Whole-Genome Sequencing Framework for Prioritizing Candidate Antimicrobial-Resistance Variants in Mycobacterium tuberculosis: A Nigeria-Focused Methodological Study

Tuberculosis remains a major cause of infectious-disease mortality, and drug-resistant disease continues to undermine treatment and control programmes.Whole-genome sequencing (WGS) can provide comprehensive information on established resistance mutations, bacterial lineages and potential transmission clusters, but variants absent from validated catalogues require cautious interpretation, particularly where African genomes and linked phenotypic data are underrepresented.This paper presents a transparent simulation-based framework showing how WGS-derived variables can be integrated with phenotypic drug-susceptibility results to evaluate resistance prediction and prioritise candidate antimicrobial-resistance variants in a Nigerian context.A deterministic synthetic scenario representing 200 non-duplicate hypothetical Mycobacterium tuberculosis isolate records was constructed from prespecified marginal totals.No patients, clinical specimens, cultures, raw sequence reads or sequencing runs were involved.The scenario included demographic and geographical variables, resistance phenotypes, sequencing-quality indicators, lineage assignments, recognised resistance mutations and deliberately introduced unclassified variants.Descriptive analysis, genotype-phenotype agreement measures, logistic-regression illustration and simulated phylogenetic clustering were used to demonstrate an analytical workflow.Within the constructed scenario, agreement was highest for rifampicin, isoniazid, fluoroquinolones and amikacin and lower for ethambutol and pyrazinamide.Lineage 4 was the predominant assigned lineage, while Lineage 2 was configured to occur more frequently with advanced resistance.Application of prespecified prioritisation rules retained five hypothetical candidate variants; these are not empirical discoveries or validated resistance determinants.The framework demonstrates reporting logic for future empirical WGS investigations and identifies the additional evidence required for causal and clinical interpretation, including actual isolates, raw-read provenance, minimum inhibitory concentrations, population-structure correction, independent replication and functional validation.Its principal contribution is methodological: it provides a structured model for designing multicentre Nigerian genomic-surveillance studies without presenting synthetic outputs as population estimates or biological findings.