Data from: Genetic subdivision and candidate genes under selection in North American gray wolves

Previous genetic studies of the highly mobile gray wolf (Canis lupus) found population structure that coincides with habitat and phenotype differences. We hypothesized that these ecologically distinct populations (ecotypes) should exhibit signatures of selection in genes related to morphology, coat color, and metabolism. To test these predictions, we quantified population structure related to habitat using a genotyping array to assess variation in 42,036 SNPs in 111 North American gray wolves. Using these SNP data and individual-level measurements of 12 environmental variables, we identified six ecotypes: West Forest, Boreal Forest, Arctic, High Arctic, British Columbia, and Atlantic Forest. Next, we explored signals of selection across these wolf ecotypes through the use of three complementary methods to detect selection: FST/haplotype homozygosity bivariate percentile, BayeScan, and environmentally correlated directional selection with Bayenv. Across all methods, we found consistent signals of selection on genes related to morphology, coat coloration, metabolism, as predicted, as well as vision and hearing. In several high-ranking candidate genes, including LEPR, TYR, and SLC14A2, we found variation in allele frequencies that follow environmental changes in temperature and precipitation, a result that is consistent with local adaptation rather than genetic drift. Our findings show that local adaptation can occur despite gene flow in a highly mobile species and can be detected through a moderately dense genomic scan. These patterns of local adaptation revealed by SNP genotyping likely reflect high fidelity to natal habitats of dispersing wolves, strong ecological divergence among habitats, and moderate levels of linkage in the wolf genome.过往针对高度移动性灰狼（Canis lupus）的遗传学研究发现，其种群结构与生境及表型差异高度契合。我们据此提出假说：这类生态分化的种群（生态型，ecotypes）应在与形态、毛色及代谢相关的基因中呈现选择信号。为验证该假说，我们利用基因分型芯片对111只北美灰狼的42036个单核苷酸多态性（Single Nucleotide Polymorphisms，SNPs）位点进行变异分型，以此量化与生境相关的种群结构。结合上述SNP数据与12项环境变量的个体水平测定结果，我们共鉴定出6类灰狼生态型：西部森林型、北方针叶林型、北极型、高北极型、不列颠哥伦比亚型与大西洋森林型。随后，我们采用三种互补的选择检测方法——FST/单倍型纯合性双变量百分位数法、BayeScan以及基于Bayenv的环境关联定向选择分析——对这些灰狼生态型的选择信号展开系统探究。所有分析方法均一致检测到与预测相符的形态、毛色、代谢相关基因的选择信号，同时还发现视觉与听觉相关基因存在显著选择信号。在LEPR、TYR及SLC14A2等多个排名靠前的候选基因中，我们发现等位基因频率随温度与降水的环境梯度发生规律性变化，该结果符合本地适应而非遗传漂变的理论预期。本研究结果表明，即便在移动性极强的物种种群中存在基因流，本地适应仍可发生，且可通过中等密度的基因组扫描进行有效检测。本次通过SNP分型揭示的本地适应模式，大概率反映了三个关键特征：扩散个体对出生地生境的高度保真度、不同生境间强烈的生态分化，以及灰狼基因组中中等程度的连锁水平。