Multilayered genetic and omics dissection of mitochondrial activity in a mouse reference population

The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study, we quantified the transcriptome--a subset of the metabolome--and, using targeted proteomics, quantified a subset of the liver proteome from 40 strains of the BXD mous...

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Published in:Cell 2014-09, Vol.158 (6), p.1415-1430
Main Authors: Wu, Yibo, Williams, Evan G, Dubuis, Sébastien, Mottis, Adrienne, Jovaisaite, Virginija, Houten, Sander M, Argmann, Carmen A, Faridi, Pouya, Wolski, Witold, Kutalik, Zoltán, Zamboni, Nicola, Auwerx, Johan, Aebersold, Ruedi
Format: Article
Language:English
Subjects:
Animals
Gene Expression Profiling
Glucose - metabolism
Humans
Ketone Oxidoreductases - metabolism
Liver - chemistry
Liver - cytology
Liver - metabolism
Mice - classification
Mice - genetics
Mice - metabolism
Mice, Inbred C57BL
Mice, Inbred DBA
Mitochondria - chemistry
Mitochondria - metabolism
Proteome - analysis
Quantitative Trait Loci
Serum - chemistry
Serum - metabolism
Unfolded Protein Response
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Summary:The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study, we quantified the transcriptome--a subset of the metabolome--and, using targeted proteomics, quantified a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein, and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. These integrated molecular profiles also allowed further characterization of complex pathways, particularly the mitochondrial unfolded protein response (UPR(mt)). UPR(mt) shows strikingly variant responses at the transcript and protein level that are remarkably conserved among C. elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
ISSN:0092-8674
1097-4172
DOI:10.1016/j.cell.2014.07.039