Advances made through family breeding at the Aquaculture Genetics and Breeding Technology Center at the Virginia Institute of Marine Science have yielded substantial gains in economically-important traits for the eastern oyster, Crassostrea virginica , including improvements in survival, growth rate and meat yield. Shape characteristics, such as fan shape and cup depth are monitored and included in a multi-trait selection index. Genetic g ains from family breeding are transferred to the commercial industry through yearly production of two licensed family-based broodstock lines. The lines are derived from top families for improved performance in low salinity , low disease-pressure environments and moderate salinity, high disease pressure environments .
Pedigree-based breeding has limitations , however, utilizing estimated breeding values (EBV) calculated as an average value for the family as a whole, thereby possibly under- or over-estimating the breeding potential of individuals. It also relies on assumed genetic relationships based on believed coancestry. In contrast, g enomic selection calculates more accurate breeding values and relationships through genotyping. Through combined efforts of the East Coast Oyster Breeding Consortium members , a 66K SNP array has been developed specifically for east coast oyster populations. ABC has utilized this tool to genotype over 4,700 oysters, (531 parents, 3073 progeny) from 4 years of family production and testing. In spring 2023, genomic selection was used for the first time to calculate genomic estimated breeding values (GEBV) on broodstock candidates, initially selected based on high EBV. The spread of GEBVs within families indicated a high degree of genetic gain is possible using genomic selection over pedigree-based approaches. To test this, s pawns were executed to create 57 high salinity , 57 low salinity a nd 5 low- ranked GEBV families. Field trials of these families, to be assessed in fall 2024, will be the first step in validation of realized gains associated with genomic selection.