miRNAminer: A tool for homologous microRNA gene search
© Artzi et al; licensee BioMed Central Ltd. 2008
Received: 28 September 2007
Accepted: 23 January 2008
Published: 23 January 2008
MicroRNAs (miRNAs), present in most metazoans, are small non-coding RNAs that control gene expression by negatively regulating translation through binding to the 3'UTR of mRNA transcripts. Previously, experimental and computational methods were used to construct miRNA gene repositories agreeing with careful submission guidelines.
An algorithm we developed – miRNAminer – is used for homologous conserved miRNA gene search in several animal species. Given a search query, candidate homologs from different species are tested for their known miRNA properties, such as secondary structure, energy and alignment and conservation, in order to asses their fidelity. When applying miRNAminer on seven mammalian species we identified several hundreds of high-confidence homologous miRNAs increasing the total collection of (miRbase) miRNAs, in these species, by more than 50%. miRNAminer uses stringent criteria and exhibits high sensitivity and specificity.
We present – miRNAminer – the first web-server for homologous miRNA gene search in animals. miRNAminer can be used to identify conserved homolog miRNA genes and can also be used prior to depositing miRNAs in public databases. miRNAminer is available at http://pag.csail.mit.edu/mirnaminer.
MicroRNAs (miRNAs) are short, ~22 nt non-coding RNAs that control gene expression. miRNAs bind to the 3'UTRs of their regulated mRNA transcripts to facilitate mRNA degradation or translation inhibition [1, 2]. miRNAs are present in most metazoans and are thought to regulate a diverse range of biological processes [3, 4]. miRNA genes' evolution is unique since they mostly emerge through duplication events ; exhibit most often unidirectional evolution ; are generally gained and not lost ; show several cases of rapid evolution in primates [8, 9]; are rarely changed due to functional constraints ; and, show relatively rare evolutionary acquisition events (accounted by their relatively small numbers).
miRNA predictions based on computational methods, which followed initial extensive cloning efforts, are based on the secondary structure of the miRNA, its phylogenetic conservation and thermodynamic stability [11, 12]. miRNA gene repositories are constantly expanding giving rise to more than 3500 reported miRNAs in more than 30 animal species (Sanger miRbase database, Version 10.0 [13, 14]). However, it is apparent that even this comprehensive repository is far from completion, accounted by the very few miRNAs listed for dog (6) and chimpanzee (83), compared to human (533), to name two examples. Since these differences cannot be accounted merely by species-specific miRNAs, we saw the need for a computational tool for miRNA homologous searches.
We present miRNAminer, a tool for automatic identification of homolog miRNAs based on a given user defined query miRNA. The tool exploits numerous characteristics of miRNAs: high conservation of precursor sequences, very high conservation of mature sequences (particularly in the seed region, nt 2–8 ), and hairpin secondary structure with high folding energy and base pairing. miRNAminer first uses BLAST  to select candidate matches and ranks them according to their e-values. Then it employs a series of rigorous filters to improve specificity.
An input query consists of a precursor miRNA, mature miRNA, a set of filter threshold values and the number of best-fitted results requested in the output. We designed miRNAminer's algorithm to maximize specificity of matches. This is because the designed application of miRNAminer is to identify homolog matches after a miRNA has been experimentally confirmed. We estimated the default values presented below so that each filter by itself selects 95% of known miRNAs in training genomes (criteria was also based on ).
Known registered miRbase miRNAs and new candidates identified by miRNAminer.
Candidate non-registered miRNAs identified by miRNAminer in human.
Results in H. sapiens
Identity with original
base pair %
For searches with relaxed parameters (reduced stringency) we suggest initially performing the following modifications: (i) do not 'Require seed conservation in mature miRNA (nt 2–8)' (uncheck box); (ii) increase 'maximal number of gaps in miRNA precursor alignment' from 10 (default) to 15; (iii) decrease 'minimal mature miRNA identity' from 0.8 (default) to 0.7; (iv) decrease 'minimal base pairing percentage in miRNA precursor' from 55 (default) to 40; and (v) change 'minimal/maximal length of precursor sequence (nt)' from 70/180 (default) to 50/250. In order to view miRNAs which are other than the top candidate we suggest increasing the 'number of results to report' from 1 (default) to 5. The parameters (i–v) above are listed in the order that would output an increasing total number of identified miRNAs. For example, reducing mature miRNA identity from 0.8 (default) to 0.7 increases miRNAs from 22 to 24 (9%) and 31 to 36 (16%) in human and mouse, respectively. On the other hand, we found that changing the length of the miRNA precursor from 70–180 nt (default) to 50–250 nt, added only 1 additional miRNA in human and none in mouse. This, however, might change when run in combination with other modified parameters. Altogether each of the modified parameters listed above will result, independently, in an average miRNA increase of 11% when tested on seven mammalian species.
Sensitivity of miRNAminer.
Several approaches to identify miRNA homologs have been previously described, both in plants , and in animals [5, 41, 42]. However, the only tool that is available as a web service, microHARVESTER , is targeted for plants. miRNAminer is the first available miRNA gene homolog search tool for animal genomes.
Availability and requirements
Project name: miRNAminer; Project home page: http://pag.csail.mit.edu/mirnaminer; Operating system: Platform independent; Programming language: Java; License: Open source, see http://opensource.org/licenses/mit-licence.php; Code is available upon request. miRNAs identified using miRNAminer will be incorporated in next miRbase versions, see http://microrna.sanger.ac.uk.
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