Comparing genomic signatures of domestication in two Atlantic salmon (Salmo salar L.) populations with different geographical origins

• Published in: Evolutionary Applications
• Main Authors: López, Maria, E, Benestan, Laura, Moore, Jean-Sébastien, Perrier, Charles, Gilbey, John, Genova, Alex, Di, Maass, Alejandro, Diaz, Diego, Lhorente, Jean-Paul, Correa, Katharina, Neira, Roberto, Bernatchez, Louis, Yáñez, José, M
• Other Authors: Universidad de Chile = University of Chile Santiago (UCHILE), Institut de Biologie Intégrative et des Systèmes Québec (IBIS), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD France-Sud )-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Marine Scotland Science (MSS), SOAFD Freshwater Fisheries Laboratory, Faskally, Center for Mathematical Modeling (CMM), Center for Genome Regulation Santiago (CGR), Aquainnovo, Núcleo Milenio de Salmónidos Invasores (INVASAL), Financial support was provided by CORFO (11IEI-12843 and 12PIE17669). We are grateful to Doctoral scholarship from CONICYT (21120382), Government of Chile; Canada–Chile Leadership Exchange Scholarship program, Government of Canada. JMY is supported by Núcleo Milenio INVASAL funded by Chile’s government program, Iniciativa Científica Milenio from Ministerio de Economía, Fomento y Turismo.
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2018
• Subjects: Salmo salar; selective sweeps; single nucleotide polymorphisms; [SDV.GEN]Life Sciences [q-bio]/Genetics; Atlantic salmon
• Online Access: https://hal.inrae.fr/hal-02921349; https://hal.inrae.fr/hal-02921349/document; https://hal.inrae.fr/hal-02921349/file/P31.Lopez-etal-EVA-2018.pdf; https://doi.org/10.1111/eva.12689

International audience Selective breeding and genetic improvement have left detectable signatures on the genomes of domestic species. The elucidation of such signatures is fundamental for detecting genomic regions of biological relevance to domestication and improving management practices. In aquaculture, domestication was carried out independently in different locations worldwide, which provides opportunities to study the parallel effects of domestication on the genome of individuals that have been selected for similar traits. In this study, we aimed to detect potential genomic signatures of domestication in two independent pairs of wild/domesticated Atlantic salmon populations of Canadian and Scottish origins, respectively. Putative genomic regions under divergent selection were investigated using a 200K SNP array by combining three different statistical methods based either on allele frequencies (LFMM, Bayescan) or haplotype differentiation (Rsb). We identified 337 and 270 SNPs potentially under divergent selection in wild and hatchery populations of Canadian and Scottish origins, respectively. We observed little overlap between results obtained from different statistical methods, highlighting the need to test complementary approaches for detecting a broad range of genomic footprints of selection. The vast majority of the outliers detected were population-specific but we found four candidate genes that were shared between the populations. We propose that these candidate genes may play a role in the parallel process of domestication. Overall, our results suggest that genetic drift may have override the effect of artificial selection and/or point toward a different genetic basis underlying the expression of similar traits in different domesticated strains. Finally, it is likely that domestication may predominantly target polygenic traits (e.g., growth) such that its genomic impact might be more difficult to detect with methods assuming selective sweeps.