Abstract
We demonstrate that paired expression profiles of microRNAs (miRNAs) and mRNAs can be used to identify functional miRNA-target relationships with high precision. We used a Bayesian data analysis algorithm, GenMiR++, to identify a network of 1,597 high-confidence target predictions for 104 human miRNAs, which was supported by RNA expression data across 88 tissues and cell types, sequence complementarity and comparative genomics data. We experimentally verified our predictions by investigating the result of let-7b downregulation in retinoblastoma using quantitative reverse transcriptase (RT)-PCR and microarray profiling: some of our verified let-7b targets include CDC25A and BCL7A. Compared to sequence-based predictions, our high-scoring GenMiR++ predictions had much more consistent Gene Ontology annotations and were more accurate predictors of which mRNA levels respond to changes in let-7b levels.
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Acknowledgements
J.C.H. and T.B. were supported by Natural Science and Engineering Research Council postgraduate scholarships. T.W.C. was supported by a Canada Graduate Scholarship from the Canadian Institutes for Health Research (CIHR). This study was supported by a Natural Sciences and Engineering Research Council operating grant and Canadian Foundation for Innovation and Ontario Research Fund infrastructure grants to Q.D.M.; a CIHR grant to B.J.F. and T.R.H; an Ontario Genomics Institute and Genome Canada grant to B.J.F. and B.J.B.; a CIHR and National Cancer Institute of Canada grant to B.J.B.; and a US National Institutes of Health grant to B.L.G. B.J.F. is a Fellow of the Canadian Institute for Advanced Research.
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Huang, J., Babak, T., Corson, T. et al. Using expression profiling data to identify human microRNA targets. Nat Methods 4, 1045–1049 (2007). https://doi.org/10.1038/nmeth1130
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DOI: https://doi.org/10.1038/nmeth1130
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