Conserved Expression Patterns Predict microRNA Targets

• Published in: PLoS computational biology Vol. 5; no. 9; p. e1000513
• Main Authors: Ritchie, William, Rajasekhar, Megha, Flamant, Stephane, Rasko, John E. J.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.09.2009; Public Library of Science (PLoS)
• Subjects: Algorithms; Animals; Computational Biology - methods; Computational Biology/Genomics; Experiments; Gene expression; Gene Expression Profiling - methods; Gene Expression Regulation; Genes, Reporter - genetics; Genetics and Genomics/Bioinformatics; Genetics and Genomics/Gene Expression; HeLa Cells; Humans; Luciferase; Luciferases - genetics; Luciferases - metabolism; Messenger RNA; Mice; MicroRNAs - genetics; Molecular Biology/Bioinformatics; Molecular Biology/mRNA Stability; Molecular Biology/Post-Translational Regulation of Gene Expression; Oligonucleotide Array Sequence Analysis - methods; Regulation; Reproducibility of Results; RNA, Messenger - genetics; ROC Curve; Statistics as Topic; Reproducibility of Results; Oligonucleotide Array Sequence Analysis; Humans; Computational Biology; Gene Expression Regulation; Gene Expression Profiling; Statistics as Topic; Animals; Luciferases; MicroRNAs; ROC Curve; Mice; HeLa Cells; RNA, Messenger; Genes, Reporter
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1000513

microRNAs (miRNAs) are major regulators of gene expression and thereby modulate many biological processes. Computational methods have been instrumental in understanding how miRNAs bind to mRNAs to induce their repression but have proven inaccurate. Here we describe a novel method that combines expression data from human and mouse to discover conserved patterns of expression between orthologous miRNAs and mRNA genes. This method allowed us to predict thousands of putative miRNA targets. Using the luciferase reporter assay, we confirmed 4 out of 6 of our predictions. In addition, this method predicted many miRNAs that act as expression enhancers. We show that many miRNA enhancer effects are mediated through the repression of negative transcriptional regulators and that this effect could be as common as the widely reported repression activity of miRNAs. Our findings suggest that the indirect enhancement of gene expression by miRNAs could be an important component of miRNA regulation that has been widely neglected to date.