Category Archives: Past

Sequence-dependent but not sequence-specific piRNA adhesion traps mRNAs to the germ plasm

Publication

nature

 

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Nature. 2016 Mar 7. doi: 10.1038/nature17150

Abstract
The conserved Piwi family of proteins and piwi-interacting RNAs (piRNAs) have a central role in genomic stability, which is inextricably linked to germ-cell formation, by forming Piwi ribonucleoproteins (piRNPs) that silence transposable elements. In Drosophila melanogaster and other animals, primordial germ-cell specification in the developing embryo is driven by maternal messenger RNAs and proteins that assemble into specialized messenger ribonucleoproteins (mRNPs) localized in the germ (pole) plasm at the posterior of the oocyte. Maternal piRNPs, especially those loaded on the Piwi protein Aubergine (Aub), are transmitted to the germ plasm to initiate transposon silencing in the offspring germ line. The transport of mRNAs to the oocyte by midoogenesis is an active, microtubule-dependent process; mRNAs necessary for primordial germ-cell formation are enriched in the germ plasm at late oogenesis via a diffusion and entrapment mechanism, the molecular identity of which remains unknown. Aub is a central component of germ granule RNPs, which house mRNAs in the germ plasm, and interactions between Aub and Tudor are essential for the formation of germ granules. Here we show that Aub-loaded piRNAs use partial base-pairing characteristics of Argonaute RNPs to bind mRNAs randomly in Drosophila, acting as an adhesive trap that captures mRNAs in the germ plasm, in a Tudor-dependent manner. Notably, germ plasm mRNAs in drosophilids are generally longer and more abundant than other mRNAs, suggesting that they provide more target sites for piRNAs to promote their preferential tethering in germ granules. Thus, complexes containing Tudor, Aub piRNPs and mRNAs couple piRNA inheritance with germline specification. Our findings reveal an unexpected function for piRNP complexes in mRNA trapping that may be generally relevant to the function of animal germ granules.

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Genomic and Epigenetic Alterations Deregulate microRNA Expression in Human Epithelial Ovarian Cancer

Publication

ovarian

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Proc Natl Acad Sci U S A ,105(19) ,7004-9.

Abstract
MicroRNAs (miRNAs) are an abundant class of small noncoding RNAs that function as negative gene regulators. miRNA deregulation is involved in the initiation and progression of human cancer; however, the underlying mechanism and its contributions to genome-wide transcriptional changes in cancer are still largely unknown. We studied miRNA deregulation in human epithelial ovarian cancer by integrative genomic approach, including miRNA microarray (n = 106), array-based comparative genomic hybridization (n = 109), cDNA microarray (n = 76), and tissue array (n = 504). miRNA expression is markedly down-regulated in malignant transformation and tumor progression. Genomic copy number loss and epigenetic silencing, respectively, may account for the down-regulation of ≈15% and at least ≈36% of miRNAs in advanced ovarian tumors and miRNA down-regulation contributes to a genome-wide transcriptional deregulation. Last, eight miRNAs located in the chromosome 14 miRNA cluster (Dlk1-Gtl2 domain) were identified as potential tumor suppressor genes. Therefore, our results suggest that miRNAs may offer new biomarkers and therapeutic targets in epithelial ovarian cancer.

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DIANA-microT web server: elucidating microRNA functions through target prediction.

Publication

microtwebserver

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Nucleic Acids Res. ,37(Web Server issue):W273-6.

Abstract
Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT.

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DIANA-mirPath: Integrating human and mouse microRNAs in pathways.

Publication

mirpath

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Bioinformatics. ,2009 Aug 1;25(15):1991-3.

Abstract
DIANA-mirPath is a web-based computational tool developed to identify molecular pathways potentially altered by the expression of single or multiple microRNAs. The software performs an enrichment analysis of multiple microRNA target genes comparing each set of microRNA targets to all known KEGG pathways. The combinatorial effect of co-expressed microRNAs in the modulation of a given pathway is taken into account by the simultaneous analysis of multiple microRNAs. The graphical output of the program provides an overview of the parts of the pathway modulated by microRNAs, facilitating the interpretation and presentation of the analysis results.

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Accurate microRNA target prediction correlates with protein repression levels.

Publication

accurateBMC

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BMC Bioinformatics ,2009 Sep 18;10:295.

Abstract

DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at http://www.microrna.gr/microT

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Review: Lost in translation: an assessment and perspective for computational microRNA target identification.

Publication

lost_in_translation

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Bioinformatics , 25(23):3049-55

Review
MicroRNAs (miRNAs) are a class of short endogenously expressed RNA molecules that regulate gene expression by binding directly to the messenger RNA of protein coding genes. They have been found to confer a novel layer of genetic regulation in a wide range of biological processes. Computational miRNA target prediction remains one of the key means used to decipher the role of miRNAs in development and disease. Here we introduce the basic idea behind the experimental identification of miRNA targets and present some of the most widely used computational miRNA target identification programs. The review includes an assessment of the prediction quality of these programs and their combinations.

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miRGen 2.0: a database of microRNA genomic information and regulation

Publication
mirgen2

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Nucleic Acids Research , 38(Database issue): D137–D141.

Abstract

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 targetprediction 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/.

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The DIANA-mirExTra web server: from gene expression data to microRNA function.

Publication

mirextra

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PLoS ONE ,5(2):e9171

Abstract
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. 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 3′ untranslated region (3’UTR) 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. 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 is provided, the results can be filtered to display the analysis for miRNAs of interest only.

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In vivo profiling of hypoxic gene expression in gliomas using the hypoxia marker EF5 and laser-capture microdissection.

Publication

hypoxia

Full Text
Cancer Res ,71(3):779-89

Abstract
Hypoxia is a key determinant of tumor aggressiveness, yet little is known regarding hypoxic global gene regulation in vivo. We used the hypoxia marker EF5 coupled with laser-capture microdissection to isolate RNA from viable hypoxic and normoxic regions of 9L experimental gliomas. Through microarray analysis, we identified several mRNAs (including the HIF targets Vegf, Glut-1, and Hsp27) with increased levels under hypoxia compared with normoxia both in vitro and in vivo. However, we also found striking differences between the global in vitro and in vivo hypoxic mRNA profiles. Intriguingly, the mRNA levels of a substantial number of immunomodulatory and DNA repair proteins including CXCL9, CD3D, and RAD51 were found to be downregulated in hypoxic areas in vivo, consistent with a protumorigenic role of hypoxia in solid tumors. Immunohistochemical staining verified increased HSP27 and decreased RAD51 protein levels in hypoxic versus normoxic tumor regions. Moreover, CD8(+) T cells, which are recruited to tumors upon stimulation by CXCL9 and CXCL10, were largely excluded from viable hypoxic areas in vivo. This is the first study to analyze the influence of hypoxia on mRNA levels in vivo and can be readily adapted to obtain a comprehensive picture of hypoxic regulation of gene expression and its influence on biological functions in solid tumors.

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Review: Online resources for microRNA analysis.

Publication

review_jnai

Full Text
Journal of Nucleic Acid Investigation, 2(1)

Abstract

The use of online tools for bioinformatics analyses is becoming increasingly widespread. Resources specific to the field of microRNAs are available, varying in scope and usability. Online tools are the most useful for casual as well as power users since they need no installation, are hardware independent and are used mostly through graphic user interfaces and links to external sources. Here, we present an overview of useful online resources that have to do with microRNA genomics, gene finding, target prediction and functional analysis.

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