QTLs Associated with Resistance to Cardiomyopathy Syndrome in Atlantic Salmon.
Atlantic salmon
QTL analysis
cardiomyopathy syndrome
field outbreak
genetic correlations
heritability
Journal
The Journal of heredity
ISSN: 1465-7333
Titre abrégé: J Hered
Pays: United States
ID NLM: 0375373
Informations de publication
Date de publication:
10 10 2019
10 10 2019
Historique:
received:
18
01
2019
accepted:
01
07
2019
pubmed:
10
7
2019
medline:
21
7
2020
entrez:
10
7
2019
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 31287894
pii: 5530261
doi: 10.1093/jhered/esz042
pmc: PMC6785937
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
727-737Informations de copyright
© The American Genetic Association 2019.
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