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Nat Commun. 2016 Feb 2;7:10464. doi: 10.1038/ncomms10464.

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

Author information

1
Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA.
2
St Jude Proteomics Facility, St Jude Children's Research Hospital, Memphis, Tennessee 38105, USA.
3
Laboratory of Integrative and Systems Physiology, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
4
Department of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA.
5
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA.
6
Department of Human Genetics, University of California, Los Angeles, California 90095, USA.
7
Molecular Resource Center, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA.
8
Gladstone Institutes, San Francisco, California 94158, USA.
9
Division of Biostatistics and Institute for Human Genetics, University of California, San Francisco, California 94158, USA.
10
Animal Science Department, University of Nebraska, Lincoln, Nebraska 68583, USA.
11
Joint Institute for Computational Sciences, University of Tennessee-Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA.
12
Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA.

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.

PMID:
26833085
PMCID:
PMC4740880
DOI:
10.1038/ncomms10464
[Indexed for MEDLINE]
Free PMC Article
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