CLIP and complementary methods

核糖核酸 计算生物学 核糖核蛋白 免疫沉淀 RNA结合蛋白 计算机科学 结合位点 生物 遗传学 基因
作者
Markus Hafner,Maria Katsantoni,Tino Köster,James Marks,Joyita Mukherjee,Dorothee Staiger,Jernej Ule,Mihaela Zavolan
出处
期刊:Nature Reviews Methods Primers [Springer Nature]
卷期号:1 (1) 被引量:364
标识
DOI:10.1038/s43586-021-00018-1
摘要

RNA molecules start assembling into ribonucleoprotein (RNP) complexes during transcription. Dynamic RNP assembly, largely directed by cis-acting elements on the RNA, coordinates all processes in which the RNA is involved. To identify the sites bound by a specific RNA-binding protein on endogenous RNAs, cross-linking and immunoprecipitation (CLIP) and complementary, proximity-based methods have been developed. In this Primer, we discuss the main variants of these protein-centric methods and the strategies for their optimization and quality assessment, as well as RNA-centric methods that identify the protein partners of a specific RNA. We summarize the main challenges of computational CLIP data analysis, how to handle various sources of background and how to identify functionally relevant binding regions. We outline the various applications of CLIP and available databases for data sharing. We discuss the prospect of integrating data obtained by CLIP with complementary methods to gain a comprehensive view of RNP assembly and remodelling, unravel the spatial and temporal dynamics of RNPs in specific cell types and subcellular compartments and understand how defects in RNPs can lead to disease. Finally, we present open questions in the field and give directions for further development and applications. Ule and colleagues discuss cross-linking and immunoprecipitation (CLIP) methods for characterizing the RNA binding partners of RNA-binding proteins and explore the data analysis workflows, best practices and applications for these techniques. The Primer also considers methods for characterizing the protein binding partners of specific RNAs and discusses how data from these complementary methods can be integrated into CLIP workflows.
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