The accuracy of genomic predictions for bacterial cold water disease resistance remains higher than the pedigree-based model one generation after model training in a commercial rainbow trout breeding population

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. Previously, we reported high genomic prediction accuracy of 0.72 for BCWD resistance rainbow trout using the 57 K Axiom SNP array. Due to cost phenotyping genotyping breeding programs, it is paramount know if acceptable can be obtained subsequent generation without retraining model. In current study, found that model was reduced from 0.65 0.61 0.56 0.53 a lower density array 10 SNPs panel 49 QTL-linked SNPs, respectively. Although markedly than with retraining, better pedigree-based (PBLUP) (0.48) substantially higher PBLUP (0.22). We conclude selection provides traditional even when ‘skipping’ one retraining. The weighted single-step GBLUP (wssGBLUP) Bayesian multiple regression BayesB (ssBMR-BayesB) had (ssGBLUP), which consistent oligogenic inheritance this population. Imputation genotypes back did not improve prediction, likely due linkage disequilibrium aquaculture populations architecture resistance.