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Epigenetic profiling of hematopoietic stem cells identifies KDR and PU.1 as regulators of aging transcriptome and caloric restriction response

GSE284988 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 58 samples Submitted 2025/12/09 Platform GPL17021Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 58 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
58 samples: 21 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.
Paper
Epigenetic profiling of hematopoietic stem cells from male mice identifies KDR and PU.1 as regulators of aging transcriptome and caloric restriction responseNature communications · 2026
Summary (written by the submitters)
The ability to cope with fluctuations in energy supply is essential for an organism's survival and health. While caloric restriction (CR) provides benefits towards many aspects of aging, it is associated with loss of immune function. The mechanisms by which the hematopoietic stem cells (HSCs) respond to this stress and potentially contribute to this loss of immunity remain unclear.
Read the full summary ↓
In this study, using both lifelong and short-term CR mice models, we found that reduced energy supply leads to a decrease in total peripheral blood white blood cell production that is myeloid- and thrombo-erythroid-biased. This strategy prioritizes the production of cell types essential for survival, such as red blood cells, platelets, and innate immune cells, at the expense of adaptive immune cell differentiation. Consistent with change in blood composition, HSCs under CR are driven into cell cycle to support the myeloid differentiation rather than self-renewal. Interestingly, despite the altered hematopoietic output, lifelong CR mitigates age-associated transcriptome changes of the HSCs, but these modifications are swiftly lost after ad libitum feeding. Epigenetic profiling identified KDR as a key regulator of the CR response and experimental knockdown of Kdr in aged HSCs reproduced the more youthful aging transcriptome observed in lifelong CR HSCs. Additionally, we show that PU.1 acts as an intracellular regulator of the CR response, regulating HSC self-renewal and differentiation under CR conditions by increased binding to its target genes.
Published in
Epigenetic profiling of hematopoietic stem cells from male mice identifies KDR and PU.1 as regulators of aging transcriptome and caloric restriction response
Zong L, Park B, Tekin-Turhan F et al. · Nature communications 2026 · PMID 41720793 · doi:10.1038/s41467-026-69718-0
This dataset
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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 GSE284988_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 PRJNA1200743 and SRA study SRP552780. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41720793) ↗
Study design
21 conditions, mostly in duplicate
ATAC_OAL ×4 mRNAseq_YCRRF ×4 mRNAseq_YCR ×4 mRNAseq_YAL ×4 mRNAseq_OCR ×4 mRNAseq_OAL ×4 mRNAseq_GFP_Kdr_shRNA ×4 ATAC_OCR ×4 +13 more

Supports a between-group comparison across 58 samples.

How we read this: 21 replicated groups read from 58 sample titles; they account for 58 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

+ 18 more — browse all 58 samples with per-sample file links →

Datasets on a similar topic

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