HeliCis: a DNA motif discovery tool for colocalized motif pairs with periodic spacing.

Artikel i vetenskaplig tidskrift, 2007

ABSTRACT: BACKGROUND: Correct temporal and spatial gene expression during metazoan development relies on combinatorial interactions between different transcription factors. As a consequence, cis-regulatory elements often colocalize in clusters termed cis-regulatory modules. These may have requirements on organizational features such as spacing, order and helical phasing (periodic spacing) between binding sites. Due to the turning of the DNA helix, a small modification of the distance between a pair of sites may sometimes drastically disrupt function, while insertion of a full helical turn of DNA (10-11 bp) between cis elements may cause functionality to be restored. Recently, de novo motif discovery methods which incorporate organizational properties such as colocalization and order preferences have been developed, but there are no tools which incorporate periodic spacing into the model. RESULTS: We have developed a web based motif discovery tool, HeliCis, which features a flexible model that allows de novo detection of motifs with periodic spacing. Depending on the parameter settings it may also be used for discovering colocalized motifs without periodicity or motifs separated by a fixed gap of known or unknown length. We show on simulated data that it can efficiently capture the synergistic effects of colocalization and periodic spacing to improve detection of weak DNA motifs. It provides a simple to use web interface which interactively visualizes the current settings and thereby makes it easy to understand the parameters and the model structure. CONCLUSIONS: HeliCis provides simple and efficient de novo discovery of colocalized DNA motif pairs, with or without periodic spacing. Our evaluations show that it can detect weak periodic patterns which are not easily discovered using a sequential approach, i.e. first finding the binding sites and second analyzing the properties of their pairwise distances.