Abstract
Genomic selection has the potential to increase the rate of genetic gain in aquaculture breeding programs by enabling selection between and within families without phenotyping selection candidates. Due to the wide range of environments in which oysters are cultured, an industry-wide approach of multiple regional breeding programs has been suggested for Crassostrea sp. This necessitates genotyping large numbers of individuals across regions, and therefore implementation of genomic selection is predicated on cost-efficient genotyping. In this study, we examined the efficacy of three genotyping strategies in a simulated oyster breeding program informed by genotype data from existing breeding programs and Crassostrea populations worldwide. We found that, given oyster specific genome parameters, nearly maximal GEBV accuracy was achieved using high-density genotyping of broodstock in combination with low-density genotyping of 250–500 SNP loci for all other animals. Using pedigree-informed imputation methods to infer missing genotypes in the phenotyped and selection candidate animals produced functionally equivalent data to high-density genotyping of all individuals. This strategy can minimize genotyping costs for breeding programs and facilitate the adoption of genomic selection in Crassostrea aquaculture.
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