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CLIP and complementary methods

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TLDR
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 are discussed.
Abstract
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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Improved analysis of (e)CLIP data with RCRUNCH yields a compendium of RNA-binding protein binding sites and motifs

TL;DR: RCRUNCH as discussed by the authors is an end-to-end solution to CLIP data analysis for identification of binding sites and sequence specificity of RNA-binding proteins, which can analyze not only reads that map uniquely to the genome but also those that map to multiple genome locations or across splice boundaries and can consider various types of background in the estimation of read enrichment.
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Improved analysis of (e)CLIP data with RCRUNCH yields a compendium of RNA-binding protein binding sites and motifs

TL;DR: RCRUNCH as mentioned in this paper is an end-to-end solution to CLIP data analysis for identification of binding sites and sequence specificity of RNA-binding proteins, which can analyze not only reads that map uniquely to the genome, but also those that map to multiple genome locations or across splice boundaries, and can consider various types of background in the estimation of read enrichment.
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The role of RNA binding proteins in hepatocellular carcinoma.

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