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accession-icon GSE5509
Expression data from Rat liver 48 hours after treated with different toxic compounds.
  • organism-icon Rattus norvegicus
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Rat has been treated with different compounds with the purpose of investigating toxicological mechanisms. But toxic and non-toxic compounds has been administered. 3 toxic (ANIT, DMN, NMF) 3 non-tox (Caerulein, dinitrophenol(DNP), Rosiglitazone) in 5-plicates (30 arrays in all) and 9 untreated (control), 39 samples in all.

Publication Title

Integration of clinical chemistry, expression, and metabolite data leads to better toxicological class separation.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP018886
Global analyses of how 3'' UTR-isoform choice influences mRNA stability and translational efficiency
  • organism-icon Mus musculus
  • sample-icon 14 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina Genome Analyzer II

Description

We obtained global measurements of decay and translation rates for mammalian mRNAs with alternative 3'' untranslated regions (3'' UTRs). Overall design: 1 3P-Seq sample from 3T3 cells and 1 3P-Seq sample from mouse ES cells; 2 2P-Seq steady state and 4 2P-Seq with actinomycin D; 6 polysome fraction 2P-Seq

Publication Title

3' UTR-isoform choice has limited influence on the stability and translational efficiency of most mRNAs in mouse fibroblasts.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon SRP049508
Constraint and divergence of global gene expression in the mammalian embryo
  • organism-icon Mus musculus
  • sample-icon 174 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000, IlluminaGenomeAnalyzerIIx

Description

We profiled genome-wide gene expression of 170 individual mid-gestation (embryonic day 11.5) whole mouse embryos derived from a 2-generation interspecies mouse cross and asked to what extent genetic variation drives four important parameters of regulatory architecture: allele-specific expression (ASE), imprinting, trans-regulatory effects, and maternal effect. The inbred strain C57BL/6J and wild-derived inbred strain CAST/EiJ were used in reciprocal crosses to generate F1 embryos. F1 progeny were backcrossed to C57BL/6J in reciprocal crosses to generate 154 N2 embryos. We employed a backcross design, in which N2 offspring have genotypically distinct parents, to enable comparison of gene expression for offspring from each side of the reciprocal cross. Our findings demonstrate that genetic variation contributes to widespread gene expression differences during mammalian embryogenesis. Overall design: Transcriptome analysis of E11.5 mouse embryos: 16 F1 embryos from reciprocally crossed C57BL/6J and CastEi/J parents; and 154 N2 embryos from reciprocal backcross of F1s to the C57BL/6J parent.

Publication Title

Constraint and divergence of global gene expression in the mammalian embryo.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE41819
Active STAT5 in CD8 T cells
  • organism-icon Mus musculus
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Active STAT5 regulates T-bet and eomesodermin expression in CD8 T cells and imprints a T-bet-dependent Tc1 program with repressed IL-6/TGF-β1 signaling.

Sample Metadata Fields

Specimen part

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accession-icon GSE26945
Optimized CD8 effector TL
  • organism-icon Mus musculus
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Transcriptome analyses of naive, effector and memory CD8 TCRP1A lymphocytes expressing or not an active form of the transcription factor Stat5.

Publication Title

Active STAT5 regulates T-bet and eomesodermin expression in CD8 T cells and imprints a T-bet-dependent Tc1 program with repressed IL-6/TGF-β1 signaling.

Sample Metadata Fields

Specimen part

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accession-icon GSE18997
Transcriptional profiling of testicular biopsies with Sertoli-cell-only and spermatogonial presence
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The aim of the study was to identify in vivo spermatogonial gene expression within the context of their biological niche.

Publication Title

Screening for biomarkers of spermatogonia within the human testis: a whole genome approach.

Sample Metadata Fields

Specimen part

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accession-icon GSE35640
Identification of a predictive gene signature to recMAGE A3 antigen-specific cancer immunotherapy in metastatic melanoma and non-small-cell lung cancer
  • organism-icon Homo sapiens
  • sample-icon 64 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGEA3

Publication Title

Predictive gene signature in MAGE-A3 antigen-specific cancer immunotherapy.

