1288 0 0 0 1288 0 75.24 0 4469298 0 0 0 0.0 5939829.0 5727664.0 0.0 1258366.0 111560.0 100464.0 0.0 141.0 4469298.0 96.4 0.0 21.2 1.9 1.7 0.0 0.0 75.2 2508060 SRR976228 SRP029889 SRS479320 SRX348544 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229106: hB3; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;56.54|rin;;8.1|sex;;male|source_name;;(H3)98-127 (Holland 2)|tissue;;brain GEO Accession;;GSM1229106 GSM1229106 hB3 96638703 4601843 2013-10-17 10:08:32 49023518 96638703 4601843 1 4601843 index:0,count:4601843,average:21,stdev:0 GSM1229106_r1 GEO 5.55 4.17 0.35 92641151 127629486 72586178 102763332 137.77 141.57 0 0 0 0 0 0 71.49 91.77 6564400 3181272 6564400 3181272 78.5 86.23 6564400 3492841 6564400 2989238 4797455 5.18 0.00 0 21.36 0 1.78 0 1.53 0 0.00 0 0.00 0 4449732 0 21 0 20.94 0 1.00 0 0.00 0 0.00 0 0.00 0 172.57 0 0.09 0 0 0 4601843 0 983124 0 81791 0 70214 0 0 0 106 0 0 0 0 0 2 0 1123 0 0 0 1125 0 75.33 0 3466608 0 0 0 0.0 4601843.0 4449732.0 0.0 983124.0 81791.0 70214.0 0.0 106.0 3466608.0 96.7 0.0 21.4 1.8 1.5 0.0 0.0 75.3 2508094 SRR976229 SRP029889 SRS479321 SRX348545 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229107: hB4; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;75.09|rin;;6.6|sex;;male|source_name;;NDRI_OD09512|tissue;;brain GEO Accession;;GSM1229107 GSM1229107 hB4 114697632 5461792 2013-10-17 10:08:32 59201864 114697632 5461792 1 5461792 index:0,count:5461792,average:21,stdev:0 GSM1229107_r1 GEO 7.18 4.45 0.4 109501298 157039179 81522077 119664873 143.41 146.79 0 0 0 0 0 0 67.67 91.39 8266353 3557002 8266353 3557002 75.35 83.0 8266353 3960834 8266353 3230449 6041747 5.52 0.00 0 24.99 0 2.13 0 1.63 0 0.00 0 0.00 0 5256653 0 21 0 20.95 0 1.00 0 0.00 0 0.00 0 0.00 0 180.39 0 0.05 0 0 0 5461792 0 1364698 0 116232 0 88821 0 0 0 86 0 0 0 0 0 0 0 870 0 0 0 870 0 71.26 0 3891955 0 0 0 0.0 5461792.0 5256653.0 0.0 1364698.0 116232.0 88821.0 0.0 86.0 3891955.0 96.2 0.0 25.0 2.1 1.6 0.0 0.0 71.3 2508315 SRR976230 SRP029889 SRS479322 SRX348546 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229108: hB5; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;48.54|rin;;8.7|sex;;male|source_name;;(H1)97-159 (Holland 1)|tissue;;brain GEO Accession;;GSM1229108 GSM1229108 hB5 113755446 5416926 2013-10-17 10:08:32 57994570 113755446 5416926 1 5416926 index:0,count:5416926,average:21,stdev:0 GSM1229108_r1 GEO 4.93 4.3 0.33 109171939 150814094 85288043 120418848 138.14 141.19 0 0 0 0 0 0 71.48 91.98 7770611 3745163 7770611 3745163 78.99 86.28 7770611 4138337 7770611 3513044 5387264 4.93 0.00 0 21.55 0 1.83 0 1.45 0 0.00 0 0.00 0 5239262 0 21 0 20.95 0 0.00 0 0.00 0 0.00 0 0.00 0 216.68 0 0.05 0 0 0 5416926 0 1167355 0 99151 0 78418 0 0 0 95 0 0 0 0 0 1 0 1177 0 0 0 1178 0 75.17 0 4071907 