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

Maha R Farhat; Luca Freschi; Roger Calderon; Thomas Ioerger; Matthew Snyder; Conor Meehan; Bouke de Jong; Leen Rigouts; Alex Sloutsky; Devinder Kaur; Shamil Sunyaev; Dick van Soolingen; Jay Shendure; Jim Sacchettini; Megan Murray

doi:10.1038/s41467-019-10110-6

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

Maha R Farhat, Luca Freschi, Roger Calderon, Thomas Ioerger, Matthew Snyder, Conor Meehan, Bouke de Jong, Leen Rigouts, Alex Sloutsky, Devinder Kaur, Shamil Sunyaev, Dick van Soolingen, Jay Shendure, Jim Sacchettini, Megan Murray

Mycobacteriology

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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.

Original language	English
Article number	2128
Journal	Nature Communications
Volume	10
Issue number	1
Number of pages	11
ISSN	2041-1723
DOIs	https://doi.org/10.1038/s41467-019-10110-6
Publication status	Published - 2019

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2019ncom2128Final published version, 2.5 MBLicence: CC BY

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Farhat, M. R., Freschi, L., Calderon, R., Ioerger, T., Snyder, M., Meehan, C., de Jong, B., Rigouts, L., Sloutsky, A., Kaur, D., Sunyaev, S., van Soolingen, D., Shendure, J., Sacchettini, J., & Murray, M. (2019). GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions. Nature Communications, 10(1), Article 2128. https://doi.org/10.1038/s41467-019-10110-6

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title = "GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions",

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.",

author = "Farhat, {Maha R} and Luca Freschi and Roger Calderon and Thomas Ioerger and Matthew Snyder and Conor Meehan and {de Jong}, Bouke and Leen Rigouts and Alex Sloutsky and Devinder Kaur and Shamil Sunyaev and {van Soolingen}, Dick and Jay Shendure and Jim Sacchettini and Megan Murray",

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Farhat, MR, Freschi, L, Calderon, R, Ioerger, T, Snyder, M, Meehan, C, de Jong, B , Rigouts, L, Sloutsky, A, Kaur, D, Sunyaev, S, van Soolingen, D, Shendure, J, Sacchettini, J & Murray, M 2019, 'GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions', Nature Communications, vol. 10, no. 1, 2128. https://doi.org/10.1038/s41467-019-10110-6

TY - JOUR

T1 - GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions

AU - Farhat, Maha R

AU - Freschi, Luca

AU - Calderon, Roger

AU - Ioerger, Thomas

AU - Snyder, Matthew

AU - Meehan, Conor

AU - de Jong, Bouke

AU - Rigouts, Leen

AU - Sloutsky, Alex

AU - Kaur, Devinder

AU - Sunyaev, Shamil

AU - van Soolingen, Dick

AU - Shendure, Jay

AU - Sacchettini, Jim

AU - Murray, Megan

N1 - FTX; DOAJ; (CC BY 4.0)

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

U2 - 10.1038/s41467-019-10110-6

DO - 10.1038/s41467-019-10110-6

M3 - A1: Web of Science-article

C2 - 31086182

SN - 2041-1723

VL - 10

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 2128

ER -

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

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