Efficient Inference of Recent and Ancestral Recombination within Bacterial Populations

Abstract

Prokaryotic evolution is affected by horizontal transfer of genetic material through recombination. Inference of an evolutionary tree of bacteria thus relies on accurate identification of the population genetic structure and recombination-derived mosaicism. Rapidly growing databases represent a challenge for computational methods to detect recombinations in bacterial genomes. We introduce a novel algorithm called fastGEAR which identifies lineages in diverse microbial alignments, and recombinations between them and from external origins. The algorithm detects both recent recombinations (affecting a few isolates) and ancestral recombinations between detected lineages (affecting entire lineages), thus providing insight into recombinations affecting deep branches of the phylogenetic tree. In simulations, fastGEAR had comparable power to detect recent recombinations and outstanding power to detect the ancestral ones, compared with state-of-the-art methods, often with a fraction of computational cost. We demonstrate the utility of the method by analyzing a collection of 616 whole-genomes of a recombinogenic pathogen Streptococcus pneumoniae, for which the method provided a high-resolution view of recombination across the genome. We examined in detail the penicillin-binding genes across the Streptococcus genus, demonstrating previously undetected genetic exchanges between different species at these three loci. Hence, fastGEAR can be readily applied to investigate mosaicism in bacterial genes across multiple species. Finally, fastGEAR correctly identified many known recombination hotspots and pointed to potential new ones. Matlab code and Linux/Windows executables are available at https://users.ics.aalto.fi/~pemartti/fastGEAR/ (last accessed February 6, 2017).

Whole genome phylogenies reflect long-tailed distributions of recombination rates in many bacterial species

“…[8,19]. Based on this idea, several tools have been developed that detect recombination events by comparing local phylogenies with the overall reference phylogeny constructed from the entire genome [20,21]. In contrast, some recent studies have argued that recombination is so common in some bacterial species that it is impossible to meaningfully reconstruct the clonal ancestry from the genome sequences, and that these species should be considered freely recombining, e.g.…”

Prevalence and global distribution ofblaKPC-2andblaNDM-1genes inKlebsiella Pneumoniae

“…Core_genome_alignment.aln, the output file of Roary pipeline was conveyed to fastGEAR to identify Lineages by hierBAPS 25 .…”

The effect of recombination on the evolution of a population ofNeisseria meningitidis

“…To then analyse the recombinations between clusters in the entire Burkina Faso collection, we ran fastGEAR (Mostowy et al, 2017) on alignments of each gene of the Burkina Faso collection's pan-genome, as inferred by panaroo (Tonkin-Hill et al, 2020) and aligned using MAFFT (Katoh and Standley, 2013), using the whole-genome clustering inferred by poppunk. fastGEAR infers recombinations explicity with directionality, allowing the flow of recombination events between clusters to be visualised as a network.…”