Identification of positively selected genes in Mycobacterium tuberculosis from southern Xinjiang Uygur autonomous region of China

中国新疆维吾尔自治区南部结核分枝杆菌中正选择基因的鉴定

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Abstract

BACKGROUND: Tuberculosis (TB), mainly caused by Mycobacterium tuberculosis (Mtb), remains a serious public health problem. Increasing evidence supports that selective evolution is an important force affecting genomic determinants of Mtb phenotypes. It is necessary to further understand the Mtb selective evolution and identify the positively selected genes that probably drive the phenotype of Mtb. METHODS: This study mainly focused on the positive selection of 807 Mtb strains from Southern Xinjiang of China using whole genome sequencing (WGS). PAML software was used for identifying the genes and sites under positive selection in 807 Mtb strains. RESULTS: Lineage 2 (62.70%) strains were the dominant strains in this area, followed by lineage 3 (19.45%) and lineage 4 (17.84%) strains. There were 239 codons in 47 genes under positive selection, and the genes were majorly associated with the functions of transcription, defense mechanisms, and cell wall/membrane/envelope biogenesis. There were 28 codons (43 mutations) in eight genes (gyrA, rpoB, rpoC, katG, pncA, embB, gid, and cut1) under positive selection in multi-drug resistance (MDR) strains but not in drug-susceptible (DS) strains, in which 27 mutations were drug-resistant loci, 9 mutations were non-drug-resistant loci but were in drug-resistant genes, 2 mutations were compensatory mutations, and 5 mutations were in unknown drug-resistant gene of cut1. There was a codon in Rv0336 under positive selection in L3 strains but not in L2 and L4 strains. The epitopes of T and B cells were both hyper-conserved, particularly in the T-cell epitopes. CONCLUSION: This study revealed the ongoing selective evolution of Mtb. We found some special genes and sites under positive selection which may contribute to the advantage of MDR and L3 strains. It is necessary to further study these mutations to understand their impact on phenotypes for providing more useful information to develop new TB interventions.

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