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Soluble DLK1 secreted by telomere-shortening-induced senescent microglia impairs oligodendrocyte functions and alters neuronal activity(ipsc_cell)

GSE315100 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2026/07/09 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 28 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
28 samples
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)
Aging is a predominant risk factor of neurodegenerative disorders such as Alzheimer’s and Parkinson’s disease. Here, we investigated the impact of telomere shortening, a physiological hallmark of aging, on brain function. Telomere-shortened mice exhibited cognitive decline and exacerbated lipofuscinosis, accompanied by the emergence of senescent microglia with a senescence-associated secretory phenotype and oligodendrocyte lineage cells with impaired maturation.
Read the full summary ↓
Using iPSC-derived microglia with shortened telomeres, we identified DLK1 as a novel senescence-associated ligand secreted by senescent microglia. Elevated soluble DLK1 was detected in the cerebrospinal fluid of both telomere-shortened and physiologically aged mice, and this increase was abolished by microglial depletion, confirming its microglial origin. Functionally, AAV-mediated expression of sDLK1 in mouse brains induced hypomyelination and disrupted oligodendrocyte differentiation in vivo. In human iPSC-derived systems, sDLK1 impaired late-stage oligodendrocyte maturation and disrupted neuronal calcium signaling. Together, these findings establish replicative microglial senescence as a pathological feature of telomere shortening and identify sDLK1 as one key effector linking senescent microglia to oligodendrocyte dysfunction and neuronal dysregulation during brain aging.
This dataset
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.

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 GSE315100_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1395000 and SRA study SRP658572. Searching any of these in the dataset finder brings you back here.

Study design
A cohort of 28 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run bal_001 … bal_028 and carry no group information.

Samples in this study
Datasets on a similar topic

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