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Detection of Horizontal Gene Transfer Mediated by Natural Conjugative Plasmids in E. coli
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Predicting horizontal gene transfers with perfect transfer networks.

Alitzel López Sánchez1, Manuel Lafond2

  • 1Department of Computer Science, Université de Sherbrooke, Sherbrooke, Canada. alitzel.lopez.sanchez@usherbrooke.ca.

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|February 6, 2024
PubMed
Summary

This study introduces perfect transfer networks, a novel method using character traits to infer ancient horizontal gene transfer events. This approach overcomes limitations of sequence-based methods, improving the detection of evolutionary relationships.

Keywords:
Character-basedGene-expressionHorizontal gene transferIndirect phylogenetic methodsPerfect phylogeniesTree-based networks

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Area of Science:

  • Computational Biology
  • Evolutionary Genetics
  • Phylogenetics

Background:

  • Traditional horizontal gene transfer (HGT) inference relies on gene sequences, which struggle to detect ancient transfers due to mutation-induced sequence divergence.
  • Character-based methods offer an alternative by leveraging conserved functional or expression profiles, even with low DNA similarity, to identify homologous genes.

Purpose of the Study:

  • To introduce and investigate 'perfect transfer networks' as a model for inferring HGT events using character data.
  • To explore the structural and algorithmic properties of perfect transfer networks and compare them with existing models like perfect phylogenetic networks.

Main Methods:

  • Developed the 'perfect transfer network' model, assuming unique character origins and rare character loss.
  • Analyzed the computational complexity of validating a given network against taxa character data.
  • Proposed an algorithm to augment phylogenetic trees with transfer edges to explain observed character distributions.

Main Results:

  • Demonstrated that determining the validity of a perfect transfer network can be done in polynomial time.
  • Provided methods for constructing and analyzing networks that explain character evolution under HGT.
  • Established worst-case lower and upper bounds for the number of transfers required to explain a given set of taxa characters.

Conclusions:

  • Character-based phylogenetic networks provide a powerful framework for detecting ancient horizontal gene transfer events.
  • The perfect transfer network model offers a computationally tractable approach to inferring HGT and understanding its evolutionary impact.