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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
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Inferring Ancestral Recombination Graphs from Bacterial Genomic Data.
Timothy G Vaughan1,2, David Welch3,2, Alexei J Drummond3,2
1Centre for Computational Evolution, The University of Auckland, 1010, New Zealand tgvaughan@gmail.com.
Genetics
|December 24, 2016
Summary
This study introduces a new method for bacterial evolution analysis, enabling joint inference of recombination graphs and parameters. The Bacter software package aids in understanding bacterial phylogeny and evolution.
Area of Science:
- Microbiology
- Evolutionary Biology
- Bioinformatics
Background:
- Homologous recombination is crucial for bacterial evolution but complicates traditional phylogenetic analyses.
- Existing methods struggle with the joint inference of bacterial recombination graphs and their parameters.
- Phylogenetic inference in bacteria is challenged by recombination events.
Purpose of the Study:
- To present a novel method for joint inference of bacterial recombination graphs and associated parameters.
- To address the limitations of current phylogenetic methods in handling bacterial recombination.
- To develop an open-source software package for bacterial phylogenetic inference.
Main Methods:
- A new Markov chain Monte Carlo (MCMC) algorithm was developed for phylogenetic inference.
- The ClonalOrigin model was utilized for phylogenetic analysis.
- The method was implemented as an open-source BEAST 2 package named Bacter.
Main Results:
- The new method successfully performed joint inference of bacterial recombination graphs and parameters.
- The utility of the method was demonstrated using Escherichia coli multilocus sequence typing data.
- Analysis included pathogenic and nonpathogenic E. coli serotypes O157 and O26 from New Zealand.
Conclusions:
- The developed method and Bacter package offer a significant advancement in analyzing bacterial evolution.
- This approach facilitates a more comprehensive understanding of bacterial phylogeny in the presence of recombination.
- The open-source availability promotes wider application in microbial evolutionary studies.
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