Seed Bioinformatics

Analysis of gene expression data sets is a potent tool for gene function prediction, cis -element discovery, and hypothesis generation for the model plant Arabidopsis thaliana , and more recently for other agriculturally relevant species. In the case of Arabidopsis thaliana , experiments conducted by individual researchers to document its transcriptome have led to large numbers of data sets being made publicly available for data mining by the so-called “electronic northerns,” co-expression analysis and other methods. Given that approximately 50% of the genes in Arabidopsis have no function ascribed to them by “conventional” homology searches, and that only around 10% of the genes have had their function experimentally determined in the laboratory, these analyses can accelerate the identification of potential gene function at the click of a mouse. This chapter covers the use of bioinformatic data mining tools available at the Bio-Array Resource (http://www.bar.utoronto.ca ) and elsewhere for hypothesis generation in the context of seed biology.