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mirWIP: microRNA target prediction based on microRNA-containing ribonucleoprotein–enriched transcripts

Nature Methods volume 5, pages 813–819 (2008)Cite this article

Abstract

Target prediction for animal microRNAs (miRNAs) has been hindered by the small number of verified targets available to evaluate the accuracy of predicted miRNA-target interactions. Recently, a dataset of 3,404 miRNA-associated mRNA transcripts was identified by immunoprecipitation of the RNA-induced silencing complex components AIN-1 and AIN-2. Our analysis of this AIN-IP dataset revealed enrichment for defining characteristics of functional miRNA-target interactions, including structural accessibility of target sequences, total free energy of miRNA-target hybridization and topology of base-pairing to the 5′ seed region of the miRNA. We used these enriched characteristics as the basis for a quantitative miRNA target prediction method, miRNA targets by weighting immunoprecipitation-enriched parameters (mirWIP), which optimizes sensitivity to verified miRNA-target interactions and specificity to the AIN-IP dataset. MirWIP can be used to capture all known conserved miRNA-mRNA target relationships in Caenorhabditis elegans at a lower false-positive rate than can the current standard methods.

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Figure 1: Flowchart for the mirWIP target prediction method.
Figure 2: Characteristics of miRNA target sites in AIN-IP transcripts.
Figure 3: Sensitivity and specificity of mirWIP.
Figure 4: Distribution of miRNA predictions.

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Acknowledgements

We thank C. Hammell and all members of the Ambros lab for useful discussions and the Computational Molecular Biology and Statistics Core at the Wadsworth Center for providing computing resources for this work. This research was supported by US National Institutes of Health grants GM34028 and GM066826 to V.A., GM068726 to Y.D. and GM47869 to M. Han as well as US National Science Foundation grant DBI-0650991 to Y.D.; and the Howard Hughes Medical Institute, of which M. Han is an investigator.

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Authors and Affiliations

  1. Program in Molecular Medicine, University of Massachusetts Medical School, 373 Plantation Street, Suite 306, Worcester, 01605, Massachusetts, USA

    Molly Hammell, Andrew Lee & Victor Ambros

  2. New York State Department of Health, Wadsworth Center, 150 New Scotland Avenue, Albany, 12208, New York, USA

    Dang Long, C Steven Carmack & Ye Ding

  3. Department of Molecular, Howard Hughes Medical Institute, Cellular and Developmental Biology, Campus Box 347, University of Colorado at Boulder, Boulder, 80309, Colorado, USA

    Liang Zhang & Min Han

Authors
  1. Molly Hammell
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  2. Dang Long
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  4. Andrew Lee
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  6. Min Han
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  7. Ye Ding
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  8. Victor Ambros
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Corresponding authors

Correspondence to Ye Ding or Victor Ambros.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3, Supplementary Tables 1–2, Supplementary Results, Supplementary Methods (PDF 1271 kb)

Supplementary Software

The source code for mirWIP and the RNAhybrid modifications. (ZIP 211 kb)

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Hammell, M., Long, D., Zhang, L. et al. mirWIP: microRNA target prediction based on microRNA-containing ribonucleoprotein–enriched transcripts. Nat Methods 5, 813–819 (2008). https://doi.org/10.1038/nmeth.1247

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