0 0 0 0.0 5416926.0 5239262.0 0.0 1167355.0 99151.0 78418.0 0.0 95.0 4071907.0 96.7 0.0 21.6 1.8 1.4 0.0 0.0 75.2 2508347 SRR976231 SRP029889 SRS479323 SRX348547 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229109: hH1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;5.00|rin;;8.6|sex;;male|source_name;;Maryl_1185|tissue;;heart GEO Accession;;GSM1229109 GSM1229109 hH1 206929779 9853799 2013-10-17 10:08:32 163732242 206929779 9853799 1 9853799 index:0,count:9853799,average:21,stdev:0 GSM1229109_r1 GEO 6.52 3.72 0.48 192162268 250771030 122654699 167555065 130.5 136.61 0 0 0 0 0 0 52.97 85.37 17818632 5052875 17818632 5052875 66.31 80.47 17818632 6325497 17818632 4762741 22611066 11.77 0.00 0 36.75 0 2.14 0 0.91 0 0.00 0 0.14 0 9539736 0 21 0 20.72 0 0.00 0 0.00 0 0.00 0 0.00 0 238.08 0 0.19 0 0 0 9853799 0 3621117 0 211015 0 89461 0 0 0 13587 0 0 0 0 0 11 0 13081 0 0 0 13092 0 60.06 0 5918619 0 0 0 0.0 9853799.0 9539736.0 0.0 3621117.0 211015.0 89461.0 0.0 13587.0 5918619.0 96.8 0.0 36.7 2.1 0.9 0.0 0.1 60.1 2508378 SRR976232 SRP029889 SRS479325 SRX348548 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229110: hH2; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;64.50|rin;;8.8|sex;;male|source_name;;NDRI-OD10035|tissue;;heart GEO Accession;;GSM1229110 GSM1229110 hH2 183055761 8716941 2013-10-17 10:08:32 146626733 183055761 8716941 1 8716941 index:0,count:8716941,average:21,stdev:0 GSM1229110_r1 GEO 6.98 4.77 1.88 167787142 208266199 94353464 130204454 124.13 138.0 0 0 0 0 0 0 45.99 85.43 17342704 3896668 17342704 3896668 58.99 80.45 17342704 4997990 17342704 3669196 26209328 15.62 0.00 0 44.88 0 2.15 0 0.49 0 0.00 0 0.16 0 8473117 0 21 0 20.69 0 0.00 0 0.00 0 0.00 0 0.00 0 210.61 0 0.21 0 0 0 8716941 0 3912030 0 187145 0 42593 0 0 0 14086 0 0 0 0 0 14 0 11600 0 0 0 11614 0 52.32 0 4561087 0 0 0 0.0 8716941.0 8473117.0 0.0 3912030.0 187145.0 42593.0 0.0 14086.0 4561087.0 97.2 0.0 44.9 2.1 0.5 0.0 0.2 52.3 2508410 SRR976233 SRP029889 SRS479324 SRX348549 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229111: hH3; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;73.53|rin;;7.8|sex;;male|source_name;;NDRI-47268|tissue;;heart GEO Accession;;GSM1229111 GSM1229111 hH3 283227021 13487001 2013-10-17 10:08:32 222072645 283227021 13487001 1 13487001 index:0,count:13487001,average:21,stdev:0 GSM1229111_r1 GEO 9.7 3.22 0.29 269484608 385099995 184586192 269529549 142.9 146.02 0 0 0 0 0 0 63.24 93.4 21636733 8249928 21636733 8249928 78.34 87.3 21636733 10220077 21636733 7711568 16687999 6.19 0.00 0 31.23 0 2.02 0 1.22 0 0.00 0 0.03 0 13045168 0 21 0 20.90 0 0.00 0 0.00 0 0.00 0 0.00 0 242.77 0 0.12 0 0 0 13487001 0 4212089 0 273007 0 165190 0 0 0 3636 0 0 0 0 0 8 0 6616 0 0 0 6624 0 65.49 0 8833079 0 0 0 