Amoebic gill disease (AGD) is one of the largest threats to salmon aquaculture. Although initially limited to Tasmania, AGD is now observed in salmon production worldwide and causes serious economic and animal welfare burden. Treatments are expensive and can be environmentally damaging, hence the need for alternative strategies. Breeding for disease resistance can contribute to control of AGD, providing long-term cumulative benefits in selected stocks. The use of genomic selection can expedite selection for disease resistance, since selection accuracy is typically improved compared to pedigree-based approaches. The aim of this work was to quantify and characterise genetic variation in AGD resistance in salmon, the architecture of the trait, and the potential of genomic selection as a contributor to disease control. An AGD challenge was performed in 1,500 Atlantic salmon, using gill damage (mean gill score) and amoebic load (qPCR) as indicator traits. Our findings show that both traits are heritable and show high positive correlation, indicating they may be good measurements of host resistance to AGD. Heritability of resistance was moderate in magnitude (h2 0.25-0.30) and underpinned by a largely polygenic genetic architecture. However, two regions on chromosome 18 were identified with a suggestive association with both AGD resistance traits, and merit independent verification and potentially functional studies to identify underlying genes. Accuracy of prediction for both traits using genetic markers was up to 18 % higher than using pedigree alone, and reduction in marker density as low as <1,000 SNPs was sufficient to obtain that accuracy. This work shows that resistance to AGD is a suitable trait for genomic selection, and the addition of this trait to Atlantic salmon breeding programs can lead to more resistant stocks. Keywords: aquaculture, amoebic gill disease, Salmo salar, disease resistance
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Electronic Poster Session - Species - Aquaculture 1, , 467, 2018
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