Genomic selection study on resistance to Cryptocaryon irritans in turbot (Scophthalmus maximus)

Cryptocaryon irritans , the causative agent of Cryptocaryoniasis disease, poses a major threat to turbot ( Scophthalmus maximus ) aquaculture. This study presents the first comprehensive genomic selection (GS) analysis for C. irritans resistance in turbot. A breeding population comprising 30 full-sib families was challenged with C. irritans via cohabitation, and survival time was recorded as the resistance phenotype. Whole-genome resequencing of 458 fish produced 3276,196 high-quality SNPs for analysis. Genomic heritability estimates ranged from 0.28 to 0.33, substantially higher than the pedigree-based estimate (0.25). All genomic prediction models (GBLUP, ssGBLUP, BayesA, BayesB, Bayes Lasso) significantly outperformed traditional pedigree-based BLUP in cross-validation. Although ssGBLUP achieved numerically higher accuracy, the performance differences among the GS models were marginal. Furthermore, prediction accuracy plateaued at approximately ∼10k SNPs, indicating that a low-density SNP panel is sufficient for accurate genomic prediction. Our findings demonstrate that C. irritans resistance is a heritable trait in turbot that can be effectively improved through GS, providing a foundation for implementing cost-effective breeding programs to enhance disease resistance in this high-value species. • All evaluated GS models significantly outperformed traditional pedigree-based methods in predicting resistance to Cryptocaryon irritans. • The ssBLUP method achieved only a slight advantage over other genomic prediction approaches. • Accurate genomic prediction can be achieved with a cost-effective low-density SNP panel (∼10k markers).