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Arturo Torres Ortiz1,2, Xavier Didelot3, Louis Grandjean2

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Whole-genome sequencing in Mycobacterium tuberculosis requires accurate variant inference. A new hybrid workflow corrects mapping biases, improving the characterization of genetic variations in bacterial pathogens.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Microbiology

Background:

  • Whole-genome sequencing (WGS) generates extensive genetic data.
  • Accurate genomic variant inference is crucial for clinical and epidemiological studies.
  • Comparative genomics of Mycobacterium tuberculosis often uses short-read mapping to a single reference, risking mapping bias.

Purpose of the Study:

  • To analyze the impact of mapping bias in Mycobacterium tuberculosis comparative genomics.
  • To propose and validate a novel hybrid workflow to overcome mapping bias.
  • To improve the characterization of genomic variations and lineages in M. tuberculosis.

Main Methods:

  • Analysis of mapping reads from diverse M. tuberculosis lineages to the H37Rv reference.
  • Development of a three-step hybrid workflow: de novo assembly, alignment to reference, and read mapping to the aligned assembly.
  • Evaluation of bias correction and improved characterization of lineages and hypervariable regions.

Main Results:

  • Mapping bias was observed to vary by M. tuberculosis lineage and gene.
  • The proposed hybrid workflow significantly corrected lineage and gene-specific mapping biases.
  • The new approach enhances the characterization of bacterial genomic diversity.

Conclusions:

  • Standard short-read mapping can introduce significant bias in M. tuberculosis comparative genomics.
  • The novel hybrid workflow effectively mitigates mapping bias, leading to more accurate variant detection.
  • This method facilitates deeper understanding of genetic variations in M. tuberculosis and other bacterial pathogens.