GenVectors: an integrative analytical tool for spatial genetics
Duarte, L.; Lima, J.; Maestri, R.; Debastiani, V.; Collevatti, R.
Show abstract
Metapopulations are sets of local populations connected by dispersal. While genetic turnover informs about the number of alleles shared by (meta)populations, a set of populations that do not share alleles with a second set may still show low genetic divergence to it. Recent secondary contact driven by anthropogenic habitat fragmentation and/or current climate change, for instance, may erase the historical track of genetic turnover. On the other hand, genetic turnover among sets of populations is expected to be related to the degree of genetic divergence among them if metapopulations become isolated from others due to vicariance or ancient dispersal. Yet, current analytical tools do not permit direct inference about alternative processes underlying spatial, environmental and/or biogeographic correlates of genetic turnover among populations. We introduce GenVectors, a new R package that offers flexible analytical tools that allow evaluating biogeographic or environmental correlates of genetic turnover among sets of local populations based on fuzzy set theory. Analyses implemented in GenVectors allow exploring the distribution of haplotypes or SNPs across sets of local populations. Moreover, GenVectors provides tools to analyze environmental or biogeographic correlates of haplotype or SNP turnover among sets of local populations by applying appropriate null models, which enable to discriminate history-driven genetic turnover (vicariance, ancient dispersal) from non-historical ones (recent secondary contact). Finally, we demonstrate the application of GenVectors in two empirical datasets, one based on single-locus marker (haplotypes) and other based on multi-loci marker (SNPs).
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