PRJNA669138
Iterative Epigenomic Analyses in the Same Single Cell
Gene expression in individual cells is epigenetically regulated by DNA modifications, histone modifications, transcription factors and other DNA-binding proteins. It has been shown that multiple histone modifications can predict gene expression and reflect future responses of bulk cells to extracellular cues. However, the predictive ability of epigenomic analysis is still limited for mechanistic research at a single cell level. To overcome this limitation, it is useful to acquire reliable signals from multiple epigenetic marks in the same single cell. Here, we propose a new approach for analysis of several components of the epigenome in the same single cell. The new method allows reanalysis of the same single cell. We found that reanalysis of the same single cell is feasible, and provides confirmation of the signals and allows application of statistical analysis to identify reliable signals using data sets generated only from the single cell. Reanalysis of the same single cell is also useful to acquire multiple-epigenetic marks from the same single cells. The method can acquire at least 5 epigenetic marks, H3K27ac, H3K27me3, mediator complex subunit 1, a DNA modification and a DNA interacting protein. We predicted active signaling pathways in K562 single cells using the data. We confirmed that the prediction results showed a strong correlation with actual active signaling pathways shown by RNA-seq results. These results suggest that the new approach provides mechanistic insights for cellular phenotypes through multi-layered epigenome analysis in the same single cells.