panRGP: a pangenome-based method to predict genomic islands and explore their diversity

Abstract

Motivation Horizontal gene transfer (HGT) is a major source of variability in prokaryotic genomes. Regions of genome plasticity (RGPs) are clusters of genes located in highly variable genomic regions. Most of them arise from HGT and correspond to genomic islands (GIs). The study of those regions at the species level has become increasingly difficult with the data deluge of genomes. To date, no methods are available to identify GIs using hundreds of genomes to explore their diversity. Results We present here the panRGP method that predicts RGPs using pangenome graphs made of all available genomes for a given species. It allows the study of thousands of genomes in order to access the diversity of RGPs and to predict spots of insertions. It gave the best predictions when benchmarked along other GI detection tools against a reference dataset. In addition, we illustrated its use on metagenome assembled genomes by redefining the borders of the leuX tRNA hotspot, a well-studied spot of insertion in Escherichia coli. panRPG is a scalable and reliable tool to predict GIs and spots making it an ideal approach for large comparative studies. Availability and implementation The methods presented in the current work are available through the following software: https://github.com/labgem/PPanGGOLiN. Detailed results and scripts to compute the benchmark metrics are available at https://github.com/axbazin/panrgp_supdata.

The ESKAPE mobilome contributes to the spread of antimicrobial resistance and CRISPR-mediated conflict between mobile genetic elements

“…Several bioinformatic tools exist to look for plasmids and prophages, but currently the options for ICEs/IMEs are scarce [64]. We provide here an accurate identification of these elements, building upon a recently reported tool to scan RGPs [65]. However, our approach depends on the availability of a pangenome for the considered taxa, which is an important limitation for species with an insufficient number of completely sequenced genomes.…”

Genomic Stability and Genetic Defense Systems in Dolosigranulum pigrum , a Candidate Beneficial Bacterium from the Human Microbiome

“…Gene clustering and annotation data were exported from the Anvi’o output and imported into PPanGGOLiN version 1.1.141 ( P artitioned PanG enome G raph O f Li nked N eighbors) ( 68 ) to create a partitioned pangenome graph (PPG) that assigned GCs to the “persistent,” “shell,” and “cloud” partitions. Regions of genome plasticity (RGPs) and spots of insertion were predicted ( 122 ), and subgraphs of the hot spots of interest were generated by providing the sequence of the flanking proteins in a fasta file. The output of the PPanGGOLiN analysis and the code used to generate it are available online ( https://github.com/KLemonLab/DpiMGE_Manuscript/blob/master/SupplementalMethods_PPanGGOLiN.md ).…”

Construction of a complete set of Neisseria meningitidis mutants and its use for the phenotypic profiling of this human pathogen

“…The other parameters have been used with default values to compute the persistent, shell and cloud partitions. The PPanGGOLiN results were then used to predict regions of genomic plasticity using the panRGP module within PPanGGOLiN (version 1.1.85), with default options 30 .…”