Decoding RNA–Protein Interactions: Methodological Advances and Emerging Challenges

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Abstract

RNA–protein interactions are fundamental to cellular processes such as gene regulation and RNA metabolism. Over the past decade, significant advancements in methodologies have transformed the ability to study these interactions with unprecedented resolution and specificity. This review systematically compares RNA- and protein-centric approaches, highlighting their strengths, limitations, and optimal applications. RNA-centric methods, including hybridization-based pulldowns, proximity labeling, and CRISPR-assisted techniques, enable the identification of proteins interacting with specific RNAs, even low-abundance or transient partners. Protein-centric strategies, such as immunoprecipitation-based CLIP-seq, and emerging proximity-tagging methods, map RNA interactomes of RNA-binding proteins with nucleotide precision. This study evaluates key innovations like LACE-seq and ARTR-seq, which minimize cell input requirements, and HyPro-MS, which bypasses genetic modifications. Guidelines for method selection are provided, emphasizing experimental goals, RNA abundance, interaction dynamics, and technical constraints. Critical challenges are also discussed, including capturing low-affinity interactions, resolving RNA structural complexities, and integrating multi-omics data. This review underscores the importance of method-tailoring to biological contexts, offering a roadmap for researchers to navigate the evolving landscape of RNA–protein interaction studies. By bridging technical advancements with practical recommendations, this study aims to accelerate discoveries in RNA biology, therapeutic development, and precision medicine. © 2025 The Author(s)
Original languageEnglish
Article number2500011
Number of pages19
JournalAdvanced Genetics
DOIs
Publication statusPublished - 12 May 2025

Bibliographical note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Funding

The authors are grateful to the members of the Yan lab for reading the manuscript. The authors appreciate Dr. Xiao Wang and Dr. Shimeng Cao from the Ling-Ling Chen lab (Chinese Academy of Sciences) for their valuable suggestions on sgRNA design for circRNAs. The authors extend their sincere gratitude to Dr. Furong Ju and Ms. Yitong Lyu (City University of Hong Kong) for their constructive feedback and expertise during the preparation of this manuscript. The authors also express their apologies to colleagues whose pertinent work could not be cited owing to space constraints. This research was supported by the following funding sources: Shenzhen Medical Research Fund (B2302027), National Natural Science Foundation of China (32270634), Natural Science Foundation of Guangdong Province (2024A1515012685), the Research Grants Council of Hong Kong (11101022), Innovation and Technology Commission (ITS/087/22), and City University of Hong Kong (7005747).

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