Identifying Directional Selection Signals

We used LOSITAN to identify outlier loci associated with directional selection [46 (link)]. Outlier analyses such as these frequently produce some degree of false positives [47 (link)]. To overcome this, we selected the 84 K set with a higher MAF threshold for this analysis to highlight the strongest signals of selection and biasing towards genomic regions with large effects. We included only the 104 dogs that grouped with their capture location in the DAPC for better identification of the differentiating loci in each population. We ran 1,000,000 simulations and applied a 95% confidence interval and a false discovery rate of 0.1. We considered loci significant when designated as ‘candidate positive selection’ and when the calculated F_ST was higher than the expected F_ST in all simulations (P(Simulated F_ST < sample F_ST) = 1).
The genome location of each significant SNP identified using LOSITAN was expanded to a 10 kb genomic interval of CanFam3 (5 kb either side of the SNP coordinates). We then surveyed each of the 10 kb regions for the presence of genes and identified corresponding gene ontology (GO) terms through the Mouse Genome Informatics Batch Query Search [48 (link)]. GO terms were evaluated for putative associations towards the exposures faced within the environment (e.g., GO:0,010,212 “response to ionizing radiation”).