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Epigenetic control of microglial mitochondrial immunity by KAT7 drives Alzheimer’s disease pathogenesis [RNA-Seq]

GSE327604 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/04/15 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 3 × WT vs 3 × Kat7_KO vs 3 × LPS_WT vs 3 × LPS_Kat7_KOGroups 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)
Mitochondrial DNA (mtDNA)-driven innate immune signaling sustains chronic neuroinflammation in neurological diseases such as Alzheimer’s disease (AD), yet how this pathway is regulated in microglia remains poorly understood. Here, we identify the histone acetyltransferase KAT7 (HBO1) as a central epigenetic regulator that links chromatin remodeling to mitochondrial immune activation.
Read the full summary ↓
KAT7 and its histone mark H3K14ac are elevated in microglia from 5×FAD mice and human AD brains. Integrative transcriptomic and epigenomic analyses reveal that KAT7 activates transcription of Cmpk2, a mitochondrial kinase essential for mtDNA synthesis. Loss of KAT7 reduces Cmpk2 expression, impairs mtDNA replication and release, and consequently suppresses cGAS-STING and NLRP3 signaling. Importantly, both microglia-specific deletion and pharmacological inhibition of KAT7 mitigate cytosolic mtDNA-induced neuroinflammation, decrease amyloid-β burden, restore synaptic plasticity, and improve cognitive function in 5×FAD mice. Together, these findings uncover an epigenetic-mitochondrial axis sustaining microglial pathogenicity and establish KAT7 as a promising therapeutic target for AD.
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 GSE327604_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 PRJNA1451514 and SRA study SRP690797. Searching any of these in the dataset finder brings you back here.

Study design
3 × WT vs 3 × Kat7_KO vs 3 × LPS_WT vs 3 × LPS_Kat7_KO

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
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