A comprehensive mouse IBD database for the efficient localization of quantitative trait loci

Abstract

Traditional fine-mapping approaches in mouse genetics that go from a linkage region to a candidate gene are very costly and time consuming. Shared ancestry regions, along with the combination of genetics and genomics approaches, provide a powerful tool to shorten the time and effort required to identify a causative gene. In this article we present a novel methodology that predicts IBD (identical by descent) regions between pairs of inbred strains using single nucleotide polymorphism (SNP) maps. We have validated this approach by comparing the IBD regions, estimated using different algorithms, to the results derived using the sequence information in the strains present in the Celera Mouse Database. We showed that based on the current publicly available SNP genotypes, large IBD regions (>1 Mb) can be identified successfully. By assembling a list of 21,514 SNPs in 61 common inbred strains, we inferred IBD regions between all pairs of strains and confirmed, for the first time, that existing quantitative trait genes (QTG) and susceptibility genes all lie outside of IBD regions. We also illustrated how knowledge of IBD structures can be applied to strain selection for future crosses. We have made our results available for data mining and download through a public website ( http://www.mouseibd.florida.scripps.edu ).