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; Sigbjorn  Lien; Daniel John MacQueen

doi:10.1038/s41467-020-18972-x

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 JohnstonSimen R. Sandve, Sigbjorn Lien^* (Corresponding Author), Daniel John MacQueen^* (Corresponding Author)

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

38 Citations (Scopus)

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.

Original language	English
Article number	5176
Number of pages	16
Journal	Nature Communications
Volume	11
DOIs	https://doi.org/10.1038/s41467-020-18972-x
Publication status	Published - 14 Oct 2020

Keywords

ALIGNMENT
GENETICS
EVOLUTION
BEHAVIOR
FORMAT
TOOL

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Bertolotti, A. C., Layer, R. M., Gundappa, M. K., Gallagher, M. D., Pehlivanoglu, E., Nome, T., Robledo, D., Kent , M. P., Røsæg, L. L., Holen, M. M., Mulugeta, T. D., Ashton, T. J., Hindar, K., Sægrov, H., Florø-Larsen, B., Erkinaro, J., Primmer, C. R., Bernatchez, L., Martin, S. A. M., ... MacQueen, D. J. (2020). The structural variation landscape in 492 Atlantic salmon genomes. Nature Communications, 11, [5176]. https://doi.org/10.1038/s41467-020-18972-x

Bertolotti, AC, Layer, RM, Gundappa, MK, Gallagher, MD, Pehlivanoglu, E, Nome, T, Robledo, D, Kent , MP, Røsæg, LL, Holen, MM, Mulugeta, TD, Ashton, TJ, Hindar, K, Sægrov, H, Florø-Larsen, B, Erkinaro, J, Primmer, CR, Bernatchez, L, Martin, SAM, Johnston, IA, Sandve, SR, Lien, S & MacQueen, DJ 2020, 'The structural variation landscape in 492 Atlantic salmon genomes', Nature Communications, vol. 11, 5176. https://doi.org/10.1038/s41467-020-18972-x

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title = "The structural variation landscape in 492 Atlantic salmon genomes",

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.",

keywords = "ALIGNMENT, GENETICS, EVOLUTION, BEHAVIOR, FORMAT, TOOL",

author = "Bertolotti, {Alicia C} and Layer, {Ryan M.} and Gundappa, {Manu Kumar} and Gallagher, {Michael D} and Ege Pehlivanoglu and Torfinn Nome and Diego Robledo and Kent, {Matthew P.} and R{\o}s{\ae}g, {Line L.} and Holen, {Matilde M.} and Mulugeta, {Teshome D.} and Ashton, {Thomas J.} and Kjetil Hindar and Harald S{\ae}grov and Bj{\o}rn Flor{\o}-Larsen and Jaakko Erkinaro and Primmer, {Craig R} and Louis Bernatchez and Martin, {Samuel A M} and Johnston, {Ian A} and Sandve, {Simen R.} and Sigbjorn Lien and MacQueen, {Daniel John}",

note = "Acknowledgements: The study was supported by Biotechnology and Biological Sciences Research Council grants BB/M016455/1, BB/S004181/1, BBS/E/D/10002070 and BBS/E/D/30002275. Wild Atlantic salmon genome sequencing was funded by the Research Council of Norway (The Aqua Genome project; ref: 221734). We thank Dr. Chris Hollenbeck (formerly Xelect Ltd; currently Texas A&M, USA) for support with Snakemake and Drs. Serap Gonen and Matt Baranski (Mowi AS) for sharing sequencing data. We thank Terese Andersstuen and Dr. Mariann {\'A}rnyasi (both NMBU) for organizing the sequencing of wild Atlantic salmon samples. We acknowledge the use of computing clusters at the University of Aberdeen (Maxwell), University of Edinburgh (EDDIE) and CIGENE, NMBU (Orion). Storage resources were provided by the Norwegian National Infrastructure for Research Data (NIRD, project NS9055K). D.J.M. thanks Prof. Seth Grant (University of Edinburgh) for helpful discussion concerning the Atlantic salmon SV outliers and synaptic genes.",

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doi = "10.1038/s41467-020-18972-x",

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AU - Bertolotti, Alicia C

AU - Layer, Ryan M.

AU - Gundappa, Manu Kumar

AU - Gallagher, Michael D

AU - Pehlivanoglu, Ege

AU - Nome, Torfinn

AU - Robledo, Diego

AU - Kent , Matthew P.

AU - Røsæg, Line L.

AU - Holen, Matilde M.

AU - Mulugeta, Teshome D.

AU - Ashton, Thomas J.

AU - Hindar, Kjetil

AU - Sægrov, Harald

AU - Florø-Larsen, Bjørn

AU - Erkinaro, Jaakko

AU - Primmer, Craig R

AU - Bernatchez, Louis

AU - Martin, Samuel A M

AU - Johnston, Ian A

AU - Sandve, Simen R.

AU - Lien, Sigbjorn

AU - MacQueen, Daniel John

N1 - Acknowledgements: The study was supported by Biotechnology and Biological Sciences Research Council grants BB/M016455/1, BB/S004181/1, BBS/E/D/10002070 and BBS/E/D/30002275. Wild Atlantic salmon genome sequencing was funded by the Research Council of Norway (The Aqua Genome project; ref: 221734). We thank Dr. Chris Hollenbeck (formerly Xelect Ltd; currently Texas A&M, USA) for support with Snakemake and Drs. Serap Gonen and Matt Baranski (Mowi AS) for sharing sequencing data. We thank Terese Andersstuen and Dr. Mariann Árnyasi (both NMBU) for organizing the sequencing of wild Atlantic salmon samples. We acknowledge the use of computing clusters at the University of Aberdeen (Maxwell), University of Edinburgh (EDDIE) and CIGENE, NMBU (Orion). Storage resources were provided by the Norwegian National Infrastructure for Research Data (NIRD, project NS9055K). D.J.M. thanks Prof. Seth Grant (University of Edinburgh) for helpful discussion concerning the Atlantic salmon SV outliers and synaptic genes.

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N2 - 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.

AB - 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.

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The structural variation landscape in 492 Atlantic salmon genomes

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