ArticleBioinformatics (Oxford, England)2025
Pitfalls of bacterial pan-genome analysis approaches: a case study of Mycobacterium tuberculosis and two less clonal bacterial species.
Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Comprehensive genome-based characterization and pan-genome analysis of Bacillus paranthracis SM02 isolated from a fermented food ecosystem.Functional & integrative genomics · 2026Article
- Within-host pathogen population diversity predicts treatment response in Tuberculosis.medRxiv : the preprint server for health sciences · 2026Article
- Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response.Nature communications · 2026Article
- Genome characteristics and type IV effector protein repertoire of Coxiella burnetii depend rather on Genomic Groups than on host species.BMC microbiology · 2026Article
- Genome announcement of sulfate-reducingMicrobiology resource announcements · 2026Article
- Genome graphs reveal the importance of structural variation in Mycobacterium tuberculosis evolution and drug resistance.Nature communications · 2025Article
- Evolutionary Reasoning Does Not Arise in Standard Usage of Protein Language Models.bioRxiv : the preprint server for biology · 2025Article
- Linkage-based ortholog refinement in bacterial pangenomes with CLARC.Nucleic acids research · 2025Article
- Beyond H37Rv:Frontiers in microbiology · 2025Review
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Abstract
summaryPan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety in methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. Using Mycobacterium tuberculosis, a clonally evolving bacterium with a small accessory genome, as a model system, we systematically evaluated sources of variability in pan-genome estimates. Our analysis revealed that differences in assembly type (short-read versus hybrid), annotation pipeline, and pan-genome software, significantly impact predictions of core and accessory genome size. Extending our analysis to two additional bacterial species, Escherichia coli and Staphylococcus aureus, we observed consistent tool-dependent biases but species-specific patterns in pan-genome variability. Our findings highlight the importance of integrating nucleotide- and protein-level analyses to improve the reliability and reproducibility of pan-genome studies across diverse bacterial populations. AVAILABILITY AND IMPLEMENTATION: Panqc is freely available under an MIT license at https://github.com/maxgmarin/panqc.
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