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accession-icon SRP118618
Defining transcription factor networks that govers SCC growth [RNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Differential gene expression analysis were performed between Pitx1 silenced SCC cells and controls in two independent SCC lines Overall design: Compared control and Pitx1 deficient cells to define gene sets control by Pitx1 in SCCs.

Publication Title

De Novo PITX1 Expression Controls Bi-Stable Transcriptional Circuits to Govern Self-Renewal and Differentiation in Squamous Cell Carcinoma.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE40540
IP of 5-hydroxymethylcytosine (5-hmC) and 5-methylcytosine (5-mC) enriched DNA fragments from control and PB treated mouse livers
  • organism-icon Mus musculus
  • sample-icon 49 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Dynamic changes in 5-hydroxymethylation signatures underpin early and late events in drug exposed liver.

Sample Metadata Fields

Sex, Specimen part, Treatment, Time

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accession-icon GSE45465
Dynamic changes in liver 5-hydroxymethylcytosine profiles upon non-genotoxic carcinogen exposure [Replicated control vs. pb treated study]
  • organism-icon Mus musculus
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Dynamic changes in the mouse liver DNA methylome associated with short (1 day) and prolonged (7, 28 and 91 days) exposure to the rodent liver non-genotoxic carcinogen (NGC), phenobarbital (PB).

Publication Title

Dynamic changes in 5-hydroxymethylation signatures underpin early and late events in drug exposed liver.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE28887
Gene expression profile of Age associated B cells, Follicular B cells, and B1 cells
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We performed gene expression profile of different B cell populations found in old (18 months old) C57BL/6 female mouse (B1 cells were recovered from both young and old C57BL/6 mice). Mice were nave and healthy (no autoimmunity was detected at the time of the experiment).

Publication Title

Toll-like receptor 7 (TLR7)-driven accumulation of a novel CD11c⁺ B-cell population is important for the development of autoimmunity.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE40773
Dynamic changes in liver 5-hydroxymethylcytosine profiles upon non-genotoxic carcinogen exposure
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

29-32 days old male mice where either treated with Phenobarbital or untreated

Publication Title

Dynamic changes in 5-hydroxymethylation signatures underpin early and late events in drug exposed liver.

Sample Metadata Fields

Sex, Specimen part, Treatment, Time

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accession-icon GSE26990
Analysis of Promoter Methylation in Breast Cancer
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

Promoter methylation was assayed in a number of breast cancer and control normal samples along with the effects of 5'-aza-2'-deoxycytidine on breast cancer cell line transcriptomes.

Publication Title

Transcriptionally repressed genes become aberrantly methylated and distinguish tumors of different lineages in breast cancer.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP033104
Lsh regulates LTR retrotransposon repression independent of Dnmt3b function (RNA-Seq)
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1000

Description

Background: Global DNA methylation contributes to genomic integrity by supressing repeat associated transposition events. Several chromatin factors are required in addition to DNA methyltransferases to maintain DNA methylation at intergenic and satellite repeats. Embryos lacking Lsh, a member of the SNF2 superfamily of chromatin helicases, are hypomethylated. The interaction of Lsh with the de novo methyltransferase, Dnmt3b, facilitates the deposition of DNA methylation at stem cell genes. We wished to determine if a similar targeting mechanism operates to maintain DNA methylation at repetitive sequences. Results: We used HELP-seq to map genome wide DNA methylation patterns in Lsh-/- and Dnmt3b-/- somatic cells. DNA methylation is predominantly lost from specific genomic repeats in Lsh-/- cells: LTR-retrotransposons, LINE-1 repeats and mouse satellites. RNA-seq experiments demonstrate that specific IAP (Intracisternal A-type particle) LTRs and satellites, but not LINE-1 elements, are aberrantly transcribed inLsh-/- cells. LTR hypomethylation in Dnmt3b-/- cells is moderate and hypomethylated repetitive elements (IAP, LINE-1 and satellite) are silent. Chromatin immunoprecipitation (ChIP) indicates that repressed LINE-1 elements gain H3K4me3, but H3K9me3 levels are unaltered in Lsh-/- cells, indicating that DNA hypomethylation alone is not permissive for their transcriptional activation. Mis-expressed IAPs and satellites lose H3K9me3 and gain H3K4me3 in Lsh-/- cells. Conclusions: Our study emphasizes that regulation of repetitive elements by DNA methylation is selective and context dependent. We propose a model where Lsh is specifically required at a precise developmental window to target de novo methylation to repeat sequences, which is subsequently maintained by Dnmt1 in somatic cells to enforce repeat silencing thus contributing to genomic integrity. Overall design: Two pairs of RNA samples compared: WT and Lsh-/- RNA isolations from tail-tip fibroblasts; WT and Lsh-/- RNA isolations from E13.5 mouse embryos.

