miRGen: a database for the study of animal microRNA genomic organization and function

miRGen is an integrated database of (i) positional relationships between animal miRNAs and genomic annotation sets and (ii) animal miRNA targets according to combinations of widely used target prediction programs. A major goal of the database is the study of the relationship between miRNA genomic organization and miRNA function. This is made possible by three integrated and user friendly interfaces. The Genomics interface allows the user to explore where whole-genome collections of miRNAs are located with respect to UCSC genome browser annotation sets such as Known Genes, Refseq Genes, Genscan predicted genes, CpG islands and pseudogenes. These miRNAs are connected through the Targets interface to their experimentally supported target genes from TarBase, as well as computationally predicted target genes from optimized intersections and unions of several widely used mammalian target prediction programs. Finally, the Clusters interface provides predicted miRNA clusters at any given inter-miRNA distance and provides specific functional information on the targets of miRNAs within each cluster. All of these unique features of miRGen are designed to facilitate investigations into miRNA genomic organization, co-transcription and targeting. miRGen can be freely accessed at

Isoform Specific Gene Auto-Regulation via miRNAs: A Case Study on miR-128b and ARPP-21

In this study, we investigate whether miRNAs located within “host” protein-coding genes may regulate the expression of their host genes. We find that 43 of 174 miRNAs encoded within RefSeq genes are predicted to target their host genes. Statistical analysis of this phenomenon suggests that gene auto-regulation via miRNAs may be under positive selective pressure. Our analysis also indicates that several of the 43 miRNAs have a much lower expectation of targeting their host genes by chance than others. Among these examples, we identify miR-128b:ARPP-21 (cyclic AMP-regulated phosphoprotein, 21 kD) as a case in which both the miRNA and the target site are also evolutionarily conserved. We provide experimental support for this miRNA:target interaction via reporter silencing assays, and present evidence that this isoform-specific gene auto-regulation has been preserved in vertebrate species in order to prevent detrimental consequences of ARPP-21 over-expression in brain

The DIANA-mirExTra Web Server: From Gene Expression Data to MicroRNA Function

Background: High-throughput gene expression experiments are widely used to identify the role of genes involved in biological conditions of interest. MicroRNAs (miRNA) are regulatory molecules that have been functionally associated with several developmental programs and their deregulation with diverse diseases including cancer. Methodology/Principal Findings: Although miRNA expression levels may not be routinely measured in high-throughput experiments, a possible involvement of miRNAs in the deregulation of gene expression can be computationally predicted and quantified through analysis of overrepresented motifs in the deregulated genes 39 untranslated region (39UTR) sequences. Here, we introduce a user-friendly web-server, DIANA-mirExTra (www.microrna.gr/mirextra) that allows the comparison of frequencies of miRNA associated motifs between sets of genes that can lead to the identification of miRNAs responsible for the deregulation of large numbers of genes. To this end, we have investigated different approaches and measures, and have practically implemented them on experimental data. Conclusions/Significance: On several datasets of miRNA overexpression and repression experiments, our proposed approaches have successfully identified the deregulated miRNA. Beyond the prediction of miRNAs responsible for the deregulation of transcripts, the web-server provides extensive links to DIANA-mirPath, a functional analysis tool incorporating miRNA targets in biological pathways. Additionally, in case information about miRNA expression changes i

TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support

As the relevant literature and the number of experiments increase at a super linear rate, databases that curate and collect experimentally verified microRNA (miRNA) targets have gradually emerged. These databases attempt to provide efficient access to this wealth of experimental data, which is scattered in thousands of manuscripts. Aim of TarBase 6.0 (http://www.microrna.gr/tarbase) is to face this challenge by providing a significant increase of available miRNA targets derived from all contemporary experimental techniques (gene specific and high-throughput), while incorporating a powerful set of tools in a user-friendly interface. TarBase 6.0 hosts detailed information for each miRNA–gene interaction, ranging from miRNA- and gene-related facts to information specific to their interaction, the experimental validation methodologies and their outcomes. All database entries are enriched with function-related data, as well as general information derived from external databases such as UniProt, Ensembl and RefSeq. DIANA microT miRNA target prediction scores and the relevant prediction details are available for each interaction. TarBase 6.0 hosts the largest collection of manually curated experimentally validated miRNA–gene interactions (more than 65 000 targets), presenting a 16.5–175-fold increase over other available manually curated databases

Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia.

BACKGROUND: In mammalians, HIF is a master regulator of hypoxia gene expression through direct binding to DNA, while its role in microRNA expression regulation, critical in the hypoxia response, is not elucidated genome wide. Our aim is to investigate in depth the regulation of microRNA expression by hypoxia in the breast cancer cell line MCF-7, establish the relationship between microRNA expression and HIF binding sites, pri-miRNA transcription and microRNA processing gene expression. METHODS: MCF-7 cells were incubated at 1% Oxygen for 16, 32 and 48 h. SiRNA against HIF-1α and HIF-2α were performed as previously published. MicroRNA and mRNA expression were assessed using microRNA microarrays, small RNA sequencing, gene expression microarrays and Real time PCR. The Kraken pipeline was applied for microRNA-seq analysis along with Bioconductor packages. Microarray data was analysed using Limma (Bioconductor), ChIP-seq data were analysed using Gene Set Enrichment Analysis and multiple testing correction applied in all analyses. RESULTS: Hypoxia time course microRNA sequencing data analysis identified 41 microRNAs significantly up- and 28 down-regulated, including hsa-miR-4521, hsa-miR-145-3p and hsa-miR-222-5p reported in conjunction with hypoxia for the first time. Integration of HIF-1α and HIF-2α ChIP-seq data with expression data showed overall association between binding sites and microRNA up-regulation, with hsa-miR-210-3p and microRNAs of miR-27a/23a/24-2 and miR-30b/30d clusters as predominant examples. Moreover the expression of hsa-miR-27a-3p and hsa-miR-24-3p was found positively associated to a hypoxia gene signature in breast cancer. Gene expression analysis showed no full coordination between pri-miRNA and microRNA expression, pointing towards additional levels of regulation. Several transcripts involved in microRNA processing were found regulated by hypoxia, of which DICER (down-regulated) and AGO4 (up-regulated) were HIF dependent. DICER expression was found inversely correlated to hypoxia in breast cancer. CONCLUSIONS: Integrated analysis of microRNA, mRNA and ChIP-seq data in a model cell line supports the hypothesis that microRNA expression under hypoxia is regulated at transcriptional and post-transcriptional level, with the presence of HIF binding sites at microRNA genomic loci associated with up-regulation. The identification of hypoxia and HIF regulated microRNAs relevant for breast cancer is important for our understanding of disease development and design of therapeutic interventions

miRGen 2.0: a database of microRNA genomic information and regulation

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/

Accurate microRNA target prediction correlates with protein repression levels

MicroRNAs are small endogenously expressed non-coding RNA molecules that regulate target gene expression through translation repression or messenger RNA degradation. MicroRNA regulation is performed through pairing of the microRNA to sites in the messenger RNA of protein coding genes. Since experimental identification of miRNA target genes poses difficulties, computational microRNA target prediction is one of the key means in deciphering the role of microRNAs in development and diseas