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accession-icon GSE76192
RNAPol2 accounts for tumor cells liability to JQ1
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Compensatory RNA polymerase 2 loading determines the efficacy and transcriptional selectivity of JQ1 in Myc-driven tumors.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE16158
Gene expression induced by trace fear conditioning in murine hippocampus
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Gene expression profiling following different learning paradigms may help in defining the moleular pathways of memory formation. In this study we analyzed the gene expression pattern of murine hippocampus at different time points (0.5 h, 2h, 6h) after trace fear conditioning. We compared trained mice with naive mice that remained in their homecages.

Publication Title

Temporal gene expression profile of the hippocampus following trace fear conditioning.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE76188
RNAPol2 accounts for tumor cells liability to JQ1 [Affymetrix]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We here use B-cell tumors as a model to address the mechanism of action of JQ1, a widely used BET inhibitor.

Publication Title

Compensatory RNA polymerase 2 loading determines the efficacy and transcriptional selectivity of JQ1 in Myc-driven tumors.

Sample Metadata Fields

Treatment

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accession-icon SRP106243
Integrative analysis of RNA Polymerase II and transcriptional dynamics upon Myc activation [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 56 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Over-expression of the Myc transcription factor causes its widespread interaction with regulatory domains in the genome, but leads to the up- and down-regulation of discrete sets of genes. The molecular determinants of these selective transcriptional responses remain elusive. Here, we present an integrated time-course analysis of transcription and mRNA dynamics following Myc activation in proliferating mouse fibroblasts, based on chromatin immunoprecipitation, metabolic labeling of newly synthesized RNA, extensive sequencing and mathematical modeling. Transcriptional activation correlated with the highest increases in Myc binding at promoters. Repression followed a reciprocal scenario, with the lowest gains in Myc binding. Altogether, the relative abundance (henceforth, “share”) of Myc at promoters was the strongest predictor of transcriptional responses in diverse cell types, predominating over Myc's association with the co-repressor Miz1. Myc activation elicited immediate loading of RNAPII at activated promoters, followed by increases in pause-release5, while repressed promoters showed opposite effects. Gains and losses in RNAPII loading were proportional to the changes in the Myc share, suggesting that repression by Myc may be largely indirect, owing - at least in part - to competition for limiting amounts of RNAPII. Secondary to the changes in RNAPII loading, the dynamics of elongation and pre-mRNA processing were also rapidly altered at Myc regulated genes, leading to the transient accumulation of partially or aberrantly processed mRNAs. Altogether, our results shed light on how over-expressed Myc alters the various phases of the RNAPII cycle and the resulting transcriptional response. Overall design: Time course profiling of 4sU-labeled and total RNA upon Myc activation in 3T9-MycER mouse fibroblasts

Publication Title

Integrative analysis of RNA polymerase II and transcriptional dynamics upon MYC activation.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP015689
A user-friendly chromatographic method to purify small regulatory RNAs
  • organism-icon Drosophila melanogaster
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx, Illumina HiSeq 2000

Description

The discovery of the small regulatory RNA populations has changed our vision of cellular regulations. Indeed, loaded on Argonaute proteins they formed ribonucleoprotein complexes that target complementary sequences and achieved widespread silencing mechanisms conserved in most eukaryotes. The recent development of deep sequencing approaches highly contributed to their detection. Small RNA isolation form cells and/or tissues remains a crucial stage to generate robust and relevant sequencing data. In 2006, a novel strategy based on anion-exchange chromatography has been purposed as an alternative to the standard size-isolation purification procedure. However, the eventual biases of such a method have been poorly investigated. Moreover, this strategy not only relies on advanced technical skills and expensive material but is time consuming and requires an elevated starting biological material amount. Using bioinformatic comparative analysis of six independent small RNA-sequencing libraries of Drosophila ovaries, we here demonstrate that anion-exchange chromatography purification prior to small RNA extraction unbiasedly enriches datasets in bona fide reads (small regulatory RNA reads) and depletes endogenous contaminants (ribosomal RNAs and degradation products). The resulting increase of sequencing depth provides a major benefit to study rare populations. We then developed a fast and basic manual procedure to purify loaded small non coding RNAs using anion-exchange chromatography at the bench. We validated the efficiency of this new method and used this strategy to purify small RNAs from various tissues and organisms. We moreover determined that our manual purification increases the output of the previously described anion-exchange chromatography procedure. Overall design: Comparison of small regulatory RNA populations obtained after three different small RNA purification procedures

Publication Title

A user-friendly chromatographic method to purify small regulatory RNAs.

