A novel technique for detecting putative horizontal gene transfer in the sequence space

Sagi Snir, Edward Trifonov

Research output: Contribution to journalArticlepeer-review

Abstract

Horizontal transfer (HT) is the event of a DNA sequence being transferred between species not by inheritance. This phenomenon violates the tree-like evolution of the species under study turning the trees into networks. At the sequence level, HT offers basic characteristics that enable not only clear identification and distinguishing from other sequence similarity cases but also the possibility of dating the events. We developed a novel, self-contained technique to identify relatively recent horizontal transfer elements (HTEs) in the sequences. Appropriate formalism allows one to obtain confidence values for the events detected. The technique does not rely on such problematic prerequisites as reliable phylogeny and/or statistically justified pairwise sequence alignment. In conjunction with the unique properties of HT, it gives rise to a two-level sequence similarity algorithm that, to the best of our knowledge, has not been explored. From evolutionary perspective, the novelty of the work is in the combination of small scale and large scale mutational events. The technique is employed on both simulated and real biological data. The simulation results show high capability of discriminating between HT and conserved regions. On the biological data, the method detected documented HTEs along with their exact locations in the recipient genomes. Supplementary Material is available online at www.libertonline.com/cmb.

Original languageEnglish
Pages (from-to)1417-1430
Number of pages14
JournalJournal of Computational Biology
Volume17
Issue number11
DOIs
StatePublished - 1 Nov 2010

Keywords

  • algorithms
  • biology
  • computational molecular biology
  • evolution

ASJC Scopus subject areas

  • Computational Mathematics
  • Genetics
  • Molecular Biology
  • Computational Theory and Mathematics
  • Modeling and Simulation

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