Data from: Molecular evolutionary and population genomic analysis of the nine-spined stickleback using a modified restriction-site-associated DNA tag approach
Bruneaux, Matthieu et al. (2012), Data from: Molecular evolutionary and population genomic analysis of the nine-spined stickleback using a modified restriction-site-associated DNA tag approach, Dryad, Dataset, https://doi.org/10.5061/dryad.44sf1
In recent years, the explosion of affordable next generation sequencing technology has provided an unprecedented opportunity to conduct genome-wide studies of adaptive evolution in organisms previously lacking extensive genomic resources. Here, we characterise genome-wide patterns of variability and differentiation using pooled DNA from eight populations of the nine-spined stickleback (Pungitius pungitius L.) from marine, lake and pond environments. We developed a novel genome complexity reduction protocol, defined as paired-end double restriction-site associated DNA (PE dRAD), to maximise read coverage at sequenced locations. This allowed us to identify over 114,000 short consensus sequences and 15,000 SNPs throughout the genome. A total of 6,834 SNPs mapped to a single position on the related three-spined stickleback genome, allowing the detection of genomic regions affected by divergent and balancing selection, both between species and between freshwater and marine populations of the nine-spined stickleback. Gene ontology (GO) analysis revealed 15 genomic regions with elevated diversity, enriched for genes involved in functions including immunity, chemical stimulus response, lipid metabolism and signalling pathways. Comparisons of marine and freshwater populations identified nine regions with elevated differentiation related to kidney development, immunity and MAP kinase pathways. In addition, our analysis revealed that a large proportion of the identified SNPs mapping to LG XII are likely to represent alternative alleles from divergent X and Y chromosomes, rather than true autosomal markers following Mendelian segregation. Our work demonstrates how population-wide sequencing and combining inter- and intra-specific RAD analysis can uncover genome-wide patterns of differentiation and adaptations in a non-model species.