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uvCLAP is a fast and non-radioactive method to identify in vivo targets of RNA-binding proteins

Author

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  • Daniel Maticzka

    (University of Freiburg)

  • Ibrahim Avsar Ilik

    (Max Planck Institute of Immunobiology and Epigenetics)

  • Tugce Aktas

    (Max Planck Institute of Immunobiology and Epigenetics)

  • Rolf Backofen

    (University of Freiburg
    University of Freiburg)

  • Asifa Akhtar

    (Max Planck Institute of Immunobiology and Epigenetics)

Abstract

RNA-binding proteins (RBPs) play important and essential roles in eukaryotic gene expression regulating splicing, localization, translation, and stability of mRNAs. We describe ultraviolet crosslinking and affinity purification (uvCLAP), an easy-to-use, robust, reproducible, and high-throughput method to determine in vivo targets of RBPs. uvCLAP is fast and does not rely on radioactive labeling of RNA. We investigate binding of 15 RBPs from fly, mouse, and human cells to test the method’s performance and applicability. Multiplexing of signal and control libraries enables straightforward comparison of samples. Experiments for most proteins achieve high enrichment of signal over background. A point mutation and a natural splice isoform that change the RBP subcellular localization dramatically alter target selection without changing the targeted RNA motif, showing that compartmentalization of RBPs can be used as an elegant means to generate RNA target specificity.

Suggested Citation

  • Daniel Maticzka & Ibrahim Avsar Ilik & Tugce Aktas & Rolf Backofen & Asifa Akhtar, 2018. "uvCLAP is a fast and non-radioactive method to identify in vivo targets of RNA-binding proteins," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03575-4
    DOI: 10.1038/s41467-018-03575-4
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    Cited by:

    1. Jorge Vaquero-Garcia & Joseph K. Aicher & San Jewell & Matthew R. Gazzara & Caleb M. Radens & Anupama Jha & Scott S. Norton & Nicholas F. Lahens & Gregory R. Grant & Yoseph Barash, 2023. "RNA splicing analysis using heterogeneous and large RNA-seq datasets," Nature Communications, Nature, vol. 14(1), pages 1-20, December.

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