Prediction of auxin response elements based on data fusion in Arabidopsis thaliana

The plant hormone “auxin” is a key regulator of plant development and environmental responses. Many genes in Arabidopsis thaliana are known to be up-regulated in response to auxin. Auxin response factors activate or repress the expression of genes by binding at their promoter regions within auxin response elements (AuxRE) that are key regulatory cis-acting motives. Therefore, the identification of auxin-response elements is among the most important issues to understand the auxin regulation mechanisms. Thus, searching the TGTCTC motif is an unreliable method to identify AuxRE because many AuxRE variants may also be functional. In the present study, we perform an In-silico prediction of AuxREs in promoters of primary auxin responsive genes. We exploit microarray data of auxin response in Arabidopsis thaliana seedlings, in order to provide biological annotation to AuxRE. We apply a data fusion method based on the combined use of evidence theory and fuzzy sets to scan upstream sequences of response genes.