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.

中文翻译：

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使用单步基因组最佳线性无偏预测法对Hanwoo肉牛提高线性身体测量性状的基因组评估准确性

最近，人们对农场动物体内测量性状的遗传改良越来越感兴趣。它们被广泛用作性能，寿命和生产性状的预测指标，因此值得研究这些特性的基因组选择的预测准确性。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括来自基因型和非基因型亲戚的信息。因此，我们旨在比较仅对基因型动物的基于谱系的BLUP，传统的基于谱系的BLUP（PBLUP），基因组BLUP（GBLUP）和单步基因组BLUP的预测准确性。 （ssGBLUP）方法用于Hanwoo牛一岁以下以下10个身体测量特征：身高（BH），身长（BL），胸部深度（CD），胸围（CG），胸部宽度（CW），臀部高度（HH），臀部宽度（HW），臀围长度（RL），臀围宽度（RW）和摆幅（TW）。该数据集包括用于身体测量特征的13067个表型记录和具有34460个单核苷酸多态性的1523个基因型动物。使用五重交叉验证仅对基因型动物评估每种性状和模型的准确性。分别使用PBLUP-G，PBLUP，GBLUP和ssGBLUP方法评估的准确性范围为0.02至0.19、0.22至0.42、0.21至0.44和0.36至0.55。各性状的平均预测准确度分别为PBLUP-G 0.13，PBLUP 0.34，GBLUP 0.33和ssGBLUP方法0.45。我们的结果表明，在所有性状上的平均值，ssGBLUP分别优于PBLUP和GBLUP 33％和43％，在预测准确性方面。此外，均方根误差的最小根是通过ssGBLUP方法获得的。我们的发现表明，考虑ssGBLUP模型可能是确保可接受的身体测量性状预测准确性的有希望的方法，尤其是对于在进行中的Hanwoo育种计划中提高选择候选者的预测准确性而言。