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Maximum parsimony reconciliation in the DTLOR model.

Jingyi Liu1, Ross Mawhorter2, Nuo Liu1,3

  • 1Department of Computer Science, Harvey Mudd College, Claremont, CA, USA.

BMC Bioinformatics
|August 5, 2021
PubMed
Summary

We introduce the DTLOR model to improve microbial evolution analysis by including gene origins and rearrangements. This new model offers deeper insights into microbial evolutionary histories than the standard duplication-transfer-loss (DTL) model.

Keywords:
Maximum parsimony reconciliationMicrobial evolutionPhylogenetic trees

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Area of Science:

  • Computational biology
  • Evolutionary genomics
  • Microbial evolution

Background:

  • Microbial evolution analyses commonly employ reconciliation methods.
  • The standard duplication-transfer-loss (DTL) model has limitations in fully sampled species trees and gene rearrangements.
  • Gene families can originate from outside sampled species trees, and genes can rearrange within genomes.

Purpose of the Study:

  • To extend the DTL model to incorporate gene origins from outside the species tree and gene syntenic region rearrangements.
  • To develop an efficient algorithm for maximum parsimony reconciliation within this new DTLOR model.
  • To adapt the model for non-binary gene trees and integrate it into tools for reconstructing genomic island histories.

Main Methods:

  • Extension of the standard DTL model to the DTLOR model.
  • Development of an efficient maximum parsimony reconciliation algorithm.
  • Adaptation for non-binary gene trees to handle topological uncertainty.
  • Integration into the xenoGI tool for genomic island history reconstruction.

Main Results:

  • The DTLOR model effectively accounts for gene origins and rearrangements in microbial evolution.
  • An efficient algorithm for maximum parsimony reconciliation in the DTLOR model was developed.
  • Preliminary experimental results demonstrate successful integration into the xenoGI tool for bacterial genomic island analysis.

Conclusions:

  • The DTLOR model provides enhanced capabilities for analyzing microbial evolution compared to the standard DTL model.
  • Reconciliation using the DTLOR model offers novel insights into microbial evolutionary processes.
  • The developed algorithm and its integration facilitate a more comprehensive understanding of genomic island histories.