Discovering MicroRNAs from deep sequencing data using MiRDeep

Max Delbrück Centrum für Molekulare Medizin, Robert-Rössle-Strasse 10, D-13125 Berlin-Buch, Germany.
Nature Biotechnology (Impact Factor: 41.51). 05/2008; 26(4):407-15. DOI: 10.1038/nbt1394
Source: PubMed

ABSTRACT The capacity of highly parallel sequencing technologies to detect small RNAs at unprecedented depth suggests their value in systematically identifying microRNAs (miRNAs). However, the identification of miRNAs from the large pool of sequenced transcripts from a single deep sequencing run remains a major challenge. Here, we present an algorithm, miRDeep, which uses a probabilistic model of miRNA biogenesis to score compatibility of the position and frequency of sequenced RNA with the secondary structure of the miRNA precursor. We demonstrate its accuracy and robustness using published Caenorhabditis elegans data and data we generated by deep sequencing human and dog RNAs. miRDeep reports altogether approximately 230 previously unannotated miRNAs, of which four novel C. elegans miRNAs are validated by northern blot analysis.

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Available from: Catherine Adamidi, Sep 27, 2015
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    • "Primary data analysis was done using the Illumina CASAVA Pipeline software v.1.8.2, and the sequence reads were further processed by trimming for adapters and filtering for low quality using Trimmomatic (Lohse et al., 2012). Identification of conserved and novel candidate microRNA genes in the bowhead genome was accomplished by applying the miRDeep2 algorithm (Friedlä nder et al., 2008, 2012). "
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    • "and miRNA counts generated for each sample [1]. Both miRDeep [5] and miRExpress 2.0 [6] were used to generate counts, and each provided comparable results, with over 50% of the reads mapping to miRNAs in either the human or EBV genomes (Table 3). Identification of known miRNAs was based on miRBase Release 19 [7], with an alignment identity of 1%, a tolerance range of 4, and a similarity threshold of 0.8 [1]. "
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    • "For a summary of the number of reads at each step, see Supplementary Table 1. Potentially novel miRNAs were identified using miRDeep2 (v2.0.0.5) [17]. The predicted novel miRNAs that were independently predicted in at least three samples and fulfilled all of the following criteria were submitted to miRBase: the mature sequence was expressed in at least ten samples and was expressed at a minimum of 100 reads per million (RPM); the predicted miRNA had a high (>90%) probability of being a true miRNA according to miRDeep2; and the hairpin structure had a RandFold P value <0.05. "
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