文献类型： 外文期刊

作者： Xu, Lei ¹ ; Wang, Zezhao ¹ ; Zhu, Bo ¹ ; Liu, Ying ¹ ; Li, Hongwei ¹ ; Bordbar, Farhad ¹ ; Chen, Yan ¹ ; Zhang, Lupei ¹ ; Ga ¹ ;

作者机构： 1.Chinese Acad Agr Sci, Inst Anim Sci, Beijing 100193, Peoples R China

2.Anhui Acad Agr Sci, Inst Anim Husb & Vet Res, Hefei 230031, Anhui, Peoples R China

3.Chinese Agr Univ, Coll Anim Sci & Technol, Natl Engn Lab Anim Breeding, Key Lab Anim Genet Breeding & Reprod,Minist Agr, Beijing 100193, Peoples R China

关键词： genomic prediction; linkage disequilibrium; resampling approaches; Chinese indigenous cattle

期刊名称：ANIMALS （ 影响因子：2.752； 五年影响因子：2.942 ）

ISSN： 2076-2615

年卷期： 2019 年 9 卷 10 期

页码：

收录情况： SCI

摘要： Simple Summary In order to evaluate the potential application of genomic selection (GS) for Chinese indigenous cattle, we assessed the influence of combining multiple populations on the reliability of genomic predictions for 10 indigenous breeds of Chinese cattle using simulated data. We found the predictive accuracies to be low when the reference and validation populations were sampled from different breeds. When using multiple breeds for the reference population, the predictive accuracies were higher if the reference was comprised of breeds with close relationships. In addition, the accuracy increased in all scenarios when the heritability increased, and the genetic architecture of the QTL can affect genomic prediction. Our study suggested that the application of meta-populations can increase accuracy in scenarios with a reduced size of reference populations. Abstract Genomic selection (GS) has been widely considered as a valuable strategy for enhancing the rate of genetic gain in farm animals. However, the construction of a large reference population is a big challenge for small populations like indigenous cattle. In order to evaluate the potential application of GS for Chinese indigenous cattle, we assessed the influence of combining multiple populations on the reliability of genomic predictions for 10 indigenous breeds of Chinese cattle using simulated data. Also, we examined the effect of different genetic architecture on prediction accuracy. In this study, we simulated a set of genotype data by a resampling approach which can reflect the realistic linkage disequilibrium pattern for multiple populations. We found within-breed evaluations yielded the highest accuracies ranged from 0.64 to 0.68 for four different simulated genetic architectures. For scenarios using multiple breeds as reference, the predictive accuracies were higher when the reference was comprised of breeds with a close relationship, while the accuracies were low when prediction were carried out among breeds. In addition, the accuracy increased in all scenarios with the heritability increased. Our results suggested that using meta-population as reference can increase accuracy of genomic predictions for small populations. Moreover, multi-breed genomic selection was feasible for Chinese indigenous populations with genetic relationships.