Reference : Systems proteomics of liver mitochondria function.
Scientific journals : Article
Life sciences : Genetics & genetic processes
http://hdl.handle.net/10993/43154
Systems proteomics of liver mitochondria function.
English
Williams, Evan mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Wu, Yibo [> >]
Jha, Pooja [> >]
Dubuis, Sebastien [> >]
Blattmann, Peter [> >]
Argmann, Carmen A. [> >]
Houten, Sander M. [> >]
Amariuta, Tiffany [> >]
Wolski, Witold [> >]
Zamboni, Nicola [> >]
Aebersold, Ruedi [> >]
Auwerx, Johan [> >]
2016
Science (New York, N.Y.)
352
6291
aad0189
Yes (verified by ORBilu)
0036-8075
1095-9203
United States
[en] Animals ; Cholesterol/metabolism ; Diet ; Electron Transport Complex IV/genetics/metabolism ; Genetic Variation ; Hep G2 Cells ; Humans ; Liver/metabolism ; Metabolic Networks and Pathways/genetics ; Metabolome ; Metabolomics ; Mice ; Mice, Inbred Strains ; Mitochondria, Liver/genetics/metabolism ; Molecular Sequence Data ; Proteome ; Proteomics ; Quantitative Trait Loci ; Transcriptome
[en] Recent improvements in quantitative proteomics approaches, including Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH-MS), permit reproducible large-scale protein measurements across diverse cohorts. Together with genomics, transcriptomics, and other technologies, transomic data sets can be generated that permit detailed analyses across broad molecular interaction networks. Here, we examine mitochondrial links to liver metabolism through the genome, transcriptome, proteome, and metabolome of 386 individuals in the BXD mouse reference population. Several links were validated between genetic variants toward transcripts, proteins, metabolites, and phenotypes. Among these, sequence variants in Cox7a2l alter its protein's activity, which in turn leads to downstream differences in mitochondrial supercomplex formation. This data set demonstrates that the proteome can now be quantified comprehensively, serving as a key complement to transcriptomics, genomics, and metabolomics--a combination moving us forward in complex trait analysis.
http://hdl.handle.net/10993/43154
Copyright (c) 2016, American Association for the Advancement of Science.

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