Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine

Background  

MicroRNAs (miRNAs) are a group of short (~22 nt) non-coding RNAs that play important regulatory roles. MiRNA precursors (pre-miRNAs) are characterized by their hairpin structures. However, a large amount of similar hairpins can be folded in many genomes. Almost all current methods for computational prediction of miRNAs use comparative genomic approaches to identify putative pre-miRNAs from candidate hairpins. Ab initio method for distinguishing pre-miRNAs from sequence segments with pre-miRNA-like hairpin structures is lacking. Being able to classify real vs. pseudo pre-miRNAs is important both for understanding of the nature of miRNAs and for developing ab initio prediction methods that can discovery new miRNAs without known homology.     

MicroRNA targets in Drosophila

Background  

The recent discoveries of microRNA (miRNA) genes and characterization of the first few target genes regulated by miRNAs in Caenorhabditis elegans and Drosophila melanogaster have set the stage for elucidation of a novel network of regulatory control. We present a computational method for whole-genome prediction of miRNA target genes. The method is validated using known examples. For each miRNA, target genes are selected on the basis of three properties: sequence complementarity using a position-weighted local alignment algorithm, free energies of RNA-RNA duplexes, and conservation of target sites in related genomes. Application to the D. melanogaster, Drosophila pseudoobscura and Anopheles gambiae genomes identifies several hundred target genes potentially regulated by one or more known miRNAs.     

Cloning and characterization of microRNAs from wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Background  

MicroRNAs (miRNAs) are a class of small, non-coding regulatory RNAs that regulate gene expression by guiding target mRNA cleavage or translational inhibition. So far, identification of miRNAs has been limited to a few model plant species, such as Arabidopsis, rice and Populus, whose genomes have been sequenced. Wheat is one of the most important cereal crops worldwide. To date, only a few conserved miRNAs have been predicted in wheat and the computational identification of wheat miRNAs requires the genome sequence, which is unknown.     

MapMi: automated mapping of microRNA loci

Background  

A large effort to discover microRNAs (miRNAs) has been under way. Currently miRBase is their primary repository, providing annotations of primary sequences, precursors and probable genomic loci. In many cases miRNAs are identical or very similar between related (or in some cases more distant) species. However, miRBase focuses on those species for which miRNAs have been directly confirmed. Secondly, specific miRNAs or their loci are sometimes not annotated even in well-covered species. We sought to address this problem by developing a computational system for automated mapping of miRNAs within and across species. Given the sequence of a known miRNA in one species it is relatively straightforward to determine likely loci of that miRNA in other species. Our primary goal is not the discovery of novel miRNAs but the mapping of validated miRNAs in one species to their most likely orthologues in other species.     

Dynamic expression of small non-coding RNAs, including novel microRNAs and piRNAs/21U-RNAs, during Caenorhabditis elegans development

Background  

Small non-coding RNAs, including microRNAs (miRNAs), serve an important role in controlling gene expression during development and disease. However, little detailed information exists concerning the relative expression patterns of small RNAs during development of animals such as Caenorhabditis elegans.     

Plasma and synovial fluid microRNAs as potential biomarkers of rheumatoid arthritis and osteoarthritis

Introduction  

MicroRNAs (miRNAs), endogenous small noncoding RNAs regulating the activities of target mRNAs and cellular processes, are present in human plasma in a stable form. In this study, we investigated whether miRNAs are also stably present in synovial fluids and whether plasma and synovial fluid miRNAs could be biomarkers of rheumatoid arthritis (RA) and osteoarthritis (OA).     

Identification of baboon microRNAs expressed in liver and lymphocytes

Background  

MicroRNAs (miRNAs) are small noncoding RNAs (~22 nucleotides) that regulate gene expression by cleaving mRNAs or inhibiting translation. The baboon is a well-characterized cardiovascular disease model; however, no baboon miRNAs have been identified. Evidence indicates that the baboon and human genomes are highly conserved; based on this conservation, we hypothesized that comparative genomic methods could be used to identify baboon miRNAs.     

TAM: A method for enrichment and depletion analysis of a microRNA category in a list of microRNAs

Background  

MicroRNAs (miRNAs) are a class of important gene regulators. The number of identified miRNAs has been increasing dramatically in recent years. An emerging major challenge is the interpretation of the genome-scale miRNA datasets, including those derived from microarray and deep-sequencing. It is interesting and important to know the common rules or patterns behind a list of miRNAs, (i.e. the deregulated miRNAs resulted from an experiment of miRNA microarray or deep-sequencing).     

Diversity,expression and mRNA targeting abilities of Argonaute-targeting miRNAs among selected vascular plants

Background

Micro (mi)RNAs are important regulators of plant development. Across plant lineages, Dicer-like 1 (DCL1) proteins process long ds-like structures to produce micro (mi) RNA duplexes in a stepwise manner. These miRNAs are incorporated into Argonaute (AGO) proteins and influence expression of RNAs that have sequence complementarity with miRNAs. Expression levels of AGOs are greatly regulated by plants in order to minimize unwarranted perturbations using miRNAs to target mRNAs coding for AGOs. AGOs may also have high promoter specificity-sometimes expression of AGO can be limited to just a few cells in a plant. Viral pathogens utilize various means to counter antiviral roles of AGOs including hijacking the host encoded miRNAs to target AGOs. Two host encoded miRNAs namely miR168 and miR403 that target AGOs have been described in the model plant Arabidopsis and such a mechanism is thought to be well conserved across plants because AGO sequences are well conserved.

Results

We show that the interaction between AGO mRNAs and miRNAs is species-specific due to the diversity in sequences of two miRNAs that target AGOs, sequence diversity among corresponding target regions in AGO mRNAs and variable expression levels of these miRNAs among vascular plants. We used miRNA sequences from 68 plant species representing 31 plant families for this analysis. Sequences of miR168 and miR403 are not conserved among plant lineages, but surprisingly they differ drastically in their sequence diversity and expression levels even among closely related plants. Variation in miR168 expression among plants correlates well with secondary structures/length of loop sequences of their precursors.

Conclusions

Our data indicates a complex AGO targeting interaction among plant lineages due to miRNA sequence diversity and sequences of miRNA targeting regions among AGO mRNAs, thus leading to the assumption that the perturbations by viruses that use host miRNAs to target antiviral AGOs can only be species-specific. We also show that rapid evolution and likely loss of expression of miR168 isoforms in tobacco is related to the insertion of MITE-like transposons between miRNA and miRNA* sequences, a possible mechanism showing how miRNAs are lost in few plant lineages even though other close relatives have abundantly expressing miRNAs.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1049) contains supplementary material, which is available to authorized users.