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Non-necroptotic MLKL function damages mitochondria and promotes hematopoietic stem cell aging

GSE285111 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 26 samples Submitted 2026/02/10 Platform GPL19057Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 26 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
26 samples: 8 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
Non-necroptotic MLKL function damages mitochondria and promotes hematopoietic stem cell agingNature communications · 2026
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
Non-necroptotic MLKL function damages mitochondria and promotes hematopoietic stem cell aging
Yamada Y, Yang J, Saiki-Tsuchiya A et al. · Nature communications 2026 · PMID 41942424 · doi:10.1038/s41467-026-71060-4
This dataset
Open GSE285111 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 GSE285111_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 PRJNA1201182 and SRA study SRP553024. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41942424) ↗
Study design
8 conditions, mostly in triplicate
Aged WT HSC, RNA-seq, ×4 Aged Mlkl-/- HSC, RNA-seq, ×4 Young WT HSC, ATAC-seq, ×3 Young Mlkl-/- HSC, ATAC-seq, ×3 Aged WT HSC, ATAC-seq, ×3 Aged Mlkl-/- HSC, ATAC-seq, ×3 Young WT HSC, RNA-seq, ×3 Young Mlkl-/- HSC, RNA-seq, ×3

Supports a between-group comparison across 26 samples.

How we read this: 8 replicated groups read from 26 sample titles; they account for 26 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
Datasets on a similar topic

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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.