Mycobacterium tuberculosis (Mtb) is the causative agent of human tuberculosis (TB) which remains one of the deadliest pathogens worldwide. The observed genetic diversity among Mtb lineages has been associated with differences in virulence, pathogenicity and drug resistance. However, a better understanding of Mtb strain diversity and its implications for Mtb biology will inform the development of TB control tools, including diagnostics, drugs, and vaccines. Through the application of ‘omics approaches, this thesis presents a comprehensive analysis of whole‐genome sequence (WGS) data from Mtb clinical isolates to improve the understanding of the pathogen biology and inform on pathogenicity and drug resistance. The integrated analysis of the genome, transcriptome and methylome of ancient and modern lineages of Mtb revealed genetic variants and methylation patterns with a potential role in gene expression regulation. Through the analysis of the frequency and distribution of mutations associated with resistance to the new anti‐TB drugs (bedaquiline, delamanid and pretomanid) in a large data set (∼30k isolates), mutations pre‐dating the introduction of these drugs with likely functional effects were observed. This result suggests possible intrinsic or cross‐resistance, and potential threats to the effectiveness of MDR‐TB treatments. Moreover, by using long‐read sequence data, it was possible to characterise the genetic diversity of the 169 pe/ppe genes, which are loci traditionally removed from WGS analysis due to their repetitive GC‐rich regions. Structural variants in pe/ppe genes with lineage‐specific patterns were found. Finally, with sequencing technologies gaining traction as diagnostic tools, the use of the MinION portable and long‐read platform was assessed. The results support its suitability for epidemiological applications and drug resistance detection, with the potential to characterise pe/ppe genes through improved coverage of GC‐rich regions. Overall, this thesis demonstrates the potential of sequencing platforms to inform TB control and improve the understanding of Mtb biology. The application of different ‘omics provides with a comprehensive analysis of the different Mtb lineages showing distinct genomic and transcriptomic profiles that translate into different behaviours, with diagnostic and treatment implications.
