Hairpins in a Haystack: Recognizing microRNA precursors in comparative genomics data

Abstract

Summary: Recently, genome-wide surveys for non-coding RNAs have provided evidence for tens of thousands of previously undescribed evolutionary conserved RNAs with distinctive secondary structures. The annotation of these putative ncRNAs, however, remains a difficult problem. Here we describe an SVM-based approach that, in conjunction with a non-stringent filter for consensus secondary structures, is capable of efficiently recognizing microRNA precursors in multiple sequence alignments. The software was applied to recent genome-wide RNAz surveys of mammals, urochordates, and nematodes. © 2006 Oxford University Press.