0.0 13487001.0 13045168.0 0.0 4212089.0 273007.0 165190.0 0.0 3636.0 8833079.0 96.7 0.0 31.2 2.0 1.2 0.0 0.0 65.5 2508442 SRR976234 SRP029889 SRS479326 SRX348550 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229112: hH4; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;51.50|rin;;7.7|sex;;male|source_name;;NDRI-OD10512|tissue;;heart GEO Accession;;GSM1229112 GSM1229112 hH4 417189906 19866186 2013-10-17 10:08:32 317595986 417189906 19866186 1 19866186 index:0,count:19866186,average:21,stdev:0 GSM1229112_r1 GEO 13.08 2.79 0.36 392158307 550117392 243833526 344151144 140.28 141.14 0 0 0 0 0 0 54.77 89.53 34287752 10474035 34287752 10474035 74.38 84.51 34287752 14224700 34287752 9886757 34479864 8.79 0.00 0 37.38 0 2.28 0 1.43 0 0.00 0 0.02 0 19124414 0 21 0 20.84 0 1.00 0 0.00 0 0.00 0 0.00 0 293.11 0 0.13 0 0 0 19866186 0 7426151 0 453256 0 283591 0 0 0 4925 0 0 0 0 0 8 0 15967 0 0 0 15975 0 58.89 0 11698263 0 0 0 0.0 19866186.0 19124414.0 0.0 7426151.0 453256.0 283591.0 0.0 4925.0 11698263.0 96.3 0.0 37.4 2.3 1.4 0.0 0.0 58.9 2508473 SRR976235 SRP029889 SRS479327 SRX348551 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229113: hK1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;22.00|rin;;8.5|sex;;male|source_name;;Maryl_777|tissue;;kidney GEO Accession;;GSM1229113 GSM1229113 hK1 349659135 16650435 2013-10-17 10:08:32 269686312 349659135 16650435 1 16650435 index:0,count:16650435,average:21,stdev:0 GSM1229113_r1 GEO 7.65 3.93 0.39 323351549 431561057 195442668 270625243 133.46 138.47 0 0 0 0 0 0 50.26 85.18 30169834 8021808 30169834 8021808 66.18 79.11 30169834 10561898 30169834 7450337 36893475 11.41 0.00 0 39.30 0 2.80 0 1.29 0 0.00 0 0.06 0 15960377 0 21 0 20.75 0 1.00 0 0.00 0 0.00 0 0.00 0 235.06 0 0.23 0 0 0 16650435 0 6543071 0 465566 0 215080 0 0 0 9412 0 0 0 0 0 12 0 21365 0 0 0 21377 0 56.56 0 9417306 0 0 0 0.0 16650435.0 15960377.0 0.0 6543071.0 465566.0 215080.0 0.0 9412.0 9417306.0 95.9 0.0 39.3 2.8 1.3 0.0 0.1 56.6 2508505 SRR976236 SRP029889 SRS479328 SRX348552 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229114: hK4; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;67.50|rin;;9|sex;;male|source_name;;NDRI-OD09498|tissue;;kidney GEO Accession;;GSM1229114 GSM1229114 hK4 194182590 9246790 2013-10-17 10:08:32 148380905 194182590 9246790 1 9246790 index:0,count:9246790,average:21,stdev:0 GSM1229114_r1 GEO 8.71 3.57 0.35 181146405 255671908 119684030 174902699 141.14 146.14 0 0 0 0 0 0 58.28 89.84 15873026 5169252 15873026 5169252 72.83 83.71 15873026 6460666 15873026 4816680 14070773 7.77 0.00 0 33.70 0 2.48 0 1.52 0 0.00 0 0.06 0 8870383 0 21 0 20.80 0 1.00 0 0.00 0 1.00 0 0.00 0 275.11 0 0.15 0 0 0 9246790 0 3116580 0 229731 0 140689 0 0 0 5987 0 0 0 0 0 3 0 7385 0 0 0 7388 0 