Genetic Variation, GWAS and Accuracy of Prediction for Host Resistance to in Farmed Gilthead Sea Bream ().

Gilthead sea bream () belongs to a group of teleost which has high importance in Mediterranean aquaculture industry. However, industrial production is increasingly compromised by an elevated outbreak of diseases in sea cages, especially a disease caused by monogeneans parasite This parasite mainly colonizes gill tissues of host and causes considerable economical losses with mortality and reduction in growth. The aim of current study was to explore the genetics of host resistance against and investigate the potential for genomic selection to possibly accelerate genetic progress. To achieve the desired goals, a test population derived from the breeding nucleus of Andromeda Group was produced. This experimental population was established by crossing of parents mated in partial factorial crosses of ∼8 × 8 using 58 sires and 62 dams. The progeny obtained from this mating design was challenged with using a controllable cohabitation infection model. At the end of the challenge, fish were recorded for parasite count, and all the recorded fish were tissue sampled for genotyping by sequencing using 2b-RAD methodology. The initial (before challenge test) and the final body weight (after challenge test) of the fish were also recorded. The results obtained through the analysis of phenotypic records ( = 615) and the genotypic data ( = 841, 724 offspring and 117 parents) revealed that the resistance against this parasite is lowly heritable ( = 0.147 with pedigree and 0.137 with genomic information). We observed moderately favorable genetic correlation ( = -0.549 to -0.807) between production traits (i.e., body weight and specific growth rate) and parasite count, which signals a possibility of indirect selection. A locus at linkage group 17 was identified that surpassed chromosome-wide Bonferroni threshold which explained 22.68% of the total genetic variance, and might be playing role in producing genetic variation. The accuracy of prediction was improved by 8% with genomic information compared to pedigree.