Outlier SNP markers reveal fine‐scale genetic structuring across European hake populations (Merluccius merluccius)

Abstract

Shallow population structure is generally reported for most marine fish and explained as a consequence of high dispersal, connectivity and large population size. Targeted gene analyses and more recently genome-wide studies have challenged such view, suggesting that adaptive divergence might occur even when neutral markers provide genetic homogeneity across populations. Here, 381 SNPs located in transcribed regions were used to assess large- and fine-scale population structure in the European hake (Merluccius merluccius), a widely distributed demersal species of high priority for the European fishery. Analysis of 850 individuals from 19 locations across the entire distribution range showed evidence for several outlier loci, with significantly higher resolving power. While 299 putatively neutral SNPs confirmed the genetic break between basins (F(CT) = 0.016) and weak differentiation within basins, outlier loci revealed a dramatic divergence between Atlantic and Mediterranean populations (F(CT) range 0.275-0.705) and fine-scale significant population structure. Outlier loci separated North Sea and Northern Portugal populations from all other Atlantic samples and revealed a strong differentiation among Western, Central and Eastern Mediterranean geographical samples. Significant correlation of allele frequencies at outlier loci with seawater surface temperature and salinity supported the hypothesis that populations might be adapted to local conditions. Such evidence highlights the importance of integrating information from neutral and adaptive evolutionary patterns towards a better assessment of genetic diversity. Accordingly, the generated outlier SNP data could be used for tackling illegal practices in hake fishing and commercialization as well as to develop explicit spatial models for defining management units and stock boundaries.

Outlier analyses to test for local adaptation to breeding grounds in a migratory arctic seabird

“…Outlier analyses can be powerful tools to detect loci that are under selection, especially when levels of background genomic differentiation are low (e.g., Hess et al., 2013; Keller et al., 2013; Milano et al., 2014). However, several factors can limit the power of these methods or confound the interpretation of results (Mita et al., 2013; Edwards et al., 2015; Lotterhos & Whitlock, 2014; Narum & Hess, 2011).…”

“…We first investigated genetic differentiation between common and thick‐billed murres to test for hybrids. We then performed clustering analyses to test whether the loci putatively under selection grouped individual thick‐billed murres differently from the complete dataset (as in e.g., Milano et al., 2014; Keller et al., 2013). We analyzed two separate datasets—one that included all loci and one that included only outlier loci—using two different clustering methods.…”

“…An exponential increase in the number of genotyped loci and coverage of the genome over previous methods has also increased power to detect loci that deviate from a neutral model of evolution (i.e., outlier loci) and potentially underlie adaptation. Outlier analyses have allowed researchers to detect loci putatively under selection, which were then able to reveal fine differentiation patterns in otherwise homogenous populations and species (Hess, Campbell, Close, Docker, & Narum, 2013; Keller et al., 2013; Milano et al., 2014). …”

Parallel evolution and adaptation to environmental factors in a marine flatfish: Implications for fisheries and aquaculture management of the turbot (Scophthalmus maximus)

“…However, various factors can bring about genetic differentiation, such as habitat shifts (ecotones) and oceanic currents (Blanco‐Gonzalez, Knutsen, & Jorde, 2016; Galarza et al., 2009; Nielsen, Nielsen, Meldrup, & Hansen, 2004; Vera et al., 2016a), and natural selection in response to environmental variation (Milano et al., 2014; Vandamme et al., 2014; Vilas, Bouza, Vera, Millán, & Martínez, 2010; Vilas et al., 2015). Distinguishing between neutral and adaptive genetic variation has become a central issue in evolutionary biology, allowing for understanding of population structure in both historical/demographic and adaptive terms (Bernatchez, 2016; Nielsen, Hemmer‐Hansen, Larsen, & Bekkevold, 2009), thereby providing essential information for the conservation and management of wild populations.…”

Population Genomics of Marine Fishes: Next-Generation Prospects and Challenges

“…Alternative approaches combine transcriptome and genome sequence data (e.g., Lamichaney et al,. 2012;Montes et al, 2013) or split variant discovery and genotyping in two steps, applying various sequencing methods to identify genetic variation that is subsequently genotyped on high-throughput platforms (e.g., Limborg et al, 2012;Milano et al, 2014; see also Table 1 for examples of next-generation sequencing studies in marine fishes).…”