Prediction of genomic breeding values based on pre-selected SNPs using ssGBLUP, WssGBLUP and BayesB for Edwardsiellosis resistance in Japanese flounder

Abstract

Background: Edwardsiella tarda causes acute symptoms with ascites in Japanese flounder (Paralichthys olivaceus) and is a major problem for China's aquaculture sector. Genomic selection (GS) has been widely adopted in breeding industries because it shortens generation intervals and results in the selection of individuals that have great breeding potential with high accuracy. Based on an artificial challenge test and re-sequenced data of 1099 flounders, the aims of this study were to estimate the genetic parameters of resistance to E. tarda in Japanese flounder and to evaluate the accuracy of single-step GBLUP (ssGBLUP), weighted ssGBLUP (WssGBLUP), and BayesB for improving resistance to E. tarda by using three subsets of pre-selected single nucleotide polymorphisms (SNPs). In addition, SNPs that are associated with this trait were identified using a single-SNP genome-wide association study (GWAS) and WssGBLUP. Results: We estimated a heritability of 0.13 ± 0.02 for resistance to E. tarda in Japanese flounder. One million SNPs at fixed intervals were selected from 4,978,724 SNPs that passed quality controls. GWAS identified significant SNPs on chromosomes 14 and 24. WssGBLUP revealed that the putative quantitative trait loci on chromosomes 1 and 14 contained SNPs that explained more than 1% of the genetic variance. Three 50 k-SNP subsets were pre-selected based on different criteria. Compared with pedigree-based prediction (ABLUP), the three genomic methods evaluated resulted in at least 7.7% greater accuracy of predictions. The accuracy of these genomic prediction methods was almost unchanged when pre-selected trait-related SNPs were used for prediction. Conclusions: Resistance to E. tarda in Japanese flounder has a low heritability. GWAS and WssGBLUP revealed that the genetic architecture of this trait is polygenic. Genomic prediction of breeding values performed better than ABLUP. It is feasible to implement genomic selection to increase resistance to E. tarda in Japanese flounder with 50 k SNPs. Based on the criteria used here, pre-selection of SNPs was not beneficial and other criteria for pre-selection should be considered.

Genomic Prediction Using Alternative Strategies of Weighted Single-Step Genomic BLUP for Yearling Weight and Carcass Traits in Hanwoo Beef Cattle

“…In this respect, Teissier et al [35] concluded that for polygenic traits, the same accuracy could be obtained with the ssGBLUP and WssGBLUP method, which is in complete agreement with the findings of our study. Recently, Lu et al [45] indicated that WssGBLUP was more accurate (6%) than ssGBLUP for Edwardsiellosis resistance in Japanese flounder, which may be due to the presence of QTL on chromosome 14 with large effects for this trait.…”

Genomic prediction of growth in a commercially, recreationally, and culturally important marine resource, the Australian snapper (Chrysophrys auratus)

“…Owing to the inclusion of most of the causal mutations, and decreased limitation due to linkage between SNPs and causal mutations, the use of whole-genome resequencing (WGS) could increase predictive ability. However, empirical results comparing the use of WGS vs a set of SNPs show nil to marginal increase in genomic prediction accuracy ( Lu et al 2020 ; Yoshida and Yáñez 2021 ). This suggests WGS is unnecessary for this purpose and supports our suggestion that reduced genome representation provides accurate genomic prediction estimates to assist in the selection of elite broodstock lines.…”

Genomic prediction of growth in a commercially, recreationally, and culturally important marine resource, the Australian snapper (Chrysophrys auratus)

“…Owing to the inclusion of most of the causal mutations, and decreased limitation due to linkage between SNPs and causal mutations, the use of whole genome resequencing (WGS) could increase predictive ability. However, empirical results comparing the use of WGS versus a set of SNPs show nil to marginal increase in genomic prediction accuracy (Lu et al . 2020; Yoshida and Yáñez 2021).…”

“…Owing to the inclusion of most of the causal mutations, and decreased limitation due to linkage between SNPs and causal mutations, the use of whole genome resequencing (WGS) could increase predictive ability. However, empirical results comparing the use of WGS versus a set of SNPs show nil to marginal increase in genomic prediction accuracy (Lu et al 2020;Yoshida and Yáñez 2021). This suggests WGS is unnecessary for this purpose and supports our suggestion that reduced genome representation provides accurate genomic prediction estimates to assist in the selection of elite broodstock lines.…”