Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin
Name
nihms-1632906.pdf
Description
Accepted version
Size
3.05 MB
Format
Adobe PDF
Checksum (MD5)
589edd8464c9fd2d3215c6e08720d81c
Author(s)
Ma, Sai
Zhang, Bing
LaFave, Lindsay M
Earl, Andrew S
Chiang, Zachary
Hu, Yan
Ding, Jiarui
Brack, Alison
Kartha, Vinay K
Tay, Tristan
Date Issued
2020
Journal
Cell
Publisher
Elsevier BV
Citation
Ma, Sai, Zhang, Bing, LaFave, Lindsay M, Earl, Andrew S, Chiang, Zachary et al. 2020. "Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin." Cell, 183 (4).
Version
Author's final manuscript
Abstract
© 2020 Elsevier Inc. Cell differentiation and function are regulated across multiple layers of gene regulation, including modulation of gene expression by changes in chromatin accessibility. However, differentiation is an asynchronous process precluding a temporal understanding of regulatory events leading to cell fate commitment. Here we developed simultaneous high-throughput ATAC and RNA expression with sequencing (SHARE-seq), a highly scalable approach for measurement of chromatin accessibility and gene expression in the same single cell, applicable to different tissues. Using 34,774 joint profiles from mouse skin, we develop a computational strategy to identify cis-regulatory interactions and define domains of regulatory chromatin (DORCs) that significantly overlap with super-enhancers. During lineage commitment, chromatin accessibility at DORCs precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for lineage commitment. We computationally infer chromatin potential as a quantitative measure of chromatin lineage-priming and use it to predict cell fate outcomes. SHARE-seq is an extensible platform to study regulatory circuitry across diverse cells in tissues.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Koch Institute for Integrative Cancer Research at MIT
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/J.CELL.2020.09.056
