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Single-cell analysis of mouse microglia carrying the mouse Nlrp3 wildtype locus, the human NLRP3 wildtype knock-in or the human NLRP3 D305N variant knock-in gene.

GSE328214 Mus musculus (mouse) Single-cell RNA-seq 8 samples Submitted 2026/07/21 Platform GPL34328
At a glance

Single-cell RNA-seq · mouse · 8 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
8 samples: 8 samples, each with a distinct title — no replicated groupsGroups 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)
Mice with the humanized NLRP3 D305N gain-of-function mutation (hNLRP3_D305N) demonstrate peripheral immune cell infiltration into the brain. We used single cell RNA-sequencing to characterize the immune cell population of CD45+ cells in the brains of these mice, compared to hNLRP3_WT and mNlrp3_WT controls. We identified elevated peripheral immune cell populations in hNLRP3_D305N, with neutrophils, T cells, and monocytes as the most prevalent populations.
Read the full summary ↓
hNLRP3_D305N microglia also showed broad transcriptional shifts towards more reactive profiles and the emergence of distinct subpopulations that were also defined by expression of proinflammatory genes.
This dataset
Open GSE328214 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 GSE328214_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 PRJNA1454358 and SRA study SRP692366. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 samples, each with a distinct title — no replicated groups

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

How we read this: Read from 8 sample titles: 8 distinct titles with little repetition. 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

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.