Cited by 483Genomics and Chromatin DynamicsSingle-cell and spatial transcriptomicsEpigenetics and DNA Methylation

The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index; 3 of the 22 sources its claims cite were checked for support.

Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues

Open access
Bartosovic, Marek, Kabbe, Mukund, Castelo-Branco, Gonçalo·2021·Nature Biotechnology

Abstract

In contrast to single-cell approaches for measuring gene expression and DNA accessibility, single-cell methods for analyzing histone modifications are limited by low sensitivity and throughput. Here, we combine the CUT&Tag technology, developed to measure bulk histone modifications, with droplet-based single-cell library preparation to produce high-quality single-cell data on chromatin modifications. We apply single-cell CUT&Tag (scCUT&Tag) to tens of thousands of cells of the mouse central nervous system and probe histone modifications characteristic of active promoters, enhancers and gene bodies (H3K4me3, H3K27ac and H3K36me3) and inactive regions (H3K27me3). These scCUT&Tag profiles were sufficient to determine cell identity and deconvolute regulatory principles such as promoter bivalency, spreading of H3K4me3 and promoter–enhancer connectivity. We also used scCUT&Tag to investigate the single-cell chromatin occupancy of transcription factor OLIG2 and the cohesin complex component RAD21. Our results indicate that analysis of histone modifications and transcription factor occupancy at single-cell resolution provides unique insights into epigenomic landscapes in the central nervous system. An improved method for single-cell analysis of histone modifications is applied to the mouse brain.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

The paper develops single-cell CUT&Tag (scCUT&Tag) by coupling CUT&Tag with droplet-based 10x Genomics scATAC-seq, enabling high-throughput profiling of histone modifications and transcription factor occupancy in complex tissues. Applied to tens of thousands of mouse CNS cells, it resolves major brain cell types and reveals regulatory features such as promoter bivalency, H3K4me3 spreading, and enhancer-promoter connectivity.

Key findings

  • scCUT&Tag generated profiles for 47,340 single cells across histone modifications, with median unique fragments per cell ranging from 98 (H3K36me3) to 453 (H3K27ac); 39.4%–85.6% of fragments fell within narrow peak regions.
  • In a three-cell-line mixture, H3K27me3 scCUT&Tag yielded 4,872 and 3,873 single cells with 597 and 568 unique fragments per cell, respectively, and separated mESC, NIH-3T3, and Oli-neu populations.
  • In mouse brain, scCUT&Tag identified major CNS populations including mature oligodendrocytes, astrocytes, OECs, vascular cells, OPC/COP/NFOL, neurons, and microglia; H3K4me3 breadth increased during oligodendrocyte differentiation, and H3K27me3 was enriched in oligodendrocytes, microglia, and a subset of neurons.
  • TF scCUT&Tag recovered Olig2 and Rad21 binding with median 48 and 240 unique reads per cell, respectively; ABC modeling predicted ~200,000 enhancer-promoter loops, refined to 61,000 with H3K4me3 and ~5,000 with Rad21 on both sides, and Cicero found 14,322 correlated features with score >0.2 in mOLs.

Methods

  • Design: CUT&Tag was combined with droplet-based 10x Genomics single-cell ATAC-seq library preparation; nuclei from mouse CNS or cell lines were barcoded after antibody-directed tagmentation.
  • Sample/data: Mouse Sox10:Cre/RCE brains at P15 and P21–P25 were FACS-sorted into GFP+ and GFP− cells; antibodies targeted H3K4me3, H3K27ac, H3K36me3, H3K27me3, Olig2, and Rad21.
  • Analysis: Cell-feature matrices used 5-kb or 50-kb bins; clustering used LSI, UMAP, SNN, and Leiden in Seurat/Signac; integration used CCA with scRNA-seq; enhancer-promoter predictions used the ABC model and Cicero, with HiChIP validation.

Limitations

  • The paper states that scCUT&Tag currently distinguishes major cell types but fails to uncover subpopulation heterogeneity in an unsupervised manner; oligodendrocyte heterogeneity was only revealed at H3K4me3 level after integration with scRNA-seq.
  • The paper states that TF scCUT&Tag data are sparser than histone scCUT&Tag, and Rad21 binding could not distinguish vascular cells and OPCs, the smallest populations sharing features with larger populations.
  • The paper states that improving unique fragments per cell and introducing multi-omic approaches, such as simultaneous scCUT&Tag and RNA-seq from the same cell, would further enhance applications; evident from the text, TF profiles required annotation assumptions based on correlation with H3K4me3/H3K27ac rather than direct marker-based clustering.

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Integrity signals

Registry

Crossref · 10.1038/s41587-021-00869-9

Cites

56 of 56 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

72 Own result · 11 Own interpretation · 10 Not checked yet · 4 Own method · 4 No basis given · 1 Supported · 1 Partly supported · accuracy not yet measured

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Show all 64 claims

  • It may state two separate claims as one. 35
  • Probably not a substantial claim. 10
39 of 39
  • The authors state this as an assumption.

    Olig2 and Rad21 binding in specific cell types correlates with enhancer and promoter activity.

    “we based cluster annotation on the assumption that Olig2/Rad21 binding in specific cell types is correlated with enhancer/promoter activity.”
  • The paper relies on this without support.

    The number of unique reads per cell reflects the absolute amount of a histone modification in single cells.

    “We used the number of unique reads per cell as a proxy for absolute amount of the histone modification in single cells.”
2 of 2

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Metadata

Authors
Bartosovic, M., Kabbe, M., & Castelo-Branco, G.
Affiliations
Karolinska Institutet (SE)
Venue
Nature Biotechnology
Published
2021-04-12
Volume
39
Issue
7
Pages
825-835
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
OpenAlex
W3156830838
Cited by
483
References
54
Citations by year
2026: 96 · 2025: 94 · 2024: 106 · 2023: 93 · 2022: 63 · 2021: 30
FWCI
23.47
Type
journal article
Language
en
Open access
Locations
  • Nature Biotechnology (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
Keywords
histone modifications, chromatin accessibility, transcription factor occupancy, Olig2, RAD21, cohesin, H3K4me3, H3K27ac, H3K36me3, H3K27me3, central nervous system, mice, epigenomics
MeSH terms
Animals, Brain, Gene Expression Regulation, Histones, Humans, Transcription Factors, Cluster Analysis, Mice, Single-Cell Analysis

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