← BioTransfer GEO Dataset Finder
GEO series

Immune response to adeno-associated viral vectors in a human iPSC-derived microglia chimeric mouse model

GSE312740 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2026/03/25 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 16 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.
Paper
Immune response to adeno-associated viral vectors in a human iPSC-derived microglia chimeric mouse modelCell reports methods · 2026
Summary (written by the submitters)
Adeno-associated virus (AAV)-based gene therapy for severe neurological diseases is challenged by immune responses, which are difficult to study accurately in genetically divergent rodent models or in in vitro human iPSC-derived microglia (iMGL) that acquire activated phenotypes lacking complex brain environment cues. To address this, we generated human microglia chimeric mice.
Read the full summary ↓
We developed a high-yield iMGL differentiation protocol incorporating a cryopreservation stopping point at the induced hematopoietic precursor cell (iHPC) stage, which increased flexibility and enabled high level of chimerism. Engrafted iMGL transcriptionally and phenotypically resembled primary human microglia and were functionally active, displaying phagocytosis and immune response to inflammatory stimuli. Assessment of AAV serotypes revealed that murine microglia induced a larger immune response compared to human iMGL, cautioning against overinterpreting inflammatory responses in rodent models. This model provides a critical tool to define the human immune response to AAVs early in vector discovery.
Published in
Immune response to adeno-associated viral vectors in a human iPSC-derived microglia chimeric mouse model
Detrez JR, Eykens C, Gillet G et al. · Cell reports methods 2026 · PMID 41895259 · doi:10.1016/j.crmeth.2026.101362
This dataset
Open GSE312740 in finder → Find more 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 GSE312740_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 PRJNA1375804 and SRA study SRP651849. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41895259) ↗
Study design
16 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 16 sample titles: 16 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 RNA-seq datasets in GEO →

Share this dataset

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.