GEO series
A mutant ASXL1-EHMT complex contributes to heterochromatin dysfunction in clonal hematopoiesis and chronic monomyelocytic leukemia [Cut & Run]
GSE274875
Mus musculus (mouse)
ChIP-seq / ATAC-seq (genome binding and open chromatin)
38 samples
Submitted 2025/01/06
Platform GPL17021
At a glance
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 38 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Mus musculus (mouse)
- Samples
- 38 samples: 38 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.
- Paper
- A mutant ASXL1-BAP1-EHMT complex contributes to heterochromatin dysfunction in clonal hematopoiesis and chronic monomyelocytic leukemiaProceedings of the National Academy of Sciences of the United States of America · 2025
Summary (written by the submitters)
ASXL1 is one of the three most frequently mutated genes in age-related clonal hematopoiesis (CH), with the others being DNMT3A and TET2. CH can progress to myeloid malignancies including chronic monomyelocytic leukemia (CMML), and is also strongly associated with inflammatory cardiovascular disease and all-cause mortality in humans. DNMT3A and TET2 regulate DNA methylation and demethylation pathways respectively, and DNMT3A and TET2 loss-of-function mutations in CH reduce DNA methylation in heterochromatin, allowing de-repression of silenced elements in heterochromatin.
Read the full summary ↓
In contrast, the mechanisms that connect mutant ASXL1 and CH are not yet fully understood. CH/CMML-associated ASXL1 mutations encode C-terminally truncated proteins that enhance the deubiquitinase activity of the ASXL-BAP1 “PR-DUB” deubiquitinase complex, which removes mono-ubiquitin from H2AK119Ub. Here we show that ASXL1 mutant proteins interact with the EHMT1-EHMT2 methyltransferase complex, which generates H3K9me1 and me2, the latter a repressive modification in constitutive heterochromatin. Compared to cells from age-matched wildtype mice, we found that expanded myeloid cells from old Asxl1tm/+ mice, a heterozygous knock-in mouse model of CH, display genome-wide decreases of H3K9me2, H3K9me3 and H2AK119Ub as well as an associated increase in expression of transposable elements (TEs) and satellite repeats. Increased TE expression was also observed in monocytes from ASXL1-mutant CMML patients compared to monocytes from healthy control individuals. Our data suggest that mutant ASXL1 proteins compromise the integrity of both constitutive and facultative heterochromatin in an age-dependent manner, by reducing the levels of H3K9me2/3 and H2AK119Ub respectively. The resulting increase in TE expression can alter the expression of nearby genes and promote the expression of inflammation-associated and interferon-inducible genes (ISGs).
Published in
Dong Z, Sepulveda H, Arteaga-Vazquez LJ et al.
· Proceedings of the National Academy of Sciences of the United States of America 2025
· PMID 39752521
· doi:10.1073/pnas.2413302121
This dataset
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.
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 GSE274875_RAW.tar (it can run to tens of gigabytes).
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.
What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1148395 and SRA study SRP526559. Searching any of these in the dataset finder brings you back here.
