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The retrotransposable element-silencing factor Daxx controls microglia identity and function in the adult brain

GSE255329 Mus musculus (mouse) Single-cell RNA-seq 93 samples Submitted 2026/06/22 Platform GPL19057Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 93 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
93 samples: 18 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.
Summary (written by the submitters)
Death domain-associated protein (Daxx) is one of the two main H3.3 chaperones in mammalian cells and acts as key repressor of RTEs of viral origin. In present study, we found that Daxx is an IFN-stimulated gene mediating repression of RTEs and IFN-stimulated genes (ISGs) upon inflammatory stimuli in microglia. Using both bulk and single-cell genomics, we demonstrated that shortly after Daxx loss microglia displayed co-expression of DNA damage/p53, IFN/developmental and DAM-like signatures, suggesting lowering of the epigenetic barrier and increased plasticity.
Read the full summary ↓
With time, Daxx-deficient microglia become restricted to a DAM-like/ApoeHIGH profile, associated with decreased synaptic puncta and altered behavior. Finally, brains from older microglia-specific Daxx KO mice accumulate ApoE protein along with lysosomal markers. Together, our data revealed a role of Daxx in maintenance of the homeostatic state of microglia in the adult brain, with implications for our understanding of the relationship between loss of epigenetic barriers and neuroinflammation and its potential implications for brain function and aging.
This dataset
Open GSE255329 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 GSE255329_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1074682 and SRA study SRP488883. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 conditions, mostly in triplicate
in vivo Daxx KO microglia TAM 1wpi ×4 in vitro Daxx WT microglia control ×3 in vitro Daxx KO microglia control ×3 in vitro Daxx WT microglia LPS-6h ×3 in vitro Daxx KO microglia LPS-6h ×3 in vitro Daxx WT microglia LPS-24h ×3 in vitro Daxx KO microglia LPS-24h ×3 in vitro Daxx WT microglia LPS-48h ×3 +50 more

Supports a between-group comparison across 53 samples.

How we read this: 18 replicated groups read from 93 sample titles; they account for 53 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

+ 53 more — browse all 93 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.