Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes

John A. Lees, Minna Vehkala, Niko Välimäki, Simon R. Harris, Claire Chewapreecha, Nicholas J. Croucher, Pekka Marttinen, Mark R. Davies, Andrew C. Steer, Steven Y. C. Tong, Antti Honkela, Julian Parkhill, Stephen D. Bentley and Jukka Corander ()
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John A. Lees: Pathogen Genomics, Wellcome Trust Sanger Institute
Minna Vehkala: University of Helsinki
Niko Välimäki: Genome-Scale Biology Research Program, University of Helsinki
Simon R. Harris: Pathogen Genomics, Wellcome Trust Sanger Institute
Claire Chewapreecha: University of Cambridge
Nicholas J. Croucher: Imperial College
Pekka Marttinen: Aalto University
Mark R. Davies: Peter Doherty Institute for Infection and Immunity, University of Melbourne
Andrew C. Steer: Centre for International Child Health, University of Melbourne
Steven Y. C. Tong: Menzies School of Health Research
Antti Honkela: Helsinki Institute for Information Technology HIIT, University of Helsinki
Julian Parkhill: Pathogen Genomics, Wellcome Trust Sanger Institute
Stephen D. Bentley: Pathogen Genomics, Wellcome Trust Sanger Institute
Jukka Corander: Pathogen Genomics, Wellcome Trust Sanger Institute

Nature Communications, 2016, vol. 7, issue 1, 1-8

Abstract: Abstract Bacterial genomes vary extensively in terms of both gene content and gene sequence. This plasticity hampers the use of traditional SNP-based methods for identifying all genetic associations with phenotypic variation. Here we introduce a computationally scalable and widely applicable statistical method (SEER) for the identification of sequence elements that are significantly enriched in a phenotype of interest. SEER is applicable to tens of thousands of genomes by counting variable-length k-mers using a distributed string-mining algorithm. Robust options are provided for association analysis that also correct for the clonal population structure of bacteria. Using large collections of genomes of the major human pathogens Streptococcus pneumoniae and Streptococcus pyogenes, SEER identifies relevant previously characterized resistance determinants for several antibiotics and discovers potential novel factors related to the invasiveness of S. pyogenes. We thus demonstrate that our method can answer important biologically and medically relevant questions.

Date: 2016
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DOI: 10.1038/ncomms12797

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