Reconstruction of Reticulate Networks from Gene Trees

  • Daniel H. Huson
  • Tobias Klöpper
  • Pete J. Lockhart
  • Mike A. Steel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3500)


One of the simplest evolutionary models has molecular sequences evolving from a common ancestor down a bifurcating phylogenetic tree, experiencing point-mutations along the way. However, empirical analyses of different genes indicate that the evolution of genomes is often more complex than can be represented by such a model. Thus, the following problem is of significant interest in molecular evolution: Given a set of molecular sequences, compute a reticulate network that explains the data using a minimal number of reticulations. This paper makes four contributions toward solving this problem. First, it shows that there exists a one-to-one correspondence between the tangles in a reticulate network, the connected components of the associated incompatibility graph and the netted components of the associated splits graph. Second, it provides an algorithm that computes a most parsimonious reticulate network in polynomial time, if the reticulations contained in any tangle have a certain overlapping property, and if the number of reticulations contained in any given tangle is bounded by a constant. Third, an algorithm for drawing reticulate networks is described and a robust and flexible implementation of the algorithms is provided. Fourth, the paper presents a statistical test for distinguishing between reticulations due to hybridization, and ones due to other events such as lineage sorting or tree-estimation error.


Gene Tree Horizontal Gene Transfer Phylogenetic Network Tree Edge Recombination Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Daniel H. Huson
    • 1
  • Tobias Klöpper
    • 1
  • Pete J. Lockhart
    • 2
  • Mike A. Steel
    • 3
  1. 1.Center for Bioinformatics (ZBIT)Tübingen UniversityTübingenGermany
  2. 2.Institute of Molecular BioSciencesMassey UniversityPalmerston NorthNew Zealand
  3. 3.Biomathematics Research CentreUniversity of CanterburyChristchurchNew Zealand

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