Fine Mapping in 94 Inbred Mouse Strains Using a High-Density Haplotype Resource

Abstract

The genetics of phenotypic variation in inbred mice has for nearly a century provided a primary weapon in the medical research arsenal. A catalog of the genetic variation among inbred mouse strains, however, is required to enable powerful positional cloning and association techniques. A recent whole-genome resequencing study of 15 inbred mouse strains captured a significant fraction of the genetic variation among a limited number of strains, yet the common use of hundreds of inbred strains in medical research motivates the need for a high-density variation map of a larger set of strains. Here we report a dense set of genotypes from 94 inbred mouse strains containing 10.77 million genotypes over 121,433 single nucleotide polymorphisms (SNPs), dispersed at 20-kb intervals on average across the genome, with an average concordance of 99.94% with previous SNP sets. Through pairwise comparisons of the strains, we identified an average of 4.70 distinct segments over 73 classical inbred strains in each region of the genome, suggesting limited genetic diversity between the strains. Combining these data with genotypes of 7570 gap-filling SNPs, we further imputed the untyped or missing genotypes of 94 strains over 8.27 million Perlegen SNPs. The imputation accuracy among classical inbred strains is estimated at 99.7% for the genotypes imputed with high confidence. We demonstrated the utility of these data in high-resolution linkage mapping through power simulations and statistical power analysis and provide guidelines for developing such studies. We also provide a resource of in silico association mapping between the complex traits deposited in the Mouse Phenome Database with our genotypes. We expect that these resources will facilitate effective designs of both human and mouse studies for dissecting the genetic basis of complex traits.

Imputation of Single-Nucleotide Polymorphisms in Inbred Mice Using Local Phylogeny

“…Furthermore, our analysis can inform the selection of strains for which full genomic sequence would substantially improve the ability to confidently impute other strains and the optimal strains for maximal SNP discovery. Kirby et al (2010) imputed 657 million genotypes over 94 strains consisting of 65 classical and 13 wild-derived low-density sequenced strains and 12 classical and 4 wildderived high-density sequenced strains. They imputed the 78 low-density sequences (121,433 SNPs) with the high-density NIEHS/Perlegen data set (8.27 million SNPs) (Frazer et al 2007) and missing genotypes in the 16 high-density sequences.…”

“…These improvements are due, in part, to the use of a more complete set of sequence data and the fact that our lowerdensity set, at .500,000 markers, is considerably denser than in previous studies. Furthermore, the MDA platform, designed specifically to highlight the diversity within our sample set, is better equipped to identify appropriate imputation genotypes than the sparser 135,000-marker Broad SNP set (Kirby et al 2010) used in previous efforts.…”

“…In SM/J, our method imputed 64.95% of SNPs with high confidence, Kirby et al (2010) imputed 57.26% with high confidence (they define this as posterior probability .0.98), and Szatkiewicz et al (2008) imputed 72.39% with high confidence (posterior probability .0.9). Using our validation genotypes as the ground truth, our method achieved a per-SNP error rate of 0.03% while previous methods achieved error rates of 1.60% and 5.76%, respectively (Table 4).…”

“…There have been two recent imputation efforts in the laboratory mouse (Szatkiewicz et al 2008;Kirby et al 2010). Szatkiewicz and co-workers imputed genotypes at 7.9 million loci by combining low-density genotypes from 51 classical and wild-derived inbred mouse strains with high-density SNP discovery data obtained on a subset of 16 inbred strains (Frazer et al 2007;Yang et al 2007).…”

Host genetic and environmental effects on mouse intestinal microbiota

“…Individuals within several strains appear to be more cohesive than others (for example, C3HRI, DBAJR and WSB), indicating that a gradient of host genetic factors produces varied levels of strain-level conformity. Unlike microbial communities of wild primates , dendrograms of strain-wise relationships based on cecum microbiota failed to recapitulate apparent natural histories of the hosts (Petkov et al, 2004;Kirby et al, 2010). Mice of the same strain purchased from different vendors also harbor different microbial communities (Friswell et al, 2010).…”