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

Bioinformatics. 2006 Sep 15;22(18):2196-203. doi: 10.1093/bioinformatics/btl369. Epub 2006 Jul 12.


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), which exploits compositional biases using variable order motif distributions and captures more reliably the local composition of a sequence compared with fixed-order methods. For optimal localization of the boundaries of each predicted region, a second order, two-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


Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Biological Evolution
  • DNA, Bacterial / genetics*
  • Gene Transfer, Horizontal / genetics*
  • Genome, Bacterial / genetics
  • Genomic Islands / genetics*
  • Salmonella / genetics*
  • Salmonella / pathogenicity*
  • Virulence / genetics*
  • Virulence Factors / genetics


  • DNA, Bacterial
  • Virulence Factors