Genomic Prediction Using LD-Based Haplotypes Inferred From High-Density Chip and Imputed Sequence Variants in Chinese Simmental Beef Cattle - Li, Hongwei; Zhu, Bo; Xu, Ling; Wang, Zezhao; Xu, Lei; Zhou, Peinuo; Gao, Han; Guo, Peng; Chen, Yan; Gao, Xue; Zhang, Lupei; Gao, Huijiang; et al. (Frontiers in Genetics, 2021)
A haplotype is defined as a combination of alleles at adjacent loci belonging to the same chromosome that can be transmitted as a unit. In this study, we untilized both the BovineHD chip and imputed whole-genome sequence (WGS) data to explore haploblocks and assess haplotype effects according to different LD thresholds. The accuracies of genomic prediction (GP) for dressing percentage (DP), meat percentage (MP) and rib eye roll weight (RERW) based on haplotype were investigated and compared for both data sets in Chinese Simmental beef cattle. The accuracies of GP using the entire imputed WGS data showed a decrease compared with the BovineHD chip in all cases. For DP and MP, the haploblock approaches (include GHBLUP and GHBLUP+GBLUP) outperformed individual SNPs approach (GBLUP_In_Block) at specific LD levels (r^2). Hotelling’s test confirmed that haplotypes prediction based on LD using WGS data can significantly increase the accuracies of GP for RERW compared with SNP-based approach (~1.4% and 1.9% for GHBLUP and GHBLUP+GBLUP, respectively). We found the accuracies of GP using haploblock approach varied with different LD thresholds. The LD thresholds (r^2≥0.5) was optimal for most of scenarios. Haplotypes prediction based on LD was an effective method to improve accuracy of carcass traits for both BovineHD chip and imputed WGS data under the optimal LD thresholds in Chinese Simmental beef cattle.