Abstract
BackgroundGenomic selection has become a standard tool in dairy cattle breeding. However, for other animal species, implementation of this technology is hindered by the high cost of genotyping. One way to reduce the routine costs is to genotype selection candidates with an SNP (single nucleotide polymorphism) panel of reduced density. This strategy is investigated in the present paper. Methods are proposed for the approximation of SNP positions, for selection of SNPs to be included in the low-density panel, for genotype imputation, and for the estimation of the accuracy of genomic breeding values. The imputation method was developed for a situation in which selection candidates are genotyped with an SNP panel of reduced density but have high-density genotyped sires. The dams of selection candidates are not genotyped. The methods were applied to a sire line pig population with 895 German Piétrain boars genotyped with the PorcineSNP60 BeadChip.ResultsGenotype imputation error rates were 0.133 for a 384 marker panel, 0.079 for a 768 marker panel, and 0.022 for a 3000 marker panel. Error rates for markers with approximated positions were slightly larger. Availability of high-density genotypes for close relatives of the selection candidates reduced the imputation error rate. The estimated decrease in the accuracy of genomic breeding values due to imputation errors was 3% for the 384 marker panel and negligible for larger panels, provided that at least one parent of the selection candidates was genotyped at high-density.Genomic breeding values predicted from deregressed breeding values with low reliabilities were more strongly correlated with the estimated BLUP breeding values than with the true breeding values. This was not the case when a shortened pedigree was used to predict BLUP breeding values, in which the parents of the individuals genotyped at high-density were considered unknown.ConclusionsGenomic selection with imputation from very low- to high-density marker panels is a promising strategy for the implementation of genomic selection at acceptable costs. A panel size of 384 markers can be recommended for selection candidates of a pig breeding program if at least one parent is genotyped at high-density, but this appears to be the lower bound.
Highlights
Genomic selection has become a standard tool in dairy cattle breeding
Genomic selection refers to the use of large numbers of single nucleotide polymorphisms (SNPs) spread across the genome for breeding value estimation and subsequent selection of individuals based on genomically enhanced breeding values [1,2]
Missing genotypes can be imputed using genotyping information from the individuals in the reference population and the genomic breeding values can be estimated for the selection candidates in the same way as if they were genotyped for the full set of SNPs
Summary
Genomic selection has become a standard tool in dairy cattle breeding. for other animal species, implementation of this technology is hindered by the high cost of genotyping. Genomic selection refers to the use of large numbers of single nucleotide polymorphisms (SNPs) spread across the genome for breeding value estimation and subsequent selection of individuals based on genomically enhanced breeding values [1,2] This technique has become a standard tool in dairy cattle breeding schemes, where it shortens the generation interval substantially [3]. Missing genotypes can be imputed using genotyping information from the individuals in the reference population and the genomic breeding values can be estimated for the selection candidates in the same way as if they were genotyped for the full set of SNPs. The accuracy of imputation depends on several factors, such as the number of SNPs in the low density panel, their informativeness and distribution across the genome, the relationship between the animals genotyped, the effective population size, and the method used. Some methods use both types of information, e.g. LDMIP [16] and AlphaImpute [17]
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