A Model-Free Approach For Detecting Genomic Regions Of Deep Divergence Using The Distribution Of Haplotype Distances

Recent advances in comparative genomics have revealed that divergence between populations is not necessarily uniform across all parts of the genome. There are examples of regions with divergent haplotypes that are substantially more different from each other that the genomic average.\n\nTypically, these regions are of interest, as their persistence over long periods of time may reflect balancing selection. However, they are hard to detect unless the divergent sub-populations are known prior to analysis.\n\nHere, we introduce HaploDistScan, an R-package implementing model-free detection of deep-divergence genomic regions based on the distribution of pair-wise haplotype distances, and show that it can detect such regions without use of a priori information about population sub-division. We apply the method to real-world data sets, from ruff and Darwins finches, and show that we are able to recover known instances of balancing selection - originally identified in studies reliant on detailed phenotyping - using only genotype data. Furthermore, in addition to replicating previously known divergent haplotypes as a proof-of-concept, we identify novel regions of interest in the Darwins finch genome and propose a plausible, data-driven evolutionary history for each novel locus individually.\n\nIn conclusion, HaploDistScan requires neither phenotypic nor demographic input data, thus filling a gap in the existing set of methods for genome scanning, and provides a useful tool for identification of regions under balancing selection or similar evolutionary processes.