The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Profiling chromatin states using single-cell itChIP-seq
Abstract
Single-cell measurement of chromatin states, including histone modifications and non-histone protein binding, remains challenging. Here, we present a low-cost, efficient, simultaneous indexing and tagmentation-based ChIP-seq (itChIP-seq) method, compatible with both low cellular input and single cells for profiling chromatin states. itChIP combines chromatin opening, simultaneous cellular indexing and chromatin tagmentation within a single tube, enabling the processing of samples from tens of single cells to, more commonly, thousands of single cells per assay. We demonstrate that single-cell itChIP-seq (sc-itChIP-seq) yields ~9,000 unique reads per cell. Using sc-itChIP-seq to profile H3K27ac, we sufficiently capture the earliest epigenetic priming event during the cell fate transition from naive to primed pluripotency, and reveal the basis for cell-type specific enhancer usage during the differentiation of bipotent cardiac progenitor cells into endothelial cells and cardiomyocytes. Our results demonstrate that itChIP is a widely applicable technology for single-cell chromatin profiling of epigenetically heterogeneous cell populations in many biological processes.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“However, for highly complex adult organs such as the brain, this single-cell characterization has not been achieved.”
From Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues (2021) · cites this paper as [8]
Citations
Cites
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration
Thorvaldsdottir, H., Robinson, J. T., & Mesirov, J. P. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs017 · Cited by 9,049
deepTools2: a next generation web server for deep-sequencing data analysis
Ramírez, F., Ryan, D. P., Grüning, B., Bhardwaj, V., Kilpert, F., Richter, A. S., Heyne, S., Dündar, F., & Manke, T. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw257 · Cited by 8,096
Spatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055
A robust and high-throughput Cre reporting and characterization system for the whole mouse brain
Madisen, L., Zwingman, T. A., Sunkin, S. M., Oh, S. W., Zariwala, H. A., Gu, H., Ng, L. L., Palmiter, R. D., Hawrylycz, M. J., Jones, A. R., et al. (2010) · Nature Neuroscience · doi:10.1038/nn.2467 · Cited by 6,907
Reversed graph embedding resolves complex single-cell trajectories
Qiu, X., Mao, Q., Tang, Y., Wang, L., Chawla, R., Pliner, H. A., & Trapnell, C. (2017) · Nature Methods · doi:10.1038/nmeth.4402 · Cited by 5,070
The ground state of embryonic stem cell self-renewal
Ying, Q.-L., Wray, J., Nichols, J., Batlle-Morera, L., Doble, B., Woodgett, J., Cohen, P., & Smith, A. (2008) · Nature · doi:10.1038/nature06968 · Cited by 3,442
ATAC-seq: a method for assaying chromatin accessibility genome-wide
Buenrostro, J. D., Wu, B., Chang, H. Y., & Greenleaf, W. J. (2015) · Current Protocols in Molecular Biology · doi:10.1002/0471142727.mb2129s109 · Cited by 3,289
Single-cell chromatin accessibility reveals principles of regulatory variation
Buenrostro, J. D., Wu, B., Litzenburger, U. M., Ruff, D., Gonzales, M. L., Snyder, M. P., Chang, H. Y., & Greenleaf, W. J. (2015) · Nature · doi:10.1038/nature14590 · Cited by 2,308
Cited by
Sorted by citations
Single-cell chromatin state analysis with Signac
Stuart, T., Srivastava, A., Madad, S., Lareau, C. A., & Satija, R. (2021) · Nature Methods · doi:10.1038/s41592-021-01282-5 · Cited by 1,769
Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues
Bartosovic, M., Kabbe, M., & Castelo-Branco, G. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00869-9 · Cited by 483
Efficient low-cost chromatin profiling with CUT&Tag
Kaya-Okur, H. S., Janssens, D. H., Henikoff, J. G., Ahmad, K., & Henikoff, S. (2020) · Nature Protocols · doi:10.1038/s41596-020-0373-x · Cited by 425
Joint profiling of histone modifications and transcriptome in single cells from mouse brain
Zhu, C., Zhang, Y., Li, Y. E., Lucero, J., Behrens, M. M., & Ren, B. (2021) · Nature Methods · doi:10.1038/s41592-021-01060-3 · Cited by 301
Methods for ChIP-seq analysis: A practical workflow and advanced applications
Nakato, R., & Sakata, T. (2021) · Methods · doi:10.1016/j.ymeth.2020.03.005 · Cited by 267
Metadata
- Authors
- Ai, S., Xiong, H., Li, C. C., Luo, Y., Shi, Q., Liu, Y., Yu, X., Li, C., & He, A.
- Affiliations
- Peking University (CN)
- Corresponding author
- He, Aibin
- Venue
- Nature Cell Biology
- Published
- 2019-09
- Volume
- 21
- Issue
- 9
- Pages
- 1164-1172
- ISSN
- 1465-7392 (ISSN-L)
- 1476-4679
- OpenAlex
- W2972263821
- Cited by
- 140
- References
- 48
- Citations by year
- 2026: 7 · 2025: 15 · 2024: 12 · 2023: 23 · 2022: 23 · 2021: 33 · 2020: 27
- FWCI
- 6.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature Cell Biology (publishedVersion)
- PubMed (publishedVersion)
- 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, H3K27ac, epigenetic priming, cardiac progenitor cells, endothelial differentiation, cardiomyocyte differentiation, epigenetic heterogeneity
- MeSH terms
- Animals, Binding Sites, Chromatin, Histones, Mice, Transgenic, Protein Processing, Post-Translational, Sequence Analysis, DNA, Endothelial Cells, Chromatin Immunoprecipitation, Epigenomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
