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

Abstract

Viral Nervous Necrosis (VNN) is a major threat for the European sea bass (Dicentrarchus labrax) aquaculture industry. The improvement of disease resistance through selective breeding is a promising option to reduce outbreaks. With the development of high-throughput genotyping technologies, identification of genomic regions involved in the resistance could improve the efficiency of selective breeding. The aim of this study was to identify quantitative trait loci (QTL) involved in VNN resistance and to quantify their effect.Four experimental backcross families comprising 378, 454, 291 and 211 individuals and two commercial populations A and B comprising 1027 and 1042 individuals obtained from partial factorial crosses (59♂ x 20♀ for pop A; 39♂ x 14♀ for pop B) were submitted to a redspotted grouper nervous necrosis virus (RGNNV) challenge by bath. A high-density single nucleotide polymorphism (SNP) chip panel was designed to develop the ThermoFisher Axiom™ 57 k SNP DlabChip, which was used for genotyping all individuals and building a high quality linkage map. In the backcross families, composite interval mapping was performed on 30,917, 23,592, 30,656 and 31,490 markers, respectively. In the commercial populations, 40,263 markers in pop A and 41,166 markers in pop B were used to perform genome-wide association studies (GWAS) using a GBLUP and a BayesCπ approach.Please note that this is an author-produced PDF of an article accepted for publication following peer review. The definitive publisher-authenticated version is available on the publisher Web site.One QTL was identified on chromosome LG12 in three of the four experimental backcross families, and one additional QTL on LG8 was detected in only one family. In commercial populations, QTL mapping revealed a total of seven QTLs, among which the previously mentioned QTL on LG12 was detected in both. This QTL, which was mapped to an interval of 3.45 cM, explained 9.21% of the total genetic variance in pop A, while other identified QTLs individually explained less than 1% of the total genetic variance.The identification of QTL regions involved in VNN resistance in European sea bass, with one having a strong effect, should have a great impact on the aquaculture industry. Future work could focus on the fine mapping of the causal mutation present on LG12 using whole genome sequencing. Highlights► Viral Nervous Necrosis is a major disease for European sea bass. ► A novel SNP array for European sea bass was designed. ► A total of nine QTL were detected. ► One QTL, shared by five over six of the data sets and located on the LG12 explained 9.2% of the total genetic variance.

Optimization of Genomic Selection to Improve Disease Resistance in Two Marine Fishes, the European Sea Bass (Dicentrarchus labrax) and the Gilthead Sea Bream (Sparus aurata)

“…The heritability estimates were very different between linear model and threshold model, even after applying the correction of the linear estimates proposed by Dempster and Lerner (1950) (data not shown). Our heritability estimates were similar to those reported in former studies, when available: for VNN resistance in sea bass, threshold model heritability estimates were in the range 0.21-0.42, to be compared to previous values of 0.24-0.43 estimated using threshold model or linear model corrected using Dempster and Lerner formula (Doan et al, 2017;Palaiokostas et al, 2018;Griot et al, 2021). For pasteurellosis resistance in sea bream, our estimates from linear model (0.14-0.16) were in the lower range of those from previous studies, estimated using linear model (0.22-0.45) (Antonello et al, 2009;Palaiokostas et al, 2016;Aslam et al, 2018).…”

“…One other factor that can explain the difference in accuracy between traits is the genetic architecture. As VNN resistance was reported to be an oligogenic trait (Griot et al, 2021), a model that can take advantage of genetic architectures that are not polygenic (wssGBLUP or BayesB) could perform better than a GBLUP model (Daetwyler et al, 2010;Vallejo et al, 2017).…”

“…Cohort VIB (2,100 individuals) was produced by mating 60 sires with 18 dams in three factorial subsets (20 × 6, 20 × 7, and 20 × 5) and cohort PAS (1,200 individuals) was produced by mating 50 sires with 23 dams in 6 factorial subsets (8 × 4, 10 × 3, 7 × 4, 10 × 4, 7 × 5, and 8 × 3). The cohorts VNN_A and VNN_B were referred as popA and popB in Griot et al (2021).…”

“…In Griot et al (2021), the authors showed that one strong effect QTL is involved in VNN resistance in European sea bass. Among the markers within the confidence interval, they highlighted one marker (LG12_8815613) with high potential for marker assisted selection.…”

“…To select for genetically resistant individuals, enough genetic variability must exist within the species. Moderate to high heritability (0.24-0.43) has been reported for resistance to VNN in European sea bass (Doan et al, 2017;Palaiokostas et al, 2018;Griot et al, 2021) and for resistance to pasteurellosis in gilthead sea bream (from 0.22 to 0.32) (Palaiokostas et al, 2016;Aslam et al, 2018), thus presenting opportunity for genetic improvement.…”