Introduction
The sustainable development of European seabass aquaculture strongly depends on the ability to control the epidemics that can impact farms. For open ocean farms, one of the main threats is viral nervous necrosis (VNN) caused by the NNV virus which can cause up to 90% mortality. A bacterial pathogen, Vibrio harveyi is also considered a highly problematic pathogen across species, including seabass . The mortality caused by Vibrio harveyi can reach 50% in case of an outbreak. The French seabass breeding and hatchery industry is now leading the application of new selection methods , notably by being the first in Europe to have implemented genomic selection in this species.
In this study , we obtained whole-genome sequences (WGS; NovaSeq sequencer, Illumina) of sires and/or dams from several selection cohorts which enabled us to perform fine-mapping of QTL regions for VNN and Vibrio resistance. GWAS was performed for each population and each resistance phenotype separately, using a Bayesian sparse linear mixed model (BSLMM) with GEMMA software. The most interesting SNPs from each QTL identified by these models were integrated into a panel of SNPs genotyped with the Agriseq technology, in order to evaluate to identify to the effect of these candidate variants in the next generation of fish, for the two diseases studied.
Materials and methods
A total of 5799 European sea bass (Dicentrarchus labrax ) from two French breeding companies, EMGi and FMDS, were used in a first study (S1), to analyze VNN resistance. In a second study (S2), 3498 European sea bass (Dicentrarchus labrax ) from the French breeding companies EMGi was used to analyse resistance to Vibrio harveyi . T o study survival, all offspring were experimentally challenged to VNN in S1 and to Vibrio harveyi in S2. Both challenges were performed at the SYSAAF-ANSES Fortior Genetics platform (ANSES, Plouzané , France) to assess resistance by enumerating dead or surviving individuals. All challenged individuals were genotyped on the ThermoFisher 57K DlabCHIP SNP chip (Griot et al., 2021). The whole-genome of the sires and/or dams used in the crosses of the commercial populations were sequenced, on a NovaSeq sequencer (Illumina), in order to identify all genetic variants characterizing both populations. V ariant calling was processed according to the DeepVariant best practice and after classical filtering steps we identified nearly 1 million SNPs shared by the two commercial populations for S1, and 2.5 million SNPs for S2. Second, FImpute v2.2 software was used to obtain an imputed genotype for these million SNPs for all S1 and S2 offspring, using their known 57K genotype .
GWAS was performed for each population separately, using a Bayesian sparse linear mixed model (BSLMM) on a dataset of these imputed SNPs for all challenged individuals, using GEMMA software. Several QTL regions were identified on the European sea bass genome, 18 QTL in the S1 analysis (Delpuech et al., 2023) and 14 QTL in the S2 analysis with a Bayesian factor higher than 10 . From these QTL, 282 candidate variants for NNV resistance were selected, as well as 82 candidate variants for Vibrio harveyi resistance.
A validation approach for these candidate variants was performed. For this purpose, two groups of European sea bass offspring were created: the first group consisted of 2,772 individuals challenged for resistance to Vibrio harveyi , and the second group consisted of 3,401 individuals challenged for resistance to NNV. Genetic data from the tested individuals were obtained by targeted genotyping using AgriSeq sequencing (Thermofisher ). A total of 563 markers were genotyped and these markers can be divided into three groups, 199 markers to perform parentage assignment, 282 markers to detect NNV resistance, and 82 markers to detect Vibrio harveyi resistance. These disease resistance specific markers were genotyped in order to validate in the offspring generation a single nucleotide polymorphism identified by GWAS in the parental generation.
Results
C hallenges for individuals of the offspring generation were conducted over approximately 40 days. Survival rates were 59% for VNN challenges and 37% for Vibrio challenges . Peak mortality was at 17 days post-infection for VNN challenges and at 2 days post-infection for Vibrio challenges (Figure 1).
Survival rates were close to 50% as expected in both challenges . W e studied the effect on survival of the highest-effect QTLs identified in the parental generation, on LG12 for VNN (Figure 2a), and on LG22-25 for Vibrio harveyi (Figure2b). For each of the candidate markers presented, better survival was confirmed for resistant genotypes compared to susceptible genotypes, identified from previous generations via GWAS analyses.
Further analyses on validation of models for estimation of breeding values will be performed on the same data and presented at the conference.
Acknowledgments
This work is part of the GeneSea and MedMax projects, funded by the European Maritime and Fisheries Fund and French government under the numbers R FEA 4700 16 FA 100 0005 and FEA470020FA1000002.
References
Delpuech E, Vandeputte M, Morvezen R et al. Whole‐genome sequencing identifies interferon-induced protein IFI6/IFI27-like as a strong candidate gene for VNN resistance in European sea bass. Genet Sel Evol 55 , 30 (2023). https://doi.org/10.1186/s12711-023-00805-2
Griot R, Allal F, Phocas F, et al. , Genome-wide association studies for resistance to viral nervous necrosis in three populations of European sea bass (Dicentrarchus labrax) using a novel 57k SNP array DlabChip. Aquaculture , Volume 530, 2021. https://doi.org/10.1016/j.aquaculture.2020.735930