Identifiability Issues in Phylogeny-Based Detection of Horizontal Gene Transfer

  • Cuong Than
  • Derek Ruths
  • Hideki Innan
  • Luay Nakhleh
Conference paper

DOI: 10.1007/11864127_17

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4205)
Cite this paper as:
Than C., Ruths D., Innan H., Nakhleh L. (2006) Identifiability Issues in Phylogeny-Based Detection of Horizontal Gene Transfer. In: Bourque G., El-Mabrouk N. (eds) Comparative Genomics. RCG 2006. Lecture Notes in Computer Science, vol 4205. Springer, Berlin, Heidelberg

Abstract

Prokaryotic organisms share genetic material across species boundaries by means of a process known as horizontal gene transfer (HGT). Detecting this process bears great significance on understanding prokaryotic genome diversification and unraveling their complexities. Phylogeny-based detection of HGT is one of the most commonly used approaches for this task, and is based on the fundamental fact that HGT may cause gene trees to disagree with one another, as well as with the species phylogeny. Hence, methods that adopt this approach compare gene and species trees, and infer a set of HGT events to reconcile the differences among these trees.

In this paper, we address some of the identifiability issues that face phylogeny-based detection of HGT. In particular, we show the effect of inaccuracies in the reconstructed (species and gene) trees on inferring the correct number of HGT events. Further, we show that a large number of maximally parsimonious HGT scenarios may exist. These results indicate that accurate detection of HGT requires accurate reconstruction of individual trees, and necessitates the search for more than a single scenario to explain gene tree disagreements. Finally, we show that disagreements among trees may be a result of not only HGT, but also lineage sorting, and make initial progress on incorporating HGT into the coalescent model, so as to stochastically distinguish between the two and make an accurate reconciliation. This contribution is very significant, particularly when analyzing closely related organisms.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Cuong Than
    • 1
  • Derek Ruths
    • 1
  • Hideki Innan
    • 2
  • Luay Nakhleh
    • 1
  1. 1.Dept. of Computer ScienceRice UniversityHoustonUSA
  2. 2.Human Genetics CenterThe University of Texas Health Science CenterHoustonUSA

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