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. 2014 Jan;42(Database issue):D68-73.
doi: 10.1093/nar/gkt1181. Epub 2013 Nov 25.

miRBase: Annotating High Confidence microRNAs Using Deep Sequencing Data

Free PMC article

miRBase: Annotating High Confidence microRNAs Using Deep Sequencing Data

Ana Kozomara et al. Nucleic Acids Res. .
Free PMC article


We describe an update of the miRBase database (, the primary microRNA sequence repository. The latest miRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the miRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to miRBase entries. We now provide a high confidence subset of miRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at We also describe embedding microRNA-specific Wikipedia pages on the miRBase website to encourage the microRNA community to contribute and share textual and functional information.


Figure 1.
Figure 1.
The patterns of small RNA deep sequencing reads mapping to three mouse microRNAs. Hairpin microRNA sequences are shown at the bottom of each panel, with derived mature microRNA sequences shown in magenta, and predicted base-paired secondary structure in dot-bracket notation underneath. Read sequences are shown in blue, with the summed count across all data sets on the right. (A) The annotation of mmu-mir-3072 is supported by reads mapped to both mature sequences, pairing with a 2-nt 3′ overhang, and mmu-mir-3072 is therefore annotated as a high confidence microRNA. (B) Reads from the available deep sequencing data sets map to only one arm of the mmu-mir-184 hairpin, which cannot therefore be annotated with high confidence. (C) The pattern of reads mapping to the annotated mmu-mir-1940 locus refutes the microRNA annotation—reads mapping to the two arms of the predicted hairpin do not pair with the 2-nt 3′ overhang characteristic of microRNA processing.
Figure 2.
Figure 2.
Proportions of microRNAs in model species that are included in the high confidence microRNA set.
Figure 3.
Figure 3.
The miRBase entry page for dme-mir-10, showing the embedded Wikipedia page on the mir-10 microRNA precursor family.

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    1. Okamura K, Phillips MD, Tyler DM, Duan H, Chou Y, Lai EC. The regulatory activity of microRNA* species has substantial influence on microRNA and 3’ UTR evolution. Nat. Struct. Mol. Biol. 2008;15:354–363. - PMC - PubMed
    1. Yang J-S, Phillips MD, Betel D, Mu P, Ventura A, Siepel AC, Chen KC, Lai EC. Widespread regulatory activity of vertebrate microRNA* species. RNA. 2011;17:312–326. - PMC - PubMed
    1. Marco A, Hui JHL, Ronshaugen M, Griffiths-Jones S. Functional shifts in insect microRNA evolution. Genome Biol. Evol. 2010;2:686–696. - PMC - PubMed
    1. Griffiths-Jones S, Hui JHL, Marco A, Ronshaugen M. MicroRNA evolution by arm switching. EMBO Rep. 2011;12:172–177. - PMC - PubMed
    1. Kozomara A, Griffiths-Jones S. miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res. 2011;39:D152–D157. - PMC - PubMed

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