National Key Laboratory for Swine Genetics, Breeding and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Genet Sel Evol. 2023 Mar 28;55(1):21. doi: 10.1186/s12711-023-00794-2.
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 ([Formula: see text] = 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 ([Formula: see text]) 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.
基因组选择被广泛应用于家畜杂交繁育体系的遗传改良，以选择优秀的核心纯种（PB）动物，并提高商业杂交（CB）动物的性能。目前大多数预测仅基于 PB 的表现。我们的目标是探索使用具有极端表型的 CB 动物的基因型作为参考群体，对 PB 动物进行基因组选择的潜在应用。使用真实的 PB 基因型作为祖先，我们模拟了一个杜洛克猪x（长白猪x约克夏猪）DLY 杂交繁育体系中 10 万头猪的生产。使用不同遗传力（[Formula: see text] = 0.1、0.3 和 0.5）的性状的 PB 动物基因型和表型（1）PB 动物、（2）极端表型的 DLY 动物和（3）随机 DLY 动物，比较了不同参考群体大小（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））对 PB 动物对 CB 表现的育种值的预测性能。
使用由具有极端表型的 CB 动物组成的参考群体，对中低遗传力性状具有明确的预测优势，并且与 BSLMM 模型结合，显著提高了 CB 表现的选择反应。对于高遗传力性状，如果考虑 PB 和 CB 性能之间遗传相关（[Formula: see text]）对使用 PB 参考群体获得的准确性的影响，则具有极端 CB 表型的参考群体的预测性能可与 PB 表型相媲美，并且如果参考群体足够大，前者可以超过后者。对于一个三杂交繁育体系的第一和终端公猪的选择，使用极端 CB 表型的预测优于使用 PB 表型，而对于第一母本的参考群体的最佳设计取决于相应品种的个体百分比以及目标性状的遗传力。
商业杂交群体是基因组预测参考群体设计的有希望的选择，并且对具有极端表型的 CB 动物进行选择性基因分型有可能最大限度地提高猪产业中 CB 表现的遗传改良。
