Data from: Outlier SNP markers reveal fine-scale genetic structuring across European hake populations (Merluccius merluccius)
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https://datadryad.org/dataset/doi:10.5061/dryad.7bn22
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资源简介:
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 (FCT =
0.016) and weak differentiation within basins, outlier loci revealed a
dramatic divergence between Atlantic and Mediterranean populations (FCT
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.
提供机构:
Dryad
创建时间:
2013-10-22