62.22 0 5753803 0 0 0 0.0 9246790.0 8870383.0 0.0 3116580.0 229731.0 140689.0 0.0 5987.0 5753803.0 95.9 0.0 33.7 2.5 1.5 0.0 0.1 62.2 2508536 SRR976237 SRP029889 SRS479329 SRX348553 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229115: hK5; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;45.03|rin;;9.3|sex;;male|source_name;;Finn 1|tissue;;kidney GEO Accession;;GSM1229115 GSM1229115 hK5 358913856 17091136 2013-10-17 10:08:32 280053791 358913856 17091136 1 17091136 index:0,count:17091136,average:21,stdev:0 GSM1229115_r1 GEO 12.27 3.23 0.35 335285297 469203502 202807142 291794165 139.94 143.88 0 0 0 0 0 0 51.82 87.45 30233816 8527138 30233816 8527138 70.28 81.75 30233816 11564646 30233816 7971448 32145145 9.59 0.00 0 39.23 0 2.54 0 1.13 0 0.00 0 0.04 0 16454884 0 21 0 20.80 0 1.00 0 0.00 0 0.00 0 0.00 0 230.44 0 0.25 0 0 0 17091136 0 6704287 0 434917 0 193977 0 0 0 7358 0 0 0 0 0 16 0 18701 0 0 0 18717 0 57.05 0 9750597 0 0 0 0.0 17091136.0 16454884.0 0.0 6704287.0 434917.0 193977.0 0.0 7358.0 9750597.0 96.3 0.0 39.2 2.5 1.1 0.0 0.0 57.1 2508568 SRR976238 SRP029889 SRS479331 SRX348554 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229116: hL1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;21.50|rin;;8.2|sex;;male|source_name;;NDRI-OD10707|tissue;;liver GEO Accession;;GSM1229116 GSM1229116 hL1 123162249 5864869 2013-10-17 10:08:32 73047732 123162249 5864869 1 5864869 index:0,count:5864869,average:21,stdev:0 GSM1229116_r1 GEO 3.12 2.46 0.41 117673025 154835958 79717694 112210809 131.58 140.76 0 0 0 0 0 0 61.71 91.63 9299120 3492803 9299120 3492803 69.35 85.28 9299120 3924986 9299120 3250540 17222934 14.64 0.00 0 31.51 0 2.03 0 1.46 0 0.00 0 0.00 0 5660012 0 21 0 20.91 0 1.00 0 0.00 0 0.00 0 0.00 0 207.00 0 0.11 0 0 0 5864869 0 1848309 0 118893 0 85804 0 0 0 160 0 0 0 0 0 1 0 9980 0 0 0 9981 0 64.99 0 3811703 0 0 0 0.0 5864869.0 5660012.0 0.0 1848309.0 118893.0 85804.0 0.0 160.0 3811703.0 96.5 0.0 31.5 2.0 1.5 0.0 0.0 65.0 2508599 SRR976239 SRP029889 SRS479330 SRX348555 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229117: hL1_GAII; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;21.50|rin;;8.2|sex;;male|source_name;;NDRI-OD10707|tissue;;liver GEO Accession;;GSM1229117 GSM1229117 hL1_GAII 227791368 10847208 2013-10-17 10:08:32 174789993 227791368 10847208 1 10847208 index:0,count:10847208,average:21,stdev:0 GSM1229117_r1 GEO 1.95 3.41 0.51 209938738 251117627 126563145 170322519 119.61 134.58 0 0 0 0 0 0 48.93 83.5 20227123 5104186 20227123 5104186 55.76 77.85 20227123 5816821 20227123 4758586 40688081 19.38 0.00 0 39.81 0 2.58 0 1.21 0 0.00 0 0.03 0 10431416 0 21 0 20.70 0 1.00 0 0.00 0 1.00 0 0.00 0 221.87 0 0.27 0 0 0 10847208 0 4318587 0 280261 0 131739 0 0 0 3792 0 0 0 0 0 7 0 28852 0 0 