Using Supernetworks to Distinguish Hybridization from Lineage-sorting

Background: A simple and widely used approach for detecting hybridization in phylogenies is to reconstruct gene trees from independent gene loci, and to look for gene tree incongruence. However, this approach may be confounded by factors such as poor taxon-sampling and/or incomplete lineage-sorting.

Results: Using coalescent simulations, we investigated the potential of supernetwork methods to differentiate between gene tree incongruence arising from taxon sampling and incomplete lineage-sorting as opposed to hybridization. For few hybridization events, a large number of independent loci, and well-sampled taxa across these loci, we found that it was possible to distinguish incomplete lineage-sorting from hybridization using the filtered Z-closure and Q-imputation supernetwork methods. Moreover, we found that the choice of supernetwork method was less important than the choice of filtering, and that count-based filtering was the most effective filtering technique.

Conclusion: Filtered supernetworks provide a tool for detecting and identifying hybridization events in phylogenies, a tool that should become increasingly useful in light of current genome sequencing initiatives and the ease with which large numbers of independent gene loci can be determined using new generation sequencing technologies.