The structural variation landscape in 492 Atlantic salmon genomes

Alicia C. Bertolotti, Ryan M. Layer, Manu Kumar Gundappa, Michael D. Gallagher, Ege Pehlivanoglu, Torfinn Nome, Diego Robledo, Matthew P. Kent, Line L. Røsæg, Matilde M. Holen, Teshome D. Mulugeta, Thomas J. Ashton, Kjetil Hindar, Harald Sægrov, Bjørn Florø-Larsen, Jaakko Erkinaro, Craig R. Primmer, Louis Bernatchez, Samuel A. M. Martin, Ian A. Johnston, Simen R. Sandve, Sigbjørn Lien () and Daniel J. Macqueen ()
Additional contact information
Alicia C. Bertolotti: University of Aberdeen
Ryan M. Layer: University of Colorado
Manu Kumar Gundappa: University of Edinburgh
Michael D. Gallagher: University of Edinburgh
Ege Pehlivanoglu: University of Edinburgh
Torfinn Nome: Norwegian University of Life Sciences
Diego Robledo: University of Edinburgh
Matthew P. Kent: Norwegian University of Life Sciences
Line L. Røsæg: Norwegian University of Life Sciences
Matilde M. Holen: Norwegian University of Life Sciences
Teshome D. Mulugeta: Norwegian University of Life Sciences
Thomas J. Ashton: Xelect Ltd
Kjetil Hindar: Norwegian Institute for Nature Research (NINA)
Harald Sægrov: Rådgivende Biologer AS
Bjørn Florø-Larsen: Norwegian Veterinary Institute
Jaakko Erkinaro: Natural Resources Institute Finland (Luke)
Craig R. Primmer: University of Helsinki
Louis Bernatchez: Université Laval Québec
Samuel A. M. Martin: University of Aberdeen
Ian A. Johnston: Xelect Ltd
Simen R. Sandve: Norwegian University of Life Sciences
Sigbjørn Lien: Norwegian University of Life Sciences
Daniel J. Macqueen: University of Edinburgh

Nature Communications, 2020, vol. 11, issue 1, 1-16

Abstract: Abstract Structural variants (SVs) are a major source of genetic and phenotypic variation, but remain challenging to accurately type and are hence poorly characterized in most species. We present an approach for reliable SV discovery in non-model species using whole genome sequencing and report 15,483 high-confidence SVs in 492 Atlantic salmon (Salmo salar L.) sampled from a broad phylogeographic distribution. These SVs recover population genetic structure with high resolution, include an active DNA transposon, widely affect functional features, and overlap more duplicated genes retained from an ancestral salmonid autotetraploidization event than expected. Changes in SV allele frequency between wild and farmed fish indicate polygenic selection on behavioural traits during domestication, targeting brain-expressed synaptic networks linked to neurological disorders in humans. This study offers novel insights into the role of SVs in genome evolution and the genetic architecture of domestication traits, along with resources supporting reliable SV discovery in non-model species.

Date: 2020
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DOI: 10.1038/s41467-020-18972-x

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