Study design
38 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 38 sample titles: 38 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
- GSM8459740 H2AK119ub,MT,Rep1,CUT&RUN
- GSM8459741 H2AK119ub,MT,Rep2,CUT&RUN
- GSM8459742 H2AK119ub,WT,Rep1,CUT&RUN
- GSM8459743 H2AK119ub,WT,Rep2,CUT&RUN
- GSM8459744 H3K9me2,MT,Rep1,CUT&RUN
- GSM8459745 H3K9me2,MT,Rep2,CUT&RUN
- GSM8459746 H3K9me2,MT,Rep3,CUT&RUN
- GSM8459747 H3K9me2,WT,Rep1,CUT&RUN
- GSM8459748 H3K9me2,WT,Rep2,CUT&RUN
- GSM8459749 H3K9me2,WT,Rep3,CUT&RUN
- GSM8459750 H3K9me3,MT,Rep1,CUT&RUN
- GSM8459751 H3K9me3,MT,Rep2,CUT&RUN
- GSM8459752 H3K9me3,WT,Rep1,CUT&RUN
- GSM8459753 H3K9me3,WT,Rep2,CUT&RUN
- GSM8459754 H3K27me3,MT,Rep1,CUT&RUN
- GSM8459755 H3K27me3,MT,Rep2,CUT&RUN
- GSM8459756 H3K27me3,WT,CUT&RUN
- GSM8459757 H3K4me3,MT,Rep1,CUT&RUN
- GSM8459758 H3K4me3,MT,Rep2,CUT&RUN
- GSM8459759 H3K4me3,WT,Rep1,CUT&RUN
- GSM8459760 H3K4me3,WT,Rep2,CUT&RUN
- GSM8459761 IgG_for_H2AK119ub,MT,CUT&RUN
- GSM8459762 IgG_for_H2AK119ub,WT,CUT&RUN
- GSM8459763 IgG_for_H3K9me2,MT,Rep1,CUT&RUN
- GSM8459764 IgG_for_H3K9me2,MT,Rep2,CUT&RUN
- GSM8459765 IgG_for_H3K9me2,WT,Rep1,CUT&RUN
- GSM8459766 IgG_for_H3K9me2,WT,Rep2,CUT&RUN
- GSM8459767 IgG_for_H3K9me2,WT,Rep3,CUT&RUN
- GSM8459768 IgG_for_H3K9me3,MT,Rep1,CUT&RUN
- GSM8459769 IgG_for_H3K9me3,MT,Rep2,CUT&RUN
- GSM8459770 IgG_for_H3K9me3,WT,Rep1,CUT&RUN
- GSM8459771 IgG_for_H3K9me3,WT,Rep2,CUT&RUN
- GSM8459772 IgG_for_H3K27me3,MT,CUT&RUN
- GSM8459773 IgG_for_H3K27me3,WT,CUT&RUN
- GSM8459774 IgG_for_H3K4me3,MT,Rep1,CUT&RUN
- GSM8459775 IgG_for_H3K4me3,MT,Rep2,CUT&RUN
- GSM8459776 IgG_for_H3K4me3,WT,Rep1,CUT&RUN
- GSM8459777 IgG_for_H3K4me3,WT,Rep2,CUT&RUN
Datasets on a similar topic
- GSE274878 A mutant ASXL1-EHMT complex contributes to heterochromatin dysfunction in clonal hematopoiesis and chronic monomyelocytic leukemia [RNAseq_mouse] 19 samples shares asxl1-ehmt, heterochromatin, monomyelocytic, hematopoiesis, contributes, dysfunction, leukemia, complex
- GSE261181 Regulation of heterochromatin formation and tumor suppression in leukemia by IKAROS, HDAC1 and EZH2 [ChIP-seq] 28 samples shares heterochromatin, leukemia
- GSE276308 Two mutations associated with leukemia that change a single tyrosine residue in the STAT5B SH2 domain have opposite effects on the transcriptional programs controlling hematopoiesis [ChIP-seq] 13 samples shares hematopoiesis, leukemia
- GSE312126 In vivo CRISPR screening identifies SAGA complex members as a key regulators of hematopoiesis [ChIP] 12 samples shares hematopoiesis, complex
- GSE294772 Single-Cell Epigenomics Uncovers Heterochromatin Instability and Transcription Factor Dysfunction during Mouse Brain Aging [snATAC-Seq] [10X Multiome] 142 samples shares heterochromatin, dysfunction
- GSE276311 Two mutations associated with leukemia that change a single tyrosine residue in the STAT5B SH2 domain have opposite effects on the transcriptional programs controlling hematopoiesis [RNA-seq] 61 samples shares hematopoiesis, leukemia
- GSE312282 In vivo CRISPR screening identifies SAGA complex members as a key regulators of hematopoiesis [RNA] 56 samples shares hematopoiesis, complex
- GSE276312 Two mutations associated with leukemia that change a single tyrosine residue in the STAT5B SH2 domain have opposite effects on the transcriptional programs controlling hematopoiesis [scRNA-seq] 23 samples shares hematopoiesis, leukemia
Share this dataset
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.