Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA109261 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Lipoprotein lipase (Lpl) was predicted as a causal gene for abdominal using a novel statistical method named LCMS (Schadt et al., 2005, Nature Genetics). In order to validate this prediction, we profiled the liver tissues of lipoprotein lipase heterozygous knockout mice (Lpl+/-) and their littermate wild-type (wt) controls to examine the gene expression signature as well as pathways/networks resulting from the single gene perturbation. 8 Lpl+/- mice and 8 wt controls were profiled. Reference pool included RNA extracted from the liver of 9 wt control mice. Dye-swap was involved in the profiling.
2009-03-07 | E-GEOD-11991 | biostudies-arrayexpress
Project description:Lipoprotein lipase (Lpl) was predicted as a causal gene for abdominal using a novel statistical method named LCMS (Schadt et al., 2005, Nature Genetics). In order to validate this prediction, we profiled the liver tissues of lipoprotein lipase heterozygous knockout mice (Lpl+/-) and their littermate wild-type (wt) controls to examine the gene expression signature as well as pathways/networks resulting from the single gene perturbation.
2009-03-08 | GSE11991 | GEO
Project 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. This SuperSeries is composed of the following subset Series: GSE11991: Liver gene expression profiling of lipoprotein lipase heterozygous knockout mice GSE11992: Liver gene expression profiling of cytosolic malic enzyme knockout mice GSE11993: Liver gene expression profiling of zinc finger binding protein 90 (Zfp90) transgenic mice GSE11994: Liver gene expression profiling of transforming growth factor beta receptor 2 heterozygous knockout (Tgfbr2+/-) mice GSE11995: Liver gene expression profiling of complement component 3a receptor 1 knockout (C3ar1-/-) mice GSE11996: Gas7 male transgenic liver expression vs FVB male wildtype control GSE11997: Gpx3 male transgenic liver expression vs B6/DBA male wildtype control GSE11998: Gyk female heterozygous liver expression vs C57Bl/6J female wildtype control GSE11999: Lactb male transgenic liver expression vs FVB male wildtype control Refer to individual Series
2009-03-07 | E-GEOD-12000 | biostudies-arrayexpress
Project description:Sigurdsson2010 - Genome-scale metabolic model
of Mus Musculus (iMM1415)
This model is described in the article:
A detailed genome-wide
reconstruction of mouse metabolism based on human Recon 1.
Sigurdsson MI, Jamshidi N,
Steingrimsson E, Thiele I, Palsson BØ.
BMC Syst Biol 2010; 4: 140
Abstract:
BACKGROUND: Well-curated and validated network
reconstructions are extremely valuable tools in systems
biology. Detailed metabolic reconstructions of mammals have
recently emerged, including human reconstructions. They raise
the question if the various successful applications of
microbial reconstructions can be replicated in complex
organisms. RESULTS: We mapped the published, detailed
reconstruction of human metabolism (Recon 1) to other mammals.
By searching for genes homologous to Recon 1 genes within
mammalian genomes, we were able to create draft metabolic
reconstructions of five mammals, including the mouse. Each
draft reconstruction was created in compartmentalized and
non-compartmentalized version via two different approaches.
Using gap-filling algorithms, we were able to produce all
cellular components with three out of four versions of the
mouse metabolic reconstruction. We finalized a functional model
by iterative testing until it passed a predefined set of 260
validation tests. The reconstruction is the largest, most
comprehensive mouse reconstruction to-date, accounting for
1,415 genes coding for 2,212 gene-associated reactions and
1,514 non-gene-associated reactions.We tested the mouse model
for phenotype prediction capabilities. The majority of
predicted essential genes were also essential in vivo. However,
our non-tissue specific model was unable to predict gene
essentiality for many of the metabolic genes shown to be
essential in vivo. Our knockout simulation of the lipoprotein
lipase gene correlated well with experimental results,
suggesting that softer phenotypes can also be simulated.
CONCLUSIONS: We have created a high-quality mouse genome-scale
metabolic reconstruction, iMM1415 (Mus Musculus, 1415 genes).
We demonstrate that the mouse model can be used to perform
phenotype simulations, similar to models of microbe metabolism.
Since the mouse is an important experimental organism, this
model should become an essential tool for studying metabolic
phenotypes in mice, including outcomes from drug screening.
This model is hosted on
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and identified by:
MODEL1507180055.
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2015-07-30 | MODEL1507180055 | BioModels
Project description:Liver gene expression profiling of transforming growth factor beta receptor 2 heterozygous knockout (Tgfbr2+/-) mice
| PRJNA109267 | ENA
Project description:Gene expression data from murine liver samples comparing hormone sensitive lipase (HSL) knockout mice vs. wildtype mice
| PRJNA108173 | ENA
Project description:SILAC based protein correlation profiling using size exclusion of protein complexes derived from Mus musculus tissues (Heart, Liver, Lung, Kidney, Skeletal Muscle, Thymus)
2021-05-05 | PXD022309 | Pride
Project description:SILAC based protein correlation profiling using size exclusion of protein complexes derived from seven Mus musculus tissues (Heart, Brain, Liver, Lung, Kidney, Skeletal Muscle, Thymus)
2018-04-24 | PXD007288 | Pride
Project description:Gene expression profiling of liver-specific NCOR knockout mice
| PRJNA213910 | ENA
Project description:Liver gene expression profiling of cytosolic malic enzyme knockout mice
| PRJNA109263 | ENA