refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 17 results
Sort by

Filters

Technology

Platform

accession-icon GSE33785
Gene expression in the chronic ethanol-treated rat liver during liver regeneration
  • organism-icon Rattus norvegicus
  • sample-icon 72 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

In this study, we analyzed the effects of chronic alcohol consumption on liver repair and regeneration after partial hepatectomy (PHx). Rats were fed a liquid diet containing 36% of total calories derived from ethanol for 5 weeks; corresponding pair-fed calorie-matched controls were fed diets in which ethanol calories were replaced either by carbohydrate or by fat. After 5 weeks, rats were subjected to 70% PHx and liver samples were collected at 1, 6 and 24h after the surgery. The excised liver samples at t=0 served as within-animal controls. We used Affymetrix Rat Gene 1.0 ST arrays to obtain global gene expression data from each liver sample (n=4 replicate rats, 72 arrays total).

Publication Title

Chronic ethanol feeding enhances miR-21 induction during liver regeneration while inhibiting proliferation in rats.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE67242
Analysis of the role of miR-21 in liver regeneration after partial hepatectomy (PHx) in chronic ethanol-treated rats through in vivo inhibition using LNAs
  • organism-icon Rattus norvegicus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 2.0 ST Array (ragene20st)

Description

In this study, we analyzed the role of miR-21 in liver regeneration after partial hepatectomy (PHx) in chronic ethanol-treated rats. Male Sprague-Dawley rats were fed a liquid diet containing 36% of total calories derived from ethanol for 5 weeks; corresponding pair-fed calorie-matched controls were fed diets in which ethanol calories were replaced by carbohydrate. After 5 weeks, locked nucleic acid (LNA)-modified oligo antisense to miR-21 (AM21, Exiqon, Vedbaek, Denmark) was used to inhibit miRNA in vivo, and rats were subjected to 70% PHx. Liver samples were collected at 24h after the surgery. The excised liver samples at t=0 served as within-animal controls. Rat Gene 2.0 ST (Affymetrix, Santa Clara, CA) arrayswere used to obtain global gene expression data from pooled liver samples (pools of 3 or 4 biological replicates/array, total 8 arrays).

Publication Title

Inhibition of miR-21 rescues liver regeneration after partial hepatectomy in ethanol-fed rats.

Sample Metadata Fields

Sex, Specimen part, Treatment, Time

View Samples
accession-icon GSE2665
Lymphe node vs. Tonsil
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Lymph node vs. tonsil

Publication Title

Differential expression of a gene signature for scavenger/lectin receptors by endothelial cells and macrophages in human lymph node sinuses, the primary sites of regional metastasis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE12748
Weighted Gene Coexpression Network Analysis Identifies Biomarkers in Glycerol Kinase Deficient Mice
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Symptomatic glycerol kinase deficiency (GKD) is associated with episodic metabolic and central nervous system deterioration. We report here the first application of Weighted Gene Co-Expression Network Analysis (WGCNA) to investigate a knockout (KO) murine model of a human genetic disease. WGCNA identified networks and key hub transcripts from liver mRNA of glycerol kinase (Gyk) KO and wild type (WT) mice. Day of life 1 (dol1) samples from KO mice contained a network module enriched for organic acid metabolism before Gyk KO mice develop organic acidemia and die on dol3-4 and the module containing Gyk was enriched with apoptotic genes. Roles for the highly connected Acot, Psat and Plk3 transcripts were confirmed in cell cultures and subsequently validated by causality testing. We provide evidence that GK may have an apoptotic moonlighting role that is lost in GKD. This systems biology strategy has improved our understanding of GKD pathogenesis and suggests possible treatments.

Publication Title

Weighted gene co-expression network analysis identifies biomarkers in glycerol kinase deficient mice.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE23006
Transcriptional profiling of a wound healing process in skin and oral mucosa
  • organism-icon Mus musculus
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

When compared to skin, oral mucosal wounds heal rapidly and with reduced scar formation. This study used an Affymetrix microarray platform to compare the transcriptomes of oral mucosa and skin wounds in order to identify critical differences in the healing response at these two sites.

Publication Title

Positional differences in the wound transcriptome of skin and oral mucosa.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon SRP055930
Alteration in the transcriptome of the lung during TGFa-induced pulmonary fibrosis
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1000

Description

Pulmonary fibrosis (PF) is associated with many chronic lung diseases including Systemic sclerosis (SSc), Idiopathic Pulmonary Fibrosis (IPF) and Cystic Fibrosis (CF) which are characterized by the progressive accumulation of stromal cells and formation of scar tissue. Pulmonary fibrosis is a dysregulated response to alveolar injury which causes a progressive decline in lung function and refractory to current pharmacological therapies. Airway and alveolar epithelial cells and stromal cells contribute to pulmonary fibrosis but the cell-specific pathways and gene networks that are responsible for the pathophysiology are unknown. Recent animals models generated in our lab demonstrate clinical phenotypes seen in human fibrotic disease. The mouse model of transforming growth factor-a (TGFa)-induced fibrosis include conditionally expressing TGFa in the lung epithelium under control of the CCSP promoter driving rtTA expression (CCSP/TGFa). This allow the TGFa is only expressed in airway and alveolar epithelial cells and only when mice fed doxycycline (Dox). Similar to PF in humans, TGFa mice on Dox developed a progressive and extensive adventitial, interstitial and pleural fibrosis with a decline in lung mechanics. Thus, the TGFa transgenic mouse is a powerful model to determine lung cell-specific molecular signatures involved in pulmonary fibrosis. In this study, we sought to determine changes in the transcriptome during TGFa-induced pulmonary fibrosis. Our results showed that several pro-fibrotic genes increased in the lungs of TGFa mice. This study demonstrates that WT1 network gene changes associated with fibrosis and myfibroblast accumulation and thus may serve as a critical regulator fibrotic lung disease. Overall design: mRNA profiles of CCSP/- and CCSP/TGFalpha mice treated with Dox

Publication Title

Fibrocytes Regulate Wilms Tumor 1-Positive Cell Accumulation in Severe Fibrotic Lung Disease.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE12000
Obesity study in transgenic and knockout animals
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge IconSentrix MouseRef-8 Expression BeadChip (Target ID), Rosetta/Merck Mouse TOE 75k Array 1 microarray

Description

A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.

Publication Title

Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE11999
Lactb male transgenic liver expression vs FVB male wildtype control
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconSentrix MouseRef-8 Expression BeadChip (Target ID)

Description

A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.

Publication Title

Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE11996
Gas7 male transgenic liver expression vs FVB male wildtype control
  • organism-icon Mus musculus
  • sample-icon 14 Downloadable Samples
  • Technology Badge IconSentrix MouseRef-8 Expression BeadChip (Target ID)

Description

A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.

Publication Title

Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE11998
Gyk female heterozygous liver expression vs C57Bl/6J female wildtype control
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconSentrix MouseRef-8 Expression BeadChip (Target ID)

Description

A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.

Publication Title

Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.

Sample Metadata Fields

No sample metadata fields

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