Genome-Wide Association Mapping of Quantitative Traits in Outbred Mice

Abstract

Abstract Recent developments in high-density genotyping and statistical analysis methods that have enabled genome-wide association studies in humans can also be applied to outbred mouse populations. Increased recombination in outbred populations is expected to provide greater mapping resolution than traditional inbred line crosses, improving prospects for identifying the causal genes. We carried out genome-wide association mapping by using 288 mice from a commercially available outbred stock; NMRI mice were genotyped with a high-density single-nucleotide polymorphism array to map loci influencing high-density lipoprotein cholesterol, systolic blood pressure, triglyceride levels, glucose, and urinary albumin-to-creatinine ratios. We found significant associations (P < 10−5) with high-density lipoprotein cholesterol and identified Apoa2 and Scarb1, both of which have been previously reported, as candidate genes for these associations. Additional suggestive associations (P < 10−3) identified in this study were also concordant with published quantitative trait loci, suggesting that we are sampling from a limited pool of genetic diversity that has already been well characterized. These findings dampen our enthusiasm for currently available commercial outbred stocks as genetic mapping resources and highlight the need for new outbred populations with greater genetic diversity. Despite the lack of novel associations in the NMRI population, our analysis strategy illustrates the utility of methods that could be applied to genome-wide association studies in humans.