0 28859 0 56.35 0 6112829 0 0 0 0.0 10847208.0 10431416.0 0.0 4318587.0 280261.0 131739.0 0.0 3792.0 6112829.0 96.2 0.0 39.8 2.6 1.2 0.0 0.0 56.4 2508823 SRR976240 SRP029889 SRS479332 SRX348556 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229118: hL1_rep; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;21.50|rin;;8.2|sex;;male|source_name;;NDRI-OD10707|tissue;;liver GEO Accession;;GSM1229118 GSM1229118 hL1_rep 104260842 4964802 2013-10-17 10:08:32 47636853 104260842 4964802 1 4964802 index:0,count:4964802,average:21,stdev:0 GSM1229118_r1 GEO 5.08 2.5 0.4 100055363 133503233 63568832 91119850 133.43 143.34 0 0 0 0 0 0 58.33 92.35 7737424 2805210 7737424 2805210 67.39 85.99 7737424 3241140 7737424 2612018 17730489 17.72 0.00 0 35.69 0 1.63 0 1.49 0 0.00 0 0.00 0 4809612 0 21 0 20.93 0 1.00 0 0.00 0 0.00 0 0.00 0 192.19 0 0.09 0 0 0 4964802 0 1772136 0 81001 0 73974 0 0 0 215 0 0 0 0 0 0 0 1470 0 0 0 1470 0 61.18 0 3037476 0 0 0 0.0 4964802.0 4809612.0 0.0 1772136.0 81001.0 73974.0 0.0 215.0 3037476.0 96.9 0.0 35.7 1.6 1.5 0.0 0.0 61.2 2508854 SRR976241 SRP029889 SRS479333 SRX348557 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229119: hL2; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;83.50|rin;;6.7|sex;;male|source_name;;NDRI-OD09497|tissue;;liver GEO Accession;;GSM1229119 GSM1229119 hL2 63999180 3047580 2013-10-17 10:08:32 47015717 63999180 3047580 1 3047580 index:0,count:3047580,average:21,stdev:0 GSM1229119_r1 GEO 13.3 2.12 0.28 61701438 87431959 38569741 55062142 141.7 142.76 0 0 0 0 0 0 56.94 91.5 4791516 1685659 4791516 1685659 75.31 85.1 4791516 2229422 4791516 1567702 6716825 10.89 0.00 0 36.69 0 1.51 0 1.34 0 0.00 0 0.00 0 2960478 0 21 0 20.94 0 1.00 0 0.00 0 0.00 0 0.00 0 243.81 0 0.13 0 0 0 3047580 0 1118185 0 46129 0 40879 0 0 0 94 0 0 0 0 0 0 0 1770 0 0 0 1770 0 60.45 0 1842293 0 0 0 0.0 3047580.0 2960478.0 0.0 1118185.0 46129.0 40879.0 0.0 94.0 1842293.0 97.1 0.0 36.7 1.5 1.3 0.0 0.0 60.5 2508887 SRR976242 SRP029889 SRS479334 SRX348558 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229120: hL3; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;87.25|rin;;6.4|sex;;male|source_name;;NDRI-OD11414|tissue;;liver GEO Accession;;GSM1229120 GSM1229120 hL3 101371872 4827232 2013-10-17 10:08:32 44499688 101371872 4827232 1 4827232 index:0,count:4827232,average:21,stdev:0 GSM1229120_r1 GEO 9.76 2.58 0.55 97972542 134566872 63041522 89370997 137.35 141.77 0 0 0 0 0 0 59.41 92.89 7502022 2797812 7502022 2797812 72.44 85.54 7502022 3411466 7502022 2576470 11179489 11.41 0.00 0 35.17 0 1.28 0 1.15 0 0.00 0 0.01 0 4709598 0 21 0 20.93 0 1.00 0 0.00 0 0.00 0 0.00 0 182.93 0 0.07 0 0 0 4827232 0 1697739 0 61744 0 55500 0 0 0 390 0 0 0 0 0 0 0 2344 0 0 0 2344 0 62.39 0 3011859 0 0 0 0.0 4827232.0 