Northern European Salmo trutta (L.) populations are genetically divergent across geographical regions and environmental gradients

Dorte Bekkevold*, Johann Höjesjö, Einar Eg Nielsen, David Aldvén, Thomas Damm Als, Marte Sodeland, Matthew Peter Kent, Sigbjørn Lien, Michael Møller Hansen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The salmonid fish Brown trout is iconic as a model for the application of conservation genetics to understand and manage local interspecific variation. However, there is still scant information about relationships between local and large‐scale population structure, and to what extent geographic and environmental variables are associated with barriers to gene flow. We used information from 3782 mapped SNPs developed for the present study and conducted outlier tests and gene‐environment association (GEA) analyses in order to examine drivers of population structure. Analyses comprised >2600 fish from 72 riverine populations spanning a central part of the species’ distribution in northern Europe. We report hitherto unidentified genetic breaks in population structure, indicating strong barriers to gene flow. GEA loci were widely spread across genomic regions and showed correlations with climatic, abiotic and geographical parameters. In some cases, individual loci showed consistent GEA across the geographical regions Britain, Europe and Scandinavia. In other cases, correlations were observed only within a subset of regions, suggesting that locus specific variation was associated with local processes. A paired population sampling design allowed us to evaluate sampling effects on detection of outlier loci and GEA. Two widely applied methods for outlier detection (pcadapt, bayescan) showed low overlap in loci identified as statistical outliers across subsets of data. Two GEA analytical approaches (LFMM, RDA) showed good correspondence concerning loci associated with specific variables, but LFMM identified five times more statistically significant associations than RDA. Our results emphasize the importance of carefully considering the statistical methods applied for the hypotheses being tested in outlier analysis. Sampling design may have lower impact on results if the objective is to identify GEA loci and their population distribution. Our study provides new insights into trout populations and results have direct management implications in serving as a tool for identification of conservation units.
Original languageEnglish
JournalEvolutionary Applications (Online)
Number of pages45
ISSN1752-4563
DOIs
Publication statusAccepted/In press - 2019

Keywords

  • Brown trout
  • Genotype‐environment association
  • Local adaptation
  • Outlier test
  • Salmonid

Cite this

Bekkevold, Dorte ; Höjesjö, Johann ; Eg Nielsen, Einar ; Aldvén, David ; Als, Thomas Damm ; Sodeland, Marte ; Kent, Matthew Peter ; Lien, Sigbjørn ; Hansen, Michael Møller. / Northern European Salmo trutta (L.) populations are genetically divergent across geographical regions and environmental gradients. In: Evolutionary Applications (Online). 2019.
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title = "Northern European Salmo trutta (L.) populations are genetically divergent across geographical regions and environmental gradients",
abstract = "The salmonid fish Brown trout is iconic as a model for the application of conservation genetics to understand and manage local interspecific variation. However, there is still scant information about relationships between local and large‐scale population structure, and to what extent geographic and environmental variables are associated with barriers to gene flow. We used information from 3782 mapped SNPs developed for the present study and conducted outlier tests and gene‐environment association (GEA) analyses in order to examine drivers of population structure. Analyses comprised >2600 fish from 72 riverine populations spanning a central part of the species’ distribution in northern Europe. We report hitherto unidentified genetic breaks in population structure, indicating strong barriers to gene flow. GEA loci were widely spread across genomic regions and showed correlations with climatic, abiotic and geographical parameters. In some cases, individual loci showed consistent GEA across the geographical regions Britain, Europe and Scandinavia. In other cases, correlations were observed only within a subset of regions, suggesting that locus specific variation was associated with local processes. A paired population sampling design allowed us to evaluate sampling effects on detection of outlier loci and GEA. Two widely applied methods for outlier detection (pcadapt, bayescan) showed low overlap in loci identified as statistical outliers across subsets of data. Two GEA analytical approaches (LFMM, RDA) showed good correspondence concerning loci associated with specific variables, but LFMM identified five times more statistically significant associations than RDA. Our results emphasize the importance of carefully considering the statistical methods applied for the hypotheses being tested in outlier analysis. Sampling design may have lower impact on results if the objective is to identify GEA loci and their population distribution. Our study provides new insights into trout populations and results have direct management implications in serving as a tool for identification of conservation units.",
keywords = "Brown trout, Genotype‐environment association, Local adaptation, Outlier test, Salmonid",
author = "Dorte Bekkevold and Johann H{\"o}jesj{\"o} and {Eg Nielsen}, Einar and David Aldv{\'e}n and Als, {Thomas Damm} and Marte Sodeland and Kent, {Matthew Peter} and Sigbj{\o}rn Lien and Hansen, {Michael M{\o}ller}",
year = "2019",
doi = "10.1111/eva.12877",
language = "English",
journal = "Evolutionary Applications (Online)",
issn = "1752-4563",
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Northern European Salmo trutta (L.) populations are genetically divergent across geographical regions and environmental gradients. / Bekkevold, Dorte; Höjesjö, Johann; Eg Nielsen, Einar; Aldvén, David; Als, Thomas Damm; Sodeland, Marte; Kent, Matthew Peter; Lien, Sigbjørn; Hansen, Michael Møller.

