GeneScanner: profiling genetic variation across bacterial populations

Journal article

Rapid, low-cost genome sequencing has transformed microbiology, advancing efforts to link genetic and phenotypic variation across diverse bacterial systems. Laboratory functional screens now uncover causal mechanisms underlying key traits in simplified systems, such as drug resistance, pathogenicity and metabolic adaptation, while population-scale comparative genomics reveal the immense natural diversity associated with these traits in real-world settings. Despite their complementary strengths, these approaches remain challenging to integrate, especially for researchers without advanced bioinformatics skills. This skills gap can constrain the capacity to reveal the mechanisms underlying microbial traits and evolutionary adaptations. We developed GeneScanner to aid user-friendly analyses of gene- and protein-level variation across large bacterial genome collections. GeneScanner detects genetic variants and amino acid substitutions in homologous sequences to improve functional interpretation of microbial variation. Using synthetic data and three case studies across different species and phenotypes, we show that GeneScanner reliably identifies nucleotide and protein-level variants associated with specific traits. The presented examples highlight the broad applicability of GeneScanner in microbial genomics, enabling research across diverse fields, such as antimicrobial resistance, host-pathogen interactions, microbial evolution, epidemiology and public health.

Authors: Kobras, CM; Ko, S; Raikwar, PS; Aguilar-Sanjuan, B; Jolley, KA

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Microbiology Society
• Journal: Microbial Genomics
• Volume: 12
• Issue: 6
• Publication date: 2026-06-01
• DOI: 10.1099/mgen.0.001714
• EISSN: 2057-5858
• ISSN: 2057-5858
• Pmid: 42228609
• Language: English
• Keywords: Software; Bioinformatics; Biofilm; Phenotype; Genetic Variation; Genome, Bacterial; Mutation Analysis; Comparative genomics; Bacteria; Host Association; Drug Resistance, Bacterial; Genetic variation; Computational Biology; Antimicrobial resistance; Variant Calling; Genomics