Single-cell analysis of chromatin silencing programs in developmental and tumor progression
Wu, S. J.; Furlan, S. N.; Mihalas, A. B.; Kaya-Okur, H.; Feroze, A. H.; Emerson, S. N.; Zheng, Y.; Carson, K.; Cimino, P. J.; Keene, C. D.; Holland, E. C.; Sarthy, J. F.; Gottardo, R.; Ahmad, K.; Henikoff, S.; Patel, A. P.
Show abstract
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.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Overloading And unpacKing (OAK) - droplet-based combinatorial indexing for ultra-high throughput single-cell multiomic profiling 97%
- Phospho-seq: Integrated, multi-modal profiling of intracellular protein dynamics in single cells 97%
- A human neural crest model reveals the developmental impact of neuroblastoma-associated chromosomal aberrations 97%
Similar papers in this journal
- Scalable co-sequencing of RNA and DNA from individual nuclei 97%
- Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single cell resolution 96%
- ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells 96%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.