Abstract With the improvement of next-generation sequencing technology and the decline of sequencing costs, low-depth resequencing is applied to genome-wide association study analysis because of its cost-effective and ultra-high density of polymorphic loci. Nevertheless, research on low-depth resequencing for pig genome selection is still lack. In this study, 1 097 Large White pigs (Sus scrofa) were genotyped by low-coverage resequencing with an average sequencing depth of 2.4×. The results showed that the mismatch rate, mapping rate, actual depth and coverage between different batches were in stability. Then, the STITCH (Sequencing to Imputation Through Constructing Haplotypes) software was used for genotype calling and imputation from 1× and 2.4× re-sequencing data, and 15 506 511, 15 994 848 SNPs with 99.1% and 99.8% imputation accuracy were identified, respectively. In addition, overlapping or adjacent SNPs between 1× imputation data and 60K SNP chip (PorcineSNP60 v2) reached 47 421, indicating that low-depth resequencing had good compatibility with SNP chips, Further, BLUP (BLUP based on pedigree), GBLUP-WGS (GBLUP based on imputation from whole genome sequencing data), GBLUP-snp60 (GBLUP based on 60K SNP chip data) were used to predict the breeding values of 4 reproductive traits, including total number born (TNB), number born alive (NBA), healthy piglets (HP) and litter weight (LW) in the validation population. The results showed that except TNB, the prediction accuracy of other traits was GBLUP-WGS>GBLUP-snp60>BLUP, and the improvement range was 33.5%~218%, 16.7%~190%, corresponding to comparison between GBLUP-WGS and BLUP as well as between GBLUP-snp60 and BLUP. This results indicate that low-depth whole-genome sequencing offers a reliable and cost-effective method for large-scale livestock and poultry genome research and genome selection breeding.
LI Yong,YANG Man-Man,MIAO Ze-Pu, et al. Application of Low-depth Whole Genome Sequencing in Genomic Selection of Reproductive Traits in Large White Pigs (Sus scrofa)[J]. 农业生物技术学报, 2022, 30(2): 325-334.
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