Introduction
Oyster farming is a major aquaculture industry worldwide, with the Pacific oyster being the most widely cultivated species. Controlled reproduction in hatcheries enables the production of genetically improved seed using polyploidy or selective breeding. Selective breeding programs have been applied successfully in different oyster species, including the Pacific oyster, using mass selection and pedigree-based approaches. Recent advances in genomics have led to the development of high-density SNP arrays for several bivalve species, including the Pacific oyster. Genomic selection can accelerate genetic gain by reducing the generation interval and increasing selection accuracy. However, the success of genomic selection relies on the availability of accurate and reliable phenotype and genotype data, as well as appropriate statistical models. The aim of our study was to assess the potential of genomic selection for growth and quality traits in two independent mixed-family breeding designs at commercial scale in C. gigas selected lines.
Material and Methods
The study used oysters from two French breeding companies, each from a population that underwent six to eight generations of mass selection, mostly for resistance to OsHV-1, growth, and morphology. The first population resulted from seven full-factorial crosses of ten males and ten females each, generating 700 full-sib families, while the second population resulted from six full-factorial crosses of ten males and eight females each, generating 480 full-sib families. The oysters were phenotyped at 36 and 31 months old for various traits, and their genetic variability was monitored with genetic markers. All parents and offspring were genotyped on the bi-species Axiom Affymetrix 57K oyster array, Axiom_Oyster02, comprising 40,625 markers for C. gigas, and quality control analyses were carried out to ensure the quality of the data.
Results & Discussion
LD (linkage disequilibrium) strongly decreased with distance between pairs of SNPs for both populations, and that P1 had higher LD than P2 throughout the genome. Parentage assignment rates were high in both populations, with P2 having a lower assignment rate due to missing genotypes for four parents. Effective population size (Ne) was estimated at 107 for P1 and 76 for P2. Heritability was estimated for each trait and population and ranged from 0.08 ± 0.04 to 0.56 ± 0.08 for a pedigree-based model and from 0.04 ± 0.02 to 0.69 ± 0.04 for a genomic-based model. Growth-related traits were generally highly genetically and positively correlated with each other, but weakly correlated with colour traits. Accuracy of prediction was generally higher with the genomic model (GBLUP) than with the classical BLUP model, with a maximum gain of accuracy (from 0.38 to 0.66) for flesh weight adjusted by total weight in P2. Accuracy of breeding values was slightly higher for colour traits for P2, with higher heritability estimates.
Conclusion
The study found that genomic selection and mixed-family designs can improve growth and color traits in Pacific oysters. Both breeding programs evaluated showed substantial genetic variation and good genetic diversity. However, better genomic tools are needed, and interactions between genotype and environment should be evaluated to optimize breeding programs for hatcheries.
Acknowledgement
The data presented here were obtained in the Quality-Huitre project which received funding from the European Maritime and Fisheries Fund (EMFF) research grant number PFEA470018FA1000011.