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).
Chronic ethanol feeding enhances miR-21 induction during liver regeneration while inhibiting proliferation in rats.
Specimen part, Time
View SamplesIn 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).
Inhibition of miR-21 rescues liver regeneration after partial hepatectomy in ethanol-fed rats.
Sex, Specimen part, Treatment, Time
View SamplesLymph node vs. tonsil
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.
No sample metadata fields
View SamplesSymptomatic 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.
Weighted gene co-expression network analysis identifies biomarkers in glycerol kinase deficient mice.
Sex, Specimen part
View SamplesWhen 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.
Positional differences in the wound transcriptome of skin and oral mucosa.
Sex, Specimen part
View SamplesPulmonary 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
Fibrocytes Regulate Wilms Tumor 1-Positive Cell Accumulation in Severe Fibrotic Lung Disease.
No sample metadata fields
View SamplesA 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.
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
No sample metadata fields
View SamplesA 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.
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
No sample metadata fields
View SamplesA 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.
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
No sample metadata fields
View SamplesA 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.
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
No sample metadata fields
View Samples