Hybridization plays an important evolutionary role in several groups of organisms. A phylogenetic approach to detecting hybridization entails sequencing multiple loci across the genomes of a group of species of interest, reconstructing their gene trees, and exploit- ing their differences as signal of hybridization. However, methods that follow this approach mostly ignore population effects, such as incomplete lineage sorting (ILS). Given that hybridization occurs between closely related organisms, ILS may very well be at play and, hence, must be accounted for in the analysis framework. Methods that account for both hybridization and ILS currently exist for only very limited cases. The contributions of my work are two-fold:
• I devised the first parsimony criterion for the inference of phylogenetic networks (topologies alone) in the presence of ILS, along with new algorithms for the inference.
• I devised the first likelihood criterion for the inference of phylogenetic networks (topologies, branch lengths, and inheritance probabilities) in the presence of ILS, along with new algorithms for the inference.
I have implemented all the algorithms in our open-source, publicly available PhyloNet software package, and studied their performance in extensive simulation studies. Both the parsimony and likelihood approaches show very good performance in terms of identifying the location of hybridization events, as well as estimating the proportions of genes that underwent hybridization. Also, the parsimony approach shows good performance in terms of efficiency on handling large data sets in the experiments. Further, I analyzed two biological data sets (a data sets of yeast genomes and another of house mouse genomes) and found support for hybridization in both.
My work will allow, for the first time, systematic phylogenomic analyses of data sets where hybridization is suspected. Thus, biologists will be able now to revisit existing analyses and conduct new ones with richer evolutionary models and inference methods. Further, the computational techniques presented here can be extended to other reticulate evolutionary events, such as horizontal gene transfer, which are believed to be ubiquitous in bacteria.