De novo computational identification of stress-related sequence motifs and microRNA target sites in untranslated regions of a plant translatome.

Gene regulation at the transcriptional and translational level leads to diversity in phenotypes and function in organisms. Regulatory DNA or RNA sequence motifs adjacent to the gene coding sequence act as binding sites for proteins that in turn enable or disable expression of the gene. Whereas the known DNA and RNA binding proteins range in the thousands, only a few motifs have been examined. In this study, we have predicted putative regulatory motifs in groups of untranslated regions from genes regulated at the translational level in Arabidopsis thaliana under normal and stressed conditions. The test group of sequences was divided into random subgroups and subjected to three de novo motif finding algorithms (Seeder, Weeder and MEME). In addition to identifying sequence motifs, using an in silico tool we have predicted microRNA target sites in the 3' UTRs of the translationally regulated genes, as well as identified upstream open reading frames located in the 5' UTRs. Our bioinformatics strategy and the knowledge generated contribute to understanding gene regulation during stress, and can be applied to disease and stress resistant plant development.