Bioinformatics Advance Access originally published online on November 14, 2006
Bioinformatics 2007 23(2):142-149; doi:10.1093/bioinformatics/btl570
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Reliable prediction of Drosha processing sites improves microRNA gene prediction
1 Department of Computer and Information Science, Norwegian University of Science and Technology NO-7052 Trondheim, Norway
2 Interagon AS, Laboratoriesenteret NO-7006 Trondheim, Norway
3 Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology N0-7489 Trondheim, Norway
*To whom correspondence should be addressed.
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Abstract |
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Motivation: Mature microRNAs (miRNAs) are processed from long hairpin transcripts. Even though it is only the first of several steps, the initial Drosha processing defines the mature product and is characteristic for all miRNA genes. Methods that can separate between true and false processing sites are therefore essential to miRNA gene discovery.
Results: We present a classifier that predicts 5' Drosha processing sites in hairpins that are candidate miRNAs. The classifier, called Microprocessor SVM, correctly predicts the processing site for 50% of known human 5' miRNAs, and 90% of its predictions are within two nucleotides of the true site. Another classifier that is trained on the output from the Microprocessor SVM outperforms existing methods for prediction of unconserved miRNAs. Reanalysis of characteristics and supporting evidence for a set of newly annotated miRNAs shows that some miRNAs may be misannotated. This suggests that expressed hairpins should not be annotated as miRNAs until they are verified to be Drosha and Dicer substrates.
Availability: The classifiers are publicly available at https://demo1.interagon.com/miRNA/
Contact: paal.saetrom{at}interagon.com
Supplementary information: Supplementary data is available at Bioinformatics online.
Associate Editor: Chris Stoeckert
Received on August 13, 2006; revised on November 8, 2006; accepted on November 8, 2006
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