GEO series

Single-molecule, single-cell profiling of linked chromatin states [Single_cell_CoCUT&Tag]

GSE327821 Homo sapiens (human) Single-cell RNA-seq 200 samples Submitted 2026/04/30 Platform GPL34295

At a glance

Single-cell RNA-seq · human · 200 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 200 samples: 200 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.

Summary (written by the submitters)

Genomic methods for profiling multiple chromatin features face tradeoffs between specificity, sensitivity, and the ability to measure chromatin co-occupancy. As a result, context-dependent interactions between chromatin proteins remain difficult to resolve in rare cell types and primary tissues. Here, we present CoCUT&Tag, which uses synthetic antigen-peptide repeats paired with nanobodies to amplify Tn5 transposase targeting and directly measure co-occupancy of two chromatin features in single cells.

Read the full summary ↓

We applied CoCUT&Tag to test the model that bivalent chromatin, marked by the coexistence of H3K27me3 and H3K4 methylation, preserves stem-cell multipotency by keeping developmental genes poised for future activation. Instead, we find that during human hematopoiesis, stem cells are defined by a more active chromatin landscape, whereas lineage-restricted populations contain more bivalent genes. Bivalent and unmarked genes are activated with similar timing, but bivalent genes achieve higher expression, are associated with more numerous and stronger enhancers, and are preferentially derepressed following BMI1 loss. Our study shows that bivalent chromatin increases enhancer demand to enable high-amplitude gene activation, demonstrating that CoCUT&Tag can resolve longstanding questions about combinatorial chromatin regulation.

This dataset

Open GSE327821 in finder → Find more human ChIP / ATAC / CUT&Tag datasets →

Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE327821_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1452847 and SRA study SRP691388. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

200 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 200 sample titles: 200 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

