Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin

Overview

Journal Cell

Publisher Cell Press

Specialty Cell Biology

Date 2020 Oct 25

PMID 33098772

Citations 433

Authors

Sai Ma

Bing Zhang

Lindsay M LaFave

Andrew S Earl

Zachary Chiang

Yan Hu

Jiarui Ding

Alison Brack

Vinay K Kartha

Tristan Tay

Travis Law

Caleb Lareau

Ya-Chieh Hsu

Aviv Regev

Jason D Buenrostro

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

Single-nucleus multiomics reveals the gene regulatory networks underlying sex determination of murine primordial germ cells.

Alexander A, Rodriguez K, Chen Y, Amato C, Estermann M, Nicol B Elife. 2025; 13.

PMID: 40063068 PMC: 11893106. DOI: 10.7554/eLife.96591.

From morphology to single-cell molecules: high-resolution 3D histology in biomedicine.

Xu X, Su J, Zhu R, Li K, Zhao X, Fan J Mol Cancer. 2025; 24(1):63.

PMID: 40033282 PMC: 11874780. DOI: 10.1186/s12943-025-02240-x.

Generalization of the sci-L3 method to achieve high-throughput linear amplification for replication template strand sequencing, genome conformation capture, and the joint profiling of RNA and chromatin accessibility.

Chovanec P, Yin Y Nucleic Acids Res. 2025; 53(4).

PMID: 39997216 PMC: 11851118. DOI: 10.1093/nar/gkaf101.

Multiomic single-cell profiling identifies critical regulators of postnatal brain.

Clarence T, Bendl J, Cao X, Wang X, Zheng S, Hoffman G Nat Genet. 2025; 57(3):591-603.

PMID: 39962241 DOI: 10.1038/s41588-025-02083-8.

Leveraging prior knowledge to infer gene regulatory networks from single-cell RNA-sequencing data.

Stock M, Losert C, Zambon M, Popp N, Lubatti G, Hormanseder E Mol Syst Biol. 2025; 21(3):214-230.

PMID: 39939367 PMC: 11876610. DOI: 10.1038/s44320-025-00088-3.

References

Pliner H, Packer J, McFaline-Figueroa J, Cusanovich D, Daza R, Aghamirzaie D . Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data. Mol Cell. 2018; 71(5):858-871.e8. PMC: 6582963. DOI: 10.1016/j.molcel.2018.06.044. View

Mumbach M, Satpathy A, Boyle E, Dai C, Gowen B, Cho S . Enhancer connectome in primary human cells identifies target genes of disease-associated DNA elements. Nat Genet. 2017; 49(11):1602-1612. PMC: 5805393. DOI: 10.1038/ng.3963. View

Larsson A, Johnsson P, Hagemann-Jensen M, Hartmanis L, Faridani O, Reinius B . Genomic encoding of transcriptional burst kinetics. Nature. 2019; 565(7738):251-254. PMC: 7610481. DOI: 10.1038/s41586-018-0836-1. View

Zhu C, Yu M, Huang H, Juric I, Abnousi A, Hu R . An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome. Nat Struct Mol Biol. 2019; 26(11):1063-1070. PMC: 7231560. DOI: 10.1038/s41594-019-0323-x. View

Novershtern N, Subramanian A, Lawton L, Mak R, Nicholas Haining W, McConkey M . Densely interconnected transcriptional circuits control cell states in human hematopoiesis. Cell. 2011; 144(2):296-309. PMC: 3049864. DOI: 10.1016/j.cell.2011.01.004. View

Heinz S, Benner C, Spann N, Bertolino E, Lin Y, Laslo P . Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010; 38(4):576-89. PMC: 2898526. DOI: 10.1016/j.molcel.2010.05.004. View

Gonzalez A, Setty M, Leslie C . Early enhancer establishment and regulatory locus complexity shape transcriptional programs in hematopoietic differentiation. Nat Genet. 2015; 47(11):1249-59. PMC: 4626279. DOI: 10.1038/ng.3402. View

Fan X, Wang D, Burgmaier J, Teng Y, Romano R, Sinha S . Single Cell and Open Chromatin Analysis Reveals Molecular Origin of Epidermal Cells of the Skin. Dev Cell. 2018; 47(1):133. DOI: 10.1016/j.devcel.2018.09.019. View

Gonzalez-Blas C, Minnoye L, Papasokrati D, Aibar S, Hulselmans G, Christiaens V . cisTopic: cis-regulatory topic modeling on single-cell ATAC-seq data. Nat Methods. 2019; 16(5):397-400. PMC: 6517279. DOI: 10.1038/s41592-019-0367-1. View

10.

Merrill B, Gat U, Dasgupta R, Fuchs E . Tcf3 and Lef1 regulate lineage differentiation of multipotent stem cells in skin. Genes Dev. 2001; 15(13):1688-705. PMC: 312726. DOI: 10.1101/gad.891401. View

11.

Rusk N . Multi-omics single-cell analysis. Nat Methods. 2019; 16(8):679. DOI: 10.1038/s41592-019-0519-3. View

12.

Liao Y, Smyth G, Shi W . featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2013; 30(7):923-30. DOI: 10.1093/bioinformatics/btt656. View

13.

La Manno G, Soldatov R, Zeisel A, Braun E, Hochgerner H, Petukhov V . RNA velocity of single cells. Nature. 2018; 560(7719):494-498. PMC: 6130801. DOI: 10.1038/s41586-018-0414-6. View

14.

Cao Y, Chen Z, Chen X, Ai D, Chen G, McDermott J . Accurate loop calling for 3D genomic data with cLoops. Bioinformatics. 2019; 36(3):666-675. DOI: 10.1093/bioinformatics/btz651. View

15.

Mezger A, Klemm S, Mann I, Brower K, Mir A, Bostick M . High-throughput chromatin accessibility profiling at single-cell resolution. Nat Commun. 2018; 9(1):3647. PMC: 6128862. DOI: 10.1038/s41467-018-05887-x. View

16.

Hsu Y, Li L, Fuchs E . Emerging interactions between skin stem cells and their niches. Nat Med. 2014; 20(8):847-56. PMC: 4358898. DOI: 10.1038/nm.3643. View

17.

Joost S, Annusver K, Jacob T, Sun X, Dalessandri T, Sivan U . The Molecular Anatomy of Mouse Skin during Hair Growth and Rest. Cell Stem Cell. 2020; 26(3):441-457.e7. DOI: 10.1016/j.stem.2020.01.012. View

18.

Salzer M, Lafzi A, Berenguer-Llergo A, Youssif C, Castellanos A, Solanas G . Identity Noise and Adipogenic Traits Characterize Dermal Fibroblast Aging. Cell. 2018; 175(6):1575-1590.e22. DOI: 10.1016/j.cell.2018.10.012. View

19.

Yang H, Adam R, Ge Y, Hua Z, Fuchs E . Epithelial-Mesenchymal Micro-niches Govern Stem Cell Lineage Choices. Cell. 2017; 169(3):483-496.e13. PMC: 5510744. DOI: 10.1016/j.cell.2017.03.038. View

20.

Saunders A, Macosko E, Wysoker A, Goldman M, Krienen F, de Rivera H . Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain. Cell. 2018; 174(4):1015-1030.e16. PMC: 6447408. DOI: 10.1016/j.cell.2018.07.028. View