Defining the consequences of genetic variation on a proteome-wide scale

Joel M. Chick, Steven C. Munger, Petr Simecek, Edward L. Huttlin, Kwangbom Choi, Daniel M. Gatti, Narayanan Raghupathy, Karen L. Svenson, Gary A. Churchill () and Steven P. Gygi ()
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Joel M. Chick: Harvard Medical School
Steven C. Munger: The Jackson Laboratory
Petr Simecek: The Jackson Laboratory
Edward L. Huttlin: Harvard Medical School
Kwangbom Choi: The Jackson Laboratory
Daniel M. Gatti: The Jackson Laboratory
Narayanan Raghupathy: The Jackson Laboratory
Karen L. Svenson: The Jackson Laboratory
Gary A. Churchill: The Jackson Laboratory
Steven P. Gygi: Harvard Medical School

Nature, 2016, vol. 534, issue 7608, 500-505

Abstract: Abstract Genetic variation modulates protein expression through both transcriptional and post-transcriptional mechanisms. To characterize the consequences of natural genetic diversity on the proteome, here we combine a multiplexed, mass spectrometry-based method for protein quantification with an emerging outbred mouse model containing extensive genetic variation from eight inbred founder strains. By measuring genome-wide transcript and protein expression in livers from 192 Diversity outbred mice, we identify 2,866 protein quantitative trait loci (pQTL) with twice as many local as distant genetic variants. These data support distinct transcriptional and post-transcriptional models underlying the observed pQTL effects. Using a sensitive approach to mediation analysis, we often identified a second protein or transcript as the causal mediator of distant pQTL. Our analysis reveals an extensive network of direct protein–protein interactions. Finally, we show that local genotype can provide accurate predictions of protein abundance in an independent cohort of collaborative cross mice.

Date: 2016
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DOI: 10.1038/nature18270

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