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

Nature Methods volume 9, pages 840–846 (2012)Cite this article

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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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Figure 1: Sensor-seq provides a rapid, high-throughput means for assessing miRNA activity.
Figure 2: Correlating miRNA abundance and target suppression.
Figure 3: miRNAs have different effective concentrations.
Figure 4: miRNA decoy library enables pooled loss-of-function screens.

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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.

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Author notes

  1. Gavriel Mullokandov, Alessia Baccarini and Albert Ruzo: These authors contributed equally to this work.

Authors and 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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  1. Gavriel Mullokandov
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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.

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Correspondence to Brian D Brown.

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Mullokandov, G., Baccarini, A., Ruzo, A. et al. High-throughput assessment of microRNA activity and function using microRNA sensor and decoy libraries. Nat Methods 9, 840–846 (2012). https://doi.org/10.1038/nmeth.2078

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