Yan Xiaochun, Zhang Jiaxin, Li Jinquan, Wang Na, Su Rui, Wang Zhiying
College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China.
Inner Mongolia Key Laboratory of Sheep and Goat Genetics Breeding and Reproduction, Hohhot, China.
Front Vet Sci. 2024 Feb 5;11:1325831. doi: 10.3389/fvets.2024.1325831. eCollection 2024.
Inner Mongolia Cashmere Goats (IMCGs) are famous for its cashmere quality and it's a unique genetic resource in China. Therefore, it is necessary to use genomic selection to improve the accuracy of selection for fleece traits in Inner Mongolia cashmere goats. The aim of this study was to determine the effect of methods (GBLUP, BayesA, BayesB, Bayesian LASSO, Bayesian Ridge Region) and the reference population size on accuracy of genomic selection in IMCGs.
This study fully utilizes the pedigree and phenotype records of fleece traits in 2255 individuals, genotype of 50794 SNPs after quality control, and environmental data to perform genomic selection of fleece traits. Then GBLUP and Bayes series methods (BayesA, BayesB, Bayesian LASSO, Bayesian Ridge Region) were used to perform estimates of genetic parameter and genomic breeding value. And the accuracy of genomic estimated breeding value (GEBV) is evaluated using the five-fold cross validation method. And the analysis of variance and multiple comparison methods were used to determine the best method for genomic selection in fleece traits of IMCGs. Further the different reference population sizes (500, 1000, 1500, and 2000) was set. Then the best method was applied to estimate genome breeding values, and evaluate the impact of reference population sizes on the accuracy of genome selection for fleece traits in IMCGs.
It was found that the genomic prediction accuracy for each fleece trait in IMCGs by GBLUP method is highest, and it is significantly higher than that obtained by Bayesian method. The accuracy of breeding value estimation is 58.52% -68.49%. Also, it was found that the size of the reference population has a significant impact on the accuracy of genome prediction of fleece traits. When the reference population size is 2000, the accuracy of genomic prediction for each fleece trait is significantly higher than other levels, with accuracy of 55.47% -67.87%. This provides a theoretical basis for design a reasonable genome selection plan for Inner Mongolia cashmere goats in the later stag.
内蒙古绒山羊以其羊绒品质而闻名,是我国独特的遗传资源。因此,有必要采用基因组选择来提高内蒙古绒山羊羊毛性状的选择准确性。本研究的目的是确定方法(GBLUP、BayesA、BayesB、贝叶斯LASSO、贝叶斯岭回归)和参考群体大小对内蒙古绒山羊基因组选择准确性的影响。
本研究充分利用2255只个体的羊毛性状系谱和表型记录、质量控制后50794个单核苷酸多态性(SNP)的基因型以及环境数据,对羊毛性状进行基因组选择。然后使用GBLUP和贝叶斯系列方法(BayesA、BayesB、贝叶斯LASSO、贝叶斯岭回归)进行遗传参数和基因组育种值估计。并采用五倍交叉验证法评估基因组估计育种值(GEBV)的准确性。使用方差分析和多重比较方法确定内蒙古绒山羊羊毛性状基因组选择的最佳方法。进一步设置不同的参考群体大小(500、1000、1500和2000)。然后应用最佳方法估计基因组育种值,并评估参考群体大小对内蒙古绒山羊羊毛性状基因组选择准确性的影响。
发现GBLUP方法对内蒙古绒山羊各羊毛性状的基因组预测准确性最高,且显著高于贝叶斯方法获得的准确性。育种值估计准确性为58.52% - 68.49%。还发现参考群体大小对羊毛性状基因组预测准确性有显著影响。当参考群体大小为2000时,各羊毛性状的基因组预测准确性显著高于其他水平,准确性为55.47% - 67.87%。这为后期为内蒙古绒山羊设计合理的基因组选择方案提供了理论依据。