基于GBLUP和Bayes方法实现山羊体重基因组选择

Genome Selection of Body weight in Goats by GBLUP and Bayes Methods

为有效实现山羊基因组选择,提高选择准确性,根据前期对内蒙古绒山羊生产性能的遗传评估结果,以山羊的体重(h2=0.11)性状为例,结合NCBI已经公布的山羊基因组序列信息,设定群体传递过程和基因组参数,模拟获得个体表型和基因型数据,利用GBLUP和Bayes方法进行基因组育种值估计。结果表明,不同历史群体变化模式下,基因组选择对山羊体重基因组育种估计值准确性无显著影响(P>0.05)。GBLUP法估计的准确性高于Bayes Lasso,准确性达0.40。在历史群体下降模式下,基因组选择准确性高于恒定模式。

In order to effectively realize genome selection and improve GEBV accuracy, body weight (h 2=0.11) was chosen to perform genomic selection by using simulation in this study. Combing the previous genetic evaluation results of Inner Mongolian cashmere goats' production performance with goat genomic sequence information published in NCBI, the parameters including populations transmission and genomics were set probably. The phenotype and genotype data from individuals was obtained by simulation. The genomic breeding value of body weight was estimated by using GBLUP and Bayesian LASSO in each mode. The results showed:(1)Genomic selection methods had no signifiant effect on the accuracy of genomic estimated breeding value( P >0.05).(2)The accuracy by using the GBLUP method was higher than that in Bayes Lasso method, the values were up to more than 0.40. Additionally, the accuracy of genomic selection in constant mode was lower than that in decreasing mode.