Genomic selection is widely applied for genetic improvement in livestock crossbreeding systems to select excellent nucleus purebred (PB) animals and to improve the performance of commercial crossbred (CB) animals. Most current predictions are based solely on PB performance. Our objective was to explore the potential application of genomic selection of PB animals using genotypes of CB animals with extreme phenotypes in a three-way crossbreeding system as the reference population. Using real genotyped PB as ancestors, we simulated the production of 100,000 pigs for a Duroc x (Landrace x Yorkshire) DLY crossbreeding system. The predictive performance of breeding values of PB animals for CB performance using genotypes and phenotypes of (1) PB animals, (2) DLY animals with extreme phenotypes, and (3) random DLY animals for traits of different heritabilities ( $${h}^{2}$$ = 0.1, 0.3, and 0.5) was compared across different reference population sizes (500 to 6500) and prediction models (genomic best linear unbiased prediction (GBLUP) and Bayesian sparse linear mixed model (BSLMM)). Using a reference population consisting of CB animals with extreme phenotypes showed a definite predictive advantage for medium- and low-heritability traits and, in combination with the BSLMM model, significantly improved selection response for CB performance. For high-heritability traits, the predictive performance of a reference population of extreme CB phenotypes was comparable to that of PB phenotypes when the effect of the genetic correlation between PB and CB performance ( $${r}_{pc}$$ ) on the accuracy obtained with a PB reference population was considered, and the former could exceed the latter if the reference size was large enough. For the selection of the first and terminal sires in a three-way crossbreeding system, prediction using extreme CB phenotypes outperformed the use of PB phenotypes, while the optimal design of the reference group for the first dam depended on the percentage of individuals from the corresponding breed that the PB reference data comprised and on the heritability of the target trait. A commercial crossbred population is promising for the design of the reference population for genomic prediction, and selective genotyping of CB animals with extreme phenotypes has the potential for maximizing genetic improvement for CB performance in the pig industry.

中文翻译：

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使用来自商业杂交种群的数据预测猪的基因组：来自杜洛克 x（长白 x 约克郡）三向杂交系统的见解

基因组选择广泛应用于家畜杂交育种系统的遗传改良，以选择优良的核心纯种（PB）动物和提高商业杂交（CB）动物的性能。大多数当前预测仅基于 PB 性能。我们的目标是在三向杂交系统中使用具有极端表型的 CB 动物的基因型作为参考种群，探索 PB 动物基因组选择的潜在应用。使用真正的基因分型 PB 作为祖先，我们模拟了杜洛克 x（长白 x 约克郡）DLY 杂交系统的 100,000 头猪的生产。使用 (1) PB 动物，(2) 具有极端表型的 DLY 动物的基因型和表型，PB 动物的育种值对 CB 性能的预测性能，(3) 在不同参考种群规模（500 至 6500）和预测模型（基因组最佳线性无偏预测 (GBLUP) 和贝叶斯稀疏线性混合模型 (BSLMM)）。使用由具有极端表型的 CB 动物组成的参考群体显示出对中等和低遗传性性状的明确预测优势，并且结合 BSLMM 模型，显着改善了对 CB 性能的选择响应。对于高遗传性状，当 PB 和 CB 性能之间的遗传相关性 ($${r}_{pc}$$) 对使用 PB 获得的准确性的影响时，极端 CB 表型参考群体的预测性能与 PB 表型的预测性能相当考虑了参考人群，如果参考规模足够大，前者可以超过后者。对于三向杂交系统中的第一代和终端父系的选择，使用极端 CB 表型的预测优于使用 PB 表型，而第一个水坝的参考组的优化设计取决于来自相应的个体的百分比PB 参考数据包含的品种以及目标性状的遗传力。商业杂交种群有望用于基因组预测参考种群的设计，