GEO series

Decoding Genome-wide Dysregulation of Translation in eIF2B-mutant Astrocytes: Implications for Vanishing White Matter Disease

GSE252362 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/03/19 Platform GPL21626

At a glance

RNA-seq (gene expression) · mouse · 18 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: Mus musculus (mouse)
Samples: 18 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.
Paper: The translational landscape of reactive astrocytes reveals the impact of eIF2B-mediated dysregulation in VWM diseaseNAR molecular medicine · 2025

Summary (written by the submitters)

eIF2B is a master regulator of translation initiation and mediator of the integrated stress response (ISR). Partial-loss-of function mutations are associated with eIF2B-leukodystrophy termed Vanishing White Matter Disease (VWMD), a recessive neurodegenerative disorder. Astrocytes, the brain homeostasis keepers, are central to VWMD owing to their hyper-sensitivity to eIF2B activity, as manifested by their phenotypic deficits due to the mutation.

Read the full summary ↓

Here we used astrocytes isolated from the brains of WT and eIF2B5R132H/R132H mice to assess their transcriptome and translatome responses upon cytokine-mediated activation, an mTOR-driven process critical for brain homeostasis. We found that: (i) a mild eIF2B mutation has the power to disrupt translation regulation programs involving ~30% of the expressed genes; (ii) a common compensatory strategy to overcome the translation regulation failure is manipulation of mRNA abundance; and (iii) dysregulation of functionally related genes can be used to reliably predict deficits of corresponding cellular functions. Specifically, the study illuminates the molecular anomalies responsible for the impaired ribogenesis and mitochondrial respiration of eIF2B-mutant astrocytes. Moreover, it reliably predicts, for the first time, impaired cholesterol biosynthesis in eIF2B-mutant astrocytes. This work demonstrates the strength of combined transcriptome/translatome approach to decipher links between mild expression anomalies and downstream cellular defects associated with VWMD.

Published in

The translational landscape of reactive astrocytes reveals the impact of eIF2B-mediated dysregulation in VWM disease

Mandelboum S, Lev-Ari L, Atzmon A et al. · NAR molecular medicine 2025 · PMID 41255715 · doi:10.1093/narmme/ugaf009

This dataset

Open GSE252362 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 GSE252362_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: 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 PRJNA1060294 and SRA study SRP480956. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41255715) ↗

Samples in this study

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

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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.