Data from: Targeted capture and resequencing of 1040 genes reveal environmentally driven functional variation in gray wolves

In an era of ever-increasing amounts of whole genome sequence data for
individuals and populations, the utility of traditional single nucleotide
polymorphisms (SNPs) array-based genome scans is uncertain. We previously
performed a SNP array-based genome scan to identify candidate genes under
selection in six distinct gray wolf (Canis lupus) ecotypes. Using this
information, we designed a targeted capture array for 1040 genes,
including all exons and flanking regions, as well as 5000 1 kb non-genic
neutral regions and resequenced these regions in 107 wolves. Selection
tests revealed striking patterns of variation within candidate genes
relative to non-candidate regions and identified potentially functional
variants related to local adaptation. We found 27% and 47% of candidate
genes from the previous SNP array study had functional changes that were
outliers in SweeD and Bayenv analyses, respectively. This result verifies
the use of genome wide SNP surveys to tag genes that contain functional
variants between populations. We highlight non-synonymous variants in
APOB, LIPG, and USH2A that occur in functional domains of these proteins,
and that demonstrate high correlation with precipitation seasonality and
vegetation. We find Arctic and High Arctic wolf ecotypes have higher
numbers of genes under selection, which highlight their conservation value
and heightened threat due to climate change. This study demonstrates that
combining genome wide genotyping arrays with large scale resequencing and
environmental data provides a powerful approach to discern candidate
functional variants in natural populations.