Using Different Single-Step Strategies to Improve the Efficiency of Genomic Prediction on Body Measurement Traits in Pig - Song, Hailiang; Zhang, Jinxin; Zhang, Qin; Ding, Xiangdong (Frontiers in Genetics, 2019)
In genomic prediction, single-step method has been demonstrated to outperform multi-step methods. This study investigated the efficiency of genomic prediction for 7 body measurement traits in Yorkshire population using single-step method. In total, 592 individuals were genotyped with Illumina PorcineSNP80 marker panel. We compared the prediction accuracy of a traditional pedigree-based method (BLUP) with the single-step genomic BLUP (ssGBLUP) through 20 replicates of five-fold cross-validation (CV). In addition, we also compared the performance of two-trait ssGBLUP and single-trait ssGBLUP for the traits with different gradients of genetic correlation. Our results indicated the accuracies of ssGBLUP for 7 body measurement traits ranged from 0.543 to 0.785, and the unbiasedness of ssGBLUP ranged from 0.834 to 1.026, respectively. ssGBLUP generally generated 1 percentage on average higher prediction accuracy than traditional BLUP, the improvement was lower than expected mainly due to the small number of genotyped animals. Our results also demonstrated that the accuracies of genomic prediction can be further improved by implementing two-trait ssGBLUP model, the maximum gain on accuracy was 2 and 2.6 percentage for trait of chest width compared to single-trait ssGBLUP and traditional BLUP, while the gain was decreased with the weakness of genetic correlation. Two-trait ssGBLUP even performed worse than single trait analysis in low genetic correlation.