SRP002915	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).	
SRP003726	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	
SRP004042	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	
SRP004847	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.	
SRP004965	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.	
SRP005279	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.	
SRP017786	Homo sapiens Transcriptome or Gene expression	6 DGE sequencing human	
SRP029889	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.	
SRP040110	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.	
SRP055513	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)	
SRP064863	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	
SRP128731	my data		
SRP168237	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.	
SRP223635	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.	
study_acc	study_title	study_abstract	study_description