Abstract
RNA transcripts can form a variety of higher-order structures. We developed a large-scale affinity analysis system, FOREST (Folded RNA Element Profiling with Structure Library), to investigate the function of these RNA structures on transcriptome-wide scale. Here we describe a protocol to analyze RNA–protein interactions using FOREST . Users of the protocol prepare an RNA structure library comprised of diverse species of transcripts and perform high-throughput characterization of the RNA–protein interactions to obtain quantitative and comprehensive information on the binding affinities and specificities. Moreover, we demonstrate how FOREST can be used to analyze a non-canonical structure, the RNA G-quadruplex, without sequencing bias, because the quantification is performed directly on a microarray without sequence amplification. FOREST will contribute to the discovery of RNA structure motifs that determine RNA–protein interactions.
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Acknowledgments
We would like to thank P. Karagiannis for critical reading of the paper. This work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI No. 20H05626, 15H05722, to H.S.
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© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
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Miyashita, E., Komatsu, K.R., Saito, H. (2022). Large-Scale Analysis of RNA–Protein Interactions for Functional RNA Motif Discovery Using FOREST. In: Parrish, N.F., Iwasaki, Y.W. (eds) piRNA. Methods in Molecular Biology, vol 2509. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2380-0_17
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DOI: https://doi.org/10.1007/978-1-0716-2380-0_17
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