MiRdentify: high stringency miRNA predictor identifies several novel animal miRNAs. Issue 16 (22nd July 2014)

• Record Type: Journal Article
• Authors: Hansen, Thomas B.; Venø, Morten T.; Kjems, Jørgen; Damgaard, Christian K.
• Is Part Of: Nucleic acids research. Volume 42:Issue 16(2014)
• Page Start: e124
• Page End: e124
• Publication Date: 2014-07-22
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gku598
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: During recent years, miRNAs have been shown to play important roles in the regulation of gene expression. Accordingly, much effort has been put into the discovery of novel uncharacterized miRNAs in various organisms. miRNAs are structurally defined by a hairpin-loop structure recognized by the two-step processing apparatus, Drosha and Dicer, necessary for the production of mature ∼22-nucleotide miRNA guide strands. With the emergence of high-throughput sequencing applications, tools have been developed to identify miRNAs and profile their expression based on sequencing reads. However, as the read depth increases, false-positive predictions increase using established algorithms, underscoring the need for more stringent approaches. Here we describe a transparent pipeline for confident miRNA identification in animals, termed miRdentify. We show that miRdentify confidently discloses more than 400 novel miRNAs in humans, including the first male-specific miRNA, which we successfully validate. Moreover, novel miRNAs are predicted in the mouse, the fruit fly and nematodes, suggesting that the pipeline applies to all animals. The entire software package is available at www.ncrnalab.dk/mirdentify .