Identifying lineage effects when controlling for population structure improves power in bacterial association studies

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dc.contributor.author Earle, Sarah G.
dc.contributor.author Wu, Chieh-Hsi
dc.contributor.author Charlesworth, Jane
dc.contributor.author Stoesser, Nicole
dc.contributor.author Gordon, N. Claire
dc.contributor.author Walker, Timothy M.
dc.contributor.author Spencer, Chris C.A.
dc.contributor.author Iqbal, Zamin
dc.contributor.author Clifton, David A.
dc.contributor.author Hopkins, Katie L.
dc.contributor.author Woodford, Neil
dc.contributor.author Smith, E. Grace
dc.contributor.author Ismail, Nazir Ahmed
dc.contributor.author Llewelyn, Martin J.
dc.contributor.author Peto, Tim E.
dc.contributor.author Crook, Derrick W.
dc.contributor.author McVean, Gil
dc.contributor.author Walker, A. Sarah
dc.contributor.author Wilson, Daniel J.
dc.date.accessioned 2016-11-21T09:34:13Z
dc.date.available 2016-11-21T09:34:13Z
dc.date.issued 2016-04-04
dc.description.abstract Bacteria pose unique challenges for genome-wide association studies because of strong structuring into distinct strains and substantial linkage disequilibrium across the genome1,2. Although methods developed for human studies can correct for strain structure3,4, this risks considerable loss-of-power because genetic differences between strains often contribute substantial phenotypic variability5. Here, we propose a new method that captures lineage-level associations even when locus-specific associations cannot be fine-mapped. We demonstrate its ability to detect genes and genetic variants underlying resistance to 17 antimicrobials in 3,144 isolates from four taxonomically diverse clonal and recombining bacteria: Mycobacterium tuberculosis, Staphylococcus aureus, Escherichia coli and Klebsiella pneumoniae. Strong selection, recombination and penetrance confer high power to recover known antimicrobial resistance mechanisms and reveal a candidate association between the outer membrane porin nmpC and cefazolin resistance in E. coli. Hence, our method pinpoints locus-specific effects where possible and boosts power by detecting lineage-level differences when fine-mapping is intractable. en_ZA
dc.description.department Medical Microbiology en_ZA
dc.description.librarian am2016 en_ZA
dc.description.uri http://www.nature.com/nmicrobiol en_ZA
dc.identifier.citation Earle, SG, Wu, C-H, Charlesworth, J, Stoesser, N, Gordon, NC, Walker, TM, Spencer, CCA, Iqbal, Z, Clifton, DA, Hopkins, KL, Woodford, N, Smith, EG, Ismail, N, Llewelyn, MJ, Peto, TE, Crook, DW, McVean, G, Walker, AS & Wilson, DJ 2016, 'Identifying lineage effects when controlling for population structure improves power in bacterial association studies', Nature Microbiology, vol. 1, no. 5, art. #16041, pp. 1-21. en_ZA
dc.identifier.issn 2058-5276
dc.identifier.other 10.1038/nmicrobiol.2016.41
dc.identifier.uri http://hdl.handle.net/2263/58217
dc.language.iso en en_ZA
dc.publisher Springer Nature en_ZA
dc.rights © 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. en_ZA
dc.subject Bacteria en_ZA
dc.subject Strain en_ZA
dc.subject Genetic variants en_ZA
dc.subject Lineage-level en_ZA
dc.title Identifying lineage effects when controlling for population structure improves power in bacterial association studies en_ZA
dc.type Postprint Article en_ZA


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