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Regulation of lineage reprogramming by dynamic chromatin SUMOylation (ChIP-seq)

GSE311971 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 41 samples Submitted 2026/05/27 Platform GPL11154
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 41 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
Homo sapiens (human)
Samples
41 samples: 17 conditions, mostly in duplicateGroups 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)
SUMOylation has emerged as a key regulator of chromatin and transcription, yet its contribution to lineage reprogramming remains unclear. To explore how chromatin SUMOylation influences cellular plasticity, we studied CEBPA-driven lineage reprogramming of human leukemic B-cells into macrophage-like cells. By integrating ChIP-seq, ATAC-seq, RNA-seq and chromatin-directed proteomics, we mapped the chromatin landscape and transcriptomic changes during early reprogramming.
Read the full summary ↓
Lineage conversion triggered a dynamic rise in SUMO2/3 chromatin occupancy at CEBPA-bound sites, revealing a coordinated regulatory mechanism. Proteomic profiling of SUMO2/3- and CEBPA-associated chromatin uncovered extensive convergence and enrichment of differentiation-related transcription factors, chromatin remodelers and coregulators. Among these, NCOA3 displayed markedly increased SUMO2/3 association upon lineage conversion. NCOA3 co-occupied CEBPA- and SUMO2/3-bound chromatin regions, implying a SUMOylation-supported coregulatory role in lineage reprogramming. Pharmacological inhibition of SUMOylation using ML-792 (SUMOi) selectively enhanced CEBPA chromatin occupancy and chromatin accessibility, altered the CEBPA association of proteins, and modified NCOA3 binding dynamics. SUMOi also reshaped gene expression, promoting loss of B-cell identity and activation of macrophage-associated programs, including lipid metabolism. Collectively, our findings highlight chromatin SUMOylation as a dynamic and context-dependent modifier that fine-tunes lineage transitions, with implications for chromatin biology and therapeutic modulation of cell identity.
This dataset
Open GSE311971 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 GSE311971_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 PRJNA1372005 and SRA study SRP650261. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
17 conditions, mostly in duplicate
BLaER1_CEBPA_0hE2_DMSO ×2 BLaER1_CEBPA_0hE2_SUMOi ×2 BLaER1_CEBPA_6hE2_DMSO ×2 BLaER1_CEBPA_6hE2_SUMOi ×2 BLaER1_CEBPA_24hE2_DMSO ×2 BLaER1_CEBPA_24hE2_SUMOi ×2 BLaER1_SUMO23_0hE2_DMSO ×2 BLaER1_SUMO23_0hE2_SUMOi ×2 +16 more

Supports a between-group comparison across 34 samples.

How we read this: 17 replicated groups read from 41 sample titles; they account for 34 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

+ 1 more — browse all 41 samples with per-sample file links →

Datasets on a similar topic

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