AMAR-seq: Automated Multimodal Sequencing of DNA Methylation,\nChromatin Accessibility, and RNA Expression with Single-Cell Resolution

Parallel\nsingle-cell multimodal sequencing is the most intuitive\nand precise tool for cellular status research. In this study, we propose\nAMAR-seq to automate methylation, chromatin accessibility, and RNA\nexpression coanalysis with single-cell precision. We validated the\naccuracy and robustness of AMAR-seq in comparison with standard single-omics\nmethods. The high gene detection rate and genome coverage of AMAR-seq\nenabled us to establish a genome-wide gene expression regulatory atlas\nand triple-omics landscape with single base resolution and implement\nsingle-cell copy number variation analysis. Applying AMAR-seq to investigate\nthe process of mouse embryonic stem cell differentiation, we revealed\nthe dynamic coupling of the epigenome and transcriptome, which may\ncontribute to unraveling the molecular mechanisms of early embryonic\ndevelopment. Collectively, we propose AMAR-seq for the in-depth and\naccurate establishment of single-cell multiomics regulatory patterns\nin a cost-effective, efficient, and automated manner, paving the way\nfor insightful dissection of complex life processes.