‘In silico expression analysis’, a novel PathoPlant web tool to identify abiotic and biotic stress conditions associated with specific cis-regulatory sequences

Using bioinformatics, putative cis-regulatory sequences can be easily identified using pattern recognition programs on promoters of specific gene sets. The abundance of predicted cis-sequences is a major challenge to associate these sequences with a possible function in gene expression regulation. To identify a possible function of the predicted cis-sequences, a novel web tool designated ‘in silico expression analysis’ was developed that correlates submitted cis-sequences with gene expression data from Arabidopsis thaliana. The web tool identifies the A. thaliana genes harbouring the sequence in a defined promoter region and compares the expression of these genes with microarray data. The result is a hierarchy of abiotic and biotic stress conditions to which these genes are most likely responsive. When testing the performance of the web tool, known cis-regulatory sequences were submitted to the ‘in silico expression analysis’ resulting in the correct identification of the associated stress conditions. When using a recently identified novel elicitor-responsive sequence, a WT-box (CGACTTTT), the ‘in silico expression analysis’ predicts that genes harbouring this sequence in their promoter are most likely Botrytis cinerea induced. Consistent with this prediction, the strongest induction of a reporter gene harbouring this sequence in the promoter is observed with B. cinerea in transgenic A. thaliana.