GWAS on Imputed Whole-Genome Resequencing From Genotyping-by-Sequencing Data for Farrowing Interval of Different Parities in Pigs - Wu, Pingxian; Wang, Kai; Zhou, Jie; Chen, Dejuan; Yang, Qiang; Yang, Xidi; Liu, Yihui; Feng, Bo; Jiang, Anan; Shen, Linyuan; Xiao, Weihang; Jiang, Yanzhi; et al. (Frontiers in Genetics, 2019)
The whole-genome re-sequencing(WGS) data can potentially discover all genetic variants. Studies have shown the power of WGS for GWAS lies in the ability to identify quantitative trait loci(QTLs) and nucleotides(QTNs). However,the re-sequencing of thousands of target individuals is expensive. Genotype imputation is a powerful approach for WGS and to identify causal mutations. This study aimed to evaluate the imputation accuracy from genotyping-by-sequencing(GBS) to WGS in two pig breeds using a re-sequencing reference population, and to detect SNPs and candidate genes for farrowing interval (FI) of different parities using the data before and after imputation for GWAS. Six hundred target pigs, 300 Landrace and 300 Large White pigs, were genotyped by GBS, and 60 reference pigs, 20 Landrace and 40 Large White pigs, were sequenced by whole-genome re-sequencing. Imputation for pigs was conducted using Beagle software. The average imputation accuracy (allelic R2) from GBS to WGS was 0.42 for Landrace pigs and 0.45 for Large White pigs. For Landrace pigs (Large White pigs), 4,514,934 (5,533,290) SNPs had an accuracy >0.3, resulting an average accuracy of 0.73 (0.72). And, 2,093,778 (2,468,645) SNPs had an accuracy >0.8, resulting an average accuracy of 0.94 (0.93). Association studies with data before and after imputation were performed for FI of different parities in two populations. Before imputation, 18 and 128 significant SNPs were detected for FI in Landrace and Large White pigs, respectively. After imputation, 125 and 27 significant SNPs were identified for dataset with an accuracy >0.3 and 0.8 in Large White pigs, and 113 and 18 SNPs were found among imputed sequence variants. Among these significant SNPs, six top SNPs were detected in both GBS data and imputed WGS data; namely, SSC2:136127645, SSC5:103426443, SSC6:27811226, SSC10:3609429, SSC14:15199253, and SSC15:150297519. Overall, many candidate genes could be involved in FI of different parities in pigs. Although imputation from GBS to WGS data resulted in a low imputation accuracy, association analyses with imputed WGS data was optimized to detect QTNs for complex trait. The obtained results provide new insight into genotype imputation, genetic architecture and candidate genes for FI of different parities in Landrace and Large White pigs.