/scCUT-Tag

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scCUT-Tag

This site provides code and data for the manuscript entitled:

"Single-cell analysis of chromatin silencing programs in development and tumor progression"

Steven J. Wu1,5,, Scott N. Furlan2,8, Anca B. Mihalas3,7, Hatice Kaya-Okur1,6,10, Abdullah H. Feroze7, Samuel N. Emerson7, Ye Zheng4, Kalee Carson2, Patrick J. Cimino3,9, C. Dirk Keene9, Jay F. Sarthy2,8, Raphael Gottardo4, Kami Ahmad1, Steven Henikoff1,6,, & Anoop P. Patel 3,7 1Basic Sciences Division, 2Clinical Research Division, 3Human Biology Division, 4Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA. 5Molecular Engineering & Sciences Institute, University of Washington, Seattle, USA. 6Howard Hughes Medical Institute. 10Altius Institute for Biomedical Sciences, Seattle, USA. Departments of 7Neurological Surgery, 8Pediatrics, and Laboratory Medicine and Pathology9, University of Washington, Seattle, USA. * Contributed equally; **Contributed equally; Correspondence: apatel1@uw.edu, steveh@fredhutch.org

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.

Getting Started

Download fragments files:

Cell lines: https://sfurlan.com/cell_lines/sc_fragfiles/K27me3_h1de.fragments.tsv.gz https://sfurlan.com/cell_lines/sc_fragfiles/K27me3_stdcells.fragments.tsv.gz https://sfurlan.com/cell_lines/sc_fragfiles/K4me2_stdcells.fragments.tsv.gz

PBMC: https://sfurlan.com/pbmc/fragments.tsv.gz (fragments) https://sfurlan.com/pbmc/meta.csv (cell metadata - called 'singlecell.csv' in the script)

GBM: https://sfurlan.com/gbm/UW7R_raw_data/fragments.tsv.gz https://sfurlan.com/gbm/UW7_raw_data/fragments.tsv.gz