An imputed genotype resource for the laboratory mouse

Abstract

We have created a high-density SNP resource encompassing 7.87 million polymorphic loci across 49 inbred mouse strains of the laboratory mouse by combining data available from public databases and training a hidden Markov model to impute missing genotypes in the combined data. The strong linkage disequilibrium found in dense sets of SNP markers in the laboratory mouse provides the basis for accurate imputation. Using genotypes from eight independent SNP resources, we empirically validated the quality of the imputed genotypes and demonstrate that they are highly reliable for most inbred strains. The imputed SNP resource will be useful for studies of natural variation and complex traits. It will facilitate association study designs by providing high density SNP genotypes for large numbers of mouse strains. We anticipate that this resource will continue to evolve as new genotype data become available for laboratory mouse strains. The data are available for bulk download or query at http://cgd.jax.org/.

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

“…In addition to including wild-derived strains in the sample set, 64% of SNPs in the full Perlegen data set include private alleles seen only in wild-derived strains. Szatkiewicz et al (2008) imputed 269 million genotypes using a cleaned subset of 7.9 million NIEHS/Perlegen SNPs over 51 strains including 39 classical and 12 wild derived. These previous imputation efforts attempted to impute a mixture of classical laboratory strains and wild-derived strains including SNPs with private alleles in wild-derived samples.…”

“…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).…”

Mouse Forward Genetics in the Study of the Peripheral Nervous System and Human Peripheral Neuropathy

“…In the 1990's, simple sequence length polymorphisms (SSLP) markers, or microsatellites, regions of short repeats that vary in length among mouse strains, were developed, greatly increasing the number of markers available for linkage mapping [16]. SSLP markers are still commonly used, with great success, but to increase marker density and usefulness over a broader range of strains, effort has been made to develop large panels of single nucleotide polymorphism (SNP) markers [17,18,19]. SNP markers increase efficiency both in breeding, by reducing the number of mutants required to localize a mutation to a critical region, and in genotyping, by enabling the use of high-throughput methods such as MALDI-TOF mass spectrometry [20] and oligonucleotide arrays [19].…”

“…SSLP markers are still commonly used, with great success, but to increase marker density and usefulness over a broader range of strains, effort has been made to develop large panels of single nucleotide polymorphism (SNP) markers [17,18,19]. SNP markers increase efficiency both in breeding, by reducing the number of mutants required to localize a mutation to a critical region, and in genotyping, by enabling the use of high-throughput methods such as MALDI-TOF mass spectrometry [20] and oligonucleotide arrays [19]. SNP panels are also valuable as mouse geneticists attempt to utilize the natural variation among mouse strains to find the genes behind quantitative traits [21].…”