Genome-wide association analysis of resistance to bacterial cold-water disease in an important rainbow trout aquaculture breeding population

Authors: SANTANA, BRUNA - University Of Connecticut; Palti, Yniv; Gao, Guangtu; Tripathi, Vibha; MARTIN, KYLE - Troutlodge, Inc; FRAGOMENI, BRENO - University Of Connecticut

Submitted to: Frontiers in Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/19/2025
Publication Date: 9/18/2025
Citation: Santana, B., Palti, Y., Gao, G., Tripathi, V., Martin, K.E., Fragomeni, B.O. 2025. Genome-wide association analysis of resistance to bacterial cold-water disease in an important rainbow trout aquaculture breeding population. Frontiers in Genetics. 16. Article 1582138. https://doi.org/10.3389/fgene.2025.1582138.
DOI: https://doi.org/10.3389/fgene.2025.1582138

Interpretive Summary: Bacterial cold water disease (BCWD) causes significant mortality and economic losses in rainbow trout aquaculture. The main goal of our research is to improve genetic resistance against this disease using state-of-the-art genome-wide association analyses and genomic selection approaches that improve the accuracy of genetic merit predictions in commercial breeding populations. Commercial rainbow trout breeding is complicated by multiple populations that spawn naturally at different times of the year and often multiple year-classes are maintained. Previously, we found that resistance to BCWD was controlled by five to six chromosome regions that harbor genes with moderate to large effect on disease resistance in a single commercial population. In the current study, we conducted genome-wide association analysis using rainbow trout from another commercially important population that was originated from a genetically different source population. Our results confirmed that resistance to BCWD in the new population is controlled primarily by the same two large effect genome regions that were previously identified in other rainbow trout populations. This study validated the underlying genetics of the trait in rainbow trout and shows that it is important to conduct new genomic analysis in each population to validate the results from previous studies as differences in the genetic architecture of disease resistance can exist between populations with different genetic background.

Technical Abstract: Bacterial cold-water disease (BCWD) outbreaks in salmonid aquaculture have resulted in significant losses in commercial populations. Currently, there is no commercially available vaccine for the disease caused by Flavobacterium psychrophilum. BCWD is responsive to antibiotic treatment, but this method may lead to increased production costs, the development of resistant pathogens, and environmental pollution. BCWD resistance in rainbow trout exhibits moderate heritability and has been the focus of selection efforts. The understanding of key genomic regions associated with BCWD resistance has advanced since the integration of genomic information into genetic evaluations, proving successful in enhancing BCWD resistance in some commercial lines. This study aimed to conduct genome-wide association analysis (GWAS) for BCWD resistance in an important commercial rainbow trout line to further our understanding about the genetic architecture of the trait, and infer a selective breeding strategy for this line. Different scenarios were tested, including the use of all SNPs passing quality control, removal of SNPs with major effect, elimination of consistent ‘major SNPs’ in subgroups of the population, and exclusion of SNPs within haplotypes with major effect. Prediction accuracy was evaluated with different SNP weighting strategies, utilizing cross-validation groups formed either randomly or based on principal components and cluster analyses of genotypic data. Comparative analysis of cross-validation methods suggested that K-means reduced overfitting. The incorporation of SNP weighting further confirmed the oligogenic nature of the trait under investigation. Prediction accuracy with PBLUP was 0.27, and increased to 0.36 with genomic information. The relative improvement in accuracy due to the inclusion of genomic information under single-step GBLUP with SNP weighting was 1.33. The accuracy obtained with a single haplotype was 0.23. Moreover, a decrease in accuracy was observed upon excluding major SNPs and haplotypes, providing supplementary evidence of their importance on phenotypes. The two largest association peaks in Omy25 and Omy8, observed under single-step GBLUP, were consistent with previous reports, while the most significant association with weighted single-step was found in Omy25.