ViTa: prediction of host microRNAs targets on viruses

RNA biology, 2016

microRNAs (miRNAs) are an abundant class of small endogenous non-coding RNAs (ncRNAs) of ∼22 nucleotides (nts) in length. These small regulatory molecules are involved in diverse developmental, physiological and pathological processes. miRNAs target messenger RNAs (mRNAs) for translational repression and/or mRNA degradation. Predictions of miRNA binding sites facilitate experimental validation of miRNA targets. Models developed with data from CLIP studies have been used for predictions of miRNA binding sites in the whole transcriptomes of human, mouse and worm. The prediction results have been assembled into STarMirDB, a new database of miRNA binding sites available at .http://sfold.wadsworth.org/starmirDB.php STarMirDB can be searched by miRNAs or mRNAs separately or in combination. The search results are categorized into seed and seedless sites in 3' UTR, CDS and 5' UTR. For each predicted site, STarMirDB provides a comprehensive list of sequence, thermodynamic and target ...

Nucleic Acids Research, 2006

Recent work has demonstrated that microRNAs (miRNAs) are involved in critical biological processes by suppressing the translation of coding genes. This work develops an integrated database, miRNAMap, to store the known miRNA genes, the putative miRNA genes, the known miRNA targets and the putative miRNA targets. The known miRNA genes in four mammalian genomes such as human, mouse, rat and dog are obtained from miRBase, and experimentally validated miRNA targets are identified in a survey of the literature. Putative miRNA precursors were identified by RNAz, which is a non-coding RNA prediction tool based on comparative sequence analysis. The mature miRNA of the putative miRNA genes is accurately determined using a machine learning approach, mmiRNA. Then, miRanda was applied to predict the miRNA targets within the conserved regions in 3 0 -UTR of the genes in the four mammalian genomes. The miRNAMap also provides the expression profiles of the known miRNAs, cross-species comparisons, gene annotations and cross-links to other biological databases. Both textual and graphical web interface are provided to facilitate the retrieval of data from the miRNAMap. The database is freely available at http:// mirnamap.mbc.nctu.edu.tw/.

Nucleic Acids Research, 2010

MicroRNAs are small, non-protein coding RNA molecules known to regulate the expression of genes by binding to the 3'UTR region of mRNAs. MicroRNAs are produced from longer transcripts which can code for more than one mature miRNAs. miRGen 2.0 is a database that aims to provide comprehensive information about the position of human and mouse microRNA coding transcripts and their regulation by transcription factors, including a unique compilation of both predicted and experimentally supported data. Expression profiles of microRNAs in several tissues and cell lines, single nucleotide polymorphism locations, microRNA target prediction on protein coding genes and mapping of miRNA targets of co-regulated miRNAs on biological pathways are also integrated into the database and user interface. The miRGen database will be continuously maintained and freely available at http://www.microrna.gr/mirgen/.

Journal of Biomedical Informatics, 2011

MicroRNAs are small, non-coding RNA molecules that can complementarily bind to the mRNA 3 0 -UTR region to regulate the gene expression by transcriptional repression or induction of mRNA degradation. Increasing evidence suggests a new mechanism by which miRNAs may regulate target gene expression by binding in promoter and amino acid coding regions. Most of the existing databases on miRNAs are restricted to mRNA 3 0 -UTR region. To address this issue, we present miRWalk, a comprehensive database on miRNAs, which hosts predicted as well as validated miRNA binding sites, information on all known genes of human, mouse and rat.

Gene, 2011

microRNAs (miRNAs) are the most abundant class of small RNAs in mammals. They play an important role in regulation of gene expression by inducing mRNA cleavage or translational inhibition. Each miRNA targets an average of 100-200 genes by binding, preferentially, to their 3′ UTRs by means of partial sequence complementarity. Most miRNAs are localized within transcriptional units, termed host genes, and show similar expression behavior with respect to their corresponding host genes. Considering the impact of miRNA in the regulation of gene expression and their involvement in a growing number of human disorders, it is vital to develop sensitive computational approaches able to identify miRNA target genes. The HOCTAR database (db) is a publicly available resource collecting ranked list of predicted target genes for 290 intragenic miRNAs annotated in human. HOCTARdb is a unique resource that integrates miRNA target prediction genes and transcriptomic data to score putative miRNA targets looking at the expression behavior of their host genes. We demonstrated, by testing 135 known validated target genes (either at the translational or transcriptional level) for different miRNAs, that the miRNA target prediction lists present in HOCTARdb are highly reliable. Moreover, HOCTARdb associates biological roles to each miRNA-controlled transcriptional network by means of Gene Ontology analysis. This information is easily accessible through a user-friendly query page. The HOCTARdb is available at http://hoctar.tigem.it/. We believe that a detailed relationship between miRNAs and their target genes and a constant update of the information contained in HOCTARdb will provide an extremely valuable resource to assist the researcher in the discovery of miRNA target genes.

