Published November 25, 2024 | Published
Journal Article Open

ChIP-DIP maps binding of hundreds of proteins to DNA simultaneously and identifies diverse gene regulatory elements

  • 1. ROR icon California Institute of Technology
  • 2. ROR icon University of California, Los Angeles
  • 3. ROR icon University of Southern California
  • 4. ROR icon University of Massachusetts Medical School
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Abstract

Gene expression is controlled by dynamic localization of thousands of regulatory proteins to precise genomic regions. Understanding this cell type-specific process has been a longstanding goal yet remains challenging because DNA–protein mapping methods generally study one protein at a time. Here, to address this, we developed chromatin immunoprecipitation done in parallel (ChIP-DIP) to generate genome-wide maps of hundreds of diverse regulatory proteins in a single experiment. ChIP-DIP produces highly accurate maps within large pools (>160 proteins) for all classes of DNA-associated proteins, including modified histones, chromatin regulators and transcription factors and across multiple conditions simultaneously. First, we used ChIP-DIP to measure temporal chromatin dynamics in primary dendritic cells following LPS stimulation. Next, we explored quantitative combinations of histone modifications that define distinct classes of regulatory elements and characterized their functional activity in human and mouse cell lines. Overall, ChIP-DIP generates context-specific protein localization maps at consortium scale within any molecular biology laboratory and experimental system.

Copyright and License

 2024, The Author(s), under exclusive licence to Springer Nature America, Inc.

Acknowledgement

We thank S. Hiley for editing. We thank I.-M. Strazhnik and A. Koivula for illustrations and formatting the figures. This work was funded by grants from the NIH (R01 HG012216, R01 DA053178, U01 DK127420 to M.G.), the Chan Zuckerberg Initiative Ben Barres Early Career Acceleration Award, the NIH UCLA-Caltech Medical Scientist Training Program (T32GM008042, I.N.G. and B.T.Y.), NCI F30CA278005 (J.K.G.) and the University of Southern California MD/PhD program (J.K.G.). Sequencing was performed at the Millard and Muriel Jacobs Genetics and Genomics facility at Caltech with support from I. Antoshechkin and at the Broad Institute Genomics Platform.

Contributions

These authors contributed equally: Andrew A. Perez, Isabel N. Goronzy.

A.A.P., M.R.B. and M.G. conceived ChIP-DIP; A.A.P. and M.R.B. developed ChIP-DIP; A.A.P., I.N.G. and J.K.G. optimized ChIP-DIP; A.A.P. and I.N.G. generated the data presented in this paper; C.S.L., O.E. and A.B. cultured, collected and treated cells; I.N.G. developed the computational pipeline; B.T.Y. generated the GitHub repository for the pipeline; I.N.G. performed data analysis and visualization; A.A.P., I.N.G. and M.G. generated figures and wrote the paper.

Conflict of Interest

M.G., A.A.P., M.R.B., I.N.G. and J.K.G. are inventors of a submitted patent covering the ChIP-DIP method. The other authors declare no competing interests.

Supplemental Material

Supplementary Information: Supplementary Figs. 1–13, Notes 1–3, Methods and Tables 1–5.

Supplementary Data 1: Antibody ID oligonucleotide sequences.

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Additional details

Created:
February 11, 2025
Modified:
February 11, 2025