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Genetic regulation of mouse liver metabolite levels

We profiled and analyzed 283 metabolites representing eight major classes of molecules including Lipids, Carbohydrates, Amino Acids, Peptides, Xenobiotics, Vitamins and Cofactors, Energy Metabolism, and Nucleotides in mouse liver of 104 inbred and recombinant inbred strains. We find that metabolites...

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Detalles Bibliográficos
Autores principales: Ghazalpour, Anatole, Bennett, Brian J, Shih, Diana, Che, Nam, Orozco, Luz, Pan, Calvin, Hagopian, Raffi, He, Aiqing, Kayne, Paul, Yang, Wen‐pin, Kirchgessner, Todd, Lusis, Aldons J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: European Molecular Biology Organization 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4188043/
https://www.ncbi.nlm.nih.gov/pubmed/24860088
http://dx.doi.org/10.15252/msb.20135004
Descripción
Sumario:We profiled and analyzed 283 metabolites representing eight major classes of molecules including Lipids, Carbohydrates, Amino Acids, Peptides, Xenobiotics, Vitamins and Cofactors, Energy Metabolism, and Nucleotides in mouse liver of 104 inbred and recombinant inbred strains. We find that metabolites exhibit a wide range of variation, as has been previously observed with metabolites in blood serum. Using genome‐wide association analysis, we mapped 40% of the quantified metabolites to at least one locus in the genome and for 75% of the loci mapped we identified at least one candidate gene by local expression QTL analysis of the transcripts. Moreover, we validated 2 of 3 of the significant loci examined by adenoviral overexpression of the genes in mice. In our GWAS results, we find that at significant loci the peak markers explained on average between 20 and 40% of variation in the metabolites. Moreover, 39% of loci found to be regulating liver metabolites in mice were also found in human GWAS results for serum metabolites, providing support for similarity in genetic regulation of metabolites between mice and human. We also integrated the metabolomic data with transcriptomic and clinical phenotypic data to evaluate the extent of co‐variation across various biological scales.