Department of Life Science Frontiers, Center for iPS Cell Research and Application, Kyoto University, Kyoto, Japan.
xFOREST Therapeutics Co., Ltd., Kyoto, Japan.
Methods Mol Biol. 2022;2509:279-290. doi: 10.1007/978-1-0716-2380-0_17.
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.
RNA 转录本可以形成多种高级结构。我们开发了一种大规模的亲和力分析系统 FOREST(使用结构文库对折叠 RNA 元件进行分析),以在转录组范围内研究这些 RNA 结构的功能。在这里,我们描述了一种使用 FOREST 分析 RNA-蛋白质相互作用的方案。该方案的使用者制备由多种转录本组成的 RNA 结构文库,并对 RNA-蛋白质相互作用进行高通量表征,以获得关于结合亲和力和特异性的定量和全面信息。此外,我们还展示了如何在没有测序偏差的情况下使用 FOREST 来分析非规范结构 RNA 四链体,因为定量是直接在微阵列上进行的,而不需要序列扩增。FOREST 将有助于发现决定 RNA-蛋白质相互作用的 RNA 结构基序。