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

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 with other GI detection tools against a reference dataset. In addition, we illustrated its use on MetagenomeAssembled Genomes (MAGs) 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: 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.