A statistical method to identify recombination in bacterial genomes based on SNP incompatibility

Area of Science:

• Microbiology
• Bioinformatics
• Evolutionary Biology

Background:

• Bacterial phylogeny estimation assumes clonality, but recombination can obscure true evolutionary histories.
• Recombination leads to varying phylogenetic signals across different genomic regions, complicating tree reconstruction.
• Accurate identification of recombination breakpoints is essential for understanding bacterial population evolution.

Purpose of the Study:

• To develop and validate a statistically robust method for detecting recombination breakpoints in bacterial genomes.
• To improve the accuracy of phylogenetic analysis by accounting for recombination events.

Main Methods:

• An extension of the ACR (Approximate Correlation of Recombination) method, termed ptACR (permutation test ACR).
• Utilizes a permutation test to assess the statistical significance of candidate breakpoints by comparing average local compatibility.
• Evaluated on both simulated and empirical bacterial genomic datasets.

Main Results:

• ptACR demonstrates comparable sensitivity to the basic ACR method but with a reduced false positive rate and higher F1 score.
• Analysis of *Staphylococcus aureus* clinical isolates using ptACR revealed significant evidence of recombination.
• The method successfully identified statistically significant boundaries of chromosomal regions exhibiting distinct phylogenies.

Conclusions:

• ptACR is an accurate and efficient computational tool for pinpointing recombination-affected genomic regions in bacteria.
• This method enhances the reliability of phylogenetic analyses in bacterial species where recombination is prevalent.