refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 231 results
Sort by

Filters

Technology

Platform

accession-icon SRP058766
Histone H3K36M mutation impairs mesenchymal differentiation and drives sarcoma development [RNA_H33_K36M_HMT]
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The goal of this study is to understand the alterations in transcriptome induced by histone H3K36M mutations Overall design: Transcritome profiling of 3 cell lines cultured in vitro and 6 murine tumors

Publication Title

Histone H3K36 mutations promote sarcomagenesis through altered histone methylation landscape.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP065840
Genetic Diversity Through RNA Editing: Apobec1-mediated RNA editing in bulk and single cell macrophages and dendritic cells
  • organism-icon Mus musculus
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

RNA editing is a mutational mechanism that specifically alters the nucleotide content in sets of transcripts while leaving their cognate genomic blueprint intact. Editing has been detected from bulk RNA-seq data in thousands of distinct transcripts, but apparent editing rates can vary widely (from under 1% to almost 100%). These observed editing rates could result from approximately equal rates of editing within each individual cell in the bulk sample, or alternatively, editing estimates from a population of cells could reflect an average of distinct, biologically significant editing signatures that vary substantially between individual cells in the population. To distinguish between these two possibilities we have constructed a hierarchical Bayesian model which quantifies the variance of editing rates at specific sites using RNA-seq data from both single cells and a cognate bulk sample consisting of ~ 106 cells. The model was applied to data from murine bone-marrow derived macrophages and dendritic cells, and predicted high variance for specific edited sites in both cell types tested. We then 1 validated these predictions using targeted amplification of specific editable transcripts from individual macrophages. Our data demonstrate substantial variance in editing signatures between single cells, supporting the notion that RNA editing generates diversity within cellular populations. Such editing-mediated RNA-level sequence diversity could contribute to the functional heterogeneity apparent in cells of the innate immune system. Overall design: 26 samples were subjected to RNA-seq: 24 single WT macrophages, and 2 bulk samples (Apobec1 WT and KO macrophages), consisting of 500,000-1 million cells each.

Publication Title

RNA editing generates cellular subsets with diverse sequence within populations.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon E-MEXP-1287
Transcription profiling by array of Drosophila melanogaster inoculated with P.aeruginosa or mechanically injured to investigate the skeletal muscle regulatory network in response to wound infection following trauma
  • organism-icon Drosophila melanogaster
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome Array (drosgenome1)

Description

Effect of injury and Pseudomonas aeruginosa inoculation in Drosophila melanogaster

Publication Title

Involvement of skeletal muscle gene regulatory network in susceptibility to wound infection following trauma.

Sample Metadata Fields

Sex, Time

View Samples
accession-icon GSE17119
Transcriptional profiling of a novel pro-angiogenic small molecule phthalimide neovascular factor 1 (PNF1)
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We generated the transcriptional regulatory footprint of phthalimide neovascular factor 1 (PNF1)a novel synthetic small molecule that exhibits significant in vitro endothelial potency and significant in vivo microvascular network expansionby performing comparative microarray analysis on PNF1-stimulated (versus control) human microvascular endothelial cells (HMVEC) spanning 1-48 h post-supplementation. We subsequently applied network analysis tools (including substantial libraries of information regarding known associations among network components) to elucidate key signaling components and pathways involved in the PNF1 mechanism-of-action. We identified that PNF1 first induces function of the tumor necrosis factor-alpha (TNF-) signaling pathway, which in turn affects transforming growth factor-beta (TGF-) signaling.

Publication Title

Mechanistic exploration of phthalimide neovascular factor 1 using network analysis tools.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE59485
Expression data from bovine nucleus pulposus interverteral disc cells
  • organism-icon Bos taurus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Bovine Genome Array (bovine)

Description

Assessment of the putative differential gene expression profiles in high osmolality-treated bovine nucleus pulposus intervertebral disc cells for a short (5 h) and a long (24 h) time period. Identification of novel genes up- or down-regulated as an early or a late response to hyperosmotic stress.

Publication Title

Deficiency in the α1 subunit of Na+/K+-ATPase enhances the anti-proliferative effect of high osmolality in nucleus pulposus intervertebral disc cells.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE22122
Phosphoglycerate mutase knock-out mutant Saccharomyces cerevisiae: physiological investigation and transcriptome analysis
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

Characterize the gpm1 mutant growth on dual substrate of ethanol and glycerol

Publication Title

Phosphoglycerate mutase knock-out mutant Saccharomyces cerevisiae: physiological investigation and transcriptome analysis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE139601
Transcriptomic profiling of the white adipose tissue (WAT) in ApoE3L.CETP mice fed a high fat diet (HFD) or a low fat diet (LFD) for three different time periods, or chow diet at baseline
  • organism-icon Mus musculus
  • sample-icon 25 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The metabolic syndrome (MetS) is characterized by the presence of metabolic abnormalities that include abdominal obesity, dyslipidemia, hypertension, increased blood glucose/insulin resistance, hypertriglyceridemia and increased risk for cardiovascular disease (CVD). The ApoE*3Leiden.human Cholesteryl Ester Transfer Protein (ApoE3L.CETP) mouse model manifests several features of the MetS upon high fat diet (HFD) feeding. Moreover, the physiological changes in the white adipose tissue (WAT) contribute to MetS comorbidities. The aim of this study was to identify transcriptomic signatures in the gonadal WAT of ApoE3L.CETP mice in discrete stages of diet-induced MetS.

Publication Title

Transcriptome analysis of the adipose tissue in a mouse model of metabolic syndrome identifies gene signatures related to disease pathogenesis.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE44091
Genome-wide expression of the epithelial layer cells of mice injected with Clostridium difficile Toxin A and B
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Toxin A (TcdA) and Toxin B (TcdB), of the pathogen Clostridium difficile, are virulence factors that cause gross pathologic changes (e.g. inflammation, secretion, and diarrhea) in the infected host, yet the molecular and cellular pathways leading to observed host responses are poorly understood. To address this gap, TcdA and/or TcdB were injected into the ceca of mice and the genome-wide transcriptional response of epithelial layer cells was examined. Bioinformatic analysis of gene expression identified sets of cooperatively expressed genes. Further analysis of inflammation associated genes revealed dynamic chemokine responses.

Publication Title

In vivo physiological and transcriptional profiling reveals host responses to Clostridium difficile toxin A and toxin B.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP078332
H3.3 depletion has a mild effect on the global transcriptome
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Transcriptomic analysis of H3.3 KO/Kd mouse embryonic fibroblasts (MEFs) Overall design: We isolated total RNA from control shRNA treated or shH3.3A treated H3.3B KO MEFs and carried out Ribozero RNA-seq analysis. RNA-seq analysis was carried out on pooled datasets from biological duplicate experiments.

Publication Title

Histone H3.3 regulates mitotic progression in mouse embryonic fibroblasts.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon GSE29008
Human colon epithelial cells treated with Clostridium difficile Toxins A and B
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Toxin A and B from Clostridium difficile are the primary virulence factors in Clostridium difficile disease. The changes in gene transcription of human colon epithelial cells were investigated in vitro in order to better understand the many effects of both toxins.

Publication Title

Systems analysis of the transcriptional response of human ileocecal epithelial cells to Clostridium difficile toxins and effects on cell cycle control.

Sample Metadata Fields

Cell line

View Samples
...

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

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact