Panorama: A robust pangenome-based method for predicting and comparing biological systems across species
Abstract
Over the last decade, the expansion in the number of available genomes has profoundly transformed the study of genetic diversity, evolution, and ecological adaptation in prokaryotes. However, traditional bioinformatic approaches based on the analysis of individual genomes are showing their limitations when faced with the sheer scale of the data. To overcome these constraints, the concept of pangenome has emerged, offering a comprehensive framework to capture the full genetic repertoire of a species. In this study, we present PANORAMA, an innovative pangenomic tool designed to exploit pangenome graphs and enable them to be annotated and compared in order to explore the genomic diversity of several species. Based on the PPanGGOLiN pangenome graphs, PANORAMA integrates advanced methods for rule-based prediction of macromolecular systems and comparative analysis of conserved features between different pangenomes, such as spots of insertion. We illustrate the use of PANORAMA on a dataset of 941 Pseudomonas aeruginosa genomes, evaluating its performance against reference defense system prediction tools such as PADLOC and DefenseFinder. The analysis was then extended to a larger set, including four species of Enterobacteriaceae ( > 6,000 genomes), demonstrating PANORAMA’s ability to annotate, compare, and explore the diversity and distribution of biological systems across multiple species. This work provides new methods for the large-scale comparative study of microbial genomes and underlines the relevance of pangenome approaches in deciphering their evolutionary dynamics. PANORAMA is freely available and accessible through: https://github.com/labgem/PANORAMA Author summary Microorganisms are present in nearly all environments on Earth. Uncovering their diversity through the study of their genomes is essential for understanding their biology and evolution. This includes characterizing the species’ complete genetic repertoire, known as the pangenome. Such research also enables new applications in health, ecology, biotechnology, etc. Here, we present PANORAMA, a novel computational tool designed to predict macromolecular systems, such as defense mechanisms against phages, and to compare pangenome graphs across different species. By using rule-based models that combine gene function and genomic context, we can search for systems directly within pangenome graphs. This graph-based approach provides a global view of the functional content of entire species, moving beyond the analysis of individual genomes. It greatly facilitates the analysis of thousands of genomes by reducing the required computation time and directly integrating the results to identify shared and specific systems. Furthermore, PANORAMA’s comparative functionality enables the identification of conserved structures across species, such as shared spots of insertion, revealing common evolutionary mechanisms and functional modules. This work establishes a foundation for comparative pangenomics, offering an unprecedented framework to explore the adaptive potential and evolutionary dynamics of prokaryotes at scale.
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BibTeX
@article{arnoux2026panorama,
title = {{Panorama: A robust pangenome-based method for predicting and comparing biological systems across species}},
author = {Jérôme Arnoux and Jean Mainguy and Laura Bry and Quentin Fernandez de Grado and Yazid Hoblos and David Vallenet and Alexandra Calteau},
journal = {PLoS Computational Biology},
year = {2026},
month = jul,
doi = {10.1371/journal.pcbi.1013856},
url = {https://hal.science/hal-05762157v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - Panorama: A robust pangenome-based method for predicting and comparing biological systems across species
AU - Jérôme Arnoux
AU - Jean Mainguy
AU - Laura Bry
AU - Quentin Fernandez de Grado
AU - Yazid Hoblos
AU - David Vallenet
AU - Alexandra Calteau
PY - 2026
DA - 2026/07/10
JO - PLoS Computational Biology
DO - 10.1371/journal.pcbi.1013856
UR - https://hal.science/hal-05762157v1
AB - Over the last decade, the expansion in the number of available genomes has profoundly transformed the study of genetic diversity, evolution, and ecological adaptation in prokaryotes. However, traditional bioinformatic approaches based on the analysis of individual genomes are showing their limitations when faced with the sheer scale of the data. To overcome these constraints, the concept of pangenome has emerged, offering a comprehensive framework to capture the full genetic repertoire of a species. In this study, we present PANORAMA, an innovative pangenomic tool designed to exploit pangenome graphs and enable them to be annotated and compared in order to explore the genomic diversity of several species. Based on the PPanGGOLiN pangenome graphs, PANORAMA integrates advanced methods for rule-based prediction of macromolecular systems and comparative analysis of conserved features between different pangenomes, such as spots of insertion. We illustrate the use of PANORAMA on a dataset of 941 Pseudomonas aeruginosa genomes, evaluating its performance against reference defense system prediction tools such as PADLOC and DefenseFinder. The analysis was then extended to a larger set, including four species of Enterobacteriaceae ( > 6,000 genomes), demonstrating PANORAMA’s ability to annotate, compare, and explore the diversity and distribution of biological systems across multiple species. This work provides new methods for the large-scale comparative study of microbial genomes and underlines the relevance of pangenome approaches in deciphering their evolutionary dynamics. PANORAMA is freely available and accessible through: https://github.com/labgem/PANORAMA Author summary Microorganisms are present in nearly all environments on Earth. Uncovering their diversity through the study of their genomes is essential for understanding their biology and evolution. This includes characterizing the species’ complete genetic repertoire, known as the pangenome. Such research also enables new applications in health, ecology, biotechnology, etc. Here, we present PANORAMA, a novel computational tool designed to predict macromolecular systems, such as defense mechanisms against phages, and to compare pangenome graphs across different species. By using rule-based models that combine gene function and genomic context, we can search for systems directly within pangenome graphs. This graph-based approach provides a global view of the functional content of entire species, moving beyond the analysis of individual genomes. It greatly facilitates the analysis of thousands of genomes by reducing the required computation time and directly integrating the results to identify shared and specific systems. Furthermore, PANORAMA’s comparative functionality enables the identification of conserved structures across species, such as shared spots of insertion, revealing common evolutionary mechanisms and functional modules. This work establishes a foundation for comparative pangenomics, offering an unprecedented framework to explore the adaptive potential and evolutionary dynamics of prokaryotes at scale.
SN - 1553-734X
SN - 1553-7358
ER -