4709598.0 0.0 1697739.0 61744.0 55500.0 0.0 390.0 3011859.0 97.6 0.0 35.2 1.3 1.1 0.0 0.0 62.4 2508918 SRR976243 SRP029889 SRS479335 SRX348559 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229121: hL4; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;NA|rin;;8.7|sex;;male|source_name;;Witthe 1|tissue;;liver GEO Accession;;GSM1229121 GSM1229121 hL4 102791472 4894832 2013-10-17 10:08:32 47224013 102791472 4894832 1 4894832 index:0,count:4894832,average:21,stdev:0 GSM1229121_r1 GEO 5.24 2.15 0.41 99360848 131072537 64848629 89202930 131.92 137.56 0 0 0 0 0 0 60.77 93.66 7479137 2901058 7479137 2901058 70.9 86.69 7479137 3384540 7479137 2685086 15035832 15.13 0.00 0 34.24 0 1.31 0 1.16 0 0.00 0 0.00 0 4773600 0 21 0 20.94 0 1.00 0 0.00 0 0.00 0 0.00 0 238.13 0 0.07 0 0 0 4894832 0 1676109 0 64163 0 56907 0 0 0 162 0 0 0 0 0 0 0 1562 0 0 0 1562 0 63.28 0 3097491 0 0 0 0.0 4894832.0 4773600.0 0.0 1676109.0 64163.0 56907.0 0.0 162.0 3097491.0 97.5 0.0 34.2 1.3 1.2 0.0 0.0 63.3 2508952 SRR976244 SRP029889 SRS479336 SRX348560 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229122: hL5; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer age;;78.50|rin;;7.5|sex;;male|source_name;;NDRI-OD09548|tissue;;liver GEO Accession;;GSM1229122 GSM1229122 hL5 58875348 2803588 2013-10-17 10:08:32 43644158 58875348 2803588 1 2803588 index:0,count:2803588,average:21,stdev:0 GSM1229122_r1 GEO 11.02 1.99 0.29 56902161 78113341 36601741 50680943 137.28 138.47 0 0 0 0 0 0 59.88 93.57 4305672 1635988 4305672 1635988 75.44 85.87 4305672 2061044 4305672 1501371 5693545 10.01 0.00 0 35.08 0 1.32 0 1.23 0 0.00 0 0.00 0 2732021 0 21 0 20.93 0 0.00 0 0.00 0 0.00 0 0.00 0 174.02 0 0.11 0 0 0 2803588 0 983635 0 37091 0 34427 0 0 0 49 0 0 0 0 0 0 0 1347 0 0 0 1347 0 62.36 0 1748386 0 0 0 0.0 2803588.0 2732021.0 0.0 983635.0 37091.0 34427.0 0.0 49.0 1748386.0 97.4 0.0 35.1 1.3 1.2 0.0 0.0 62.4 2508983 SRR976245 SRP029889 SRS479337 SRX348561 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229123: hT1; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;70.50|rin;;6.5|sex;;male|source_name;;NDRI-46518|tissue;;testis GEO Accession;;GSM1229123 GSM1229123 hT1 231747810 11035610 2013-10-17 10:08:32 179771396 231747810 11035610 1 11035610 index:0,count:11035610,average:21,stdev:0 GSM1229123_r1 GEO 2.39 3.52 0.53 212375358 251670831 146960151 189909841 118.5 129.23 0 0 0 0 0 0 52.05 77.64 19065558 5510933 19065558 5510933 58.14 72.09 19065558 6154932 19065558 5117172 28176766 13.27 0.00 0 31.62 0 2.33 0 1.69 0 0.00 0 0.05 0 10586788 0 21 0 20.70 0 1.00 0 0.00 0 0.00 0 0.00 0 223.19 0 0.27 0 0 0 11035610 0 3488932 0 256834 0 186542 0 0 0 5446 0 0 0 0 0 18 0 17333 0 0 0 17351 0 64.32 0 7097856 0 0 0 0.0 11035610.0 10586788.0 0.0 3488932.0 