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STarMir Tools for Prediction of microRNA Binding Sites

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RNA Structure Determination

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1490))

Abstract

MicroRNAs (miRNAs) are a class of endogenous short noncoding RNAs that regulate gene expression by targeting messenger RNAs (mRNAs), which results in translational repression and/or mRNA degradation. As regulatory molecules, miRNAs are involved in many mammalian biological processes and also in the manifestation of certain human diseases. As miRNAs play central role in the regulation of gene expression, understanding miRNA-binding patterns is essential to gain an insight of miRNA mediated gene regulation and also holds promise for therapeutic applications. Computational prediction of miRNA binding sites on target mRNAs facilitates experimental investigation of miRNA functions. This chapter provides protocols for using the STarMir web server for improved predictions of miRNA binding sites on a target mRNA. As an application module of the Sfold RNA package, the current version of STarMir is an implementation of logistic prediction models developed with high-throughput miRNA binding data from cross-linking immunoprecipitation (CLIP) studies. The models incorporated comprehensive thermodynamic, structural, and sequence features, and were found to make improved predictions of both seed and seedless sites, in comparison to the established algorithms (Liu et al., Nucleic Acids Res 41:e138, 2013). Their broad applicability was indicated by their good performance in cross-species validation. STarMir is freely available at http://sfold.wadsworth.org/starmir.html.

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Acknowledgements

The Computational Molecular Biology and Statistics Core at the Wadsworth Center is acknowledged for supporting computing resources for this work. This work is supported in part by the National Science Foundation (DBI-0650991 to Y.D.), National Institutes of Health (GM099811, GM116885 to Y.D. and J.L.).

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Authors and Affiliations

  1. Wadsworth Center, New York State Department of Health, Center for Medical Science, 150 New Scotland Avenue, Albany, NY, 12208, USA

    Shaveta Kanoria, William Rennie, Chaochun Liu, C. Steven Carmack & Ye Ding

  2. Department of Genetics and Yale Stem Cell Center, Yale University, New Haven, CT, 06520, USA

    Jun Lu

Authors
  1. Shaveta Kanoria
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  2. William Rennie
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  3. Chaochun Liu
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  4. C. Steven Carmack
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  5. Jun Lu
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  6. Ye Ding
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Corresponding author

Correspondence to Ye Ding .

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Editors and Affiliations

  1. Department of Chemistry and Center for RNA Biology, University of Rochester College of Arts and Sciences, Rochester, New York, USA

    Douglas H. Turner

  2. Department of Biochemistry and Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York, USA

    David H. Mathews

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Kanoria, S., Rennie, W., Liu, C., Carmack, C.S., Lu, J., Ding, Y. (2016). STarMir Tools for Prediction of microRNA Binding Sites. In: Turner, D., Mathews, D. (eds) RNA Structure Determination. Methods in Molecular Biology, vol 1490. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6433-8_6

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  • DOI: https://doi.org/10.1007/978-1-4939-6433-8_6

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6431-4

  • Online ISBN: 978-1-4939-6433-8

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