let-7 transfection series

micro (mi) RNAs are short noncoding transcripts that post-transcriptionally regulate gene expression by sequence-specific interaction. Hundreds of human miRNAs have been discovered that collectively have thousands of predicted mRNA targets. However, despite rapid advances in miRNA identification, accurate determination of targets has slowed their functional characterization in animals. Here we present a novel computational method called GenMiR++ to discover a regulatory network of functional miRNA-mRNA interactions using sequence information and RNA expression data. Using this method, we find that tissue-specific patterns of expression of miRNA-targeted genes are surprisingly predictive of whether miRNA-mRNA interactions are functional in other tissues. We show that our targetting network is an improvement over predictions generated using solely sequence-based approaches and directly demonstrate its biological relevance by exploring miRNA misregulation in retinoblastoma. We found that downregulation of let-7b in retinoblastoma correlated with elevated levels of GenMiR++ targets, including CDC25A and BCL7A, which were reduced in response to let-7b. Our miRNA regulatory network provides a large-scale resource of functional targets that will accelerate exposition of miRNA biological roles. Keywords: miRNA transfection let-7 transfection