256834.0 186542.0 0.0 5446.0 7097856.0 95.9 0.0 31.6 2.3 1.7 0.0 0.0 64.3 2509012 SRR976246 SRP029889 SRS479338 SRX348562 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229124: hT2; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;88.50|rin;;7.7|sex;;male|source_name;;NDRI-OD09200|tissue;;testis GEO Accession;;GSM1229124 GSM1229124 hT2 181471227 8641487 2013-10-17 10:08:32 139444810 181471227 8641487 1 8641487 index:0,count:8641487,average:21,stdev:0 GSM1229124_r1 GEO 3.58 3.68 0.46 168785697 211417345 116864943 155777379 125.26 133.3 0 0 0 0 0 0 55.63 82.14 14632908 4620860 14632908 4620860 63.9 75.96 14632908 5308071 14632908 4273204 18355732 10.88 0.00 0 31.02 0 2.33 0 1.52 0 0.00 0 0.03 0 8306639 0 21 0 20.77 0 1.00 0 0.00 0 0.00 0 0.00 0 202.01 0 0.16 0 0 0 8641487 0 2680799 0 201469 0 131111 0 0 0 2268 0 0 0 0 0 2 0 9338 0 0 0 9340 0 65.10 0 5625840 0 0 0 0.0 8641487.0 8306639.0 0.0 2680799.0 201469.0 131111.0 0.0 2268.0 5625840.0 96.1 0.0 31.0 2.3 1.5 0.0 0.0 65.1 2509044 SRR976247 SRP029889 SRS479340 SRX348563 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229125: hT3; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;51.39|rin;;7.4|sex;;male|source_name;;NDRI-47376|tissue;;testis GEO Accession;;GSM1229125 GSM1229125 hT3 195691167 9318627 2013-10-17 10:08:32 147220980 195691167 9318627 1 9318627 index:0,count:9318627,average:21,stdev:0 GSM1229125_r1 GEO 2.32 3.66 0.48 182546429 228096745 133284656 176284243 124.95 132.26 0 0 0 0 0 0 58.92 82.21 14851969 5264106 14851969 5264106 65.65 76.21 14851969 5865513 14851969 4879942 18005032 9.86 0.00 0 27.15 0 2.21 0 1.89 0 0.00 0 0.02 0 8934065 0 21 0 20.81 0 1.00 0 0.00 0 0.00 0 0.00 0 215.05 0 0.14 0 0 0 9318627 0 2530447 0 206244 0 176572 0 0 0 1746 0 0 0 0 0 1 0 7948 0 0 0 7949 0 68.72 0 6403618 0 0 0 0.0 9318627.0 8934065.0 0.0 2530447.0 206244.0 176572.0 0.0 1746.0 6403618.0 95.9 0.0 27.2 2.2 1.9 0.0 0.0 68.7 2509076 SRR976248 SRP029889 SRS479339 SRX348564 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229126: hT4; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;NA|rin;;7|sex;;male|source_name;;S1483/06|tissue;;testis GEO Accession;;GSM1229126 GSM1229126 hT4 224243565 10678265 2013-10-17 10:08:32 168007158 224243565 10678265 1 10678265 index:0,count:10678265,average:21,stdev:0 GSM1229126_r1 GEO 2.38 3.6 0.52 207343967 250113773 145718840 188548311 120.63 129.39 0 0 0 0 0 0 54.22 79.06 17813534 5550854 17813534 5550854 60.83 73.2 17813534 6227632 17813534 5139439 25080364 12.10 0.00 0 30.13 0 2.27 0 1.83 0 0.00 0 0.03 0 10238077 0 21 0 20.76 0 1.00 0 0.00 0 0.00 0 0.00 0 203.40 0 0.18 0 0 0 10678265 0 3217343 0 242176 0 195326 0 0 0 2686 0 0 0 0 0 2 0 11846 0 0 0 11848 0 65.75 0 7020734 0 0 0 0.0 10678265.0 10238077.0 0.0 3217343.0 242176.0 