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Bioinformatics Advance Access published online on July 12, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl369
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© 2006 The Author(s)
Received May 3, 2006
Revised June 22, 2006
Accepted July 3, 2006

Article

Interpolated variable order motifs for identification of horizontally acquired DNA: revisiting the Salmonella pathogenicity islands

Georgios S. Vernikos 1 * and Julian Parkhill 1

1 The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK

* To whom correspondence should be addressed.
Georgios S. Vernikos, E-mail: gsv{at}sanger.ac.uk


  Abstract

Motivation: There is a growing literature on the detection of Horizontal Gene Transfer (HGT) events by means of parametric, non-comparative methods. Such approaches rely only on sequence information and utilize different low and high order indices to capture compositional deviation from the genome backbone; the superiority of the latter over the former has been shown elsewhere. However even high order k-mers may be poor estimators of HGT, when insufficient information is available, e.g. in short sliding windows. Most of the current HGT prediction methods require pre-existing annotation, which may restrict their application on newly sequenced genomes.

Results: We introduce a novel computational method, Interpolated Variable Order Motifs (IVOMs), that exploits compositional biases using variable order motif distributions and captures more reliably the local composition of a sequence compared to fixed-order methods. For optimal localization of the boundaries of each predicted region, a 2nd order, 2-state Hidden Markov Model (HMM) is implemented in a change-point detection framework. We applied the IVOM approach to the genome of Salmonella enterica serovar Typhi CT18, a well-studied prokaryote in terms of HGT events, and we show that the IVOMs outperform state-of-the-art low and high order motif methods predicting not only the already characterized Salmonella Pathogenicity Islands (SPI-1 to SPI-10) but also three novel SPIs (SPI-15, SPI-16, SPI-17) and other HGT events.

Availability: The software is available under a GPL license as a standalone application at http://www.sanger.ac.uk/Software/analysis/alien_hunter.

Supplementary Information: Supplementary data are available at Bioinformatics online.

Associate Editor: John Quackenbush
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