Genome-Wide Association and Genomic Prediction of Growth Traits in the European Flat Oyster (Ostrea edulis)

Abstract

The European flat oyster (Ostrea edulis) is a bivalve mollusc that was once widely distributed across Europe and represented an important food resource for humans for centuries. Populations of O. edulis experienced a severe decline across their biogeographic range mainly due to overexploitation and disease outbreaks. To restore the economic and ecological benefits of European flat oyster populations, extensive protection and restoration efforts are in place within Europe. In line with the increasing interest in supporting restoration and oyster farming through the breeding of stocks with enhanced performance, the present study aimed to evaluate the potential of genomic selection for improving growth traits in a European flat oyster population obtained from successive mass-spawning events. Four growth-related traits were evaluated: total weight (TW), shell height (SH), shell width (SW) and shell length (SL). The heritability of the growth traits was in the low-moderate range, with estimates of 0.45, 0.37, 0.22, and 0.32 for TW, SH, SW and SL, respectively. A genome-wide association analysis revealed a largely polygenic architecture for the four growth traits, with two distinct QTLs detected on chromosome 4. To investigate whether genomic selection can be implemented in flat oyster breeding at a reduced cost, the utility of low-density SNP panels was assessed. Genomic prediction accuracies using the full density panel were high (> 0.83 for all traits). The evaluation of the effect of reducing the number of markers used to predict genomic breeding values revealed that similar selection accuracies could be achieved for all traits with 2K SNPs as for a full panel containing 4,577 SNPs. Only slight reductions in accuracies were observed at the lowest SNP density tested (i.e., 100 SNPs), likely due to a high relatedness between individuals being included in the training and validation sets during cross-validation. Overall, our results suggest that the genetic improvement of growth traits in oysters is feasible. Nevertheless, and although low-density SNP panels appear as a promising strategy for applying GS at a reduced cost, additional populations with different degrees of genetic relatedness should be assessed to derive estimates of prediction accuracies to be expected in practical breeding programmes.

Chromosome‐level reference genome for European flat oyster (Ostrea edulis L.)

“…In this regard, the genome reported here is proving useful already, with a recent study revealing that SNP markers previously associated with Bonamia resistance (Vera et al, 2019) are located in high linkage-disequilibrium across a large region of superscaffold 8, which contains many candidate immune genes (Sambade et al, 2022). Another recent study has mapped variants genotyped with an existing medium density SNP array (Gutierrez et al, 2017) against our new O. edulis genome, identifying QTLs underpinning variation in growth traits on super-scaffold 4 (Peñaloza et al, 2022).…”

Chromosome level reference genome for European flat oyster (Ostrea edulis L.)

“…In this regard, the genome reported here is proving useful already, with a recent study revealing that SNP markers previously associated with Bonamia resistance (Vera et al, 2019) are located in high linkage-disequilibrium across a large region of super-scaffold 8, which contains many candidate immune genes (Martinez et al 2022). Another recent study from has mapped variants genotyped with an existing medium density SNP array (Gutierrez et al, 2017) against our new O. edulis genome, identifying QTLs underpinning variation in growth traits on super-scaffold 4 (Peñaloza et al, 2022). Via its public release with all accompanying raw data, we anticipate rapid uptake of our genome by the research community, and envisage the next steps for the field to include broader surveys of genome-wide diversity covering a global representation of populations.…”

Potential of imputation for cost-efficient genomic selection for resistance toFlavobacterium columnarein rainbow trout (Oncorhynchus mykiss)

“…Those values of 3K-7K SNPs being sufficient in aquaculture species to reach near maximum accuracy of prediction are in the range of what has been reported in other aquaculture species for various traits, although the maximum accuracy was usually estimated based on medium density panels ranging from 10K to 70K SNPs (17,18,20,26,29,32,(51)(52)(53)(54). The number of SNP required to accurately estimate breeding values in aquaculture species and particularly salmonids are substantially lower than what was reported for terrestrial species which ranged between 49K SNPs for pig and 168K SNPs for Holstein cattle (55,56).…”

“…Depending on the species and the trait (reviewed in Song et al, 2022) (11) are sufficient to achieve an accuracy of genomic prediction similar to that obtained with a medium or high-density panel. In those studies, further reduction of the density to hundreds of SNPs resulted in a significant drop in accuracy (17,20). This issue could potentially be resolved via the use of imputation.…”