Data from: Comparing genomic signatures of domestication in two Atlantic salmon (Salmo salar L.) populations with different geographical origins

Selective breeding and genetic improvement have left detectable signatures
on the genomes of domestic species. The elucidation of such signatures is
fundamental for detecting genomic regions of biological relevance to
domestication and improving management practices. In aquaculture,
domestication was carried out independently in different locations
worldwide, which provides opportunities to study the parallel effects of
domestication on the genome of individuals that have been selected for
similar traits. In the present study, we aimed to detect potential genomic
signatures of domestication in two independent pairs of wild/domesticated
Atlantic salmon populations of Canadian and Scottish origins respectively.
Putative genomic regions under divergent selection were investigated using
a 200K SNP array by combining three different statistical methods based
either on allele frequencies (LFMM, Bayescan) or haplotype differentiation
(Rsb). We identified 337 and 270 SNPs potentially under divergent
selection in wild and hatchery populations of Canadian and Scottish
origins respectively. We observed little overlap between results obtained
from different statistical methods, highlighting the need to test
complementary approaches for detecting a broad range of genomic footprints
of selection. The vast majority of the outliers detected were
population-specific but we found four candidate genes that were shared
between the populations. We propose that these candidate genes may play a
role in the parallel process of domestication. Overall, our results
suggest that genetic drift may have override the effect of artificial
selection and/or point towards a different genetic basis underlying the
expression of similar traits in different domesticated strains. Finally,
it is likely that domestication may predominantly target polygenic traits
(e.g., growth) such that its genomic impact might be more difficult to
detect with methods assuming selective sweeps.