DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows

MicroRNAs (miRNAs) are small endogenous RNA molecules that regulate gene expression through mRNA degradation and/or translation repression, affecting many biological processes. DIANA-microT web server (http://www.microrna.gr/webServer) is dedicated to miRNA target prediction/functional analysis, and it is being widely used from the scientific community, since its initial launch in 2009. DIANA-microT v5.0, the new version of the microT server, has been significantly enhanced with an improved target prediction algorithm, DIANA-microT-CDS. It has been updated to incorporate miRBase version 18 and Ensembl version 69. The in silico-predicted miRNA–gene interactions in Homo sapiens, Mus musculus, Drosophila melanogaster and Caenorhabditis elegans exceed 11 million in total. The web server was completely redesigned, to host a series of sophisticated workflows, which can be used directly from the on-line web interface, enabling users without the necessary bioinformatics infrastructure to perform advanced multi-step functional miRNA analyses. For instance, one available pipeline performs miRNA target prediction using different thresholds and meta-analysis statistics, followed by pathway enrichment analysis. DIANA-microT web server v5.0 also supports a complete integration with the Taverna Workflow Management System (WMS), using the in-house developed DIANA-Taverna Plug-in. This plug-in provides ready-to-use modules for miRNA target prediction and functional analysis, which can be used to form advanced high-throughput analysis pipelines.

[1]  G. Hong,et al.  Nucleic Acids Research , 2015, Nucleic Acids Research.

[2]  Nectarios Koziris,et al.  TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support , 2011, Nucleic Acids Res..

[3]  Martin Reczko,et al.  Lost in translation: an assessment and perspective for computational microRNA target identification , 2009, Bioinform..

[4]  Martin Reczko,et al.  DIANA miRPath v.2.0: investigating the combinatorial effect of microRNAs in pathways , 2012, Nucleic Acids Res..

[5]  V. Ambros,et al.  The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14 , 1993, Cell.

[6]  N. Rajewsky,et al.  Widespread changes in protein synthesis induced by microRNAs , 2008, Nature.

[7]  Nectarios Koziris,et al.  DIANA-microT Web server upgrade supports Fly and Worm miRNA target prediction and bibliographic miRNA to disease association , 2011, Nucleic Acids Res..

[8]  Carole A. Goble,et al.  Taverna: a tool for building and running workflows of services , 2006, Nucleic Acids Res..

[9]  D. Bartel MicroRNAs: Target Recognition and Regulatory Functions , 2009, Cell.

[10]  Yvonne Tay,et al.  MicroRNAs to Nanog, Oct4 and Sox2 coding regions modulate embryonic stem cell differentiation , 2008, Nature.

[11]  Ramon C. Littell,et al.  Asymptotic Optimality of Fisher's Method of Combining Independent Tests , 1971 .

[12]  Ivo Grosse,et al.  Functional microRNA targets in protein coding sequences , 2012, Bioinform..

[13]  Susumu Goto,et al.  KEGG for integration and interpretation of large-scale molecular data sets , 2011, Nucleic Acids Res..

[14]  W. Krzyzosiak,et al.  Practical Aspects of microRNA Target Prediction , 2011, Current molecular medicine.

[15]  Gautier Koscielny,et al.  Ensembl 2012 , 2011, Nucleic Acids Res..

[16]  Ana Kozomara,et al.  miRBase: integrating microRNA annotation and deep-sequencing data , 2010, Nucleic Acids Res..

[17]  C. Sander,et al.  A Mammalian microRNA Expression Atlas Based on Small RNA Library Sequencing , 2007, Cell.