Using expression profiling data to identify human microRNA targets

Jim C. Huang, Tomas Babak, Timothy W. Corson, Gordon Chua, Sofia Khan, Brenda L. Gallie, Timothy R. Hughes, Benjamin J. Blencowe, Brendan J. Frey, Quaid D. Morris

Research output: Contribution to journalArticle

329 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1045-1049
Number of pages5
JournalNature Methods
Issue number12
StatePublished - Dec 1 2007
Externally publishedYes

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

Fingerprint Dive into the research topics of 'Using expression profiling data to identify human microRNA targets'. Together they form a unique fingerprint.

  • Cite this

    Huang, J. C., Babak, T., Corson, T. W., Chua, G., Khan, S., Gallie, B. L., Hughes, T. R., Blencowe, B. J., Frey, B. J., & Morris, Q. D. (2007). Using expression profiling data to identify human microRNA targets. Nature Methods, 4(12), 1045-1049.