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

Authors :
Jinsong Huang
Artem Tishkov
Virginija Jovaisaite
Katherine S. Pollard
Robert W. Williams
Ashutosh K. Pandey
John A. Capra
Lu Lu
Megan K. Mulligan
Johan Auwerx
Zugen Chen
William L. Taylor
Junmin Peng
Khyobeni Mozhui
Lisa Bastarache
L. Darryl Quarles
Daniel C. Ciobanu
Z. Li
Evan G. Williams
Alexander O. Reznik
Joshua C. Denny
Xinnan Niu
Zhousheng Xiao
Stanley F. Nelson
Xusheng Wang
Igor B. Zhulin
Source :
Nature Communications, Vol 7, Iss 1, Pp 1-13 (2016), Nature Communications
Publication Year :
2016
Publisher :
Nature Portfolio, 2016.

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.<br />Phenome-wide association is a novel method that links sequence variants to a spectrum of phenotypes and diseases. Here the authors generate detailed mouse genetic and phenome data which links their phenome-wide association study (PheWAS) of mouse to corresponding PheWAS in human.

Details

Language :
English
ISSN :
20411723
Volume :
7
Issue :
1
Database :
OpenAIRE
Journal :
Nature Communications
Accession number :
edsair.doi.dedup.....e441e39e3468521968728a2ee56848fe