Mini Review
miRNomics—The bioinformatics of microRNA genes

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Abstract

MicroRNAs (miRNAs) are tiny genetic rheostats in plants, animals, and viruses, regulating the expression of messenger RNAs by targeting transcripts for cleavage or translational repression. Their regulatory impact is even more pervasive as a potential therapeutic tool. Since inception, computational methods have been an invaluable tool complementing experimental approaches. Here, we outline miRNA-bioinformatics highlighting the biological and therapeutic repertoire of miRNAs, in silico prediction of miRNA genes and their targets, along with a glimpse of the bioinformatic challenges that lie ahead.

Section snippets

miRNA biogenesis and function

miRNA genes are first transcribed from different genomic locations (within introns of genes or outside genes or in polycistronic clusters or exist individually) [17] as primary transcripts (pri-miRNAs) (refer to Fig. 1) by RNA polymerase II. miRNAs residing in the intron of a host gene are processed by sharing the same promoter and other regulatory elements of the host gene. Further, clustered miRNA genes in polycistronic transcripts are likely to be coordinately regulated [14]. The pri-miRNAs

Sources of miRNA data

The miRBase::Sequence database [34] (http://microrna.sanger.ac.uk/sequences) is the most popular miRNA database maintained by the Sanger Institute. This database contains all published mature miRNA sequences, together with their predicted hairpin precursors and annotation related to their discovery, structure, and function. The total miRNA entries in this database are 5071 as of August, 2007 (Release 10.0). It has three sections based on their function. (a) miRBase Sequence Database is a

Structural features of miRNA genes—basis of computational prediction

The precursor miRNAs have a well-predicted stable extended stem-loop hairpin structure with continuous helical pairing and a few internal bulges. The length of hairpin stem-loops of pre-miRNAs is generally longer in plants than that of animals. In animals these precursors are 60–80 nucleotides in length [7] whereas in plants their length ranges from 60 to more than 400 nucleotides [32]. The lengths of viral pre-miRNAs vary from 60 to 119 with an average of 79 nucleotides [35]. The molecular

Computational prediction of miRNA targets

The identification of miRNA targets is an essential step towards understanding their regulatory function. Biological functions have only been assigned to few miRNAs, mostly due to the difficulty of miRNA target identification. Computational target prediction in plants is comparatively straightforward and powerful because miRNA and target mRNA are nearly perfectly complementary [14], [36]. On the contrary, bioinformatic prediction of miRNA targets in animals is a difficult task as functional

Conclusion

With the discovery of the regulatory role of miRNA in cancers, lots of fervor have been created among the scientists. It is probably tip of the iceberg. Its immense therapeutic potential needs to be harnessed further. The convergence of genomic technologies and the development of miRNA drugs designed against specific molecular targets will provide many opportunities for using bioinformatics to bridge the gap between biological knowledge and clinical therapy. It has marked the beginning of

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