Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, P.O. Box: 4111, Karaj, 77871-31587, Iran.
Department of Animal Life and Environment Sciences, Hankyong National University, Jungang-ro 327, Anseong-si, Gyeonggi-do, South Korea.
BMC Genet. 2020 Dec 2;21(1):144. doi: 10.1186/s12863-020-00928-1.
Recently, there has been a growing interest in the genetic improvement of body measurement traits in farm animals. They are widely used as predictors of performance, longevity, and production traits, and it is worthwhile to investigate the prediction accuracies of genomic selection for these traits. In genomic prediction, the single-step genomic best linear unbiased prediction (ssGBLUP) method allows the inclusion of information from genotyped and non-genotyped relatives in the analysis. Hence, we aimed to compare the prediction accuracy obtained from a pedigree-based BLUP only on genotyped animals (PBLUP-G), a traditional pedigree-based BLUP (PBLUP), a genomic BLUP (GBLUP), and a single-step genomic BLUP (ssGBLUP) method for the following 10 body measurement traits at yearling age of Hanwoo cattle: body height (BH), body length (BL), chest depth (CD), chest girth (CG), chest width (CW), hip height (HH), hip width (HW), rump length (RL), rump width (RW), and thurl width (TW). The data set comprised 13,067 phenotypic records for body measurement traits and 1523 genotyped animals with 34,460 single-nucleotide polymorphisms. The accuracy for each trait and model was estimated only for genotyped animals using five-fold cross-validations.
The accuracies ranged from 0.02 to 0.19, 0.22 to 0.42, 0.21 to 0.44, and from 0.36 to 0.55 as assessed using the PBLUP-G, PBLUP, GBLUP, and ssGBLUP methods, respectively. The average predictive accuracies across traits were 0.13 for PBLUP-G, 0.34 for PBLUP, 0.33 for GBLUP, and 0.45 for ssGBLUP methods. Our results demonstrated that averaged across all traits, ssGBLUP outperformed PBLUP and GBLUP by 33 and 43%, respectively, in terms of prediction accuracy. Moreover, the least root of mean square error was obtained by ssGBLUP method.
Our findings suggest that considering the ssGBLUP model may be a promising way to ensure acceptable accuracy of predictions for body measurement traits, especially for improving the prediction accuracy of selection candidates in ongoing Hanwoo breeding programs.
最近，人们对农场动物体型测量性状的遗传改良越来越感兴趣。这些性状被广泛用作性能、寿命和生产性状的预测指标，因此值得研究这些性状的基因组选择预测准确性。在基因组预测中，单步基因组最佳线性无偏预测（ssGBLUP）方法允许在分析中包含已基因型和未基因型亲属的信息。因此，我们旨在比较以下 10 个韩牛周岁时的体型测量性状的基于系谱的 BLUP 仅基于基因型动物（PBLUP-G）、传统基于系谱的 BLUP（PBLUP）、基因组 BLUP（GBLUP）和单步基因组 BLUP（ssGBLUP）方法获得的预测准确性：体高（BH）、体长（BL）、胸深（CD）、胸围（CG）、胸宽（CW）、臀高（HH）、臀宽（HW）、尻长（RL）、尻宽（RW）和肘宽（TW）。数据集包括 13067 个体型测量性状的表型记录和 1523 个基因型动物，其中包含 34460 个单核苷酸多态性。使用五重交叉验证仅对基因型动物估计每个性状和模型的准确性。
使用 PBLUP-G、PBLUP、GBLUP 和 ssGBLUP 方法分别评估，准确性范围为 0.02 至 0.19、0.22 至 0.42、0.21 至 0.44 和 0.36 至 0.55。跨性状的平均预测准确性分别为 PBLUP-G 为 0.13、PBLUP 为 0.34、GBLUP 为 0.33 和 ssGBLUP 为 0.45。我们的结果表明，在所有性状的平均值上，ssGBLUP 在预测准确性方面分别比 PBLUP 和 GBLUP 高出 33%和 43%。此外，最小均方根误差是由 ssGBLUP 方法获得的。
我们的研究结果表明，考虑 ssGBLUP 模型可能是确保体型测量性状预测准确性的一种很有前途的方法，特别是对于提高正在进行的韩牛育种计划中选择候选者的预测准确性。
