Identification of clustered microRNAs using an ab initio prediction method

Background: MicroRNAs (miRNAs) are endogenous 21 to 23-nucleotide RNA molecules that regulate protein-coding gene expression in plants and animals via the RNA interference pathway. Hundreds of them have been identified in the last five years and very recent works indicate that their total number is still larger. Therefore miRNAs gene discovery remains an important aspect of understanding this new and still widely unknown regulation mechanism. Bioinformatics approaches have proved to be very useful toward this goal by guiding the experimental investigations. Results: In this work we describe our computational method for miRNA prediction and the results of its application to the discovery of novel mammalian miRNAs. We focus on genomic regions around already known miRNAs, in order to exploit the property that miRNAs are occasionally found in clusters. Starting with the known human, mouse and rat miRNAs we analyze 20 kb of flanking genomic regions for the presence of putative precursor mi...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Alain Sewer, Nicodème Paul, Pablo Landgraf, Alexei Aravin, Sébastien Pfeffer, Michael J. Brownstein, Thomas Tuschl, Erik van Nimwegen, Mihaela Zavolan
• Keywords: 23-nucleotide Rna Molecules, BMCBI 2005, Genomic Regions, RNA Interference Pathway