Sample Metadata Fields

Sex, Specimen part, Cell line, Subject

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accession-icon SRP131125
A compendium of long non-coding RNAs transcriptional fingerprint in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Multiple myeloma (MM) is a malignant proliferation of bone marrow plasma cells (PCs) characterized by highly heterogeneous genetic background and clinical course, and whose pathogenesis remains largely unknown. Long ncRNAs (lncRNAs) are a large class of non-protein-coding RNA, involved in many physiological cellular and genomic processes as well as in carcinogenesis, cancer metastasis and invasion. Although still in its infancy, the knowledge of the role of lncRNAs in MM is progressively expanding. Besides studies on selected candidates, lncRNAs expression at genome-wide transcriptome level is confined to microarray technologies, thus investigating a limited collection of transcripts. Herein, we assessed the lncRNAs expression profiling by RNA-sequencing in a cohort of 30 MM patients, aimed at defining a comprehensive catalogue of lncRNAs specifically associated with the main MM molecular subgroups and genetic alterations. We identified 391 deregulated lncRNAs, 67% of which were also detectable and validated by whole-transcript microarrays. In addition, we identified a list of lncRNAs, with potential relevance in MM, co-expressed and in close proximity to genes that might undergo a cis-regulatory relationship. Overall design: Total RNA samples from highly purified plasma cells of 30 MM cases at onset

Publication Title

Expression Pattern and Biological Significance of the lncRNA ST3GAL6-AS1 in Multiple Myeloma.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Subject

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accession-icon SRP009871
piRNA-mediated transgenerational inheritance of an acquired trait
  • organism-icon Drosophila melanogaster
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina Genome Analyzer II

Description

The maintenance of genome integrity is an essential trait to the successful transmission of genetic information. In animal germ cells, piRNAs guide PIWI proteins to silence transposable elements (TEs) in order to maintain genome integrity. In insects, most of TE silencing in the germline is achieved by secondary piRNAs that are produced by a feed-forward loop (the ping-pong cycle), which requires the piRNA-directed cleavages of two types of RNAs: mRNAs of functional euchromatic TEs and heterochromatic transcripts that contain defective TE sequences. The first cleavage which initiates such amplification loop remains poorly understood. Taking advantage of the existence of strains that are devoid of functional copies of the LINE-like I-element, we report that in such Drosophila ovaries, the initiation of a ping-pong cycle is achieved only by secondary I-element piRNAs that are produced in the ovary and deposited in the embryonic germline. This unusual secondary piRNA biogenesis, detected in the absence of functional I-element copies, results from the processing of sense and antisense transcripts of several different defective I-elements. Once acquired, for instance after ancestor aging, this capacity to produce heterochromatic-only secondary piRNAs is partially transmitted through generations via maternal piRNAs. Furthermore, such piRNAs acting as ping-pong initiators in a chromatin-independent manner confer to the progeny a high capacity to repress the I-element mobility. Our study explains at the molecular level the basis for epigenetic memory of maternal immunity that protects females from hybrid dysgenesis caused by transposition of paternally inherited functional I-elements. Overall design: Comparison of Drosophila small RNA populations in ovaries and/or eggs from 3-day-old or 25-day-old females.

Publication Title

piRNA-mediated transgenerational inheritance of an acquired trait.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Subject

View Samples
accession-icon SRP006726
Gene expression analysis of breast cancer (HCC1954) and normal breast cells (HMEC)
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

