Th-205A-11
Genome-Wide SNP Analysis Reveals a Genetic Basis for Sea-Age Variation in a Wild Atlantic Salmon Population

Thursday, August 21, 2014: 1:30 PM
205A (Centre des congrès de Québec // Québec City Convention Centre)
Craig Primmer , Biology, University of Turku, Turku, Finland
Susan Johnston , Biology, University of Turku, Turku, Finland
Panu Orell , Finnish Game & Fisheries Research Institute, Oulu, Finland
Victoria Pritchard , Biology, University of Turku, Turku, Finland
Eero Niemelä , Finnish Game & Fisheries Research Institute, Oulu, Finland
Sigbjorn Lien , Centre for Integrative Genomics, Aas, Norway
Matthew Kent , Centre for Integrative Genomics, Aas, Norway
Jaakko Erkinaro , Finnish Game & Fisheries Research Institute, Oulu, Finland
Classical life history theory predicts that trade-offs between reproductive success and survival should lead to the evolution of an optimal strategy in a given population. However, variation in mating strategies generally persists, and in general, there remains a poor understanding of genetic and physiological mechanisms underlying this variation. One extreme case of this is in Atlantic salmon (Salmo salar), which can show variation in the age at which they return from their marine migration to spawn (i.e. their “sea age”). This results in large size differences between strategies, with direct implications for individual fitness. Here, we used an Illumina Infinium SNP-array to identify regions of the genome associated with variation in sea age in a large population of Atlantic salmon in northern Europe, implementing individual-based genome-wide association studies (GWAS) and population-based F­ST outlier analyses. Several regions of the genome varied due to differences in phenotype and/or selection between sea ages, with nearby genes having functions related to muscle development, metabolism, immune response and mate choice. In addition, we found that individuals of different sea ages belong to different, yet sympatric populations in this system, indicating that reproductive isolation may be driven by divergence between stable strategies.