Genomic Prediction of Additive and Dominant Effects on Wool and Blood Traits in Alpine Merino Sheep - Zhu, Shaohua; Zhao, Hongchang; Han, Mei; Yuan, Chao; Guo, Tingting; Liu, Jianbin; Yue, Yaojing; Qiao, Guoyan; Wang, Tianxiang; Li, Fanwen; Gun, Shuangbao; Yang, Bohui (Frontiers in Veterinary Science, 2020)
Dominant genetic effects may provide a critical contribution to the total genetic variation of complex traits. However, investigations of genome-wide markers to study the genetic mechanisms and genomic prediction (GP) of complex traits generally ignore dominant genetic effects. The increasing availability of genomic datasets and the potential benefits of the inclusion of non-additive genetic effects in genomic prediction have recently renewed attention to incorporation of these effects in genomic evaluation models. In the present study, data from 498 genotyped Alpine Merino sheep were used to estimate additive and dominant genetic effects of 9 wool and blood traits via two linear models: (1) an additive effect model (MAG), and (2) a model that included both additive and dominant genetic effects (MADG). Moreover, a five-fold cross validation method was used to evaluate the accuracy of GP in the two different models. The results of variance component estimates for each trait suggested that for fleece extension rate (73%), red blood cell count (28%) and hematocrit (25%), a large proportion of phenotypic variation was explained by dominant genetic effects. The results of cross validation demonstrated that the MADG model, comprising both additive and dominant genetic effects, did not display an apparent advantage over the MAG model that included only additive genetic effects, i.e. the model that included dominant genetic effects did not improve the capability for prediction of the genomic model. Consequently, inclusion of dominant effects in the genomic prediction model was not beneficial for wool and blood traits in the Alpine Merino sheep population.