MOTIVATION: MicroRNAs (miRNAs) are major regulators of gene expression in plants and animals. They recognize their target messenger RNAs (mRNAs) by sequence complementarity and guide them to cleavage or translational arrest. So far, the prediction of plant miRNA-target pairs generally relies on the use of empirical parameters deduced from known miRNA-target interactions. RESULTS: We developed comTAR, a web tool for the prediction of miRNA targets that is mainly based on the conservation of the potential regulation in different species. We used data generated from a pipeline applied to transcript datasets of 33 angiosperms that was used to build a database of potential miRNA targets of different plant species. The database contains information describing each miRNA-target pair, their function and evolutionary conservation, while the results are displayed in a user-friendly interface. The tool also allows the search using new miRNAs. AVAILABILITY AND IMPLEMENTATION: The Web site is free to all users, with no login requirements, at http://rnabiology.ibr-conicet.gov.ar/comtar.

Abstract Summary: MicroRNAs (miRNAs) are a recently discovered class of non-coding RNAs that regulate gene and protein expression in plants and animals. MiRNAs have so far been identified mostly by specific cloning of small RNA molecules, complemented by computational methods. We present a computational identification approach that is able to identify candidate miRNA homologs in any set of sequences, given a query miRNA. The approach is based on a sequence similarity search step followed by a set of structural filters. Availability: microHARVESTER is offered as a web-service and additionally as source code upon request at Contact: [email protected]