MicroRNAs are RNAs of about 22 nucleotides that guide Argonaute proteins to partially complementary sites in mRNAs, which represses their translation and speeds up their decay. They are cut from hairpins in longer primary transcripts: Drosha releases the precursor hairpin, Dicer removes its loop, and one strand of the remaining duplex is loaded into Argonaute as the mature miRNA.
This track shows the mouse microRNA precursors of miRBase release 22.1, the reference registry that assigns microRNA names. miRBase collects the microRNAs described in the literature and submitted by their authors. The track has 1,227 precursor loci of 1,226 miRBase precursors, with 2,110 mature miRNAs drawn on top of them, colored by the arm of the hairpin they come from. For a manually curated set of mouse microRNA genes, see the MirGeneDB track.
Clicking an item opens a page with the miRBase accessions, the mature miRNAs and their positions, and the secondary structure of the precursor predicted with RNAfold. The structure is drawn with forna and can be moved and zoomed; the nucleotides of the mature miRNAs are highlighted in the colors of the track.
Each item is a precursor hairpin labeled with its miRBase name, e.g. mmu-mir-206. The mature miRNAs are drawn as colored blocks over the item and labeled with their names:
| Mature miRNA from the 5' arm of the hairpin (5p) | |
| Mature miRNA from the 3' arm of the hairpin (3p) |
The colors only give the arm. Unlike the MirGeneDB track, they do not say which strand is the dominant one, as miRBase does not annotate this. The same colors mark the mature miRNAs in the structure on the details page. Items can be searched in the position box by precursor name, mature miRNA name, and precursor and mature accessions.
miRBase annotations come mainly from author submissions, most of them from small RNA sequencing studies. miRBase checks submissions only minimally and relies on the authors and on the review of their publications; it maps reads from public small RNA sequencing data sets to its sequences and labels entries as high or low confidence based on the read patterns, and removes entries whose reads are not consistent with microRNA processing. Release 22 has 38,589 precursors from 271 organisms; release 22.1 has 1,234 mouse precursors. See Kozomara et al., 2019, for details.
The mouse annotation is the miRBase file https://mirbase.org/download/mmu.gff3, on mm10 (GRCm38). The header of the file gives the version as miRBase v22; its precursor sequences agree with those of release 22.1. It has coordinates for 1,226 of the 1,234 mouse precursors; mmu-mir-590, -696, -712, -714, -1194, -2183, -7228 and -7238 have none and are not in the track. Each precursor (type miRNA_primary_transcript) became an item and each mature miRNA (type miRNA) a colored block. mmu-mir-12186 is at two loci, and the file links a mature miRNA only to the accession of its precursor, not to the locus, so each mature miRNA was assigned to the locus that contains it. The arm was taken from the -5p or -3p suffix of the mature miRNA name; for the 328 mature miRNAs without a suffix, it was taken from the half of the precursor they lie in. In total, 1,048 mature miRNAs are on the 5' arm and 1,062 on the 3' arm; mmu-mir-3102 has two on each arm. The sequence of every precursor was taken from the genome and folded with RNAfold (ViennaRNA 2.7.2, option -d2, default energy parameters) to predict the minimum free energy (MFE) structure. At 123 precursors, the MFE structure is not one hairpin or a mature miRNA reaches into the hairpin loop. For 117 of them, the lowest-energy structure that is one hairpin with the mature miRNAs in the stem, from RNAsubopt (ViennaRNA 2.7.2) within 8 kcal/mol of the MFE, is shown. At mmu-mir-451a, which is processed by Argonaute 2, mmu-mir-468, -7041 and -7215, no such structure exists and a mature miRNA stays in the loop; mmu-mir-669e and mmu-mir-1197 keep the MFE structure. For mmu-mir-669k, a single hairpin with only 1 nt bulges in the 5p mature was chosen by hand from the RNAsubopt output, instead of the lowest-energy one with a 6 nt bulge. The Structure row of the details page says which structure is shown.
For mm39, each precursor was converted from mm10 together with its mature miRNAs with liftOver, keeping a precursor only if all of them map to mm39 with unchanged lengths, which was the case for all 1,227 loci; the mm39 sequences, and so the structures, are identical to those on mm10. The steps are documented in the makeDoc files for mm10 and mm39, and the scripts are in the kent source tree.
The data can be explored interactively in table format with the Table Browser or the Data Integrator and exported from there to spreadsheet or tab-separated tables. From scripts, the data can be accessed through our API, track=mirBase.
For automated download and analysis, the annotation is stored in two bigBed files that can be downloaded from our download server, for mm39 and mm10: mirBase.bb has the precursors with all fields shown on the details page, including the sequence and dot-bracket structure, and mirBaseArms.bb has the mature miRNAs. Individual regions or the whole annotation can be obtained using our tool bigBedToBed, which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries are on our download page. The tool can also be used to obtain features within a given range, e.g. bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/mm39/mirBase/mirBase.bb -chrom=chr19 -start=0 -end=61420004 stdout
The original annotation can be downloaded from the miRBase download page.
This track was created by Andrea Tanzer, University of Vienna, from the miRBase 22.1 mouse annotation.
miRBase is developed and maintained by Sam Griffiths-Jones and his group at the University of Manchester.
Secondary structures were predicted with RNAfold from the ViennaRNA Package, developed by Ronny Lorenz, Ivo Hofacker and colleagues at the University of Vienna. The structure display on the details page uses fornac by Peter Kerpedjiev, Stefan Hammer and Ronny Lorenz.
Kerpedjiev P, Hammer S, Hofacker IL. Forna (force-directed RNA): Simple and effective online RNA secondary structure diagrams. Bioinformatics. 2015 Oct 15;31(20):3377-9. PMID: 26099263; PMC: PMC4595900
Kozomara A, Birgaoanu M, Griffiths-Jones S. miRBase: from microRNA sequences to function. Nucleic Acids Res. 2019 Jan 8;47(D1):D155-D162. PMID: 30423142; PMC: PMC6323917
Lorenz R, Bernhart SH, Höner Zu Siederdissen C, Tafer H, Flamm C, Stadler PF, Hofacker IL. ViennaRNA Package 2.0. Algorithms Mol Biol. 2011 Nov 24;6:26. PMID: 22115189; PMC: PMC3319429