Genomic insights into bacterial kidney disease resistance in Arctic charr (Salvelinus alpinus) via a 72k SNP array

Abstract

Selection for disease resistance forms one of the most highlighted areas of aquaculture breeding. A breeding program for Arctic charr has been operating in Sweden for over 40 years, making it the oldest of its kind worldwide for this species. However, the lack of available genomic resources prevented selection for any disease-resistance traits. A 72k Axiom SNP array was produced in this study and used to assess the potential to select for charr resistant to bacterial kidney disease (BKD), which is currently a major threat to the industry. Following a challenge experiment with Renibacterium salmoninarum, the causative agent of BKD, relevant phenotypic proxies were collected from approximately 2,000 charr. Thereafter, those animals were genotyped with the new 72k SNP array. The magnitude of the estimated variance components suggested potential for breeding for BKD resistance in charr, with relevant heritabilities ranging from 0.05 to 0.56 depending on the resistance proxy used. In addition, GWAS suggested that BKD resistance is a polygenic trait. Furthermore, genomic prediction approaches indicated that BKD-resistant animals can be identified using their SNP genotypes. Accuracies, expressed as Pearson correlation coefficients, when BKD resistance was analysed as a continuous trait, ranged from 0.42 to 0.52. In the scenario where BKD resistance was treated as a binary trait, the efficiency of genomic prediction was assessed using ROC curves, with an area under the curve of 0.72. Finally, no unfavourable correlations were found with growth traits. The developed 72k SNP array has the potential of being a pivotal tool for the Swedish Arctic charr breeding program. Moreover, our data support the use of genomic prediction in breeding BKD-resistant Arctic charr. As a critical next step, further validations in actual industry conditions would be required.