Pangenome-wide association study reveals selective absence of CRISPR genes (Rv2816c-19c) in drug-resistantMycobacterium tuberculosis
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Abstract
Background The drug resistance development in Mycobacterium tuberculosis (Mtb) is attributed to the acquisition of mutations in the drug target genes. However, the role of the differential presence of non-essential accessory genes is relatively unexplored and Pan Genome-Wide Association Study (Pan-GWAS) can identify these gene sets that could contribute to drug resistance development in Mtb. Methodology Publicly available Whole Genome Sequencing (WGS) data of clinical Mtb isolates (n=2601) from TB endemic countries (India, China, Zambia, Pakistan) were used in this study. The Mtb WGS data was de novo assembled, filtered for contamination, scaffolded into longer contigs, and functionally annotated. All analyses, including Gene repertoire and Pan-GWAS, were conducted using open-source tools, and the Benjamin Hochberg test was applied to identify genes having significant association with drug-resistant Mtb isolates. Results Out of 2601 Mtb WGS data sets, 2184 qualified as high-quality and were used for Pan-GWAS analysis (drug-resistant n=1386; drug-sensitive n=798). A set of 3784 core genes, 123 softcore genes, 224 shell genes, and 762 cloud genes were identified. Sets of 33 and 39 genes showed a positive and a negative association with drug-resistant isolates, respectively, with high significance (p-value < 0.01). Gene ontology cluster analysis indicated a compromised bacterial immune system and impaired DNA repair in drug-resistant compared to the sensitive isolates. Multidrug efflux pump repressor genes (Rv3830c and Rv3855c) were also absent in the drug-resistant Mtb isolates. The absence of CRISPR-associated genes (Rv2816c-19c) is reported in other drug-resistant microbes, and a similar pattern is observed in Mtb. Conclusions This study sheds light on Mtb genes involved in drug resistance emergence and could be helpful in better understanding of host-pathogen interactions, identification of novel drug targets and diagnostics.
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- last seen: 2026-05-20T01:45:00.602351+00:00