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

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.

Whole exome sequencing of wild-derived inbred strains of mice improves power to link phenotype and genotype

“…To quantify the effect of additional genetic variation on the power to map quantitative trait loci, we simulated two different backcross experiments, started by two different pairs of parental strains: C57BL/6J and DBA/2J, which are the parental strains to the BXD family, a classic recombinant inbred family from which over 5,000 phenotypes have been collected (Wang et al 2016), and DGA and DJO, two Montpellier strains sequenced in this study. We confined the simulation to sites that were covered in all four strains.…”

“…Several important features contribute to their utility, including a high quality reference genome with more than a decade’s worth of improved assembly and annotation (Church et al 2009; Waterston et al 2002), multiple complete genomes from distinct genetic strains (Keane et al 2011; Nikolskiy et al 2015; Srivastava et al 2017; Wang et al 2016; Waterston et al 2002; Wong et al 2012) and wild individuals (Harr et al 2016), and dense genotyping of commonly used laboratory strains (Laurie et al 2007; Lindblad-Toh et al 2000; Petkov et al 2004; Wade et al 2002; Yang et al 2007; Yang et al 2009; Yang et al 2011). Thousands of phenotypes have been gathered from hundreds of inbred mouse strains (Grubb et al 2004; Wang et al 2016; White et al 2013), many of which are commercially available through institutions like The Jackson Laboratory.…”

GeneNetwork: framework for web-based genetics

“…Interactive D3 graphics are included from R/qtlcharts and presentation-ready figures can be generated. Recently we have added functionality for phenotype correlation (Wang et al 2016) and network analysis (Langfelder and Horvath 2008). …”

Reproducibility and replicability of rodent phenotyping in preclinical studies

“…The International Mouse Phenotyping Consortium (IMPC), a community effort for generating and phenotyping mice with targeted knockout mutations, has a long-term goal to knock out most of the ~20,000 mouse genes, and phenotype them on the background of the C57BL/6N mouse genome (Beckers et al, 2009). QTL “forward genetics” and knockout “reverse genetics” strategies are complementary and can increasingly be combined (Williams and Auwerx, 2015; Wang et al, 2016). Understanding phenotypic effects of genes variants is one of the core challenges of personalized medicine: Reference populations provide an excellent and replicable platform for precision experimental medicine.…”