While genetic mutation is a hallmark of cancer, many cancers also acquire epigenetic alterations during tumorigenesis including aberrant DNA hypermethylation of tumor suppressors as well as changes in chromatin modifications as caused by genetic mutations of the chromatin-modifying machinery. However, the extent of epigenetic alterations in cancer cells has not been fully characterized. Here, we describe the first complete methylome maps at single nucleotide resolution of a low-passage breast cancer cell line and primary human mammary epithelial cells. We find widespread DNA hypomethylation in the cancer cell, primarily at partially methylated domains (PMDs) in normal breast cells. Unexpectedly, genes within these regions are largely silenced in cancer cells. The loss of DNA methylation in these regions is accompanied by formation of repressive chromatin, with a significant fraction displaying allelic DNA methylation where one allele is DNA methylated while the other allele is occupied by histone modifications H3K9me3 or H3K27me3. Our results show a mutually exclusive and complementary relationship between DNA methylation and H3K9me3 or H3K27me3. These results suggest that global DNA hypomethylation in breast cancer is tightly linked to the formation of repressive chromatin domains and gene silencing, thus identifying a potential epigenetic pathway for gene regulation in cancer cells and suggesting a possible new approach toward the development of cancer therapeutics. Overall design: mRNA-Seq of polyA-selected RNA from breast cancer HCC1954 and normal breast HMEC. 36 cycles of sequencing on Illumina platform.

Publication Title

Global DNA hypomethylation coupled to repressive chromatin domain formation and gene silencing in breast cancer.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP056216
Transcription of mammalian cis-regulatory elements is restrained by actively enforced early termination [RNA]
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon

Description

Upon recruitment to active enhancers and promoters, RNA polymerase II (Pol_II) generates short non-coding transcripts of unclear function. The mechanisms that control the length and the amount of ncRNAs generated by cis-regulatory elements are largely unknown. Here, we show that the adapter protein WDR82 and its associated complexes actively limit such non-coding transcription. WDR82 targets the SET1/COMPASS H3K4 methyltransferase and the nuclear Protein Phosphatase 1 (PP1) complexes to the initiating Pol_II. WDR82 and PP1 also interact with components of the transcriptional termination and RNA processing machineries. Depletion of WDR82, SET1 or the PP1 subunit required for its nuclear import caused distinct but overlapping transcription termination defects at highly expressed genes, active enhancers and promoters, thus enabling the increased synthesis of unusually long ncRNAs. These data indicate that transcription initiated from cis-regulatory elements is tightly coordinated with termination mechanisms that impose the synthesis of short RNAs. Overall design: polyA-mRNAs or 4sU-labeled RNAs from BMDMs, either untreated or treated for with lipopolysaccharide (LPS) for the indicated time. Experiments were carried out in cells containing either a short hairpin targeting either of these: 1) Wdr82; 2) Set1a+Set1b; 3) Pnuts; or the empty vector (LMP) or a scrambled as a control. When specified, cells were pre-treated with 5,6-Dichloro-1-ß-D-ribofuranosylbenzimidazole (DRB) in order to prevent RNA polymerase II elongation.

Publication Title

Transcription of Mammalian cis-Regulatory Elements Is Restrained by Actively Enforced Early Termination.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP070815
24hr CA treatment vs. DMSO in HCT116 cells (from ''Identification of CDK8 and CDK19 substrates in human cells using cortistatin A and quantitative phosphoproteomics'')
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Cortistatin A (CA) is a highly selective inhibitor of the Mediator kinases CDK8 and CDK19. Using CA, we report here the first large-scale identification of Mediator kinase substrates in human cells (HCT116). Among over 16,000 quantified phosphosites, we identified 78 high-confidence Mediator kinase targets within 64 proteins, including DNA-binding transcription factors and proteins associated with chromatin, DNA repair, and RNA polymerase II. Although RNA-Seq data correlated with Mediator kinase targets, CA effects on gene expression were limited and distinct from CDK8 or CDK19 knockdown. Quantitative proteome analyses, which tracked about 7,000 proteins across six time points (0 – 24h), revealed that CA selectively affected pathways implicated in inflammation, growth, and metabolic regulation; contrary to expectations, increased turnover of Mediator kinase targets was not generally observed. Collectively, these data support Mediator kinases as regulators of chromatin and RNA polymerase II activity and suggest cellular roles beyond transcription, including metabolism and DNA repair. Overall design: HCT116 cells were treated with either 100nM CA or DMSO in biological triplicate for each population (6 samples total). Treatment was for 24h for compound and vehicle.

Publication Title

Identification of Mediator Kinase Substrates in Human Cells using Cortistatin A and Quantitative Phosphoproteomics.

Sample Metadata Fields

No sample metadata fields

View Samples
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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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