A method to scan genomes for introgression in a secondary contact model
This poster was presented at the 2014 meeting of the Society for Molecular Biology & Evolution, in San Juan, PR.
Abstract: Secondary contact between divergent populations, or incipient species, may result in the exchange and introgression of genomic material. We develop a simple DNA sequence measure, called Gmin, that is designed to identify genomic regions experiencing introgression in a secondary contact model. Gmin is simply defined as the ratio of the minimum between-population number of nucleotide differences to the average number of between-population differences. The utility of Gmin is that it is computationally inexpensive relative to likelihood-based methods for detecting gene flow and it has better sensitivity and specificity than traditional measures, such as Fst. We present extensive evaluations of the sensitivity and specificity of Gmin and suggest a simple statistical testing procedure for identifying genomic outliers. Finally, we present genome-level scans of Gmin for three different data sets. The first data set evaluates cosmopolitan and African populations of Drosophila melanogaster. In this case, Gmin is able to identify all of the regions of the X chromosome that were identified by a previous, more computationally intense method, in addition to one region that was not previously identified. Second, we perform genome scans of Gmin for two species of the Drosophila simulans clade. In this case, we identify large tracts of introgression between species whose hybrid males are sterile. Lastly, we apply the Gmin statistic to an analysis of African and non-African populations of domesticated rice. In this case, it was previously shown that that these populations have a history of recent genetic exchange, however, scans of Gmin show no evidence introgression of domestication genes between these two populations. Gmin is a biologically straightforward, yet powerful, alternative to Fst, as well as to more computationally intensive model-based methods for detecting gene flow.
