Abstract
The exponential increase in the number of genomes deposited in public databases can help us gain a more holistic understanding of the phylogeny and epidemiology of Klebsiella pneumoniae. However, inferring the evolutionary relationships of K. pneumoniae based on big genomic data is challenging for existing methods. In this study, core genes of K. pneumoniae were determined and analysed in terms of differences in GC content, mutation rate, size, and potential functions. We then developed a stable genes-based method for big data analysis and compared it with existing methods. Our new method achieved a higher resolution phylogenetic analysis of K. pneumoniae. Using this genes-based method, we explored global phylogenetic relationships based on a public database of nearly 953 genomes. The results provide useful information to facilitate the phylogenetic and epidemiological analysis of K. pneumoniae, and the findings are relevant for security applications.
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