RT Journal Article
SR Electronic
T1 Maximum Parsimony Inference of Phylogenetic Networks in the Presence of Polyploid Complexes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.09.28.317651
DO 10.1101/2020.09.28.317651
A1 Zhi Yan
A1 Zhen Cao
A1 Yushu Liu
A1 Luay Nakhleh
YR 2020
UL http://biorxiv.org/content/early/2020/09/29/2020.09.28.317651.abstract
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.