Finding the target sites of RNA-binding proteins.

IF 4.8 2区 生物学 Q1 CELL BIOLOGY Wiley Interdisciplinary Reviews: RNA Pub Date : 2014-01-01 Epub Date: 2013-11-11 DOI:10.1002/wrna.1201
Xiao Li, Hilal Kazan, Howard D Lipshitz, Quaid D Morris
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引用次数: 101

Abstract

RNA-protein interactions differ from DNA-protein interactions because of the central role of RNA secondary structure. Some RNA-binding domains (RBDs) recognize their target sites mainly by their shape and geometry and others are sequence-specific but are sensitive to secondary structure context. A number of small- and large-scale experimental approaches have been developed to measure RNAs associated in vitro and in vivo with RNA-binding proteins (RBPs). Generalizing outside of the experimental conditions tested by these assays requires computational motif finding. Often RBP motif finding is done by adapting DNA motif finding methods; but modeling secondary structure context leads to better recovery of RBP-binding preferences. Genome-wide assessment of mRNA secondary structure has recently become possible, but these data must be combined with computational predictions of secondary structure before they add value in predicting in vivo binding. There are two main approaches to incorporating structural information into motif models: supplementing primary sequence motif models with preferred secondary structure contexts (e.g., MEMERIS and RNAcontext) and directly modeling secondary structure recognized by the RBP using stochastic context-free grammars (e.g., CMfinder and RNApromo). The former better reconstruct known binding preferences for sequence-specific RBPs but are not suitable for modeling RBPs that recognize shape and geometry of RNAs. Future work in RBP motif finding should incorporate interactions between multiple RBDs and multiple RBPs in binding to RNA.

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寻找rna结合蛋白的靶位。
RNA-蛋白质相互作用不同于dna -蛋白质相互作用,因为RNA二级结构的中心作用。一些rna结合域(rbd)主要通过它们的形状和几何形状来识别它们的目标位点,另一些rna结合域是序列特异性的,但对二级结构环境很敏感。已经开发了许多小型和大规模的实验方法来测量体外和体内与rna结合蛋白(rbp)相关的rna。在这些分析测试的实验条件之外进行推广需要计算基序发现。通常RBP基序查找是通过适应DNA基序查找方法完成的;但二级结构背景建模可以更好地恢复rbp结合偏好。mRNA二级结构的全基因组评估最近成为可能,但这些数据必须与二级结构的计算预测相结合,才能增加预测体内结合的价值。将结构信息纳入基序模型的主要方法有两种:在一级序列基序模型中补充首选二级结构上下文(如MEMERIS和RNAcontext),以及使用随机上下文无关语法(如CMfinder和RNApromo)直接建模RBP识别的二级结构。前者更好地重建了序列特异性rbp的已知结合偏好,但不适合建模识别rna形状和几何形状的rbp。未来在RBP基序发现方面的工作应该包括多个RBP和多个RBP与RNA结合的相互作用。
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来源期刊
CiteScore
14.80
自引率
4.10%
发文量
67
审稿时长
6-12 weeks
期刊介绍: WIREs RNA aims to provide comprehensive, up-to-date, and coherent coverage of this interesting and growing field, providing a framework for both RNA experts and interdisciplinary researchers to not only gain perspective in areas of RNA biology, but to generate new insights and applications as well. Major topics to be covered are: RNA Structure and Dynamics; RNA Evolution and Genomics; RNA-Based Catalysis; RNA Interactions with Proteins and Other Molecules; Translation; RNA Processing; RNA Export/Localization; RNA Turnover and Surveillance; Regulatory RNAs/RNAi/Riboswitches; RNA in Disease and Development; and RNA Methods.
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