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ChIATAC is an efficient strategy for multi-omics mapping of 3D epigenomes from low-cell inputs

Author

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  • Haoxi Chai

    (The Jackson Laboratory for Genomic Medicine)

  • Harianto Tjong

    (The Jackson Laboratory for Genomic Medicine)

  • Peng Li

    (National Institutes of Health)

  • Wei Liao

    (National Institutes of Health)

  • Ping Wang

    (The Jackson Laboratory for Genomic Medicine)

  • Chee Hong Wong

    (The Jackson Laboratory for Genomic Medicine)

  • Chew Yee Ngan

    (The Jackson Laboratory for Genomic Medicine)

  • Warren J. Leonard

    (National Institutes of Health)

  • Chia-Lin Wei

    (The Jackson Laboratory for Genomic Medicine)

  • Yijun Ruan

    (The Jackson Laboratory for Genomic Medicine
    Zhejiang University)

Abstract

Connecting genes to their cis-regulatory elements has been enabled by genome-wide mapping of chromatin interactions using proximity ligation in ChIA-PET, Hi-C, and their derivatives. However, these methods require millions of input cells for high-quality data and thus are unsuitable for many studies when only limited cells are available. Conversely, epigenomic profiling via transposase digestion in ATAC-seq requires only hundreds to thousands of cells to robustly map open chromatin associated with transcription activity, but it cannot directly connect active genes to their distal enhancers. Here, we combine proximity ligation in ChIA-PET and transposase accessibility in ATAC-seq into ChIATAC to efficiently map interactions between open chromatin loci in low numbers of input cells. We validate ChIATAC in Drosophila cells and optimize it for mapping 3D epigenomes in human cells robustly. Applying ChIATAC to primary human T cells, we reveal mechanisms that topologically regulate transcriptional programs during T cell activation.

Suggested Citation

  • Haoxi Chai & Harianto Tjong & Peng Li & Wei Liao & Ping Wang & Chee Hong Wong & Chew Yee Ngan & Warren J. Leonard & Chia-Lin Wei & Yijun Ruan, 2023. "ChIATAC is an efficient strategy for multi-omics mapping of 3D epigenomes from low-cell inputs," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-35879-5
    DOI: 10.1038/s41467-023-35879-5
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