PT  - JOURNAL ARTICLE
AU  - Zhi Yan
AU  - Zhen Cao
AU  - Yushu Liu
AU  - Luay Nakhleh
TI  - Maximum Parsimony Inference of Phylogenetic Networks in the Presence of Polyploid Complexes
AID  - 10.1101/2020.09.28.317651
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.09.28.317651
4099  - http://biorxiv.org/content/early/2020/09/29/2020.09.28.317651.short
4100  - http://biorxiv.org/content/early/2020/09/29/2020.09.28.317651.full
AB  - Phylogenetic networks provide a powerful framework for modeling and analyzing reticulate evolutionary histories. While polyploidy has been shown to be prevalent not only in plants but also in other groups of eukaryotic species, most work done thus far on phylogenetic network inference assumes diploid hybridization. These inference methods have been applied, with varying degrees of success, to data sets with polyploid species, even though polyploidy violates the mathematical assumptions underlying these methods. Statistical methods were developed recently for handling specific types of polyploids and so were parsimony methods that could handle polyploidy more generally yet while excluding processes such as incomplete lineage sorting. In this paper, we introduce a new method for inferring most parsimonious phylogenetic networks on data that include polyploid species. Taking gene trees as input, the method seeks a phylogenetic network that minimizes deep coalescences while accounting for polyploidy. The method could also infer trees, thus potentially distinguishing between auto- and allo-polyploidy. We demonstrate the performance of the method on both simulated and biological data. The inference method as well as a method for evaluating given phylogenetic networks are implemented and publicly available in the PhyloNet software package.Competing Interest StatementThe authors have declared no competing interest.