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Stag2 dependent chromatin remodeling enforces the erythroid-specific Gata1 cistrome

GSE301108 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 45 samples Submitted 2026/06/08 Platform GPL34328Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 45 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
45 samples: 14 conditions, mostly in triplicateGroups 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
Stag2-dependent chromatin remodeling enforces the erythroid-specific Gata1 cistromeBlood · 2026
Summary (written by the submitters)
The transcription factor GATA1 has pleiotropic hematopoietic functions, particularly in erythroid and megakaryocytic ontogeny. While mechanistic investigations have uncovered many facets of GATA1 biology, how GATA1 co-regulates divergent cell fates remains incompletely characterized. We previously described that loss of Stag2, a member of the cohesin complex and a recurrent mutational target in myelodysplastic syndrome (MDS) and myeloid leukemia of Down Syndrome, results in altered chromatin accessibility, transcription factor function, and cell differentiation.
Read the full summary ↓
Hence, we hypothesized that chromatin accessibility determines GATA1 cistrome specificity and lineage fate decisions. To understand the connection between chromatin accessibility and GATA1, we comprehensively studied erythropoiesis in Stag2∆ mice. Defects in Stag2-deficient hematopoiesis included reduced numbers of erythroid progenitors (EryPs), impaired terminal erythroid differentiation, increased number of MkPs, and increased megakaryocytes. RNA- and ATAC-sequencing of EryPs revealed altered patterns of Gata1 target gene expression with altered accessibility in conjunction with loss of expression of erythroid targets and gain of megakaryocyte targets. Despite unchanged Gata1 expression, Gata1 occupancy was reprogrammed from erythroid to megakaryocyte targets with Fli1 motifs enriched at Stag2∆ Gata1 binding sites. Functionally, we observed that Stag2-deficient EryPs have diminished erythroid output and augmented megakaryocyte output in orthogonal differentiation assays, which was partially reversed with Fli1 knockdown. Human models and primary MDS patients recapitulated the essential phenotypic and molecular features of our in vivo murine MDS model. Collectively, this study establishes chromatin accessibility as a determinant of transcription factor binding specificity, revealing an accessibility-driven Gata1 retargeting mechanism underlying MDS dyserythropoiesis.
Published in
Stag2-dependent chromatin remodeling enforces the erythroid-specific Gata1 cistrome
Sudunagunta VS, Stewart EM, Chen Y et al. · Blood 2026 · PMID 42148659 · doi:10.1182/blood.2025030554
This dataset
Open GSE301108 in finder → Find more mouse 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 GSE301108_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1283283 and SRA study SRP595706. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42148659) ↗
Study design
14 conditions, mostly in triplicate
EryP_HiC_KO ×4 EryP_Feb18_WT_Gata1 ×3 EryP_Feb18_KO_Gata1 ×3 HSPC_WT_GEX ×3 HSPC_WT_ATAC ×3 HSPC_KO_GEX ×3 HSPC_KO_ATAC ×3 Ter119_KO_GEX ×3 +8 more

Supports a between-group comparison across 43 samples.

How we read this: 14 replicated groups read from 45 sample titles; they account for 43 of them. 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

+ 5 more — browse all 45 samples with per-sample file links →

Datasets on a similar topic

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