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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. Proteins begin to interact with nascent RNAs as soon as transcription is initiated. The protein complement decorating an RNA molecule changes dynamically in space and time, orchestrating RNA processing and function in the nucleus and cytoplasm 1. Ribonucleoprotein (RNP) complexes are key to every step of RNA processing and function, and understanding the roles that RNA-binding proteins (RBPs) play requires methods that identify the set of RNAs that they bind in cells during specific developmental stages, activities or disease states.

Numerous methods can characterize the RNA interactions that coordinate RNP assembly. These approaches can be protein-centric, describing the compendium of RNA sites bound by a specific RBP, or RNA-centric, identifying the RNA-bound proteome.

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