Use of haplotypes to identify regions harbouring lethal recessive variants in pigs

Abstract

BackgroundLethal recessive genetic variants are maintained at relatively low frequencies in a population in the heterozygous state, but by definition are fatal and therefore unobserved in the homozygous state. Since haplotypes allow the tagging of rare and untyped genetic variants, they have potential for studying lethal recessive variants. In this study, we used a large commercial population to identify putative lethal recessive haplotypes that impact either the total number born (TNB) or the number born alive (NBA) as a proportion of the total number born (NBA/TNB). We also compared the use of haplotypes with a single nucleotide polymorphism (SNP)-by-SNP approach and examined the benefits of using additional haplotypes imputed from low-density genotype data for the detection of lethal recessive variants. Candidate haplotypes were identified using population-wide haplotype frequencies and within-family analyses. These candidate haplotypes were subsequently assessed for putative lethal recessive effects on TNB and NBA/TNB by comparing carrier-to-carrier matings with carrier-to-non-carrier matings.ResultsUsing both medium-density and imputed low-density genotype data six regions were identified as containing putative lethal recessive haplotypes that had an effect on TNB. It is likely that these regions were related to at least four putative lethal recessive variants, each located on a different chromosome. Evidence for putative lethal recessive effects on TNB was found on chromosomes 1, 6, 10 and 14 using haplotypes. Using haplotypes from individuals genotyped only at medium-density or a SNP-by-SNP approach did not detect any lethal recessive effects. No lethal recessive haplotypes or SNPs were detected that had an effect on NBA/TNB.ConclusionsWe show that the use of haplotypes from combining medium-density and imputed low-density genotype data is superior for the identification of lethal recessive variants compared to both a SNP-by-SNP approach and to the use of only medium-density data. We developed a formal statistical framework that provided sufficient power to detect lethal recessive variants in species, which produce large full-sib families, while reducing false positive or type I errors. Applying this framework results in improvements in reproductive performance by purging lethal recessive alleles from a population in a timely and cost-effective manner.