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Increased molecular and functional heterogeneity of hematopoietic stem cells contributes to age-related decline of tissue and body function

GSE233879 Mus musculus (mouse) DNA methylation 80 samples Submitted 2025/01/02 Platform GPL21626Platform GPL32159
At a glance

DNA methylation · mouse · 80 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Mus musculus (mouse)
Samples
80 samples: 23 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
Reducing functionally defective old HSCs alleviates aging-related phenotypes in old recipient miceCell research · 2025
Summary (written by the submitters)
Aging is a process accompanied by functional decline in tissues and organs with great social and medical consequences. Previous studies have demonstrated that aged hematopoietic stem cells (HSCs) are functionally compromised, which at least partly contributes to aging-related decline of the body health. However, the underlying mechanism is largely unknown.
Read the full summary ↓
Here we reveal a clear heterogeneity of old HSCs, which can be marked by the CD150 levels. Comparative molecular and functional analyses revealed that CD150low HSCs from old mice have a younger aging clock, transcriptome, and better repopulation capacity compared to that of the CD150high HSCs. Mechanistically, CD150high HSCs from old mice have greatly compromised differentiation capacity compared to that of the CD150low HSCs. Importantly, decreasing the CD150high HSC ratio in old mice can alleviate aging-related functional decline. Thus, our study not only reveals how HSC heterogeneity contributes to aging, but also points to a potential way for rejuvenation.
Published in
Reducing functionally defective old HSCs alleviates aging-related phenotypes in old recipient mice
Wang Y, Zhang W, Zhang C et al. · Cell research 2025 · PMID 39743633 · doi:10.1038/s41422-024-01057-5
This dataset
Open GSE233879 in finder → Find more mouse RNA-seq 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 GSE233879_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 beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA978496 and SRA study SRP440646. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39743633) ↗
Study design
23 conditions, mostly in triplicate
Old_HSC_CD150L_RRBS ×4 Old_HSC_CD150H_RRBS ×4 Blood_CD150H_6M_TX_RRBS ×4 Blood_CD150L_6M_TX_RRBS ×4 Blood_Unsorted_6M_TX_RRBS ×4 Blood_Recipient_old_HSCs_10M_TX_RRBS ×4 Blood_Recipient_young_HSCs_10M_TX_RRBS ×4 Young_fresh_HSC_RNA ×3 +19 more

Supports a between-group comparison across 76 samples.

How we read this: 23 replicated groups read from 80 sample titles; they account for 76 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

+ 40 more — browse all 80 samples with per-sample file links →

Datasets on a similar topic

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