Reconstructible phylogenetic networks: do not distinguish the indistinguishable

PLoS Comput Biol. 2015 Apr 7;11(4):e1004135. doi: 10.1371/journal.pcbi.1004135. eCollection 2015 Apr.


Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biological Evolution*
  • Computer Simulation
  • Evolution, Molecular*
  • Gene Expression Regulation / genetics*
  • Gene Regulatory Networks / genetics*
  • Models, Genetic*
  • Phylogeny*

Grant support

This work was funded by a PEPS BMI 2013 grant ( from the Centre Nationale de la Recherche Scientifique. This publication is contribution no. 2015-011 of the Institut des Sciences de l’Evolution de Montpellier (ISEM, UMR 5554). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.