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

dc.contributor.authorEarle, Sarah G.
dc.contributor.authorWu, Chieh-Hsi
dc.contributor.authorCharlesworth, Jane
dc.contributor.authorStoesser, Nicole
dc.contributor.authorGordon, N. Claire
dc.contributor.authorWalker, Timothy M.
dc.contributor.authorSpencer, Chris C.A.
dc.contributor.authorIqbal, Zamin
dc.contributor.authorClifton, David A.
dc.contributor.authorHopkins, Katie L.
dc.contributor.authorWoodford, Neil
dc.contributor.authorSmith, E. Grace
dc.contributor.authorIsmail, Nazir Ahmed
dc.contributor.authorLlewelyn, Martin J.
dc.contributor.authorPeto, Tim E.
dc.contributor.authorCrook, Derrick W.
dc.contributor.authorMcVean, Gil
dc.contributor.authorWalker, A. Sarah
dc.contributor.authorWilson, Daniel J.
dc.date.accessioned2016-11-21T09:34:13Z
dc.date.available2016-11-21T09:34:13Z
dc.date.issued2016-04-04
dc.description.abstractBacteria 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.departmentMedical Microbiologyen_ZA
dc.description.librarianam2016en_ZA
dc.description.urihttp://www.nature.com/nmicrobiolen_ZA
dc.identifier.citationEarle, 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.issn2058-5276
dc.identifier.other10.1038/nmicrobiol.2016.41
dc.identifier.urihttp://hdl.handle.net/2263/58217
dc.language.isoenen_ZA
dc.publisherSpringer Natureen_ZA
dc.rights© 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.en_ZA
dc.subjectBacteriaen_ZA
dc.subjectStrainen_ZA
dc.subjectGenetic variantsen_ZA
dc.subjectLineage-levelen_ZA
dc.titleIdentifying lineage effects when controlling for population structure improves power in bacterial association studiesen_ZA
dc.typePostprint Articleen_ZA

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