Genome-wide Association Mapping of Quantitative Traits in Outbred Mice

The 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 higher mapping resolution compared to traditional inbred line crosses, improving prospects for the identification of causal genes. We have carried out genome-wide association mapping using 288 outbred NMRI mice genotyped with a high-density single-nucleotide polymorphism array to map loci influencing high-density lipoprotein (HDL) cholesterol, systolic blood pressure, triglyceride levels, plasma glucose, and urinary albumin-to-creatinine ratios. We found significant associations (P< 10-5) with HDL cholesterol and have identified Apoa2 and Scarb1, both of which have been previously reported, as candidate genes for these associations. Additional associations (P< 10-3) were identified for the other traits. Although, none of these achieved genome-wide significance, most were found to be concordant with published quantitative trait loci (QTL) from inbred strain studies. These findings suggest that we are sampling from a limited pool of genetic diversity that has already been well characterized. Outbred mouse populations have both similarities and differences with human studies. Our analysis illustrates the utility of multi-locus modeling in association mapping and the analytical methods described here could be applied to genome-wide association studies for both mice and humans