%0 Journal Article %J Genome Biol %D 2013 %T Sustained-input switches for transcription factors and microRNAs are central building blocks of eukaryotic gene circuits. %A Megraw, Molly %A Mukherjee, Sayan %A Ohler, Uwe %K Algorithms %K Animals %K Arabidopsis %K Computational Biology %K Drosophila melanogaster %K Gene Expression Regulation %K Gene Regulatory Networks %K Humans %K MicroRNAs %K Molecular Sequence Annotation %K Nucleic Acid Conformation %K Software %K Transcription Factors %X

WaRSwap is a randomization algorithm that for the first time provides a practical network motif discovery method for large multi-layer networks, for example those that include transcription factors, microRNAs, and non-regulatory protein coding genes. The algorithm is applicable to systems with tens of thousands of genes, while accounting for critical aspects of biological networks, including self-loops, large hubs, and target rearrangements. We validate WaRSwap on a newly inferred regulatory network from Arabidopsis thaliana, and compare outcomes on published Drosophila and human networks. Specifically, sustained input switches are among the few over-represented circuits across this diverse set of eukaryotes.

%B Genome Biol %V 14 %P R85 %8 2013 %G eng %N 8 %R 10.1186/gb-2013-14-8-r85 %0 Journal Article %J Nucleic Acids Res %D 2010 %T miRGen 2.0: a database of microRNA genomic information and regulation. %A Alexiou, Panagiotis %A Vergoulis, Thanasis %A Gleditzsch, Martin %A Prekas, George %A Dalamagas, Theodore %A Megraw, Molly %A Grosse, Ivo %A Sellis, Timos %A Hatzigeorgiou, Artemis G %K 3' Untranslated Regions %K Algorithms %K Animals %K Cell Line, Tumor %K Computational Biology %K Databases, Genetic %K Databases, Nucleic Acid %K Humans %K Information Storage and Retrieval %K Internet %K Mice %K MicroRNAs %K Polymorphism, Single Nucleotide %K Software %K Transcription Factors %X

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/.

%B Nucleic Acids Res %V 38 %P D137-41 %8 2010 Jan %G eng %N Database issue %R 10.1093/nar/gkp888 %0 Journal Article %J Nucleic Acids Res %D 2008 %T Frequency and fate of microRNA editing in human brain. %A Kawahara, Yukio %A Megraw, Molly %A Kreider, Edward %A Iizasa, Hisashi %A Valente, Louis %A Hatzigeorgiou, Artemis G %A Nishikura, Kazuko %K Adenosine %K Adenosine Deaminase %K Animals %K Base Sequence %K Brain %K Humans %K Inosine %K Mice %K MicroRNAs %K Molecular Sequence Data %K RNA Editing %K RNA Precursors %K RNA Processing, Post-Transcriptional %K RNA-Binding Proteins %X

Primary transcripts of certain microRNA (miRNA) genes (pri-miRNAs) are subject to RNA editing that converts adenosine to inosine (A-->I RNA editing). However, the frequency of the pri-miRNA editing and the fate of edited pri-miRNAs remain largely to be determined. Examination of already known pri-miRNA editing sites indicated that adenosine residues of the UAG triplet sequence might be edited more frequently. In the present study, therefore, we conducted a large-scale survey of human pri-miRNAs containing the UAG triplet sequence. By direct sequencing of RT-PCR products corresponding to pri-miRNAs, we examined 209 pri-miRNAs and identified 43 UAG and also 43 non-UAG editing sites in 47 pri-miRNAs, which were highly edited in human brain. In vitro miRNA processing assay using recombinant Drosha-DGCR8 and Dicer-TRBP (the human immuno deficiency virus transactivating response RNA-binding protein) complexes revealed that a majority of pri-miRNA editing is likely to interfere with the miRNA processing steps. In addition, four new edited miRNAs with altered seed sequences were identified by targeted cloning and sequencing of the miRNAs that would be processed from edited pri-miRNAs. Our studies predict that approximately 16% of human pri-miRNAs are subject to A-->I editing and, thus, miRNA editing could have a large impact on the miRNA-mediated gene silencing.

%B Nucleic Acids Res %V 36 %P 5270-80 %8 2008 Sep %G eng %N 16 %R 10.1093/nar/gkn479 %0 Journal Article %J Nucleic Acids Res %D 2007 %T miRGen: a database for the study of animal microRNA genomic organization and function. %A Megraw, Molly %A Sethupathy, Praveen %A Corda, Benoit %A Hatzigeorgiou, Artemis G %K Animals %K Data Interpretation, Statistical %K Databases, Nucleic Acid %K Genomics %K Humans %K Internet %K Mice %K MicroRNAs %K Rats %K User-Computer Interface %X

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 http://www.diana.pcbi.upenn.edu/miRGen.

%B Nucleic Acids Res %V 35 %P D149-55 %8 2007 Jan %G eng %N Database issue %R 10.1093/nar/gkl904 %0 Journal Article %J Nat Methods %D 2006 %T A guide through present computational approaches for the identification of mammalian microRNA targets. %A Sethupathy, Praveen %A Megraw, Molly %A Hatzigeorgiou, Artemis G %K 3' Untranslated Regions %K 5' Untranslated Regions %K Animals %K Computational Biology %K Gene Targeting %K Humans %K MicroRNAs %K Predictive Value of Tests %K RNA, Messenger %K Sensitivity and Specificity %K Software %X

Computational microRNA (miRNA) target prediction is a field in flux. Here we present a guide through five widely used mammalian target prediction programs. We include an analysis of the performance of these individual programs and of various combinations of these programs. For this analysis we compiled several benchmark data sets of experimentally supported miRNA-target gene interactions. Based on the results, we provide a discussion on the status of target prediction and also suggest a stepwise approach toward predicting and selecting miRNA targets for experimental testing.

%B Nat Methods %V 3 %P 881-6 %8 2006 Nov %G eng %N 11 %R 10.1038/nmeth954