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GSE30140
Mus musculus
424 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
In several models of obesity-induced diabetes, increased lipid accumulation in the liver has been associated with decreased diabetes susceptibility. For instance, deficiency in leptin receptor (db/db) leads to hyperphagia and obesity in both C57BL/6 and C57BLKS mice but, only on the C57BLKS background do the mice develop beta-cell loss leading to severe diabetes while C57BL/6 mice are relatively resistant. Liver triglyceride levels in the resistant C57BL/6 mice are 3 to 4 fold higher than in C57BLKS.
Publication Title
Systems genetics of susceptibility to obesity-induced diabetes in mice.
Sample Metadata Fields
Sex, Age
View Samples- Homo sapiens
- 50 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Comparative transcriptome analysis of human skeletal muscle in response to cold acclimation and exercise training in human volunteers.
Sample Metadata Fields
Sex, Disease, Subject, Time
View Samples- Homo sapiens
- 36 Downloadable Samples
Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
Background: Cold acclimation and exercise training were previously shown to increase peripheral insulin sensitivity in human volunteers with type 2 diabetes. Although cold is a potent activator of brown adipose tissue, the increase in peripheral insulin sensitivity by cold is largely mediated by events occurring in skeletal muscle and at least partly involves GLUT4 translocation, as is also observed for exercise training. Results: To investigate if cold acclimation and exercise training overlap in the molecular adaptive response in skeletal muscle, we performed transcriptomics analysis on vastus lateralis muscle collected from human subjects before and after 10 days of cold acclimation, as well as before and after a 12-week exercise training intervention. Methods: Cold acclimation altered the expression of 756 genes (422 up, 334 down, P<0.01), while exercise training altered the expression of 665 genes (444 up, 221 down, P<0.01). Principal Component Analysis, Venn diagram, similarity analysis and Rank–rank Hypergeometric Overlap all indicated significant overlap between cold acclimation and exercise training in upregulated genes, but not in downregulated genes. Overlapping gene regulation was especially evident for genes and pathways associated with extracellular matrix remodeling. Interestingly, the genes most highly induced by cold acclimation were involved in contraction and in signal transduction between nerve and muscle cells, while no significant changes were observed in genes and pathways related to insulin signaling or glucose metabolism. Conclusions: Overall, our results indicate that cold acclimation and exercise training have overlapping effects on gene expression in human skeletal muscle, but strikingly these overlapping genes are designated to pathways related to cell remodeling rather than metabolic pathways.
Publication Title
Comparative transcriptome analysis of human skeletal muscle in response to cold acclimation and exercise training in human volunteers.
Sample Metadata Fields
Sex, Disease, Subject, Time
View Samples- Homo sapiens
- 14 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
Background: Cold acclimation and exercise training were previously shown to increase peripheral insulin sensitivity in human volunteers with type 2 diabetes. Although cold is a potent activator of brown adipose tissue, the increase in peripheral insulin sensitivity by cold is largely mediated by events occurring in skeletal muscle and at least partly involves GLUT4 translocation, as is also observed for exercise training. Results: To investigate if cold acclimation and exercise training overlap in the molecular adaptive response in skeletal muscle, we performed transcriptomics analysis on vastus lateralis muscle collected from human subjects before and after 10 days of cold acclimation, as well as before and after a 12-week exercise training intervention. Methods: Cold acclimation altered the expression of 756 genes (422 up, 334 down, P<0.01), while exercise training altered the expression of 665 genes (444 up, 221 down, P<0.01). Principal Component Analysis, Venn diagram, similarity analysis and Rank–rank Hypergeometric Overlap all indicated significant overlap between cold acclimation and exercise training in upregulated genes, but not in downregulated genes. Overlapping gene regulation was especially evident for genes and pathways associated with extracellular matrix remodeling. Interestingly, the genes most highly induced by cold acclimation were involved in contraction and in signal transduction between nerve and muscle cells, while no significant changes were observed in genes and pathways related to insulin signaling or glucose metabolism. Conclusions: Overall, our results indicate that cold acclimation and exercise training have overlapping effects on gene expression in human skeletal muscle, but strikingly these overlapping genes are designated to pathways related to cell remodeling rather than metabolic pathways.
Publication Title
Comparative transcriptome analysis of human skeletal muscle in response to cold acclimation and exercise training in human volunteers.
Sample Metadata Fields
Sex, Disease, Subject, Time
View Samples- Mus musculus
- 23 Downloadable Samples
Illumina HiSeq 2000, NextSeq 500
Description
Local mRNA translation mediates the adaptive responses of axons to extrinsic signals but direct evidence that it occurs in mammalian CNS axons in vivo is scant. We developed an axon-TRAP-RiboTag approach in mouse that allows deep-sequencing analysis of ribosome-bound mRNAs in the retinal ganglion cell axons of the developing and adult retinotectal projection in vivo. The embryonic-to-postnatal axonal translatome comprises an evolving subset of enriched genes with axon-specific roles suggesting distinct steps in axon wiring, such as elongation, pruning and synaptogenesis. Adult axons, remarkably, have a complex translatome with strong links to axon survival, neurotransmission and neurodegenerative disease. Translationally co-regulated mRNA subsets share common upstream regulators, and novel sequence elements generated by alternative splicing that promote axonal mRNA translation. Our results indicate that intricate regulation of compartment-specific mRNA translation in mammalian CNS axons supports the formation and maintenance of neural circuits in vivo. Overall design: The profiling of ribosome-bound mRNAs in mouse retinal ganglion cell axons at 4 different developmental stages
Publication Title
On-Site Ribosome Remodeling by Locally Synthesized Ribosomal Proteins in Axons.
Sample Metadata Fields
Cell line, Subject
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