First single-step genomic prediction and genome-wide association for body weight in Russian sturgeon (Acipenser gueldenstaedtii)

Abstract

Russian sturgeon (Acipenser gueldenstaedtii)—a species of sturgeon—has a high economic value as a source of caviar and high-quality meat products. Genomic selection (GS) has the potential to shorten generation intervals and improve genetic gain for the key target traits of a breeding program. However, it has not been applied on sturgeon. We evaluated the performance of GS in breeding value estimation and carried out genome-wide association studies (GWAS) to dissect the genetic architecture of economically vital growth trait (body weight) in Russian sturgeon. Of a total of 3430 Russian sturgeons with phenotype records, 236 were sequenced. Through 10 replicates of fivefold cross-validation, we compared the accuracy of prediction obtained from a pedigree-based best linear unbiased prediction (BLUP), a single-step genomic BLUP (ssGBLUP), and a weighted ssGBLUP (WssGBLUP). We used single-step GWAS (ssGWAS) method to perform GWAS. The results showed that predictions made using ssGBLUP and WssGBLUP were 6.9% and 12.4% more accurate, respectively, compared with pedigree-based BLUP. Among the single-step methods, the performance of WssGBLUP was the best with the smallest mean squared (absolute) error. In addition, ssGWAS identified 3 potential SNPs with suggestive significance that were associated with body weight. Moreover, NOS1AP, CHMP4A, and RBMS1 genes were highlighted as functionally plausible candidate genes underlying the genetic architecture of body weight. These findings illustrate that the using GS in Russian sturgeon breeding could help in better selection of breeding candidates to facilitate complex economic growth trait.