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Panorama: A robust pangenome-based method for predicting and comparing biological systems across species
Jérôme Arnoux1, Jean Mainguy1, Laura Bry1
1LABGeM, Génomique Métabolique, CEA, Genoscope, Institut François Jacob, Université d'Évry, Université Paris-Saclay, CNRS, Évry, France.
Plos Computational Biology
|July 10, 2026
Summary
A new tool, PANORAMA, analyzes pangenome graphs to explore microbial genomic diversity and evolution. It efficiently annotates and compares large genome datasets, advancing comparative genomics for prokaryotes.
Area of Science:
- Genomics
- Bioinformatics
- Evolutionary Biology
Background:
- The increasing number of available prokaryotic genomes necessitates advanced bioinformatic approaches.
- Traditional single-genome analysis methods are insufficient for large-scale genomic data.
- Pangenome analysis offers a comprehensive framework for studying the full genetic repertoire of a species.
Purpose of the Study:
- To introduce PANORAMA, an innovative pangenomic tool for annotating and comparing pangenome graphs.
- To explore genomic diversity and evolutionary dynamics across multiple microbial species.
- To provide new methods for large-scale comparative microbial genomics.
Main Methods:
- Utilized PPanGGOLiN for pangenome graph construction.
- Integrated rule-based prediction of macromolecular systems within PANORAMA.
- Performed comparative analysis of conserved features, including insertion sites, across pangenomes.
Main Results:
- Demonstrated PANORAMA's capability to annotate and compare pangenome graphs.
- Evaluated PANORAMA's performance against existing defense system prediction tools using Pseudomonas aeruginosa.
- Successfully applied PANORAMA to a large dataset of Enterobacteriaceae (>6,000 genomes) for diversity exploration.
Conclusions:
- PANORAMA is an effective tool for large-scale comparative analysis of microbial genomes.
- Pangenome approaches are crucial for understanding microbial evolutionary dynamics.
- PANORAMA facilitates the exploration of biological system diversity and distribution across species.
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