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

• Published in: Nature (London) Vol. 534; no. 7608; pp. 500 - 505
• Main Authors: Chick, Joel M., Munger, Steven C., Simecek, Petr, Huttlin, Edward L., Choi, Kwangbom, Gatti, Daniel M., Raghupathy, Narayanan, Svenson, Karen L., Churchill, Gary A., Gygi, Steven P.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 23.06.2016; Nature Publishing Group
• Subjects: 38/43; 38/91; 631/208/480; 631/45/475; 82/80; Analysis; Animals; Female; Gene loci; Gene mapping; Genetic aspects; Genetic diversity; Genetic engineering; Genetic transcription; Genetic variance; Genetic variation; Genetic Variation - genetics; Genome - genetics; Genomes; Genotype; Humanities and Social Sciences; Liver - metabolism; Male; Mass Spectrometry; Metabolism; Mice; Models, Genetic; multidisciplinary; Mutation; Observations; Principal components analysis; Protein expression; Protein Interaction Maps; Protein-protein interactions; Proteins; Proteome - analysis; Proteome - biosynthesis; Proteome - genetics; Proteomics; Quantitative trait loci; Quantitative Trait Loci - genetics; RNA, Messenger - analysis; RNA, Messenger - genetics; Rodents; Science; Studies; Transcriptome - genetics; United States
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/nature18270

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. The effect of natural genetic diversity on the proteome is characterized using an outbred mouse model with extensive variation; both transcripts and proteins from mouse livers are quantified to identify a large set of protein quantitative trait loci (pQTL), and mediation analysis identifies causal protein intermediates of distant pQTL. Natural genetic diversity and the proteome The investigation of how genetic variation governs gene expression has so far focused mainly on quantifying the impact on RNA transcripts. These authors have focused on protein and transcript abundance in a genetically diverse population of mice. In a proteome-wide analysis, they quantify transcripts and proteins from mouse livers and identify a large set of protein-level quantitative trait loci (pQTL). Mediation analysis identifies causal protein intermediates underlying distant pQTL, and hundreds of protein–protein associations.