Motivation: MicroRNAs (miRNAs) are important regulators of biological processes in plants and animals. Recently, miRNA genes have been discovered, whose primary transcripts are spliced and which cannot be predicted directly from genomic sequence. Hence, more sophisticated programs for the detection of spliced miRNAs are required.
Results: Here, we present the first method for the prediction of spliced miRNAs in plants. For a given genomic sequence, SplamiR creates a database of complementary sequence pairs, which might encode for RNAs folding into stem-loop structures. Next, in silico splice variants of database sequences with complementarity to an mRNA of interest are classified as to whether they could represent miRNAs targeting this mRNA. Our method identifies all known cases of spliced miRNAs in rice, and a previously undiscovered miRNA in maize which is supported by an expressed sequence tag (EST). SplamiR permits identification of spliced miRNAs for a given target mRNA in many plant genomes.
Availability: The program is freely available at http://www.uni-jena.de/SplamiR.html.