ArticleBMC genomics2019
Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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42 citing papers in PubMed.
- Phenotypic and genotypic features of the Mycobacterium tuberculosis lineage 1 subgroup in central Vietnam.Scientific reports · 2021Trial
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- Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response.Nature communications · 2026Article
- Evolution of Translational Machinery in Fast- and Slow-Growing Bacteria.Microorganisms · 2026Article
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- Organ-Specific Distribution of Antimycobacterial Neolignans inMolecules (Basel, Switzerland) · 2025Article
- Evaluating selection at intermediate scales within genes provides robust identification of genes under positive selection in M. tuberculosis clinical isolates.Tuberculosis (Edinburgh, Scotland) · 2025Article
- Evaluating selection at intermediate scales within genes provides robust identification of genes under positive selection inbioRxiv : the preprint server for biology · 2025Article
- Bacterial genome-wide association studies: exploring the genetic variation underlying bacterial phenotypes.Applied and environmental microbiology · 2025Review
- South Asian origin and global transmission history ofmSystems · 2025Article
- Enhanced diagnosis of multi-drug-resistant microbes using group association modeling and machine learning.Nature communications · 2025Article
- Microevolutionary models and multi-omics analysis uncover the cross-drug resistance characteristics of capreomycin-selectedCurrent research in microbial sciences · 2025Article
- Machine learning-based approach for identification of new resistance associated mutations from whole genome sequences ofBioinformatics advances · 2025Article
- Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches.Scientific reports · 2024Article
- Large-scale statistical analysis of Mycobacterium tuberculosis genome sequences identifies compensatory mutations associated with multi-drug resistance.Scientific reports · 2024Article
- Genetic Characterization and Population Structure of Drug-ResistantAntibiotics (Basel, Switzerland) · 2024Article
- Horizontal Gene Transfer and Drug Resistance InvolvingAntibiotics (Basel, Switzerland) · 2023Article
- Molecular epidemiology and transmission dynamics of multi-drug resistant tuberculosis strains using whole genome sequencing in the Amhara region, Ethiopia.BMC genomics · 2023Article
- Comparison of in silico predicted Mycobacterium tuberculosis spoligotypes and lineages from whole genome sequencing data.Scientific reports · 2023Article
- Feature weighted models to address lineage dependency in drug-resistance prediction from Mycobacterium tuberculosis genome sequences.Bioinformatics (Oxford, England) · 2023Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundContinuing evolution of the Mycobacterium tuberculosis (Mtb) complex genomes associated with resistance to anti-tuberculosis drugs is threatening tuberculosis disease control efforts. Both multi- and extensively drug resistant Mtb (MDR and XDR, respectively) are increasing in prevalence, but the full set of Mtb genes involved are not known. There is a need for increased sensitivity of genome-wide approaches in order to elucidate the genetic basis of anti-microbial drug resistance and gain a more detailed understanding of Mtb genome evolution in a context of widespread antimicrobial therapy. Population structure within the Mtb complex, due to clonal expansion, lack of lateral gene transfer and low levels of recombination between lineages, may be reducing statistical power to detect drug resistance associated variants.
resultsTo investigate the effect of lineage-specific effects on the identification of drug resistance associations, we applied genome-wide association study (GWAS) and convergence-based (PhyC) methods to multiple drug resistance phenotypes of a global dataset of Mtb lineages 2 and 4, using both lineage-wise and combined approaches. We identify both well-established drug resistance variants and novel associations; uniquely identifying associations for both lineage-specific and -combined GWAS analyses. We report 17 potential novel associations between antimicrobial resistance phenotypes and Mtb genomic variants.
conclusionsFor GWAS, both lineage-specific and -combined analyses are useful, whereas PhyC may perform better in contexts of greater diversity. Unique associations with XDR in lineage-specific analyses provide evidence of diverging evolutionary trajectories between lineages 2 and 4 in response to antimicrobial drug therapy.
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