Reconstructing Epigenomic Dynamics through a Single-Cell Multi-Epigenome Data Integration Framework

Transcriptional regulation arises from the dynamic and combinatorial actions of multiple regulatory factors on genomic DNA. Although many epigenomic regulators have been identified, the precise order in which these factors accumulate at individual gene loci to activate transcription remains unclear. Here we show a single-cell data integration framework that infers the binding order of multiple chromatin factors at single-cell resolution. Central to this framework is sci-mtChIL-seq, a scalable single-cell method that simultaneously profiles genome-wide binding of RNA polymerase II (RNAPII) and diverse epigenomic regulators. By defining transcriptional states through RNAPII occupancy and integrating multiple sci-mtChIL-seq datasets, we systematically link the combinatorial patterns of transcription factor binding, histone modifications and chromatin remodeling. This framework reveals the temporal coordination among chromatin factors during transcriptional activation, providing a powerful approach to uncover context-dependent epigenomic dynamics and the principles of gene regulation in complex cellular systems. Overall design: Sci-mtChIL-seq for H3K4me1, H3K4me3, H3K9me3, H3K27ac, H3K27me3, H3K36me3, H3.1/3.2, and RNA PolII in SP2 cells and sci-mtChIL-seq for RNA PolII-H3K4me3, RNA PolII-H3K27me3 and RNA PolII-MyoD in embryo and for RNA PolII-H3K4me3, RNA PolII-H3K27me3, RNA PolII-MyoD, RNA PolII-H3K27ac, RNA PolII-Brg1 and RNA PolII-Myog in NIH3T3 cells.