Literature DB >> 28386669

Binets: Fundamental Building Blocks for Phylogenetic Networks.

Leo van Iersel1, Vincent Moulton2, Eveline de Swart3, Taoyang Wu2.   

Abstract

Phylogenetic networks are a generalization of evolutionary trees that are used by biologists to represent the evolution of organisms which have undergone reticulate evolution. Essentially, a phylogenetic network is a directed acyclic graph having a unique root in which the leaves are labelled by a given set of species. Recently, some approaches have been developed to construct phylogenetic networks from collections of networks on 2- and 3-leaved networks, which are known as binets and trinets, respectively. Here we study in more depth properties of collections of binets, one of the simplest possible types of networks into which a phylogenetic network can be decomposed. More specifically, we show that if a collection of level-1 binets is compatible with some binary network, then it is also compatible with a binary level-1 network. Our proofs are based on useful structural results concerning lowest stable ancestors in networks. In addition, we show that, although the binets do not determine the topology of the network, they do determine the number of reticulations in the network, which is one of its most important parameters. We also consider algorithmic questions concerning binets. We show that deciding whether an arbitrary set of binets is compatible with some network is at least as hard as the well-known graph isomorphism problem. However, if we restrict to level-1 binets, it is possible to decide in polynomial time whether there exists a binary network that displays all the binets. We also show that to find a network that displays a maximum number of the binets is NP-hard, but that there exists a simple polynomial-time 1/3-approximation algorithm for this problem. It is hoped that these results will eventually assist in the development of new methods for constructing phylogenetic networks from collections of smaller networks.

Entities:  

Keywords:  Algorithm; Binet; Phylogenetic network; Reticulate evolution; Subnetwork

Mesh:

Year:  2017        PMID: 28386669      PMCID: PMC5488434          DOI: 10.1007/s11538-017-0275-4

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  4 in total

1.  Using consensus networks to visualize contradictory evidence for species phylogeny.

Authors:  Barbara R Holland; Katharina T Huber; Vincent Moulton; Peter J Lockhart
Journal:  Mol Biol Evol       Date:  2004-04-14       Impact factor: 16.240

2.  Networks: expanding evolutionary thinking.

Authors:  Eric Bapteste; Leo van Iersel; Axel Janke; Scot Kelchner; Steven Kelk; James O McInerney; David A Morrison; Luay Nakhleh; Mike Steel; Leen Stougie; James Whitfield
Journal:  Trends Genet       Date:  2013-06-11       Impact factor: 11.639

3.  TriLoNet: Piecing Together Small Networks to Reconstruct Reticulate Evolutionary Histories.

Authors:  James Oldman; Taoyang Wu; Leo van Iersel; Vincent Moulton
Journal:  Mol Biol Evol       Date:  2016-04-15       Impact factor: 16.240

4.  How much information is needed to infer reticulate evolutionary histories?

Authors:  Katharina T Huber; Leo Van Iersel; Vincent Moulton; Taoyang Wu
Journal:  Syst Biol       Date:  2014-09-18       Impact factor: 15.683

  4 in total

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