On the Quirks of Maximum Parsimony and Likelihood on Phylogenetic Networks

TL;DR

This paper explores the extension of maximum parsimony methods from phylogenetic trees to networks, analyzing their properties and computational complexity, and comparing them to likelihood-based approaches in evolutionary studies.

Contribution

It provides the first polynomial-time algorithm for softwired maximum parsimony networks and shows that hardwired maximum parsimony networks always include at least one phylogenetic tree.

Findings

Polynomial-time algorithm for softwired maximum parsimony networks

Hardwired maximum parsimony networks always contain a phylogenetic tree

Analysis of parallels between parsimony and likelihood concepts on networks

Abstract

Maximum parsimony is one of the most frequently-discussed tree reconstruction methods in phylogenetic estimation. However, in recent years it has become more and more apparent that phylogenetic trees are often not sufficient to describe evolution accurately. For instance, processes like hybridization or lateral gene transfer that are commonplace in many groups of organisms and result in mosaic patterns of relationships cannot be represented by a single phylogenetic tree. This is why phylogenetic networks, which can display such events, are becoming of more and more interest in phylogenetic research. It is therefore necessary to extend concepts like maximum parsimony from phylogenetic trees to networks. Several suggestions for possible extensions can be found in recent literature, for instance the softwired and the hardwired parsimony concepts. In this paper, we analyze the so-called big parsimony problem under these two concepts, i.e. we investigate maximum parsimonious networks and analyze their properties. In particular, we show that finding a softwired maximum parsimony network is possible in polynomial time. We also show that the set of maximum parsimony networks for the hardwired definition always contains at least one phylogenetic tree. Lastly, we investigate some parallels of parsimony to different likelihood concepts on phylogenetic networks.