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ABSTRACTS
Year : 2021  |  Volume : 10  |  Issue : 5  |  Page : 17

Beyond spoligotyping: Reconstructing the CRISPR Locus of Mycobacterium tuberculosis complex using short reads archives (SRA) to track genome evolution


1 Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91198, Gif-sur-Yvette cedex, France
2 FEMTO-ST Institute, UMR6174, CNRS, DISC Computer Department, Univ. Bourgogne France-Comté (UFBC), 16 route de Gray, 25000 Besancon, France

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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijmy.ijmy_9_17

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Aims and objectives: Apart from Single Nucleotide Polymorphism (SNP) variations, MTBC genomes evolve by insertion, deletions, duplications, recombination, and variations of repeated sequences (phages, Insertion sequences, VNTR, CRISPR…), likely under both neutral and Darwinian selection. Methods: Spoligotyping, the typing of the CRISPR Locus using the classical Kamerbeek et al. 1997 technique has been used worldwide to produce a very large knowledge of Mycobacterium tuberculosis genetic diversity and has allowed the deciphering of MTBC population structure. It also remains, in many countries, a basic though useful molecular technique to get some clues on the very evolutionary history of a patient isolate and a first step towards genomic epidemiology. New techniques such as Whole genome sequencing, that produce Short Reads Archives (SRA) need to be linked to ancient knowledge, but must also be used to go beyond them. Results: We tackled the computationally difficult task to reconstruct the CRISPR Locus of Mycobacterium tuberculosis complex using Short Reads Archives (SRA) using a de Bruijn graph approach, since current available methods were not able to allow an efficient reconstruction of the locus. We believe that such an application will be interesting for the clinicians and epidemiologists since it both performs an equivalent of spoligotyping and goes beyond. Conclusions: Using this new software, designated as “CRISPR-builder-TB”, we show that the use of SRA allows to infer new subtle and previously hidden characteristics on the MTBC genomes and to dig into the complex history of tuberculosis with more details. This software is freely available on GitHub with adequate tutorials.


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