Systematic Detection of Large-Scale Multigene Horizontal Transfer in Prokaryotes.

Horizontal gene transfer (HGT) is central to prokaryotic evolution. However, little is known about the "scale" of individual HGT events. In this work, we introduce the first computational framework to help answer the following fundamental question: How often does more than one gene get horizontally transferred in a single HGT event? Our method, called HoMer, uses phylogenetic reconciliation to infer single-gene HGT events across a given set of species/strains, employs several techniques to account for inference error and uncertainty, combines that information with gene order information from extant genomes, and uses statistical analysis to identify candidate horizontal multigene transfers (HMGTs) in both extant and ancestral species/strains. HoMer is highly scalable and can be easily used to infer HMGTs across hundreds of genomes. We apply HoMer to a genome-scale data set of over 22,000 gene families from 103 Aeromonas genomes and identify a large number of plausible HMGTs of various scales at both small and large phylogenetic distances. Analysis of these HMGTs reveals interesting relationships between gene function, phylogenetic distance, and frequency of multigene transfer. Among other insights, we find that 1) the observed relative frequency of HMGT increases as divergence between genomes increases, 2) HMGTs often have conserved gene functions, and 3) rare genes are frequently acquired through HMGT. We also analyze in detail HMGTs involving the zonula occludens toxin and type III secretion systems. By enabling the systematic inference of HMGTs on a large scale, HoMer will facilitate a more accurate and more complete understanding of HGT and microbial evolution.

Investigating Additive and Replacing Horizontal Gene Transfers Using Phylogenies and Whole Genomes.

Horizontal gene transfer (HGT) is fundamental to microbial evolution and adaptation. When a gene is horizontally transferred, it may either add itself as a new gene to the recipient genome (possibly displacing nonhomologous genes) or replace an existing homologous gene. Currently, studies do not usually distinguish between "additive" and "replacing" HGTs, and their relative frequencies, integration mechanisms, and specific roles in microbial evolution are poorly understood. In this work, we develop a novel computational framework for large-scale classification of HGTs as either additive or replacing. Our framework leverages recently developed phylogenetic approaches for HGT detection and classifies HGTs inferred between terminal edges based on gene orderings along genomes and phylogenetic relationships between the microbial species under consideration. The resulting method, called DART, is highly customizable and scalable and can classify a large fraction of inferred HGTs with high confidence and statistical support. Our application of DART to a large dataset of thousands of gene families from 103 Aeromonas genomes provides insights into the relative frequencies, functional biases, and integration mechanisms of additive and replacing HGTs. Among other results, we find that (i) the relative frequency of additive HGT increases with increasing phylogenetic distance, (ii) replacing HGT dominates at shorter phylogenetic distances, (iii) additive and replacing HGTs have strikingly different functional profiles, (iv) homologous recombination in flanking regions of a novel gene may be a frequent integration mechanism for additive HGT, and (v) phages and mobile genetic elements likely play an important role in facilitating additive HGT.