Persistent, Private, and Mobile Genes: A Model for Gene Dynamics in Evolving Pangenomes

Area of Science:

• Bacterial genomics
• Evolutionary biology
• Computational biology

Background:

• Bacterial pangenomes encompass all genes within a species, often exceeding individual genomes.
• Evolutionary forces driving gene presence/absence patterns in pangenomes remain incompletely understood.

Purpose of the Study:

• To introduce a novel model for bacterial pangenome evolution.
• To classify genes based on their evolutionary dynamics: persistent, private, and mobile.
• To provide a mechanistic framework for understanding pangenome dynamics.

Main Methods:

• Developed the Persistent-Private-Mobile (PPM) model.
• Created an algorithm for fitting the PPM model to genomic data.
• Applied the model to 902 Salmonella enterica genomes.

Main Results:

• The PPM model successfully reproduces global patterns in gene frequency spectra.
• Gene classification by the PPM model reveals insights into accessory gene location and function.
• The model accurately captures gene presence/absence dynamics across a species phylogeny.

Conclusions:

• The PPM model offers a mechanistic understanding of bacterial pangenome evolution.
• PPM-based gene classification can be utilized for dynamics-aware analysis.
• This approach enhances our comprehension of bacterial genome diversity and adaptation.