Department of Animal Science, Shahrekord University, Shahrekord 88186-34141, Iran.
Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj 77871-31587, Iran.
Genes (Basel). 2021 Feb 12;12(2):266. doi: 10.3390/genes12020266.
The weighted single-step genomic best linear unbiased prediction (GBLUP) method has been proposed to exploit information from genotyped and non-genotyped relatives, allowing the use of weights for single-nucleotide polymorphism in the construction of the genomic relationship matrix. The purpose of this study was to investigate the accuracy of genetic prediction using the following single-trait best linear unbiased prediction methods in Hanwoo beef cattle: pedigree-based (PBLUP), un-weighted (ssGBLUP), and weighted (WssGBLUP) single-step genomic methods. We also assessed the impact of alternative single and window weighting methods according to their effects on the traits of interest. The data was comprised of 15,796 phenotypic records for yearling weight (YW) and 5622 records for carcass traits (backfat thickness: BFT, carcass weight: CW, eye muscle area: EMA, and marbling score: MS). Also, the genotypic data included 6616 animals for YW and 5134 for carcass traits on the 43,950 single-nucleotide polymorphisms. The ssGBLUP showed significant improvement in genomic prediction accuracy for carcass traits (71%) and yearling weight (99%) compared to the pedigree-based method. The window weighting procedures performed better than single SNP weighting for CW (11%), EMA (11%), MS (3%), and YW (6%), whereas no gain in accuracy was observed for BFT. Besides, the improvement in accuracy between window WssGBLUP and the un-weighted method was low for BFT and MS, while for CW, EMA, and YW resulted in a gain of 22%, 15%, and 20%, respectively, which indicates the presence of relevant quantitative trait loci for these traits. These findings indicate that WssGBLUP is an appropriate method for traits with a large quantitative trait loci effect.
加权单步基因组最佳线性无偏预测（GBLUP）方法已被提出，用于利用已基因分型和未基因分型的亲属的信息，允许在构建基因组关系矩阵时使用单核苷酸多态性的权重。本研究旨在调查以下单性状最佳线性无偏预测方法在韩牛肉牛中的遗传预测准确性：基于系谱的（PBLUP）、无权重（ssGBLUP）和加权（WssGBLUP）单步基因组方法。我们还根据它们对感兴趣性状的影响，评估了替代单 SNP 和窗口加权方法的影响。数据包括 15796 个育肥期体重（YW）的表型记录和 5622 个胴体性状（背膘厚度：BFT、胴体重：CW、眼肌面积：EMA 和大理石花纹评分：MS）的记录。此外，基因型数据包括 6616 个育肥期体重和 5134 个胴体性状的 43950 个单核苷酸多态性的 6616 个动物。与基于系谱的方法相比，ssGBLUP 显著提高了胴体性状（71%）和育肥期体重（99%）的基因组预测准确性。窗口加权程序在 CW（11%）、EMA（11%）、MS（3%）和 YW（6%）方面的表现优于单 SNP 加权，而 BFT 则没有提高准确性。此外，窗口 WssGBLUP 和无权重方法之间的准确性提高对于 BFT 和 MS 来说很小，而对于 CW、EMA 和 YW 则分别提高了 22%、15%和 20%，这表明这些性状存在相关的数量性状基因座。这些发现表明，WssGBLUP 是一种适用于具有较大数量性状基因座效应的性状的方法。
