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Abstract
Non-synonymous variation (NSV) of protein coding genes represents raw material for selection to improve adaptation to the diverse environmental scenarios in wild and livestock populations. Many aquatic species face variations in temperature, salinity and biological factors throughout their distribution range that is reflected by the presence of allelic clines or local adaptation. The turbot (Scophthalmus maximus) is a flatfish of great commercial value with a flourishing aquaculture which has promoted the development of genomic resources. In this study, we developed the first atlas of NSVs in the turbot genome by resequencing 10 individuals from Northeast Atlantic Ocean. More than 50,000 NSVs where detected in the ~ 21,500 coding genes of the turbot genome, and we selected 18 NSVs to be genotyped using a single Mass ARRAY multiplex on 13 wild populations and three turbot farms. We detected signals of divergent selection on several genes related to growth, circadian rhythms, osmoregulation and oxygen binding in the different scenarios evaluated. Furthermore, we explored the impact of NSVs identified on the 3D structure and functional relationship of the correspondent proteins. In summary, our study provides a strategy to identify NSVs in species with consistently annotated and assembled genomes to ascertain their role in adaptation.
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Details
1 Nofima, Ås, Norway (GRID:grid.22736.32) (ISNI:0000 0004 0451 2652); Norwegian University of Life Sciences (NMBU), Department of Animal and Aquacultural Sciences, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X)
2 University of Santiago de Compostela, Department of Zoology, Genetics and Physical Anthropology, Faculty of Veterinary, Lugo, Spain (GRID:grid.11794.3a) (ISNI:0000000109410645)
3 CNR, Institute of Chemical Sciences and Technologies “Giulio Natta” (SCITEC), Rome, Italy (GRID:grid.5326.2) (ISNI:0000 0001 1940 4177)
4 University of Edinburgh, The Roslin Institute and Royal (Dick) School of Veterinary Studies, Midlothian, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988)