Accurate microRNA target prediction correlates with protein repression levels

BackgroundMicroRNAs 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 disease.ResultsDIANA-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.ConclusionRecently, 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

[1]  W. J. Kent,et al.  The UCSC Genome Browser , 2003, Current protocols in bioinformatics.

[2]  N. Rajewsky,et al.  Cell-type-specific signatures of microRNAs on target mRNA expression. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[3]  C. Burge,et al.  Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets , 2005, Cell.

[4]  R. Giegerich,et al.  Fast and effective prediction of microRNA/target duplexes. , 2004, RNA.

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

[6]  Dang D. Long,et al.  Potent effect of target structure on microRNA function , 2007, Nature Structural &Molecular Biology.

[7]  A. Hatzigeorgiou,et al.  A combined computational-experimental approach predicts human microRNA targets. , 2004, Genes & development.

[8]  V. Ambros,et al.  An Extensive Class of Small RNAs in Caenorhabditis elegans , 2001, Science.

[9]  Martin Reczko,et al.  The database of experimentally supported targets: a functional update of TarBase , 2008, Nucleic Acids Res..

[10]  Andreas Prlic,et al.  Ensembl 2008 , 2007, Nucleic Acids Res..

[11]  T. Tuschl,et al.  Identification of Novel Genes Coding for Small Expressed RNAs , 2001, Science.

[12]  J. Castle,et al.  Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs , 2005, Nature.

[13]  Michael Kertesz,et al.  The role of site accessibility in microRNA target recognition , 2007, Nature Genetics.

[14]  J. M. Thomson,et al.  Argonaute2 Is the Catalytic Engine of Mammalian RNAi , 2004, Science.

[15]  Stijn van Dongen,et al.  miRBase: tools for microRNA genomics , 2007, Nucleic Acids Res..

[16]  A. Hatzigeorgiou,et al.  A guide through present computational approaches for the identification of mammalian microRNA targets , 2006, Nature Methods.

[17]  Mihaela Zavolan,et al.  Inference of miRNA targets using evolutionary conservation and pathway analysis , 2007, BMC Bioinformatics.

[18]  R. Russell,et al.  Principles of MicroRNA–Target Recognition , 2005, PLoS biology.

[19]  L. Lim,et al.  MicroRNA targeting specificity in mammals: determinants beyond seed pairing. , 2007, Molecular cell.

[20]  D. Bartel.  MicroRNAs Genomics, Biogenesis, Mechanism, and Function , 2004, Cell.

[21]  C. Burge,et al.  Prediction of Mammalian MicroRNA Targets , 2003, Cell.

[22]  D. Bartel,et al.  The impact of microRNAs on protein output , 2008, Nature.

[23]  Colin N. Dewey,et al.  A Genome-Wide Map of Conserved MicroRNA Targets in C. elegans , 2006, Current Biology.

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

[25]  Nectarios Koziris,et al.  DIANA-microT web server: elucidating microRNA functions through target prediction , 2009, Nucleic Acids Res..

[26]  L. Lim,et al.  An Abundant Class of Tiny RNAs with Probable Regulatory Roles in Caenorhabditis elegans , 2001, Science.