Nucleic Acids Research, 2011

MicroRNAs (miRNAs), i.e. small non-coding RNA molecules ($22 nt), can bind to one or more target sites on a gene transcript to negatively regulate protein expression, subsequently controlling many cellular mechanisms. A current and curated collection of miRNA-target interactions (MTIs) with experimental support is essential to thoroughly elucidating miRNA functions under different conditions and in different species. As a database, miRTarBase has accumulated more than 3500 MTIs by manually surveying pertinent literature after data mining of the text systematically to filter research articles related to functional studies of miRNAs. Generally, the collected MTIs are validated experimentally by reporter assays, western blot, or microarray experiments with overexpression or knockdown of miRNAs. miRTarBase curates 3576 experimentally verified MTIs between 657 miRNAs and 2297 target genes among 17 species. miRTarBase contains the largest amount of validated MTIs by comparing with other similar, previously developed databases. The MTIs collected in the miRTarBase can also provide a large amount of positive samples to develop computational methods capable of identifying miRNA-target interactions. miRTarBase is now available on http:// miRTarBase.mbc.nctu.edu.tw/, and is updated frequently by continuously surveying research articles.

Briefings in bioinformatics, 2011

miRNA target genes prediction represents a crucial step in miRNAs functional characterization. In this context, the challenging issue remains predictions accuracy and recognition of false positive results. In this article myMIR, a web based system for increasing reliability of miRNAs predicted targets lists, is presented. myMIR implements an integrated pipeline for computing ranked miRNA::target lists and provides annotations for narrowing them down. The system relies on knowledge base data, suitably integratedin order to extend the functional characterization of targeted genes to miRNAs, by highlighting the search on over-represented annotation terms.Validation results show a dramatic reduction in the quantity of predictions and an increase in the sensitivity, when compared to other methods. This improves the predictions accuracy and allows the formulation of novel hypotheses on miRNAs functional involvement.

Nucleic Acids Research, 2007

MicroRNAs (miRNAs) constitute an important class of regulators that are involved in various cellular and disease processes. However, the functional significance of each miRNA is mostly unknown due to the difficulty in identifying target genes and the lack of genome-wide expression data combining miRNAs, mRNAs and proteins. We introduce a novel database, miRGator, that integrates the target prediction, functional analysis, gene expression data and genome annotation. MiRNA function is inferred from the list of target genes predicted by miRanda, PicTar and TargetScanS programs. Statistical enrichment test of target genes in each term is performed for gene ontology, pathway and disease annotations. Associated terms may provide valuable insights for the function of each miRNA. For the expression analysis, miRGator integrates public expression data of miRNA with those of mRNA and protein. Expression correlation between miRNA and target mRNA/proteins is evaluated and their expression patterns can be readily compared. Our web implementation supports diverse query types including miRNA name, gene symbol, gene ontology, pathway and disease terms. Interfaces for exploring common targets or regulatory miRNAs and for profiling compendium expression data have been developed as well. Currently, miRGator, available at: http:// genome.ewha.ac.kr/miRGator/, supports the human and mouse genomes.

BMC bioinformatics, 2013

MicroRNAs (miRNA) are regulatory genes that target and repress other RNA molecules via sequence-specific binding. Several biological processes are regulated across many organisms by evolutionarily conserved miRNAs. Plants and invertebrates employ their miRNA in defense against viruses by targeting and degrading viral products. Viruses also encode miRNAs and there is evidence to suggest that virus-encoded miRNAs target specific host genes and pathways that may be beneficial for their infectivity and/or proliferation. However, it is not clear whether there are general patterns underlying cellular targets of viral miRNAs. Here we show that for several of the 135 known viral miRNAs in human viruses, the human genes targeted by the viral miRNA are enriched for specific host pathways whose targeting is likely beneficial to the virus. Given that viral miRNAs continue to be discovered as technologies evolve, we extended the investigation to 6809 putative miRNAs encoded by 23 human viruses. ...

2019

microRNAs (miRNAs) are short non-coding RNAs that can repress the expression of protein coding messenger RNAs (mRNAs) by binding to the 3'UTR of the target. Genetic mutations such as single nucleotide variants (SNVs) in the 3'UTR of the mRNAs can disrupt this regulatory effect. In this study, we presented dbMTS, the database for miRNA target site (MTS) SNVs, that include all potential MTS SNVs in the 3'UTR of human genome along with hundreds of functional annotations. This database can help studies easily identify putative SNVs that affect miRNA targeting and facilitate the prioritization of their functional importance. dbMTS is freely available at: https://sites.google.com/site/jpopgen/dbNSFP.