Evaluation for the effect of low-coverage sequencing on genomic selection in large yellow croaker

Low-coverage whole-genome sequencing (WGS) is a cost-effective genotyping technique. Combined with the imputation method, it can generate large numbers of SNPs and provide an opportunity for genomic selection (GS) using whole-genome SNPs to estimate genomic breeding values (GEBVs). However, it is unclear whether low coverage WGS is effective for GS in large yellow croakers, even or in aquaculture populations more generally. In this study, 536 fish were sequenced with whole-genome sequencing at average depth of 8x. Low-coverage WGS datasets with different depth of 0.05x, 0.1x, 0.5x, 1x, and 4x, were generated by down-sampling of reads at 8x. For the real phenotype of visceral white spot disease and simulated polygenic traits with different heritability size and QTL numbers, we evaluate the effect of low-coverage WGS on prediction accuracy of GEBVs. The results indicate that the depth of 0.5x can almost acquire the same prediction accuracy as that of 8x in both real and simulated datasets. We also investigate the prediction accuracy of population relationship between training and validation sets. It is found that depth at 0.5x almost has the same accuracy as that of 8x. However, the accuracy of the closely-related population is twice higher than that of the distantly-related population. These findings suggest that low-coverage WGS is suitable for GS in large yellow croaker.

Automated summary

The study demonstrates that low-coverage whole-genome sequencing is effective for genomic selection in large yellow croakers, with a depth of 0.5x achieving almost the same prediction accuracy as 8x. Additionally, population relationship prediction accuracy is higher in closely-related populations compared to distantly-related populations.