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 geographical and environmental variables are associated with barriers to gene flow. We used information from 3,782 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 >2,600 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 sub‐set 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 and bayescan) showed low overlap in loci identified as statistical outliers across sub‐sets of data. Two GEA analytical approaches (LFMM and 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.
Highlights
Improving our understanding of the genetic basis of local adapta‐ tion is a main aim in evolutionary biology and is of significance in applied research because of its relevance to the conservation of genetic resources, management of exploited populations and for predicting impacts of climate change (Allendorf, Hohenlohe, & Luikart, 2010; Lehnert et al, 2019)
By taking advantage of genomic resources developed for S. trutta, this study provides the most detailed examination of large‐scale genetic structure in a cen‐ tral part of the species' native range
We identified very strong sam‐ ple clustering corresponding with broad geographical regions, as well as clear genetic breaks among samples within regions, that in several
Summary
Improving our understanding of the genetic basis of local adapta‐ tion is a main aim in evolutionary biology and is of significance in applied research because of its relevance to the conservation of genetic resources, management of exploited populations and for predicting impacts of climate change (Allendorf, Hohenlohe, & Luikart, 2010; Lehnert et al, 2019). It has been suggested that in analyses of gene–environment associations (GEA), sampling mul‐ tiple populations exposed to similar environmental conditions is a means to increase detection power of true positives, especially for associations with weakly selected loci (Lotterhos & Whitlock, 2015) Studies applying such sampling design are still rare (Roschanski et al, 2016) and tend to be restricted to local geograph‐ ical scales (Ahrens et al, 2018). To compare regional structuring with patterns at broader geo‐ graphical scales, collections included three geographically re‐ mote populations: the Estonian Vainupea River (draining into the Gulf of Finland in the eastern Baltic Sea), River Tamar in Cornwall, UK (draining into the western English Channel), and from les Usses River, draining into the River Rhone in the Haute‐Savoie in south‐ ern France The latter representing the species' Mediterranean clade (Bernatchez, 2001). DNA from all samples was extracted from adi‐ pose fin clips using a commercial kit (E.Z.N.A.TM kit; Omega BioTek)
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