TitleA DNA shape-based regulatory score improves position-weight matrix-based recognition of transcription factor binding sites.
Publication TypeJournal Article
Year of Publication2015
AuthorsYang, J, Ramsey, SA
JournalBioinformatics
Volume31
Issue21
Pagination3445-50
Date Published2015 Nov 01
ISSN1367-4811
KeywordsBinding Sites, Computational Biology, DNA, Gene Expression Regulation, Humans, Models, Theoretical, Position-Specific Scoring Matrices, Protein Binding, Software, Transcription Factors
Abstract

MOTIVATION: The position-weight matrix (PWM) is a useful representation of a transcription factor binding site (TFBS) sequence pattern because the PWM can be estimated from a small number of representative TFBS sequences. However, because the PWM probability model assumes independence between individual nucleotide positions, the PWMs for some TFs poorly discriminate binding sites from non-binding-sites that have similar sequence content. Since the local three-dimensional DNA structure ('shape') is a determinant of TF binding specificity and since DNA shape has a significant sequence-dependence, we combined DNA shape-derived features into a TF-generalized regulatory score and tested whether the score could improve PWM-based discrimination of TFBS from non-binding-sites.

RESULTS: We compared a traditional PWM model to a model that combines the PWM with a DNA shape feature-based regulatory potential score, for accuracy in detecting binding sites for 75 vertebrate transcription factors. The PWM+shape model was more accurate than the PWM-only model, for 45% of TFs tested, with no significant loss of accuracy for the remaining TFs.

AVAILABILITY AND IMPLEMENTATION: The shape-based model is available as an open-source R package at that is archived on the GitHub software repository at https://github.com/ramseylab/regshape/.

CONTACT: stephen.ramsey@oregonstate.edu

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DOI10.1093/bioinformatics/btv391
Alternate JournalBioinformatics
PubMed ID26130577
PubMed Central IDPMC4838056
Grant ListHL098807 / HL / NHLBI NIH HHS / United States