PolyTB: a genomic variation map for Mycobacterium tuberculosis

Francesc Coll, Mark Preston, José Afonso Guerra-Assunção, Grant Hill-Cawthorn, David Harris, João Perdigão, Miguel Viveiros, Isabel Portugal, Francis Drobniewski, Sebastien Gagneux, Judith R. Glynn, Arnab Pain, Julian Parkhill, Ruth McNerney, Nigel Martin, Taane G. Clark

Research output: Contribution to journalArticlepeer-review

61 Citations (Scopus)

Abstract

Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) is the second major cause of death from an infectious disease worldwide. Recent advances in DNA sequencing are leading to the ability to generate whole genome information in clinical isolates of M. tuberculosis complex (MTBC). The identification of informative genetic variants such as phylogenetic markers and those associated with drug resistance or virulence will help barcode Mtb in the context of epidemiological, diagnostic and clinical studies. Mtb genomic datasets are increasingly available as raw sequences, which are potentially difficult and computer intensive to process, and compare across studies. Here we have processed the raw sequence data (>1500 isolates, eight studies) to compile a catalogue of SNPs (n = 74,039, 63% non-synonymous, 51.1% in more than one isolate, i.e. non-private), small indels (n = 4810) and larger structural variants (n = 800). We have developed the PolyTB web-based tool (http://pathogenseq.lshtm.ac.uk/polytb) to visualise the resulting variation and important meta-data (e.g. in silico inferred strain-types, location) within geographical map and phylogenetic views. This resource will allow researchers to identify polymorphisms within candidate genes of interest, as well as examine the genomic diversity and distribution of strains. PolyTB source code is freely available to researchers wishing to develop similar tools for their pathogen of interest.

Original languageEnglish
Pages (from-to)346-354
Number of pages9
JournalTuberculosis (Edinburgh, Scotland)
Volume94
Issue number3
DOIs
Publication statusPublished - May 2014

Keywords

  • Database
  • Genomics
  • Molecular epidemiology
  • Mycobacterium tuberculosis
  • Software
  • Whole-genome sequencing

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