AMAR-seq: Automated Multimodal Sequencing of DNA Methylation, Chromatin Accessibility, and RNA Expression with Single-Cell Resolution
Parallel single-cell multimodal sequencing is the most intuitive and precise tool for cellular status research. In this study, we propose AMAR-seq to automate methylation, chromatin accessibility, and RNA expression coanalysis with single-cell precision. We validated the accuracy and robustness of AMAR-seq in comparison with standard single-omics methods. The high gene detection rate and genome coverage of AMAR-seq enabled us to establish a genome-wide gene expression regulatory atlas and triple-omics landscape with single base resolution and implement single-cell copy number variation analysis. Applying AMAR-seq to investigate the process of mouse embryonic stem cell differentiation, we revealed the dynamic coupling of the epigenome and transcriptome, which may contribute to unraveling the molecular mechanisms of early embryonic development. Collectively, we propose AMAR-seq for the in-depth and accurate establishment of single-cell multiomics regulatory patterns in a cost-effective, efficient, and automated manner, paving the way for insightful dissection of complex life processes.
Authors
- Shaowei Jiang (ORCID: https://orcid.org/0000-0003-1260-4699)
- Jia Tao Song (ORCID: https://orcid.org/0000-0002-0122-8360)
- Xiaoping Yang (ORCID: https://orcid.org/0000-0003-1952-7227)
- Qiuyue Chen (ORCID: https://orcid.org/0000-0002-3304-8321)
- Chaoyong James Yang (ORCID: https://orcid.org/0000-0002-2374-5342)
- Zhi Zhu (ORCID: https://orcid.org/0000-0002-3287-4920)
- Shichao Lin (ORCID: https://orcid.org/0000-0003-3423-6225)
- Xi Zeng (ORCID: https://orcid.org/0000-0002-5355-0773)
- Zhixing Zhong
- Jin Li (ORCID: https://orcid.org/0000-0002-7957-1476)
- Huimin Zhang (ORCID: https://orcid.org/0000-0002-7343-5641)
- Xin Lin (ORCID: https://orcid.org/0000-0002-2356-2001)
- Mengwu Mo
Institutions
- Shanghai Jiao Tong University (CN)
- Xiamen University (CN)
- Shanghai Normal University (CN)
- Fudan University (CN)
- XinHua Hospital (CN)
- Zhongshan Hospital (CN)
- Tan Kah Kee Innovation Laboratory (CN)
- Collaborative Innovation Center of Chemistry for Energy Materials (CN)
- State Key Laboratory of Genetic Engineering
Publication Details
- Journal
- Analytical Chemistry
- Published
- 2024-09-09
- DOI
- https://doi.org/10.1021/acs.analchem.4c02765
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.23
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Fundamental Research Funds for the Central Universities