Potential of genomic selection for improvement of resistance to ostreid herpesvirus in Pacific oyster (Crassostrea gigas)

Abstract

Summary In genomic selection (GS), genome‐wide SNP markers are used to generate genomic estimated breeding values for selection candidates. The application of GS in shellfish looks promising and has the potential to help in dealing with one of the main issues currently affecting Pacific oyster production worldwide, which is the ‘summer mortality syndrome’. This causes periodic mass mortality in farms worldwide and has mainly been attributed to a specific variant of the ostreid herpesvirus (OsHV‐1). In the current study, we evaluated the potential of genomic selection for host resistance to OsHV‐1 in Pacific oysters, and compared it with pedigree‐based approaches. An OsHV‐1 disease challenge was performed using an immersion‐based virus exposure treatment for oysters for 7 days. A total of 768 samples were genotyped using the medium‐density SNP array for oysters. A GWAS was performed for the survival trait using a GBLUP approach in blupf90 software. Heritability ranged from 0.25 ± 0.05 to 0.37 ± 0.05 (mean ± SE) based on pedigree and genomic information respectively. Genomic prediction was more accurate than pedigree prediction, and SNP density reduction had little impact on prediction accuracy until marker densities dropped below approximately 500 SNPs. This demonstrates the potential for GS in Pacific oyster breeding programmes, and importantly, demonstrates that a low number of SNPs might suffice to obtain accurate genomic estimated breeding values, thus potentially making the implementation of GS more cost effective.

Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster (Crassostrea angulata) Using DArT-Seq Technology

“…prevalence and 0.10 for M. chungmuensis, suggesting that there is limited scope for selection against these disease traits in this population using genomic information. Our heritability estimates for disease related traits were significantly lower than those obtained for Ostreid herpesvirus disease trait in the Pacific oyster [23]. However, the results from our study originated from a field trial with natural pathogen challenge compared with pathogen specific challenge in the Pacific oyster [23].…”

“…To date, prediction accuracies have been reported in several fish and shrimp species, ranging from 0.16 to 0.83 for growth, carcass and meat quality traits, and disease resistance [15][16][17][18][19][20][21]. In molluscs, genomic selection is less common, but has been used to evaluate growth traits [22], disease resistance [23] in the Pacific oyster Crassostrea gigas, and pearl quality traits in the Pearl oyster Pinctada maxima [24]. Although genomic selection has been routinely adopted in other industries, it has not yet been widely used in aquaculture.…”

Functional Insights From the Evolutionary Diversification of Big Defensins

“…Breeding programs in C. gigas produced oyster families with different (stable) levels of resistance to POMS (80,81), triggered by the OsHV-1 µvar virus. Resistance was identified as heritable (80,82) with some candidate markers having a role in distinct antiviral pathways (79,83). Big defensins and other AMPs were not identified as associated with resistance to POMS, probably because the bacteremia comes as a secondary infection in this virus-induced immunosuppressive disease.…”

A chromosome-level genome assembly for the Pacific oyster (Crassostrea gigas)

“…Advances in DNA sequencing technologies led to rapid additional resource development for this species, including extensive transcriptome datasets [22-26], linkage maps using microsatellite and more recently SNP markers [27, 28], and medium and high density SNP arrays [29, 30]. These tools have become valuable genomic resources to enhance genetic improvement of production traits, such as growth and disease resistance [31, 32]. Nevertheless, a key resource for enabling genetics and genomic research in a given species is a high quality reference genome.…”