RT Journal Article
SR Electronic
T1 Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 038463
DO 10.1101/038463
A1 Lees, John A.
A1 Vehkala, Minna
A1 Välimäki, Niko
A1 Harris, Simon R.
A1 Chewapreecha, Claire
A1 Croucher, Nicholas J.
A1 Marttinen, Pekka
A1 Honkela, Antti
A1 Parkhill, Julian
A1 Bentley, Stephen D.
A1 Corander, Jukka
YR 2016
UL http://biorxiv.org/content/early/2016/02/01/038463.abstract
AB 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 even 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 characterised 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.