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Systematic identification of post-transcriptional regulatory modules

Author

Listed:
  • Matvei Khoroshkin

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Andrey Buyan

    (Russian Academy of Sciences)

  • Martin Dodel

    (Queen Mary University of London
    University of Oxford)

  • Albertas Navickas

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Johnny Yu

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Fathima Trejo

    (University of San Francisco)

  • Anthony Doty

    (University of San Francisco)

  • Rithvik Baratam

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Shaopu Zhou

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Sean B. Lee

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Tanvi Joshi

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Kristle Garcia

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Benedict Choi

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Sohit Miglani

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Vishvak Subramanyam

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Hailey Modi

    (Gladstone Institute of Neurological Disease
    Gladstone Institute of Data Science and Biotechnology
    University of California San Francisco)

  • Christopher Carpenter

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • Daniel Markett

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

  • M. Ryan Corces

    (Gladstone Institute of Neurological Disease
    Gladstone Institute of Data Science and Biotechnology
    University of California San Francisco)

  • Faraz K. Mardakheh

    (Queen Mary University of London
    University of Oxford)

  • Ivan V. Kulakovskiy

    (Russian Academy of Sciences
    Russian Academy of Sciences)

  • Hani Goodarzi

    (University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco
    University of California, San Francisco)

Abstract

In our cells, a limited number of RNA binding proteins (RBPs) are responsible for all aspects of RNA metabolism across the entire transcriptome. To accomplish this, RBPs form regulatory units that act on specific target regulons. However, the landscape of RBP combinatorial interactions remains poorly explored. Here, we perform a systematic annotation of RBP combinatorial interactions via multimodal data integration. We build a large-scale map of RBP protein neighborhoods by generating in vivo proximity-dependent biotinylation datasets of 50 human RBPs. In parallel, we use CRISPR interference with single-cell readout to capture transcriptomic changes upon RBP knockdowns. By combining these physical and functional interaction readouts, along with the atlas of RBP mRNA targets from eCLIP assays, we generate an integrated map of functional RBP interactions. We then use this map to match RBPs to their context-specific functions and validate the predicted functions biochemically for four RBPs. This study provides a detailed map of RBP interactions and deconvolves them into distinct regulatory modules with annotated functions and target regulons. This multimodal and integrative framework provides a principled approach for studying post-transcriptional regulatory processes and enriches our understanding of their underlying mechanisms.

Suggested Citation

  • Matvei Khoroshkin & Andrey Buyan & Martin Dodel & Albertas Navickas & Johnny Yu & Fathima Trejo & Anthony Doty & Rithvik Baratam & Shaopu Zhou & Sean B. Lee & Tanvi Joshi & Kristle Garcia & Benedict C, 2024. "Systematic identification of post-transcriptional regulatory modules," Nature Communications, Nature, vol. 15(1), pages 1-21, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-52215-7
    DOI: 10.1038/s41467-024-52215-7
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