Publication Title

Lsh regulates LTR retrotransposon repression independently of Dnmt3b function.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP165285
RNA-Seq of WT and constitutively methylated mESCs
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconNextSeq 550

Description

WT J1 and 3B3L cells (in which Dnmt3B and Dnm3L are constitutively expressed from an exogenous construct) were cultured under both serum/LIF and 2i/LIF conditions. 3B3L cells do not show ground state-associated hypomethylation phenotype. This experiment sought to analyse the gene expression changes between the two conditions. Overall design: Three biological replicates per condition J1 serum, J1 2i, 3B3-3l serum, 3B3-3l 2i.

Publication Title

DNA Methylation Directs Polycomb-Dependent 3D Genome Re-organization in Naive Pluripotency.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE44278
Redistribution of H3K27me3 upon DNA hypomethylation results in de-repression of polycomb-target genes
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Redistribution of H3K27me3 upon DNA hypomethylation results in de-repression of Polycomb target genes.

Sample Metadata Fields

Specimen part

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accession-icon SRP002244
Comparing next-generation sequencing and microarray technologies in a toxicological study of the effects of aristolochic Acid on rat kidneys
  • organism-icon Rattus norvegicus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

RNA-Seq has been increasingly used for the quantification and characterization of transcriptomes. The ongoing development of the technology promises the more accurate measurement of gene expression. However, its benefits over widely accepted microarray technologies have not been adequately assessed, especially in toxicogenomics studies. The goal of this study is to enhance the scientific community''s understanding of the advantages and challenges of RNA-Seq in the quantification of gene expression by comparing analysis results from RNA-Seq and microarray data on a toxicogenomics study. A typical toxicogenomics study design was used to compare the performance of an RNA-Seq approach (Illumina Genome Analyzer II) to a microarray-based approach (Affymetrix Rat Genome 230 2.0 arrays) for detecting differentially expressed genes (DEGs) in the kidneys of rats treated with aristolochic acid (AA), a carcinogenic and nephrotoxic chemical most notably used for weight loss. We studied the comparability of the RNA-Seq and microarray data in terms of absolute gene expression, gene expression patterns, differentially expressed genes, and biological interpretation. We found that RNA-Seq was more sensitive in detecting genes with low expression levels, while similar gene expression patterns were observed for both platforms. Moreover, although the overlap of the DEGs was only 40-50%, the biological interpretation was largely consistent between the RNA-Seq and microarray data. RNA-Seq maintained a consistent biological interpretation with time-tested microarray platforms while generating more sensitive results. However, there is clearly a need for future investigations to better understand the advantages and limitations of RNA-Seq in toxicogenomics studies and environmental health research. Overall design: Eight rats were randomly divided into two groups: four rats were administered with aristolochic acid (AA), and four rats were treated with the control vehicle. RNA samples were extracted from the kidney tissue of each rat and were independently assayed with both the NGS (Illumina Genome Analyzer II) and the microarray (Affymetrix Rat Genome 230 2.0) platforms. The RNA-Seq and microarray data were compared in terms of absolute gene expression, gene expression patterns, differentially expressed genes, and biological interpretation.

Publication Title

An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era.

Sample Metadata Fields

No sample metadata fields

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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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