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GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions

Author

Listed:
  • Maha R. Farhat

    (Harvard Medical School
    Massachusetts General Hospital)

  • Luca Freschi

    (Harvard Medical School)

  • Roger Calderon

    (Socios en Salud)

  • Thomas Ioerger

    (Texas A and M University)

  • Matthew Snyder

    (University of Washington)

  • Conor J. Meehan

    (Institute of Tropical Medicine)

  • Bouke de Jong

    (Institute of Tropical Medicine)

  • Leen Rigouts

    (Institute of Tropical Medicine)

  • Alex Sloutsky

    (University of Massachusetts Medical School)

  • Devinder Kaur

    (University of Massachusetts Medical School)

  • Shamil Sunyaev

    (Harvard Medical School
    Brigham and Women’s Hospital)

  • Dick van Soolingen

    (National Institute for Public Health and the Environment (RIVM))

  • Jay Shendure

    (University of Washington
    Howard Hughes Medical Institute
    Brotman Baty Institute for Precision Medicine)

  • Jim Sacchettini

    (Texas A and M University)

  • Megan Murray

    (Harvard Medical School)

Abstract

Drug resistance diagnostics that rely on the detection of resistance-related mutations could expedite patient care and TB eradication. We perform minimum inhibitory concentration testing for 12 anti-TB drugs together with Illumina whole-genome sequencing on 1452 clinical Mycobacterium tuberculosis (MTB) isolates. We evaluate genome-wide associations between mutations in MTB genes or non-coding regions and resistance, followed by validation in an independent data set of 792 patient isolates. We confirm associations at 13 non-canonical loci, with two involving non-coding regions. Promoter mutations are measured to have smaller average effects on resistance than gene body mutations. We estimate the heritability of the resistance phenotype to 11 anti-TB drugs and identify a lower than expected contribution from known resistance genes. This study highlights the complexity of the genomic mechanisms associated with the MTB resistance phenotype, including the relatively large number of potentially causal loci, and emphasizes the contribution of the non-coding portion of the genome.

Suggested Citation

  • Maha R. Farhat & Luca Freschi & Roger Calderon & Thomas Ioerger & Matthew Snyder & Conor J. Meehan & Bouke de Jong & Leen Rigouts & Alex Sloutsky & Devinder Kaur & Shamil Sunyaev & Dick van Soolingen , 2019. "GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10110-6
    DOI: 10.1038/s41467-019-10110-6
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    Cited by:

    1. Matthias Merker & Jean-Philippe Rasigade & Maxime Barbier & Helen Cox & Silke Feuerriegel & Thomas A. Kohl & Egor Shitikov & Kadri Klaos & Cyril Gaudin & Rudy Antoine & Roland Diel & Sonia Borrell & S, 2022. "Transcontinental spread and evolution of Mycobacterium tuberculosis W148 European/Russian clade toward extensively drug resistant tuberculosis," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Chrispin Chaguza & Dorota Jamrozy & Merijn W. Bijlsma & Taco W. Kuijpers & Diederik Beek & Arie Ende & Stephen D. Bentley, 2022. "Population genomics of Group B Streptococcus reveals the genetics of neonatal disease onset and meningeal invasion," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    3. Luca Freschi & Roger Vargas & Ashaque Husain & S. M. Mostofa Kamal & Alena Skrahina & Sabira Tahseen & Nazir Ismail & Anna Barbova & Stefan Niemann & Daniela Maria Cirillo & Anna S. Dean & Matteo Zign, 2021. "Population structure, biogeography and transmissibility of Mycobacterium tuberculosis," Nature Communications, Nature, vol. 12(1), pages 1-11, December.

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