Department of Animal Science, Iowa State University, Ames 50011, USA.
J Anim Sci. 2013 Apr;91(4):1538-51. doi: 10.2527/jas.2012-5593. Epub 2013 Jan 23.
The objective of this study was to estimate accuracies of direct genomic breeding values (DGV) for nationally evaluated traits of 1,081 American (AMH), 100 Argentine (ARH), 75 Canadian (CAH), and 395 Uruguayan (URH) Hereford animals genotyped using the Illumina BovineSNP50 BeadChip. Deregressed EBV (DEBV) were used as observations in a weighted analysis to derive DGV using BayesB and BayesC methods. The AMH animals were clustered into 4 groups, using either K-means or random clustering. Cross validation was performed with the group not used in training providing validation of the accuracies of estimated DGV. Genomic predictions were also evaluated for AMH animals by training on older animals and validating on younger animals. Bivariate animal models were used for each trait to estimate genetic correlations between DEBV and DGV. Genomic predictions were separately evaluated for foreign animals from each country using marker estimates from training on AMH or pooled international data. Pedigree estimated breeding values were developed for AMH animals, using traditional, pedigree-based BLUP (PBLUP) for comparison purposes. Using BayesB (BayesC) method, the average simple correlations between DGV and DEBV in AMH animals was 0.24 (0.21), 0.39 (0.36), and 0.32 (0.30) when training and validation sets were formed by K-means clustering, random allocation or year of birth of the animals, respectively. Genetic correlations between DEBV and DGV ranged from 0.20 (0.18) to 0.52 (0.45) in AMH animals. The DGV from BayesB were more accurate than from BayesC for most traits in AMH animals. Genomic predictions for foreign animals were less accurate than those obtained in AMH animals. Among foreign animals, genomic predictions were more accurate for CAH animals, which reflect the greater use of AMH sires in CAH in comparison with ARH and URH populations. Small changes in accuracies of DGV were observed for foreign animals by using admixed training populations. On average, genomic predictions across countries were more accurate for CAH and URH animals using BayesB. On average, accuracies of genomic predictions using BayesB (BayesC) method were 66% (55%) greater than those obtained from PBLUP. These results demonstrate the feasibility of developing DGV for American Hereford beef cattle. However, foreign breeders, especially South American Hereford breeders, need to genotype more animals to obtain more accurate genomic predictions.
本研究旨在估计使用 Illumina BovineSNP50 BeadChip 对 1081 头美国（AMH）、100 头阿根廷（ARH）、75 头加拿大（CAH）和 395 头乌拉圭（URH）赫里福德牛进行基因分型的全国评估性状的直接基因组育种值（DGV）的准确性。利用去回归 EBV（DEBV）作为观测值，采用贝叶斯 B（BayesB）和贝叶斯 C（BayesC）方法进行加权分析，推导出 DGV。将 AMH 动物聚类为 4 个组，使用 K-均值或随机聚类。使用未用于训练的组进行交叉验证，以验证估计的 DGV 的准确性。还通过在较老的动物上进行训练并在较年轻的动物上进行验证，对 AMH 动物进行了基因组预测评估。为了进行基因组预测，分别对每个国家的外国动物进行了评估，使用在 AMH 或国际 pooled 数据上的训练标记进行了评估。使用二元动物模型来估计 DEBV 和 DGV 之间的遗传相关性。使用传统的基于系谱的 BLUP（PBLUP）为 AMH 动物开发了系谱估计的育种值，用于比较目的。使用 BayesB（BayesC）方法，当训练和验证集分别通过 K-均值聚类、随机分配或动物的出生年份形成时，AMH 动物中 DGV 和 DEBV 之间的平均简单相关性分别为 0.24（0.21）、0.39（0.36）和 0.32（0.30）。在 AMH 动物中，DEBV 和 DGV 之间的遗传相关性范围为 0.20（0.18）至 0.52（0.45）。与 BayesC 相比，BayesB 的 DGV 在大多数性状上更准确。外国动物的基因组预测不如 AMH 动物的准确。在外国动物中，CAH 动物的基因组预测更准确，这反映了与 ARH 和 URH 种群相比，CAH 中更广泛地使用了 AMH 种公牛。使用混合训练群体观察到外国动物的 DGV 准确性略有变化。平均而言，使用 BayesB 对 CAH 和 URH 动物进行了跨国家的基因组预测，其准确性更高。平均而言，使用 BayesB（BayesC）方法的基因组预测准确性比使用 PBLUP 获得的准确性高 66%（55%）。这些结果表明，为美国赫里福德肉牛开发 DGV 是可行的。然而，外国饲养者，特别是南美洲赫里福德饲养者，需要对更多的动物进行基因分型，以获得更准确的基因组预测。
