QTLs Associated with Resistance to Cardiomyopathy Syndrome in Atlantic Salmon

Author:

Boison Solomon12,Ding Jingwen3,Leder Erica1,Gjerde Bjarne1,Bergtun Per Helge12,Norris Ashie12,Baranski Matthew12,Robinson Nicholas4

Affiliation:

1. Department of Breeding and Genetics, Nofima AS, Osloveien, Ås, Norway

2. Mowi Genetics AS, Sandviken, Bergen, Norway

3. Department of Aquaculture, Norwegian University of Life Sciences, Ås, Norway

4. Sustainable Aquaculture Laboratory - Temperate and Tropical (SALTT), School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia

Abstract

Abstract Cardiomyopathy syndrome (CMS) caused by piscine myocarditis virus is a major disease affecting the Norwegian Atlantic salmon industry. Three different populations of Atlantic salmon from the Mowi breeding program were used in this study. The first 2 populations (population 1 and 2) were naturally infected in a field outbreak, while the third population (population 3) went through a controlled challenged test. The aim of the study was to estimate the heritability, the genetic correlation between populations and perform genome-wide association analysis for resistance to this disease. Survival data from population 1 and 2 and heart atrium histology score data from population 3 was analyzed. A total of 571, 4312, and 901 fish from population 1, 2, and 3, respectively were genotyped with a noncommercial 55,735 Affymetrix marker panel. Genomic heritability ranged from 0.12 to 0.46 and the highest estimate was obtained from the challenge test dataset. The genetic correlation between populations was moderate (0.51–0.61). Two chromosomal regions (SSA27 and SSA12) contained single nucleotide polymorphisms associated with resistance to CMS. The highest association signal (P = 6.9751 × 10−27) was found on chromosome 27. Four genes with functional roles affecting viral resistance (magi1, pi4kb, bnip2, and ha1f) were found to map closely to the identified quantitative trait loci (QTLs). In conclusion, genetic variation for resistance to CMS was observed in all 3 populations. Two important quantitative trait loci were detected which together explain half of the total genetic variance, suggesting strong potential application for marker-assisted selection and genomic predictions to improve CMS resistance.

Funder

Norwegian Research Council

Publisher

Oxford University Press (OUP)

Subject

Genetics (clinical),Genetics,Molecular Biology,Biotechnology

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