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.
Environmental Data for 94 wolves in 6 populations
These data represent latitude and longitude coordinates for the 94 wolves used in this study for selection tests. The 12 environmental variables for each coordinate were downloaded within ArcGIS from various WORLDCLIM databases (http://www.worldclim.org/). Please see descriptions on website for information on what each variable measures. From the website: "Please note that the temperature data are in °C * 10. This means that a value of 231 represents 23.1 °C. This does lead to some confusion, but it allows for much reduced file sizes which is important as for many downloading large files remains difficult. The unit used for the precipitation data is mm (millimeter)."
EnvironmentalData_6pops_94indiv.xlsx
nacanids_111indiv_unrel_noYNP_42Ksnps.tped
The set of all 42,587 SNPs for 111 unrelated wolves, in PLINK .tped format. (http://pngu.mgh.harvard.edu/~purcell/plink/)
nacanids_111indiv_unrel_noYNP_42Ksnps.tfam
The .tfam file, in PLINK format, that corresponds to nacanids_111indiv_unrel_noYNP_42Ksnps.tped. This file has the sample names for 111 unrelated wolves.
nonAdmix_nacanids_94indiv_unrel_noYNP_42Ksnps_wEcotypes.tped
The set of all 42,587 SNPs for 94 unrelated wolves, with >50% assignment in structure, in PLINK .tped format.(http://pngu.mgh.harvard.edu/~purcell/plink/)
nonAdmix_nacanids_94indiv_unrel_noYNP_42Ksnps_wEcotypes.tfam
The corresponding TFAM file for the set of 94 unrelated individuals showing >50% assignment in structure. The first column of each line is the ecotype designation for each sample.
BayeScan results with prior odds of 10
This is the results (fst) file from running BayeScan with prior odds of 10, with 94 non-admixed individuals and the 42K snp set. Each row represents a different SNP, with the order of the SNPs the same as in the nonAdmix_nacanids_94indiv_unrel_noYNP_42Ksnps_wEcotypes.tped file.
94indiv_42Ksnps_BayeScan_pr_odd_10_output_fst.txt
BayeScan results file with prior odds of 1000
This is the results (fst) file from running BayeScan with prior odds of 1000, with 94 non-admixed individuals and the 42K snp set. Each row represents a different SNP, with the order of the SNPs the same as in the nonAdmix_nacanids_94indiv_unrel_noYNP_42Ksnps_wEcotypes.tped file.
94indiv_42Ksnps_BayeScan_pr_odd_1000_output_fst.txt
BayeScan results with prior odds of 10000
This is the results (fst) file from running BayeScan with prior odds of 10000, with 94 non-admixed individuals and the 42K snp set. Each row represents a different SNP, with the order of the SNPs the same as in the nonAdmix_nacanids_94indiv_unrel_noYNP_42Ksnps_wEcotypes.tped file.
94indiv_42Ksnps_BayeScan_pr_odd_10000_output_fst.txt
Bayenv output file
Results file from Bayenv for 94 individuals in six populations for 12 environmental variables. File is the matrix of bayes factors after averaging across ten independent runs. Each row represents a SNP, and each column contains the bayes factor for each environmental variable. BIO1: annual mean temp., BIO2: mean diurnal temp. range, BIO4: temp. seasonality, BIO5: max. temp. of warmest month, BIO6: min. temp. of coldest month), BIO12: annual precipitation, BIO15: precipitation seasonality, BIO19: precipitation of coldest quarter, LC: land cover metric, NDVIM: normalized difference vegetation index, TREE: percentage tree cover, and SRTM: shuttle radar topography metric.
bf_output_94indiv_12Var_Jan2015_average_forR.txt
Genetic distance matrix for Mantel and spatial autocorrelation tests
This date file is a square matrix of genetic distance as measured using 42K SNPs and the 111 individual data set. Genetic distance was calculated in PLINK using the '--cluster --distance-matrix' command options. The order of individuals is the same as in the nacanids_111indiv_unrel_noYNP_42Ksnps.tfam file.
nacanids_111indiv_unrel_noYNP_42Ksnps.mdist
Geographic distance matrix for Mantel and spatial autocorrelation tests
This file is a square matrix of geographic distance, in kilometers, between 111 wolves. Genalex was used to calculate these distances, using the options 'Genalex --> distance --> geographic --> decimal lat/long, square matrix'. Individuals are in the same order as in the nacanids_111indiv_unrel_noYNP_42Ksnps.tfam file.
nacanids_111indiv_geogDistInKiloMeters.txt
nacanids_unrel_42Ksnps_CoatColor_wYNP_n33.tped
PLINK formatted genotypes of 33 individuals used for coat color association test, gentoyped at 42K SNPs. This data set includes 10 Yellowstone wolves which were not included in the main analysis for the paper, but were included for the coat color association.
nacanids_123indiv_unrel_42Ksnps_CoatColor_wYNP_n33.tped
nacanids_unrel_42Ksnps_CoatColor_wYNP_n33_white.tfam
PLINK formatted TFAM file with coat color genotype for each of 33 wolves. Individuals coded as a 2 are white, individuals coded as a 1 are not white (can be black or gray).
nacanids_123indiv_unrel_42Ksnps_CoatColor_wYNP_n33_white.tfam
nacanids_123indiv_unrel_42Ksnps_CoatColor_wYNP_n33_black.tfam
PLINK formatted TFAM file with coat color genotype for each of 33 wolves. Individuals coded as a 2 are black, individuals coded as a 1 are not black (can be white or gray).