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

Xusheng Wang, Ashutosh K. Pandey, Megan Mulligan, Evan G. Williams, Khyobeni Mozhui, Zhengsheng Li, Virginija Jovaisaite, Leigh 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. Zhulin & 6 others Junmin Peng, Stanley F. Nelson, Joshua C. Denny, Johan Auwerx, Lu Lu, Robert Williams

Research output: Contribution to journalArticle

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Abstract

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 (www.genenetwork.org). 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
Volume7
DOIs
StatePublished - Feb 2 2016

Fingerprint

genes
mice
Genes
Fumarate Hydratase
Missense Mutation
mutations
Proteome
proteome
Metagenome
Minerals
Unfolded Protein Response
Reverse Genetics
Bone
Metabolome
genome
Quantitative Trait Loci
Mitochondrial Proteins
Caenorhabditis elegans
loci
Transcriptome

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)

Cite this

Joint mouse-human phenome-wide association to test gene function and disease risk. / Wang, Xusheng; Pandey, Ashutosh K.; Mulligan, Megan; Williams, Evan G.; Mozhui, Khyobeni; Li, Zhengsheng; Jovaisaite, Virginija; Quarles, Leigh; Xiao, Zhousheng; Huang, Jinsong; Capra, John A.; Chen, Zugen; Taylor, William L.; Bastarache, Lisa; Niu, Xinnan; Pollard, Katherine S.; Ciobanu, Daniel C.; Reznik, Alexander O.; Tishkov, Artem V.; Zhulin, Igor B.; Peng, Junmin; Nelson, Stanley F.; Denny, Joshua C.; Auwerx, Johan; Lu, Lu; Williams, Robert.

In: Nature Communications, Vol. 7, 10464, 02.02.2016.

Research output: Contribution to journalArticle

Wang, X, Pandey, AK, Mulligan, M, Williams, EG, Mozhui, K, Li, Z, Jovaisaite, V, Quarles, L, Xiao, Z, Huang, J, Capra, JA, Chen, Z, Taylor, WL, Bastarache, L, Niu, X, Pollard, KS, Ciobanu, DC, Reznik, AO, Tishkov, AV, Zhulin, IB, Peng, J, Nelson, SF, Denny, JC, Auwerx, J, Lu, L & Williams, R 2016, 'Joint mouse-human phenome-wide association to test gene function and disease risk', Nature Communications, vol. 7, 10464. https://doi.org/10.1038/ncomms10464
Wang, Xusheng ; Pandey, Ashutosh K. ; Mulligan, Megan ; Williams, Evan G. ; Mozhui, Khyobeni ; Li, Zhengsheng ; Jovaisaite, Virginija ; Quarles, Leigh ; Xiao, Zhousheng ; Huang, Jinsong ; Capra, John A. ; Chen, Zugen ; Taylor, William L. ; Bastarache, Lisa ; Niu, Xinnan ; Pollard, Katherine S. ; Ciobanu, Daniel C. ; Reznik, Alexander O. ; Tishkov, Artem V. ; Zhulin, Igor B. ; Peng, Junmin ; Nelson, Stanley F. ; Denny, Joshua C. ; Auwerx, Johan ; Lu, Lu ; Williams, Robert. / Joint mouse-human phenome-wide association to test gene function and disease risk. In: Nature Communications. 2016 ; Vol. 7.
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