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An alignment-free model for comparison of regulatory sequences

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Koohy, Hashem, Dyer, Nigel, Reid, John E., Koentges, Georgy and Ott, Sascha (2010) An alignment-free model for comparison of regulatory sequences. Bioinformatics, Vol.26 (No.19). pp. 2391-2397. doi:10.1093/bioinformatics/btq453 ISSN 1367-4803.

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Official URL: http://dx.doi.org/10.1093/bioinformatics/btq453

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Abstract

Motivation: Some recent comparative studies have revealed that regulatory regions can retain function over large evolutionary distances, even though the DNA sequences are divergent and difficult to align. It is also known that such enhancers can drive very similar expression patterns. This poses a challenge for the in silico detection of biologically related sequences, as they can only be discovered using alignment-free methods.

Results: Here, we present a new computational framework called Regulatory Region Scoring (RRS) model for the detection of functional conservation of regulatory sequences using predicted occupancy levels of transcription factors of interest. We demonstrate that our model can detect the functional and/or evolutionary links between some non-alignable enhancers with a strong statistical significance. We also identify groups of enhancers that are likely to be similarly regulated. Our model is motivated by previous work on prediction of expression patterns and it can capture similarity by strong binding sites, weak binding sites and even the statistically significant absence of sites. Our results support the hypothesis that weak binding sites contribute to the functional similarity of sequences.

Our model fills a gap between two families of models: detailed, data-intensive models for the prediction of precise spatio-temporal expression patterns on the one side, and crude, generally applicable models on the other side. Our model borrows some of the strengths of each group and addresses their drawbacks.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Q Science > QD Chemistry
T Technology > TP Chemical technology
Q Science > QH Natural history > QH301 Biology
Q Science > QA Mathematics
Divisions: Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) > Biological Sciences ( -2010)
Faculty of Science, Engineering and Medicine > Research Centres > Molecular Organisation and Assembly in Cells (MOAC)
Faculty of Science, Engineering and Medicine > Research Centres > Warwick Systems Biology Centre
Journal or Publication Title: Bioinformatics
Publisher: Oxford University Press
ISSN: 1367-4803
Official Date: October 2010
Dates:
DateEvent
October 2010Published
Volume: Vol.26
Number: No.19
Number of Pages: 7
Page Range: pp. 2391-2397
DOI: 10.1093/bioinformatics/btq453
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: Human Frontier Science Program Organization (HFSPO), Engineering and Physical Sciences Research Council (EPSRC), Research Councils UK (RCUK), Science Research Investment Fund
Grant number: RGP0029/2007-C

Data sourced from Thomson Reuters' Web of Knowledge

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