Database Commons

a catalog of worldwide biological databases

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. DATABASE URL: http://www.pathoplant.de/expression_analysis.php.

Plants react to pathogen attack by expressing specific proteins directed toward the infecting pathogens. This involves the transcriptional activation of specific gene sets. PathoPlant, a database on plant-pathogen interactions and signal transduction reactions, has now been complemented by microarray gene expression data from Arabidopsis thaliana subjected to pathogen infection and elicitor treatment. New web tools enable identification of plant genes regulated by specific stimuli. Sets of genes co-regulated by multiple stimuli can be displayed as well. A user-friendly web interface was created for the submission of gene sets to be analyzed. This results in a table, listing the stimuli that act either inducing or repressing on the respective genes. The search can be restricted to certain induction factors to identify, e.g. strongly up- or down-regulated genes. Up to three stimuli can be combined with the option of induction factor restriction to determine similarly regulated genes. To identify common cis-regulatory elements in co-regulated genes, a resulting gene list can directly be exported to the AthaMap database for analysis. PathoPlant is freely accessible at http://www.pathoplant.de.

Pathogen recognition and signal transduction during plant pathogenesis is essential for the activation of plant defense mechanisms. To facilitate easy access to published data and to permit comparative studies of different pathogen response pathways, a database is indispensable to give a broad overview of the components and reactions so far known. PathoPlant has been developed as a relational database to display relevant components and reactions involved in signal transduction related to plant-pathogen interactions. On the organism level, the tables 'plant', 'pathogen' and 'interaction' are used to describe incompatible interactions between plants and pathogens or diseases. On the molecular level, plant pathogenesis related information is organized in PathoPlant's main tables 'molecule', 'reaction' and 'location'. Signal transduction pathways are modeled as consecutive sequences of known molecules and corresponding reactions. PathoPlant entries are linked to associated internal records as well as to entries in external databases such as SWISS-PROT, GenBank, PubMed, and TRANSFAC. PathoPlant is available as a web-based service at http://www.pathoplant.de.