Veroneze R, Lopes M S, Hidalgo A M, Guimarães S E F, Silva F F, Harlizius B, Lopes P S, Knol E F, M van Arendonk J A, Bastiaansen J W M
J Anim Sci. 2015 Oct;93(10):4684-91. doi: 10.2527/jas.2015-9187.
Pig breeding companies keep relatively small populations of pure sire and dam lines that are selected to improve the performance of crossbred animals. This design of the pig breeding industry presents challenges to the implementation of genomic selection, which requires large data sets to obtain highly accurate genomic breeding values. The objective of this study was to evaluate the impact of different reference sets (across population and multipopulation) on the accuracy of genomic breeding values in 3 purebred pig populations and to assess the potential of using crossbreed performance in genomic prediction. Data consisted of phenotypes and genotypes on animals from 3 purebred populations (sire line [SL] 1, = 1,146; SL2, = 682; and SL3, = 1,264) and 3 crossbred pig populations (Terminal cross [TER] 1, = 183; TER2, = 106; and TER3, = 177). Animals were genotyped using the Illumina Porcine SNP60 Beadchip. For each purebred population, within-, across-, and multipopulation predictions were considered. In addition, data from the paternal purebred populations were used as a reference set to predict the performance of crossbred animals. Backfat thickness phenotypes were precorrected for fixed effects and subsequently included in the genomic BLUP model. A genomic relationship matrix that accounted for the differences in allele frequencies between lines was implemented. Accuracies of genomic EBV obtained within the 3 different sire lines varied considerably. For within-population prediction, SL1 showed higher values (0.80) than SL2 (0.61) and SL3 (0.67). Multipopulation predictions had accuracies similar to within-population accuracies for the validation in SL1. For SL2 and SL3, the accuracies of multipopulation prediction were similar to the within-population prediction when the reference set was composed by 900 animals (600 of the target line plus 300 of another line). For across-population predictions, the accuracy was mostly close to zero. The accuracies of predicting crossbreed performance were similar for the 3 different crossbred populations (ranging from 0.25 to 0.29). In summary, the differences in accuracy of the within-population scenarios may be due to line divergences in heritability and genetic architecture of the trait. Within- and multipopulation predictions yield similar accuracies. Across-population prediction accuracy was negligible. The moderate accuracy of prediction of crossbreed performance appears to be a result of the relationship between the crossbreed and its parental lines.
养猪育种公司维持着相对较小的纯系父本和母本群体，这些群体经过选育以提高杂交动物的性能。养猪行业的这种设计给基因组选择的实施带来了挑战，因为基因组选择需要大量数据集来获得高度准确的基因组育种值。本研究的目的是评估不同参考集（跨群体和多群体）对3个纯种猪群体基因组育种值准确性的影响，并评估在基因组预测中使用杂交性能的潜力。数据包括来自3个纯种群体（父本系[SL]1，n = 1146；SL2，n = 682；SL3，n = 1264）和3个杂交猪群体（终端杂交[TER]1，n = 183；TER2，n = 106；TER3，n = 177）的动物的表型和基因型。使用Illumina猪SNP60芯片对动物进行基因分型。对于每个纯种群体，考虑了群体内、跨群体和多群体预测。此外，来自父本纯种群体的数据被用作参考集来预测杂交动物的性能。背膘厚度表型针对固定效应进行了预校正，随后纳入基因组最佳线性无偏预测（GBLUP）模型。实施了一个考虑品系间等位基因频率差异的基因组关系矩阵。在3个不同父本系中获得的基因组估计育种值（EBV）的准确性差异很大。对于群体内预测，SL1显示出比SL2（0.61）和SL3（0.67）更高的值（0.80）。对于SL1中的验证，多群体预测的准确性与群体内预测的准确性相似。对于SL2和SL3，当参考集由900只动物组成（目标系的600只加上另一个系的300只）时，多群体预测的准确性与群体内预测相似。对于跨群体预测，准确性大多接近于零。对于3个不同的杂交群体，预测杂交性能的准确性相似（范围从0.25到0.29）。总之，群体内预测准确性的差异可能是由于性状的遗传力和遗传结构在品系间的差异。群体内和多群体预测产生相似的准确性。跨群体预测准确性可忽略不计。杂交性能预测的中等准确性似乎是杂交种与其亲本系之间关系的结果。
