Background: The translation start site plays an important role in the control of translation efficiency of eukaryotic mRNAs. The recognition of the start AUG codon by eukaryotic ribosomes is considered to depend on its nucleotide context. However, the fraction of eukaryotic mRNAs with the start codon in a suboptimal context is relatively large. It may be expected that mRNA should possess some features providing efficient translation, including the proper recognition of a translation start site. It has been experimentally shown that a downstream hairpin located in certain positions with respect to start codon can compensate in part for the suboptimal AUG context and also increases translation from non-AUG initiation codons. Prediction of such a compensatory hairpin may be useful in the evaluation of eukaryotic mRNA translation properties.
BackgroundMicroRNAs proceeds through the different canonical and non-canonical pathways; the most frequent of the non-canonical ones is the splicing-dependent biogenesis of mirtrons. We compare the mirtrons and non-mirtrons of human and mouse to explore how their maturation appears in the precursor structure around the miRNA.ResultsWe found the coherence of the overhang lengths what indicates the dependence between the cleavage sites. To explain this dependence we suggest the 2-lever model of the Dicer structure that couples the imprecisions in Drosha and Dicer. Considering the secondary structure of all animal pre-miRNAs we confirmed that single-stranded nucleotides tend to be located near the miRNA boundaries and in its center and are characterized by a higher mutation rate. The 5′ end of the canonical 5′ miRNA approaches the nearest single-stranded nucleotides what suggests the extension of the loop-counting rule from the Dicer to the Drosha cleavage site. A typical structure of the annotated mirtron pre-miRNAs differs from the canonical pre-miRNA structure and possesses the 1- and 2 nt hanging ends at the hairpin base. Together with the excessive variability of the mirtron Dicer cleavage site (that could be partially explained by guanine at its ends inherited from splicing) this is one more evidence for the 2-lever model. In contrast with the canonical miRNAs the mirtrons have higher snp densities and their pre-miRNAs are inversely associated with diseases. Therefore we supported the view that mirtrons are under positive selection while canonical miRNAs are under negative one and we suggested that mirtrons are an intrinsic source of silencing variability which produces the disease-promoting variants. Finally, we considered the interference of the pre-miRNA structure and the U2snRNA:pre-mRNA basepairing. We analyzed the location of the branchpoints and found that mirtron structure tends to expose the branchpoint site what suggests that the mirtrons can readily evolve from occasional hairpins in the immediate neighbourhood of the 3′ splice site.ConclusionThe miRNA biogenesis manifests itself in the footprints of the secondary structure. Close inspection of these structural properties can help to uncover new pathways of miRNA biogenesis and to refine the known miRNA data, in particular, new non-canonical miRNAs may be predicted or the known miRNAs can be re-classified.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4473-8) contains supplementary material, which is available to authorized users.
Siberian Division of Russian Academy Novosibirsk 630090, Russia of Sciences +Institute of Bioorganic Chemistry of Sciences I. Probing RNA Structure by Chemical and Enzymatic Approaches . . . . .
MicroRNAs (miRNAs) are small single-stranded noncoding RNAs that play an important role in post-transcriptional regulation of gene expression. In this paper, we present a web server for ab initio prediction of the human miRNAs and their precursors. The prediction methods are based on the hidden Markov Models and the context-structural characteristics. By taking into account the identified patterns of primary and secondary structures of the pre-miRNAs, a new HMM model is proposed and the existing context-structural Markov model is modified. The evaluation of the method performance has shown that it can accurately predict novel human miRNAs. Comparing with the existing methods we demonstrate that our method has a higher prediction quality both for human pre-miRNAs and miRNAs. The models have also showed good results in the prediction of the mouse miRNAs. The web server is available at http://wwwmgs.bionet.nsc.ru/mgs/programs/rnaanalys (mirror http://miRNA.at.nsu.ru ).
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