Profiling chromatin states using single-cell itChIP-seq

doi:10.1038/s41556-019-0383-5

. 2019 Sep;21(9):1164-1172.

doi: 10.1038/s41556-019-0383-5. Epub 2019 Sep 3.

Profiling chromatin states using single-cell itChIP-seq

Shanshan Ai^#¹, Haiqing Xiong^#^{1

2

3}, Chen C Li¹, Yingjie Luo^{1

2

3}, Qiang Shi⁴, Yaxi Liu¹, Xianhong Yu^{1

2

3}, Cheng Li⁴, Aibin He^{5

6}

Affiliations

¹ Institute of Molecular Medicine, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Peking University, Beijing, China.
² Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
³ Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
⁴ Center for Statistical Science, Center for Bioinformatics, Peking University, Beijing, China.
⁵ Institute of Molecular Medicine, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Peking University, Beijing, China. ahe@pku.edu.cn.
⁶ Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China. ahe@pku.edu.cn.

^# Contributed equally.

PMID: 31481796
DOI: 10.1038/s41556-019-0383-5

Profiling chromatin states using single-cell itChIP-seq

Shanshan Ai et al. Nat Cell Biol. 2019 Sep.

. 2019 Sep;21(9):1164-1172.

doi: 10.1038/s41556-019-0383-5. Epub 2019 Sep 3.

Authors

Shanshan Ai^#¹, Haiqing Xiong^#^{1

2

3}, Chen C Li¹, Yingjie Luo^{1

2

3}, Qiang Shi⁴, Yaxi Liu¹, Xianhong Yu^{1

2

3}, Cheng Li⁴, Aibin He^{5

6}

Affiliations

¹ Institute of Molecular Medicine, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Peking University, Beijing, China.
² Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
³ Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
⁴ Center for Statistical Science, Center for Bioinformatics, Peking University, Beijing, China.
⁵ Institute of Molecular Medicine, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Peking University, Beijing, China. ahe@pku.edu.cn.
⁶ Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China. ahe@pku.edu.cn.

^# Contributed equally.

PMID: 31481796
DOI: 10.1038/s41556-019-0383-5

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.

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References

1. Rivera, C. M. & Ren, B. Mapping human epigenomes. Cell 155, 39–55 (2013). - PubMed - DOI
1. Roh, T.-Y., Ngau, W. C., Cui, K., Landsman, D. & Zhao, K. High-resolution genome-wide mapping of histone modifications. Nat. Biotechnol. 22, 1013–1016 (2004). - PubMed - DOI
1. Kharchenko, P. V., Tolstorukov, M. Y. & Park, P. J. Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat. Biotechnol. 26, 1351–1359 (2008). - PubMed - PMC - DOI
1. Stegle, O., Teichmann, S. A. & Marioni, J. C. Computational and analytical challenges in single-cell transcriptomics. Nat. Rev. Genet. 16, 133–145 (2015). - PubMed - DOI
1. Adli, M. & Bernstein, B. E. Whole-genome chromatin profiling from limited numbers of cells using nano-ChIP-seq. Nat. Protoc. 6, 1656–1668 (2011). - PubMed - PMC - DOI

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[1] Rivera, C. M. & Ren, B. Mapping human epigenomes. Cell 155, 39–55 (2013). - PubMed - DOI

[2] Rivera, C. M. & Ren, B. Mapping human epigenomes. Cell 155, 39–55 (2013). - PubMed - DOI

[3] Roh, T.-Y., Ngau, W. C., Cui, K., Landsman, D. & Zhao, K. High-resolution genome-wide mapping of histone modifications. Nat. Biotechnol. 22, 1013–1016 (2004). - PubMed - DOI

[4] Roh, T.-Y., Ngau, W. C., Cui, K., Landsman, D. & Zhao, K. High-resolution genome-wide mapping of histone modifications. Nat. Biotechnol. 22, 1013–1016 (2004). - PubMed - DOI

[5] Kharchenko, P. V., Tolstorukov, M. Y. & Park, P. J. Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat. Biotechnol. 26, 1351–1359 (2008). - PubMed - PMC - DOI

[6] Kharchenko, P. V., Tolstorukov, M. Y. & Park, P. J. Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat. Biotechnol. 26, 1351–1359 (2008). - PubMed - PMC - DOI

[7] Stegle, O., Teichmann, S. A. & Marioni, J. C. Computational and analytical challenges in single-cell transcriptomics. Nat. Rev. Genet. 16, 133–145 (2015). - PubMed - DOI

[8] Stegle, O., Teichmann, S. A. & Marioni, J. C. Computational and analytical challenges in single-cell transcriptomics. Nat. Rev. Genet. 16, 133–145 (2015). - PubMed - DOI

[9] Adli, M. & Bernstein, B. E. Whole-genome chromatin profiling from limited numbers of cells using nano-ChIP-seq. Nat. Protoc. 6, 1656–1668 (2011). - PubMed - PMC - DOI

[10] Adli, M. & Bernstein, B. E. Whole-genome chromatin profiling from limited numbers of cells using nano-ChIP-seq. Nat. Protoc. 6, 1656–1668 (2011). - PubMed - PMC - DOI

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Profiling chromatin states using single-cell itChIP-seq

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