Olive flounder (Paralichthys olivaceus ) is one of the major mariculture fish species in the aquaculture industry of South Korea . In recent years, flounder farms have been facing huge economic losses due to several diseases. In particular, E. piscicida is an important pathogen that causes high mortality in a variety of farmed fish, and flounder is also susceptible to it. Currently, management programs such as vaccination and improvement of aquaculture facilities are being implemented in Korea, however, genomic breeding programs to develop E. piscicida -resistant flounder have not been conducted.
In this study, we performed a genome-wide association study (GWAS) and prediction model construction to identify significant SNPs and prediction accuracy associated with E. piscicida resistance in flounder. 810 healthy flounders were subjected to an E. piscicida challenge experiment, and genomic DNA was extracted from excised fin tissue and utilized for high-density SNP chip analysis. After quality control, a total of 49,363 SNP markers from 577 flounders remained from an initial set of 57,754 markers. Through GWAS, we identified at least one significant SNP from each defined trait: day post-challenge (DPC_date), and stage of mortality (STAGE). Th e heritability of flounder resistance against E. piscicida was around 0.13-0.20 . Among the prediction methods tested, GBLUP and BayesB achieved the highest prediction accuracy using a 3-fold cross-validation approach. Collectively, we suggested that these findings provide an approach to genomic breeding programs in flounder for the resistance to E. piscicida.