miRNA Annotation Research Articles

Role of miRNA in carcinogenesis and biomarker selection: a methodological view

miRNAs, their involvement in cancer development and their potential to be robust biomarkers of diagnosis, staging, prognosis and response to therapy are reviewed. In small RNA animal biogenesis, miRNA genes in the nucleus are transcribed to generate long primary transcripts (pri-miRNAs), which are first cropped by RNase-III-type enzyme Drosha to release hairpin intermediates (pre-miRNAs) in the nucleus. Pre-miRNA is then exported to the cytoplasm by exportin-5. Following arrival in the cytoplasm, pre-miRNAs are subjected to the second processing step (dicing) to release the mature miRNA duplex, which is then separated: one strand becomes the mature miRNAand the other is degraded. These tiny miRNAs induce messenger degradation, translational repression or both. However, there is no evidence to demonstrate that these two mechanisms exist in the regulation of the same gene. Since a miRNA can target numerous mRNAs, often in combination with other miRNAs, these miRNAs operate a highly complex regulatory network. The specific function in most mammalian miRNAs is unknown. However, data suggest that miRNA genes, approximately 1% of all human genes, regulate protein production for 20–30% or more of all genes. miRNA expression profiles are effective for classifying solid and hematologic human cancers, and have shown great promise for early cancer detection. This is of great importance for effective treatment before the cells metastasize; therefore, tumors can be surgically resected. Computer-based prediction approaches of miRNAs and their targets, and biological validation techniques for ascertaining these predictions, currently play a central role in the discovery of miRNAs and in elucidating their function. Guidelines have been established for the identification and annotation of new miRNAs to distinguish them from other RNAs, especially siRNAs. These guidelines take into account factors such as transcript structure, conservation and processing, and a centralized, searchable database of all possible miRNA sequence information and annotation for humans and of more than 38 other species. Two approaches are used to characterize miRNAs: studying expression of known miRNAs by hybridization-based techniques (e.g., northern blots, RNase protection, primer extension, real-time, quantitative PCR and microarrays) or discovery of novel miRNAs molecules by cloning and sequencing. Owing to their adaptability and high throughput, microarrays may prove to be the preferred platform for whole-genome miRNA expression analysis.

RNA editing of human microRNAs

A survey of RNA editing of miRNAs from ten human tissues indicates that RNA editing increases the diversity of miRNAs and their targets.

MiRBase: microRNA sequences, targets and gene nomenclature

The miRBase database aims to provide integrated interfaces to comprehensive microRNA sequence data, annotation and predicted gene targets. miRBase takes over functionality from the microRNA Registry and fulfils three main roles: the miRBase Registry acts as an independent arbiter of microRNA gene nomenclature, assigning names prior to publication of novel miRNA sequences. miRBase Sequences is the primary online repository for miRNA sequence data and annotation. miRBase Targets is a comprehensive new database of predicted miRNA target genes. miRBase is available at .

FIGENIX: Intelligent automation of genomic annotation: expertise integration in a new software platform

BackgroundTwo of the main objectives of the genomic and post-genomic era are to structurally and functionally annotate genomes which consists of detecting genes' position and structure, and inferring their function (as well as of other features of genomes). Structural and functional annotation both require the complex chaining of numerous different software, algorithms and methods under the supervision of a biologist. The automation of these pipelines is necessary to manage huge amounts of data released by sequencing projects. Several pipelines already automate some of these complex chaining but still necessitate an important contribution of biologists for supervising and controlling the results at various steps.ResultsHere we propose an innovative automated platform, FIGENIX, which includes an expert system capable to substitute to human expertise at several key steps. FIGENIX currently automates complex pipelines of structural and functional annotation under the supervision of the expert system (which allows for example to make key decisions, check intermediate results or refine the dataset). The quality of the results produced by FIGENIX is comparable to those obtained by expert biologists with a drastic gain in terms of time costs and avoidance of errors due to the human manipulation of data.ConclusionThe core engine and expert system of the FIGENIX platform currently handle complex annotation processes of broad interest for the genomic community. They could be easily adapted to new, or more specialized pipelines, such as for example the annotation of miRNAs, the classification of complex multigenic families, annotation of regulatory elements and other genomic features of interest.

A uniform system for microRNA annotation.

MicroRNAs (miRNAs) are small noncoding RNA gene products about 22 nt long that are processed by Dicer from precursors with a characteristic hairpin secondary structure. Guidelines are presented for the identification and annotation of new miRNAs from diverse organisms, particularly so that miRNAs can be reliably distinguished from other RNAs such as small interfering RNAs. We describe specific criteria for the experimental verification of miRNAs, and conventions for naming miRNAs and miRNA genes. Finally, an online clearinghouse for miRNA gene name assignments is provided by the Rfam database of RNA families.

Assessing the risk of hypoxia in flight: the need for more rational guidelines

<h3>ABSTRACT</h3> Plant microRNAs (miRNAs) are short, non-coding RNA molecules that restrict gene expression via post-transcriptional regulation and function in several essential pathways including development, growth, and stress responses. Accurately identifying miRNAs in populations of small RNA (sRNA) sequencing libraries is a computationally intensive process which has resulted in the misidentification of inaccurately annotated miRNA sequences. In recent years, criteria for miRNA annotation have been refined to reduce these misannotations. Here, we describe <i>miRador</i>, a novel miRNA identification tool that utilizes the most up-to-date, community-established criteria for accurate identification of miRNAs in plants. We combine target prediction and Parallel Analysis of RNA Ends (PARE) data to assess the precision of the miRNAs identified by <i>miRador</i>. We compare <i>miRador</i> to other commonly used miRNA prediction tools and we find that <i>miRador</i> is at least as precise as other prediction tools while being significantly faster than other tools.