In: Evolutionary Applications (Online), 2019.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Northern European Salmo trutta (L.) populations are genetically divergent across geographical regions and environmental gradients

AU - Bekkevold, Dorte

AU - Höjesjö, Johann

AU - Eg Nielsen, Einar

AU - Aldvén, David

AU - Als, Thomas Damm

AU - Sodeland, Marte

AU - Kent, Matthew Peter

AU - Lien, Sigbjørn

AU - Hansen, Michael Møller

PY - 2019

Y1 - 2019

N2 - The salmonid fish Brown trout is iconic as a model for the application of conservation genetics to understand and manage local interspecific variation. However, there is still scant information about relationships between local and large‐scale population structure, and to what extent geographic and environmental variables are associated with barriers to gene flow. We used information from 3782 mapped SNPs developed for the present study and conducted outlier tests and gene‐environment association (GEA) analyses in order to examine drivers of population structure. Analyses comprised >2600 fish from 72 riverine populations spanning a central part of the species’ distribution in northern Europe. We report hitherto unidentified genetic breaks in population structure, indicating strong barriers to gene flow. GEA loci were widely spread across genomic regions and showed correlations with climatic, abiotic and geographical parameters. In some cases, individual loci showed consistent GEA across the geographical regions Britain, Europe and Scandinavia. In other cases, correlations were observed only within a subset of regions, suggesting that locus specific variation was associated with local processes. A paired population sampling design allowed us to evaluate sampling effects on detection of outlier loci and GEA. Two widely applied methods for outlier detection (pcadapt, bayescan) showed low overlap in loci identified as statistical outliers across subsets of data. Two GEA analytical approaches (LFMM, RDA) showed good correspondence concerning loci associated with specific variables, but LFMM identified five times more statistically significant associations than RDA. Our results emphasize the importance of carefully considering the statistical methods applied for the hypotheses being tested in outlier analysis. Sampling design may have lower impact on results if the objective is to identify GEA loci and their population distribution. Our study provides new insights into trout populations and results have direct management implications in serving as a tool for identification of conservation units.

AB - The salmonid fish Brown trout is iconic as a model for the application of conservation genetics to understand and manage local interspecific variation. However, there is still scant information about relationships between local and large‐scale population structure, and to what extent geographic and environmental variables are associated with barriers to gene flow. We used information from 3782 mapped SNPs developed for the present study and conducted outlier tests and gene‐environment association (GEA) analyses in order to examine drivers of population structure. Analyses comprised >2600 fish from 72 riverine populations spanning a central part of the species’ distribution in northern Europe. We report hitherto unidentified genetic breaks in population structure, indicating strong barriers to gene flow. GEA loci were widely spread across genomic regions and showed correlations with climatic, abiotic and geographical parameters. In some cases, individual loci showed consistent GEA across the geographical regions Britain, Europe and Scandinavia. In other cases, correlations were observed only within a subset of regions, suggesting that locus specific variation was associated with local processes. A paired population sampling design allowed us to evaluate sampling effects on detection of outlier loci and GEA. Two widely applied methods for outlier detection (pcadapt, bayescan) showed low overlap in loci identified as statistical outliers across subsets of data. Two GEA analytical approaches (LFMM, RDA) showed good correspondence concerning loci associated with specific variables, but LFMM identified five times more statistically significant associations than RDA. Our results emphasize the importance of carefully considering the statistical methods applied for the hypotheses being tested in outlier analysis. Sampling design may have lower impact on results if the objective is to identify GEA loci and their population distribution. Our study provides new insights into trout populations and results have direct management implications in serving as a tool for identification of conservation units.

KW - Brown trout

KW - Genotype‐environment association

KW - Local adaptation

KW - Outlier test

KW - Salmonid

U2 - 10.1111/eva.12877

DO - 10.1111/eva.12877

M3 - Journal article

JO - Evolutionary Applications (Online)

JF - Evolutionary Applications (Online)

SN - 1752-4563

ER -