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GSE2665
Homo sapiens
19 Downloadable Samples
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- Rattus norvegicus
- 72 Downloadable Samples
- 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- Rattus norvegicus
- 8 Downloadable Samples
- 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- Mus musculus
- 7 Downloadable Samples
- 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- Mus musculus
- 48 Downloadable Samples
Sentrix 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- Mus musculus
- 16 Downloadable Samples
- Sentrix 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- Mus musculus
- 14 Downloadable Samples
- Sentrix 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- Mus musculus
- 10 Downloadable Samples
- Sentrix 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- Mus musculus
- 8 Downloadable Samples
- Sentrix 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- Mus musculus
- 46 Downloadable Samples
- 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