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High-throughput assessment of microRNA activity and function using microRNA sensor and decoy libraries

Nature Methods volume 9, pages 840846 (2012) | Download Citation

Abstract

We introduce two large-scale resources for functional analysis of microRNA (miRNA): a decoy library for inhibiting miRNA function and a sensor library for monitoring microRNA activity. To take advantage of the sensor library, we developed a high-throughput assay called Sensor-seq to simultaneously quantify the activity of hundreds of miRNAs. Using this approach, we show that only the most abundant miRNAs in a cell mediate target suppression. Over 60% of detected miRNAs had no discernible activity, which indicated that the functional 'miRNome' of a cell is considerably smaller than currently inferred from profiling studies. Moreover, some highly expressed miRNAs exhibited relatively weak activity, which in some cases correlated with a high target-to-miRNA ratio or increased nuclear localization of the miRNA. Finally, we show that the miRNA decoy library can be used for pooled loss-of-function studies. These tools are valuable resources for studying miRNA biology and for miRNA-based therapeutics.

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Acknowledgements

We thank L. Naldini, B. Gentner, E. Bernstein, E.C. Lai, A. Ventura and A. Chess for helpful discussions, and H. Iba (University of Tokyo) for pmU6-TuD-shuttle. We also thank the Mount Sinai Genomics Core Facility for deep sequencing. Oligo libraries were accessed through a collaborative technology program from Agilent Technologies. B.D.B. is supported by a US National Institute of Health Pathfinder Award (DP2DK083052-01) and funding from the Juvenile Diabetes Research Foundation (JDRF-17-2010-770). M.J.E. is supported by the Pew Charitable Funds and US National Institute of Health (R56AI091792). G.M. is supported by a Helmsley Trust Award.

Author information

Author notes

    • Gavriel Mullokandov
    • , Alessia Baccarini
    •  & Albert Ruzo

    These authors contributed equally to this work.

Affiliations

  1. Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, New York, USA.

    • Gavriel Mullokandov
    • , Alessia Baccarini
    • , Albert Ruzo
    • , Anitha D Jayaprakash
    • , Navpreet Tung
    • , Ravi Sachidanandam
    •  & Brian D Brown
  2. Department of Microbiology, Mount Sinai School of Medicine, New York, New York, USA.

    • Benjamin Israelow
    •  & Matthew J Evans

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Contributions

G.M., A.B. and A.R. designed and performed research and analyzed data. N.T. and A.D.J. performed research. B.I. and M.J.E. designed and performed research. R.S. designed the project and analyzed data. B.D.B. designed and coordinated the project and analyzed data.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Brian D Brown.

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DOI

https://doi.org/10.1038/nmeth.2078

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