← BioTransfer GEO Dataset Finder
GEO series

Fate-mapping and functional dissection reveal perilous influence of type I interferon signaling in mouse brain aging

GSE269720 Mus musculus (mouse) RNA-seq (gene expression) 37 samples Submitted 2024/06/19 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 37 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
37 samples: 18 × NIA vs 11 × IC vs 8 × MKOGroups 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)
Aging significantly elevates the risk of developing neurodegenerative diseases. Neuroinflammation is a universal hallmark of neurodegeneration as well as normal brain aging. Which branches of age-related neuroinflammation, and how they precondition the brain toward pathological progression, remain ill-understood. The presence of elevated type I interferon (IFN-I) has been documented in the aged brain, but its role in promoting degenerative processes, such as the loss of neurons in vulnerable regions, has not been studied in depth.
Read the full summary ↓
To comprehend the scope of IFN-I activity in the aging brain, we surveyed IFN-I-responsive reporter mice at multiple ages. We also examined 5- and 24-month-old mice harboring selective ablation of Ifnar1 in microglia to observe the effects of manipulating this pathway during the aging process using bulk RNA sequencing and histological parameters. We detected age-dependent IFN-I signal escalation in multiple brain cell types from various regions, especially in microglia. Selective ablation of Ifnar1 from microglia in aged mice significantly reduced overall brain IFN-I signature, dampened microglial reactivity, lessened neuronal loss, restored expression of key neuronal genes and pathways, and diminished the accumulation of lipofuscin, a core hallmark of cellular aging in the brain. Overall, our study demonstrates pervasive IFN-I activity during normal mouse brain aging and reveals a pathogenic, pro-degenerative role played by microglial IFN-I signaling in perpetuating neuroinflammation, neuronal dysfunction, and molecular aggregation. These findings extend the understanding of a principal axis of age-related inflammation in the brain, one likely shared with multiple neurological disorders, and provide a rationale to modulate aberrant immune activation to mitigate neurodegenerative process at all stages.
This dataset
Open GSE269720 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 GSE269720_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 PRJNA1123299 and SRA study SRP513598. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 × NIA vs 11 × IC vs 8 × MKO

Supports a between-group comparison across 37 samples.

How we read this: 3 replicated groups read from 37 sample titles; they account for 37 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
Datasets on a similar topic

Search all mouse 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.