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 sequencing on a chip 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, implement single-cell copy number variation analysis, and construct a single-gene, single-base resolution gene expression, DNA methylation, and chromatin accessibility landscape. 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 the unravelling of the molecular mechanisms of early embryonic development. Collectively, these results illustrate that the employment of AMAR-seq can deeply and accurately establish single-cell multi-omics regulatory networks in a single-cell context in a cost-efficient and automated manner, which paves the way for incisive dissection of complex life procedures.