Joint mouse-human phenome-wide association to test gene function and disease risk

Xusheng Wang, Ashutosh K. Pandey, Megan K. Mulligan, Evan G. Williams, Khyobeni Mozhui, Zhengsheng Li, Virginija Jovaisaite, L. Darryl Quarles, Zhousheng Xiao, Jinsong Huang, John A. Capra, Zugen Chen, William L. Taylor, Lisa Bastarache, Xinnan Niu, Katherine S. Pollard, Daniel C. Ciobanu, Alexander O. Reznik, Artem V. Tishkov, Igor B. ZhulinJunmin Peng, Stanley F. Nelson, Joshua C. Denny, Johan Auwerx, Lu Lu, Robert W. Williams

Research output: Contribution to journalArticlepeer-review

113 Scopus citations


Phenome-wide association is a novel reverse genetic strategy to analyze genome-to-phenome relations in human clinical cohorts. Here we test this approach using a large murine population segregating for ∼5 million sequence variants, and we compare our results to those extracted from a matched analysis of gene variants in a large human cohort. For the mouse cohort, we amassed a deep and broad open-access phenome consisting of ∼4,500 metabolic, physiological, pharmacological and behavioural traits, and more than 90 independent expression quantitative trait locus (QTL), transcriptome, proteome, metagenome and metabolome data sets - by far the largest coherent phenome for any experimental cohort ( We tested downstream effects of subsets of variants and discovered several novel associations, including a missense mutation in fumarate hydratase that controls variation in the mitochondrial unfolded protein response in both mouse and Caenorhabditis elegans, and missense mutations in Col6a5 that underlies variation in bone mineral density in both mouse and human.

Original languageEnglish (US)
Article number10464
JournalNature communications
StatePublished - Feb 2 2016

ASJC Scopus subject areas

  • General Chemistry
  • General Biochemistry, Genetics and Molecular Biology
  • General Physics and Astronomy


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