Sample Metadata Fields

Specimen part

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accession-icon SRP148892
Transcriptomic profiling of mock-infected primary CD4+ T cells and a model of HIV latency treated with suberoylanilide hydroxamic acid (SAHA) and Romidepsin (RMD)
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Purpose: The goal of this study is to identify host genes whose expression is perturbed in primary CD4+ T cells by histone deacetylase (HDAC) inhibitors (HDACi) SAHA and RMD, which have different potencies and specificities for various HDACs. The study aims to evaluate the effects of SAHA and RMD that may promote or inhibit reactivation of HIV provirus out of latency. Methods: Peripheral blood mononuclear cells were collected from 4 HIV-seronegative donors. CD4+ T cells were isolated and utilized to generate an in vitro model of latent HIV infection (model developed in the Spina laboratory and previously described in Spina et al., 2013). Mock-infected cells were cultured in parallel to evaluate effects of SAHA and RMD that may be dependent on the exposure of cells to virus. Following generation of the model, cells were treated with SAHA, RMD or their solvent dimethyl sulfoxide (DMSO) for 24 hours. Mock-infected cells were treated in parallel. The experiment had 4 biological replicates, 6 conditions for each, for a total of 24 samples. ERCC spikes (Thermo Fisher Scientific, Inc.) were added to cell lysates based on cell number in each sample (10 ul of 1:800 dilution per million cells). Mix 1 was used for DMSO- and mix 2 for SAHA- and RMD-treated cells. After all samples were collected, RNA was extracted and subjected to deep sequencing by Expression Analysis, Inc. Sequence reads that passed quality filters were mapped using Tophat (human genome) or Bowtie (ERCC spikes and HIV) and counted using HTSeq. ERCC spikes with the same concentration in mixes 1 and 2 were utilized to remove unwanted technical variation. Any human gene which did not achieve at least 1 count per million reads in at least 4 samples or any ERCC that did not achieve at least 5 reads in at least 4 samples was discarded. Differential gene expression analysis was performed using library EdgeR in Bioconductor R. National Center for Biotechnology Information (NCBI) HIV-1 Human Interaction Database was then searched for genes that have been implicated in controlling HIV latency. EdgeR output was used to extract expression information of the genes of interest from the NCBI database to identify genes implicated in HIV latency that were modulated by SAHA and RMD. The resulting lists were manually curated to verify relevance to HIV latency, using the Description column of the NCBI database, as well as available PubMed references. Results: Using a custom built data analysis pipeline, ~100 million reads per sample were mapped to the human genome (build hg38). After applying filtering criteria, 16058 human transcripts, 19 ERCC spikes transcripts, and HIV NL4-3 transcripts were identified with the Tophat/Bowtie and HTSeq workflow. Differential expression analysis was performed between SAHA or RMD-treated and DMSO-treated cells. In addition, differential modulation of gene expression by SAHA and RMD in the model of HIV latency and mock-infected cells was assessed using EdgeR. In mock-infected cells, SAHA upregulated 3,971 genes and downregulated 2,940 genes; RMD upregulated 5,068 genes and downregulated 4,050 genes. In the model of HIV latency, SAHA upregulated 3,498 genes and downregulated 2,904 genes; RMD upregulated 5,116 genes and downregulated 4,053 genes (FDR < 0.05). SAHA modulated 6, and RMD 11 genes differentially between mock-infected cells and the model of HIV latency. Following search of the NCBI HIV-1 Human Interaction Database, 27 genes upregulated and 29 downregulated in common between SAHA and RMD were found to be relevant to regulation of HIV latency; 31 were up- and 32 downregulated by RMD only; and 6 were up- and 2 were downregulated by SAHA only. Conclusions: This study demonstrates that SAHA and RMD, which have different potencies and specificities for HDACs, modulate a set of overlapping genes implicated in regulation of HIV latency. Some of these genes may be explored as additional host targets for improving the outcomes of “shock and kill” strategies. Overall design: Transcriptomic profiling of the in vitro model of HIV latency and mock-infected cells treated with SAHA, RMD or the solvent DMSO (N=4 donors) by deep sequencing at Expression Analysis, Inc.

Publication Title

Long non-coding RNAs and latent HIV - A search for novel targets for latency reversal.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon SRP013644
CpG islands and GC content dictate nucleosome depletion in a transcription independent manner at mammalian promoters (RNA-seq)
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

One clear hallmark of mammalian promoters is the presence of CpG islands (CGIs) at more than two thirds of genes whereas TATA boxes are only present at a minority of promoters. Using genome-wide approaches, we show that GC content and CGIs are major promoter elements in mammalian cells, able to govern open chromatin conformation and support paused transcription. First, we define three classes of promoters with distinct transcriptional directionality and pausing properties which correlate with their GC content. We further analyze the direct influence of GC content on nucleosome positioning and depletion, and show that CGIs correlate with nucleosome depletion both in vivo and in vitro. We also show that transcription is not essential for nucleosome exclusion but influences both a weak +1 and a well-positioned nucleosome at CGI borders. Altogether our data support the idea that CGIs have become an essential feature of promoter structure defining novel regulatory properties in mammals. Overall design: Nucleosome density and positioning were studied by high-throughput sequencing of DNA previously treated with Mnase. In parallel, chIPseq for PolII and H3K27ac were performed in mouse and human with different conditions to assess a potential effect of transcription on nucleosomes properties. To investigate transcription at promoters, we analyzed together with genome-wide Pol II accumulation by ChIP-Seq, paused bidirectional transcripts associated with transcription start sites (TSS RNAs).

Publication Title

CpG islands and GC content dictate nucleosome depletion in a transcription-independent manner at mammalian promoters.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE56395
Transcriptional landscape of Rag2 -/- thymocytes
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcription-dependent generation of a specialized chromatin structure at the TCRβ locus.

Sample Metadata Fields

Specimen part

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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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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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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