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Methods for quantifying gene expression 1 and chromatin accessibility 2 in single cells are well established, but single-cell analysis of chromatin regions with specific histone modifications has been technically challenging. In this study, we adapted the CUT&Tag method 3 to scalable nanowell and droplet-based single-cell platforms to profile chromatin landscapes in single cells (scCUT&Tag) from complex tissues and during the differentiation of human embryonic stem cells. We focused on profiling polycomb group (PcG) silenced regions marked by histone H3 Lys27 trimethylation (H3K27me3) in single cells as an orthogonal approach to chromatin accessibility for identifying cell states. We show that scCUT&Tag profiling of H3K27me3 distinguishes cell types in human blood and allows the generation of cell-type-specific PcG landscapes from heterogeneous tissues. Furthermore, we used scCUT&Tag to profile H3K27me3 in a patient with a brain tumor before and after treatment, identifying cell types in the tumor microenvironment and heterogeneity in PcG activity in the primary sample and after treatment. An improved method for single-cell analysis of histone modifications is applied to stem cell differentiation and cancer.

Single-cell analysis has become a powerful approach for the molecular characterization of complex tissues. Methods for quantifying gene expression1 and chromatin accessibility2 of single cells are now well-established, but analysis of chromatin regions with specific histone modifications has been technically challenging. Here, we adapt the recently published CUT&Tag method3 to scalable single-cell platforms to profile chromatin landscapes in single cells (scCUT&Tag) from complex tissues. We focus on profiling Polycomb Group (PcG) silenced regions marked by H3K27 trimethylation (H3K27me3) in single cells as an orthogonal approach to chromatin accessibility for identifying cell states. We show that scCUT&Tag profiling of H3K27me3 distinguishes cell types in human blood and allows the generation of cell-type-specific PcG landscapes from heterogeneous tissues. Furthermore, we use scCUT&Tag to profile H3K27me3 in a brain tumor patient before and after treatment, identifying cell types in the tumor microenvironment and heterogeneity in PcG activity in the primary sample and after treatment. Competing Interest Statement The authors have declared no competing interest. Footnotes * We have prepared a revised manuscript which incorporated biologic and technical replicates of H3K27me3 data and from a second histone mark (K27ac) in PBMCs. We have also provided deeper insight into data quality of the tumor samples.