Pairwise selection at SNP loci
While it is possible for individual functional SNP markers to show a global selection signature, others may only show signatures of divergent or stabilizing selection at the population level due to specific differences in local conditions among individual populations. To assess genetic divergence patterns among pairs of snow bunting populations, we calculated pairwise estimates of G’ST using both microsatellite and SNP genotype data and compared the SNP loci pairwiseG’ST values with the presumed-neutral microsatellite loci range (created using ‘diffCalc’ function’s bias-corrected bootstrapping loci approach as explained above) at the 99.9% CI to detect signatures of divergent and stabilizing selection. We used higher CI (99.9% versus 99% neutral CI used in global comparison) to avoid detection of false positives for pairwise comparisons since we are assessing 101 SNPs (useable SNPs post-filtration step; see “Bioinformatics” section above for details) and fifteen pairwise population comparisons. Corrections for multiple comparisons were not necessary as neutral range was individually developed for each comparison. We first combined all the results from the pairwise comparisons to investigate overall levels of genetic drift and selection, and also conducted a Chi-squared test to assess whether the pattern of selection signatures differed across the seven gene function categories. However, for some population pairs it was not possible to identify SNPs under stabilizing selection since the neutralG’ST range for that pairwise comparison included zero. As such, we have reported the SNP loci showing likely signals of divergent selection for all fifteen pairwise comparisons, but stabilizing selection for only nine of fifteen comparisons. For the six comparisons which had neutral ranges that included zero, the SNP loci with G’ST values less than expected neutral range (i.e., negative G’ST values) were identified as “undetermined”.
To gain further insight into specific genes that showed evidence for divergent selection, we explored the function of selected SNP loci withG’ST values that had no “undetermined” classifications across any of the fifteen pairwise comparisons. Therefore, each SNP locus in this subset was identified as either under neutral processes, stabilizing selection or divergent selection for all fifteen pairwise comparisons. This approach allowed us to assess the selection status of divergent SNP loci across all other population pairs – this allows the comparison of the role of these functional markers across all other population comparison(s) to highlight specific differences, allowing us to identify specific genes contributing to population divergence and local adaptation.