A Gibbs sampling method to detect over-represented motifs in the upstream regions of co-expressed genes

Authors:
Gert Thijs;Kathleen Marchal;Magali Lescot;Stephane Rombauts;Bart De Moor;Pierre Rouzé;Yves Moreau
Affiliations:
ESAT-SISTA/COSIC, KU Leuven, Kardinaal Mercierlaan 94, 3001 Leuven, Belgium;ESAT-SISTA/COSIC, KU Leuven, Kardinaal Mercierlaan 94, 3001 Leuven, Belgium;ESAT-SISTA/COSIC, KU Leuven;Plant Genetics, VIB, University Gent;ESAT-SISTA/COSIC, KU Leuven;INRA associated labo, VIB, University Gent;ESAT-SISTA/COSIC, KU Leuven, Kardinaal Mercierlaan 94, 3001 Leuven, Belgium
Venue:
RECOMB '01 Proceedings of the fifth annual international conference on Computational biology
Year:
2001

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Abstract

Microarray experiments can reveal useful information on the transcriptional regulation. We try to find regulatory elements in the region upstream of translation start of coexpressed genes. Here we present a modification to the original Gibbs Sampling algorithm [12]. We introduce a probability distribution to estimate the number of copies of the motif in a sequence. The second modification is the incorporation of a higher-order background model. We have successfully tested our algorithm on several data sets. First we show results on two selected data set: sequences from plants containing the G-box motif and the upstream sequences from bacterial genes regulated by O2-responsive protein FNR. In both cases the motif sampler is able to find the expected motifs. Finally, the sampler is tested on 4 clusters of coexpressed genes from a wounding experiment in Arabidopsis thaliana. We find several putative motifs that are related to the pathways involved in the plant defense mechanism.