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The aim of the study was the genotyping of Francisella tularensis subsp. mediasiatica strains using marker SNPs based on whole genome sequencing data. Materials and methods. The work used 50 complete genomes (WGS) of F. tularensis subsp. mediasiatica strains from the NCBI database and 25 genomes, which were sequenced directly by specialists from the Rostov-on-Don Anti-Plague Institute of the Rospotrebnadzor. The allocation of individual clusters on the dendrogram was carried out with a bootstrap support value of at least >90 % (when using 1000 replications). Results and discussion. A total of 5,251 SNPs identified in a representative sample of 75 F. tularensis subsp. mediasiatica genomes were selected, with each SNP detected in at least two strains. During the bioinformatics analysis, genomes with more than 500 SNPs in regions not covered by whole-genome sequencing (WGS) were excluded. Phylogenetic analysis resulted in a dendrogram that identified 11 major clusters named after the geographic locations of early or dominant strains. These clusters were supported by bootstrap values >90 % (1,000 replicates). For strain typing within the clusters, “marker” SNPs specific to each cluster and its subgroups – but absent in others – were identified. A software tool, “SNP Genotyper”, was developed to automate genotype determination based on those marker SNPs. Genetic variability of F. tularensis subsp. mediasiatica isolates of diverse origins was studied using whole-genome SNP (wgSNP) analysis. Genetic diversity was observed among subsp. mediasiatica strains isolated in Altai Territory (Russian Federation) and the Republic of Kazakhstan. Based on marker SNPs, an algorithm has been developed for the operational analysis of WGS data from F. tularensis subsp. mediasiatica genomes. The developed method for determining genetic lineages can be a useful tool both for operational analysis when isolating fresh strains, determining the phylogenetic relationships of strains, studying the genetic diversity of a population, and conducting retrospective studies.