195326.0 0.0 2686.0 7020734.0 95.9 0.0 30.1 2.3 1.8 0.0 0.0 65.7 2509108 SRR976249 SRP029889 SRS479341 SRX348565 SRA101231 GEO Quantification of gene expression from primate tissue samples We have quantified gene expression in five tissues (brain, heart, kidney, liver and testis) from humans, chimpanzees and rhesus macaques using the Illumina NlaIII Digital Gene Expression (DGE) protocol. This dataset extends a previous microarray study by Khaitovich et al. (Khaitovich et al. 2005) with the rhesus macaque outgroup and complements other previously generated tissue transcriptome profiles from primates (Enard et al. 2002; Khaitovich et al. 2006; Somel et al. 2009; Babbitt et al. 2010; Blekhman et al. 2010; Wetterbom et al. 2010). contributor: Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany Overall design: Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Illumina NlaIII DGE libraries for all samples were generated in tissue batches, randomizing species in library preparation and sequencing. Human samples originate from different, probably unrelated, individuals for each tissue. For chimpanzees and rhesus macaques the libraries for all tissues come from the same set of individuals and among these are individuals related at the half- and full-sibling level. Due to limited access to samples, the analysis could not be limited to individuals of similar age. Human individuals vary between 5 and 88 years of age, chimpanzees between 6 years and 35 years of age and rhesus macaques between 3 and 9 years of age. GSM1229127: hT5; Homo sapiens; RNA-Seq RNA-Seq TRANSCRIPTOMIC cDNA single Samples were obtained from brain (pre-frontal cortex), heart, kidney, liver, and testis tissues of male humans, chimpanzees and rhesus macaques. Samples were processed in tissue batches, randomizing species in library preparation and sequencing. Illumina NlaIII DGE libraries for all samples were generated following the vendor protocol. Expressed 3' tags from polyA RNAs Illumina Genome Analyzer II age;;NA|rin;;6.5|sex;;male|source_name;;S1324/06|tissue;;testis GEO Accession;;GSM1229127 GSM1229127 hT5 232384383 11065923 2013-10-17 10:08:32 167399423 232384383 11065923 1 11065923 index:0,count:11065923,average:21,stdev:0 GSM1229127_r1 GEO 2.48 3.69 0.49 211666769 249713725 141806807 182057598 117.97 128.38 0 0 0 0 0 0 49.12 75.54 19397681 5173730 19397681 5173730 55.7 69.78 19397681 5867514 19397681 4778776 30525385 14.42 0.00 0 33.30 0 2.56 0 2.21 0 0.00 0 0.04 0 10533839 0 21 0 20.71 0 1.00 0 0.00 0 0.00 0 0.00 0 202.22 0 0.23 0 0 0 11065923 0 3685054 0 283020 0 245011 0 0 0 4053 0 0 0 0 0 3 0 16017 0 0 0 16020 0 61.89 0 6848785 0 0 0 0.0 11065923.0 10533839.0 0.0 3685054.0 283020.0 245011.0 0.0 4053.0 6848785.0 95.2 0.0 33.3 2.6 2.2 0.0 0.0 61.9