|HOLLENBECK, CHRISTOPHER - Texas A&M University|
|MATT, JOSEPH - Texas A&M University|
Submitted to: Aquaculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/13/2022
Publication Date: 1/15/2023
Citation: Delomas, T.A., Hollenbeck, C.M., Matt, J.L., Thompson, N. 2023. Evaluating cost-effective genotyping strategies for genomic selection in oysters. Aquaculture. 562:738844. https://doi.org/10.1016/j.aquaculture.2022.738844.
Interpretive Summary: Genomic selection has the potential to increase the speed at which lines of oysters and other shellfish are improved through selective breeding. However, adoption of this technique by shellfish breeding programs has been hampered by the high cost of genotyping. We evaluated several strategies for lowering the cost of genotyping via simulation analyses in an oyster breeding program. Initial analyses were conducted with data that simulated a generic oyster population, using genetic characteristics of Pacific and eastern oysters to define the population. Additional analyses utilized empirical data from five populations distributed globally, to further investigate the utility of different genotyping strategies using real-world data. The results identified a cost-effective genotyping strategy that will allow oyster breeding programs to implement genomic selection. The identified strategy consists of applying a high-density genetic panel to broodstock and a low-density genetic panel to all other animals. A statistical process called imputation is then used to fill in the genetic data missing from the low-density panel.
Technical 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.