Recovering the tree-like trend of evolution despite extensive lateral genetic transfer: A probabilistic analysis

  • Roch S
  • Snir S
  • 36

    Readers

    Mendeley users who have this article in their library.
  • 5

    Citations

    Citations of this article.

Abstract

Lateral gene transfer (LGT) is a common mechanism of non-vertical evolution where genetic material is transferred between two more or less distantly related organisms. It is particularly common in bacteria where it contributes to adaptive evolution with important medical implications. In evolutionary studies, LGT has been shown to create widespread discordance between gene trees as genomes become mosaics of gene histories. In particular, the Tree of Life has been questioned as an appropriate representation of bacterial evolutionary history. Nevertheless a common hypothesis is that prokaryotic evolution is primarily tree-like, but that the underlying trend is obscured by LGT. Extensive empirical work has sought to extract a common tree-like signal from conflicting gene trees. Here we give a probabilistic perspective on the problem of recovering the tree-like trend despite LGT. Under a model of randomly distributed LGT, we show that the species phylogeny can be reconstructed even in the presence of surprisingly many (almost linear number of) LGT events per gene tree. Our results, which are optimal up to logarithmic factors, are based on the analysis of a robust, computationally efficient reconstruction method and provides insight into the design of such methods. Finally we show that our results have implications for the discovery of highways of gene sharing.

Author-supplied keywords

  • Lateral Gene Transfer
  • Phylogenetic Reconstruction
  • Quartet Reconstruction

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • Sebastien Roch

  • Sagi Snir

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free