title: Accuracy of Predicted Genomic Breeding Values in Purebred and Crossbred Pigs.
abstract: Genomic selection has been widely implemented in dairy cattle breeding when the aim is to improve performance of purebred animals. In pigs, however, the final product is a crossbred animal. This may affect the efficiency of methods that are currently implemented for dairy cattle. Therefore, the objective of this study was to determine the accuracy of predicted breeding values in crossbred pigs using purebred genomic and phenotypic data. A second objective was to compare the predictive ability of SNPs when training is done in either single or multiple populations for four traits: age at first insemination (AFI); total number of piglets born (TNB); litter birth weight (LBW); and litter variation (LVR). We performed marker-based and pedigree-based predictions. Within-population predictions for the four traits ranged from 0.21 to 0.72. Multi-population prediction yielded accuracies ranging from 0.18 to 0.67. Predictions across purebred populations as well as predicting genetic merit of crossbreds from their purebred parental lines for AFI performed poorly (not significantly different from zero). In contrast, accuracies of across-population predictions and accuracies of purebred to crossbred predictions for LBW and LVR ranged from 0.08 to 0.31 and 0.11 to 0.31, respectively. Accuracy for TNB was zero for across-population prediction, whereas for purebred to crossbred prediction it ranged from 0.08 to 0.22. In general, marker-based outperformed pedigree-based prediction across populations and traits. However, in some cases pedigree-based prediction performed similarly or outperformed marker-based prediction. There was predictive ability when purebred populations were used to predict crossbred genetic merit using an additive model in the populations studied. AFI was the only exception, indicating that predictive ability depends largely on the genetic correlation between PB and CB performance, which was 0.31 for AFI. Multi-population prediction was no better than within-population prediction for the purebred validation set. Accuracy of prediction was very trait-dependent.
authors.affiliation: Wageningen University, Animal Breeding and Genomics Centre, Wageningen, the Netherlands 6700 AH Swedish University of Agricultural Sciences, Department of Animal Breeding and Genetics, Uppsala, Sweden 750 07 andre.hidalgo@wur.nl.
authors.forename: André M
authors.identifier: http://orcid.org/0000-0001-5116-4628
authors.initials: AM
authors.lastname: Hidalgo
authors.affiliation: Wageningen University, Animal Breeding and Genomics Centre, Wageningen, the Netherlands 6700 AH.
authors.forename: John W M
authors.initials: JW
authors.lastname: Bastiaansen
authors.affiliation: Wageningen University, Animal Breeding and Genomics Centre, Wageningen, the Netherlands 6700 AH Topigs Norsvin Research Center, Beuningen, the Netherlands 6640 AA.
authors.forename: Marcos S
authors.initials: MS
authors.lastname: Lopes
authors.affiliation: Topigs Norsvin Research Center, Beuningen, the Netherlands 6640 AA.
authors.forename: Barbara
authors.initials: B
authors.lastname: Harlizius
authors.affiliation: Wageningen University, Animal Breeding and Genomics Centre, Wageningen, the Netherlands 6700 AH.
authors.forename: Martien A M
authors.initials: MA
authors.lastname: Groenen
authors.affiliation: Swedish University of Agricultural Sciences, Department of Animal Breeding and Genetics, Uppsala, Sweden 750 07.
authors.forename: Dirk-Jan
authors.initials: DJ
authors.lastname: de Koning
mesh_terms: D000818:Animals; D001947:Breeding; D016678:Genome; D005838:Genotype; D006824:Hybridization, Genetic; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D012641:Selection, Genetic; D013552:Swine / Q000235:genetics*
keywords: GenPred; across-population; genomic selection; multi-population; reproduction traits; shared data resource; within-population