English

Quarnet inference rules for level-1 networks

Populations and Evolution 2017-11-21 v1 Discrete Mathematics Combinatorics

Abstract

An important problem in phylogenetics is the construction of phylogenetic trees. One way to approach this problem, known as the supertree method, involves inferring a phylogenetic tree with leaves consisting of a set XX of species from a collection of trees, each having leaf-set some subset of XX. In the 1980's characterizations, certain inference rules were given for when a collection of 4-leaved trees, one for each 4-element subset of XX, can all be simultaneously displayed by a single supertree with leaf-set XX. Recently, it has become of interest to extend such results to phylogenetic networks. These are a generalization of phylogenetic trees which can be used to represent reticulate evolution (where species can come together to form a new species). It has been shown that a certain type of phylogenetic network, called a level-1 network, can essentially be constructed from 4-leaved trees. However, the problem of providing appropriate inference rules for such networks remains unresolved. Here we show that by considering 4-leaved networks, called quarnets, as opposed to 4-leaved trees, it is possible to provide such rules. In particular, we show that these rules can be used to characterize when a collection of quarnets, one for each 4-element subset of XX, can all be simultaneously displayed by a level-1 network with leaf-set XX. The rules are an intriguing mixture of tree inference rules, and an inference rule for building up a cyclic ordering of XX from orderings on subsets of XX of size 4. This opens up several new directions of research for inferring phylogenetic networks from smaller ones, which could yield new algorithms for solving the supernetwork problem in phylogenetics.

Keywords

Cite

@article{arxiv.1711.06720,
  title  = {Quarnet inference rules for level-1 networks},
  author = {Katharine T. Huber and Vincent Moulton and Charles Semple and Taoyang Wu},
  journal= {arXiv preprint arXiv:1711.06720},
  year   = {2017}
}

Comments

17 pages

R2 v1 2026-06-22T22:49:52.064Z