A guide to the integrated application of on-line data mining tools for the inference of gene functions at the systems level.

Genes function in networks to achieve a common biological response. Thus, inferences into the biological role of individual genes can be gained by analyzing their association with other genes with more precisely defined functions. Here, we present a guide, using the well-characterized Arabidopsis thaliana pathogenesis-related protein 2 gene (PR-2) as an example, to document how the sequential use of web-based tools can be applied to integrate information from different databases and associate the function of an individual gene with a network of genes and additionally identify specific biological processes in which they collectively function. The analysis begins by performing a global expression correlation analysis to build a functionally associated gene network. The network is subsequently analyzed for Gene Ontology enrichment, stimuli and mutant-specific transcriptional responses and enriched putative promoter regulatory elements that may be responsible for their correlated relationships. The results for the PR-2 gene are entirely consistent with the published literature documenting the accuracy of this type of analysis. Furthermore, this type of analysis can also be performed on other organisms with the appropriate data available and will greatly assist in understanding individual gene functions in a systems context.