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Updated: Jun 13, 2025
Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
Published on: March 12, 2021
AMAR-seq: Automated Multimodal Sequencing of DNA Methylation, Chromatin Accessibility, and RNA Expression with
Xi Zeng1, Xiaoping Yang1, Zhixing Zhong1
1The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, the Key Laboratory of Chemical Biology of Fujian Province, State Key Laboratory of Physical of Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, Department of Chemical Engineering, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence, Xiamen University, Xiamen 361005, China.
We developed AMAR-seq, an automated method for single-cell multiomics analysis, integrating methylation, chromatin accessibility, and RNA expression. This powerful tool reveals dynamic epigenetic and transcriptomic coupling during cell differentiation.
Area of Science:
- Epigenetics
- Genomics
- Cell Biology
Background:
- Single-cell multimodal sequencing offers precise cellular status insights.
- Current methods often lack comprehensive integration of multiple omics data types at single-cell resolution.
Purpose of the Study:
- To introduce AMAR-seq, an automated platform for simultaneous analysis of DNA methylation, chromatin accessibility, and RNA expression at single-cell resolution.
- To validate AMAR-seq's accuracy and robustness against established single-omics techniques.
Main Methods:
- AMAR-seq integrates methylation, chromatin accessibility, and RNA expression profiling in a single workflow.
- Method validation involved comparison with standard single-omics approaches.
- Application to mouse embryonic stem cell differentiation.
Main Results:
- AMAR-seq demonstrated high gene detection rates and genome coverage.
- Established a genome-wide gene expression regulatory atlas and triple-omics landscape with single-base resolution.
- Enabled single-cell copy number variation analysis.
- Revealed dynamic epigenome-transcriptome coupling during mouse embryonic stem cell differentiation.
Conclusions:
- AMAR-seq provides a cost-effective, efficient, and automated solution for single-cell multiomics analysis.
- Facilitates in-depth establishment of regulatory patterns and dissection of complex biological processes like early embryonic development.
