Systematic Detection of Large-Scale Multigene Horizontal Transfer in Prokaryotes

Area of Science:

• Microbial genomics and evolutionary biology
• Computational biology and bioinformatics

Background:

• Horizontal gene transfer (HGT) is a key driver of prokaryotic evolution.
• The scale and frequency of individual HGT events, particularly those involving multiple genes, remain poorly understood.

Purpose of the Study:

• To introduce the first computational framework, HoMer, for inferring horizontal multigene transfers (HMGTs).
• To quantify the frequency and characteristics of HMGTs across diverse phylogenetic scales.

Main Methods:

• HoMer utilizes phylogenetic reconciliation to identify single-gene HGT events.
• Integrates gene order information from extant genomes and statistical analyses to detect candidate HMGTs.
• Applies the framework to a large dataset of over 22,000 gene families from 103 Aeromonas genomes.

Main Results:

• Identified numerous plausible HMGTs across various phylogenetic distances.
• Observed an increased relative frequency of HMGTs with greater genomic divergence.
• Found that HMGTs frequently involve genes with conserved functions and facilitate the acquisition of rare genes.

Conclusions:

• HoMer provides a scalable computational solution for systematically inferring HMGTs.
• The findings enhance our understanding of HGT's role in microbial evolution, gene function conservation, and adaptation.
• Highlights the significance of multigene transfers in shaping microbial genomes.