GSM9666540 Single-cell CoCUT&Tag for H3K27me3 (Abcam ab6002) (S1) in peripheral blood mononuclear cells
GSM9666541 Single-cell CoCUT&Tag for H3K4me3 (Active Motif 39159) (S1) in peripheral blood mononuclear cells
GSM9666542 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K4me3 and H3K27me3 (S1) in peripheral blood mononuclear cells
GSM9666543 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K4me3 and H3K27me3 (S1) in peripheral blood mononuclear cells
GSM9666544 Single-cell CoCUT&Tag for H3K27me3 (Abcam ab6002) (S2) in peripheral blood mononuclear cells
GSM9666545 Single-cell CoCUT&Tag for H3K4me3 (Active Motif 39159) (S2) in peripheral blood mononuclear cells
GSM9666546 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K4me3 and H3K27me3 (S2) in peripheral blood mononuclear cells
GSM9666547 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K4me3 and H3K27me3 (S2) in peripheral blood mononuclear cells
GSM9666548 Single-cell CoCUT&Tag for H3K27me3 (Abcam ab6002) (S3) in peripheral blood mononuclear cells
GSM9666549 Single-cell CoCUT&Tag for H3K4me3 (Active Motif 39159) (S3) in peripheral blood mononuclear cells
GSM9666550 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K4me3 and H3K27me3 (S3) in peripheral blood mononuclear cells
GSM9666551 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K4me3 and H3K27me3 (S3) in peripheral blood mononuclear cells
GSM9666552 Single-cell CoCUT&Tag for H3K27me3 (Diagenode C15200181) (S4) in peripheral blood mononuclear cells
GSM9666553 Single-cell CoCUT&Tag for H3K4me3 (Active Motif 39159) (S4) in peripheral blood mononuclear cells
GSM9666554 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K4me3 and H3K27me3 (S4) in peripheral blood mononuclear cells
GSM9666555 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K4me3 and H3K27me3 (S4) in peripheral blood mononuclear cells
GSM9666556 Single-cell CoCUT&Tag for H3K27me3 (Diagenode C15200181) (S5) in peripheral blood mononuclear cells
GSM9666557 Single-cell CoCUT&Tag for H3K4me3 (Active Motif 39159) (S5) in peripheral blood mononuclear cells
GSM9666558 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K4me3 and H3K27me3 (S5) in peripheral blood mononuclear cells
GSM9666559 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K4me3 and H3K27me3 (S5) in peripheral blood mononuclear cells
GSM9666560 Single-cell CoCUT&Tag for H3K27me3 (Diagenode C15200181) (S6) in peripheral blood mononuclear cells
GSM9666561 Single-cell CoCUT&Tag for H3K4me3 (Active Motif 39159) (S6) in peripheral blood mononuclear cells
GSM9666562 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K4me3 and H3K27me3 (S6) in peripheral blood mononuclear cells
GSM9666563 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K4me3 and H3K27me3 (S6) in peripheral blood mononuclear cells
GSM9666564 Single-cell CoCUT&Tag for H3K27me3 (BPS Bioscience 25243) (S7) in peripheral blood mononuclear cells
GSM9666565 Single-cell CoCUT&Tag for H3K4me3 (Active Motif 39159) (S7) in peripheral blood mononuclear cells
GSM9666566 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K4me3 and H3K27me3 (S7) in peripheral blood mononuclear cells
GSM9666567 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K4me3 and H3K27me3 (S7) in peripheral blood mononuclear cells
GSM9666568 Single-cell CoCUT&Tag for H3K27me3 (BPS Bioscience 25243) (S8) in peripheral blood mononuclear cells
GSM9666569 Single-cell CoCUT&Tag for H3K4me3 (Active Motif 39159) (S8) in peripheral blood mononuclear cells
GSM9666570 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K4me3 and H3K27me3 (S8) in peripheral blood mononuclear cells
GSM9666571 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K4me3 and H3K27me3 (S8) in peripheral blood mononuclear cells
GSM9666572 Single-cell CoCUT&Tag for H3K27me3 (BPS Bioscience 25243) (S9) in peripheral blood mononuclear cells
GSM9666573 Single-cell CoCUT&Tag for H3K4me3 (Active Motif 39159) (S9) in peripheral blood mononuclear cells
GSM9666574 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K4me3 and H3K27me3 (S9) in peripheral blood mononuclear cells
GSM9666575 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K4me3 and H3K27me3 (S9) in peripheral blood mononuclear cells
GSM9666576 Single-cell CoCUT&Tag for H3K4me3 (Diagenode C15200152) (S10) in peripheral blood mononuclear cells
GSM9666577 Single-cell CoCUT&Tag for H3K27me3 (CST 9733) (S10) in peripheral blood mononuclear cells
GSM9666578 Single-cell CoCUT&Tag co-occupancy reads (R1) for H3K27me3 and H3K4me3 (S10) in peripheral blood mononuclear cells
GSM9666579 Single-cell CoCUT&Tag co-occupancy reads (R2) for H3K27me3 and H3K4me3 (S10) in peripheral blood mononuclear cells

+ 160 more — browse all 200 samples with per-sample file links →

Datasets on a similar topic

GSE327819 Single-molecule, single-cell profiling of linked chromatin states [Bulk_CoCUT&Tag] 35 samples shares single-molecule, single-cell, chromatin, linked, states, cocut
GSE337829 Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer [ChIP-Seq] 32 samples shares single-cell, chromatin
GSE337246 Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer [scRNA-Seq organoids] 35 samples shares single-cell, chromatin
GSE299348 Single-cell epigenetic, transcriptional, protein, and TCR states of HIV-1-infected cells in gut 117 samples shares single-cell, states
GSE283621 Single-cell multi-omics analysis identifies metabolism-linked epigenetic reprogramming as a driver of therapy-resistant medulloblastoma 79 samples shares single-cell, linked
GSE277469 Integrated single-cell chromatin and transcriptomic analyses of human peripheral immune cells in patients with alopecia areata. 32 samples shares single-cell, chromatin
GSE278910 Pooled CRISPR screens with joint single-nucleus chromatin accessibility and transcriptome profiling [CUT&RUN] 30 samples shares chromatin
GSE142751 Genome-wide maps of chromatin state in 142 cancer cell lines [cell line] 855 samples shares chromatin

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

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