Yan Xiaochun, Zhang Tao, Liu Lichun, Yu Yongsheng, Yang Guang, Han Yaqian, Gong Gao, Wang Fenghong, Zhang Lei, Liu Hongfu, Li Wenze, Yan Xiaomin, Mao Haoyu, Li Yaming, Du Chen, Li Jinquan, Zhang Yanjun, Wang Ruijun, Lv Qi, Wang Zhixin, Zhang Jiaxin, Liu Zhihong, Wang Zhiying, Su Rui
College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China.
Inner Mongolia Bigvet Co., Ltd., Hohhot, China.
Front Vet Sci. 2022 Mar 16;9:770539. doi: 10.3389/fvets.2022.770539. eCollection 2022.
Genomic selection in plants and animals has become a standard tool for breeding because of the advantages of high accuracy and short generation intervals. Implementation of this technology is hindered by the high cost of genotyping and other factors. The aim of this study was to determine an optional marker density panel and reference population size for using genomic selection of goats, with speculation on the number of QTLs that affect the important economic traits of goats. In addition, the effect of buck population size in the reference population on the accuracy of genomic estimated breeding value (GEBV) was discussed. Based on the previous genetic evaluation results of Inner Mongolia White Cashmere Goats, live body weight (LBW, = 0.11) and fiber diameter (FD, = 0.34) were chosen to perform genomic selection in this study. Reasonable genome parameters and generation transmission processes were set, and phenotypic and genotype data of the two traits were simulated. Then, different sizes of the reference population and validation population were selected from progeny. The GEBVs were obtained by six methods, including GBLUP (Genomic Best Linear Unbiased Prediction), ssGBLUP (Single Step Genomic Best Linear Unbiased Prediction), BayesA, BayesB, Bayesian ridge regression, and Bayesian LASSO. The correlation coefficient between the predicted and realized phenotypes from simulation was calculated and used as a measure of the accuracy of GEBV in each trait. The results showed that the medium marker density Panel (45 K) could be used for genomic selection in goats, which can ensure the accuracy of the GEBV. The reference population size of 1,500 can achieve greater genetic progress in genomic selection for fiber diameter and live body weight in goats by comparing with the population size below this level. The accuracy of the GEBV for live body weight and fiber diameter was better when the number of QTLs was 100 and 50, respectively. Additionally, the accuracy of GEBV was discovered to be good when the buck population size was up to 200. Meanwhile, the accuracy of the GEBV for medium heritability traits (FDs) was found to be higher than the accuracy of the GEBV for low heritability traits (LBWs). These findings will provide theoretical guidance for genomic selection in goats by using real data.
由于具有高精度和短世代间隔的优势，动植物的基因组选择已成为育种的标准工具。该技术的实施受到基因分型高成本等因素的阻碍。本研究的目的是确定用于山羊基因组选择的最佳标记密度面板和参考群体大小，并推测影响山羊重要经济性状的数量性状位点（QTL）数量。此外，还讨论了参考群体中种公羊群体大小对基因组估计育种值（GEBV）准确性的影响。基于内蒙古白绒山羊先前的遗传评估结果，本研究选择了体重（LBW，遗传力 = 0.11）和纤维直径（FD，遗传力 = 0.34）进行基因组选择。设定了合理的基因组参数和世代传递过程，并模拟了这两个性状的表型和基因型数据。然后，从后代中选择不同大小的参考群体和验证群体。通过六种方法获得GEBV，包括GBLUP（基因组最佳线性无偏预测）、ssGBLUP（单步基因组最佳线性无偏预测）、BayesA、BayesB、贝叶斯岭回归和贝叶斯LASSO。计算模拟预测表型与实际表型之间的相关系数，并将其用作每个性状GEBV准确性的度量。结果表明，中等标记密度面板（45K）可用于山羊的基因组选择，这可以确保GEBV的准确性。与低于该水平的群体大小相比，1500的参考群体大小在山羊纤维直径和体重的基因组选择中可以实现更大的遗传进展。当QTL数量分别为100和50时，体重和纤维直径的GEBV准确性更好。此外，发现当种公羊群体大小达到200时，GEBV的准确性良好。同时，发现中等遗传力性状（FDs）的GEBV准确性高于低遗传力性状（LBWs）的GEBV准确性。这些发现将为利用实际数据进行山羊基因组选择提供理论指导。
