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Persistent ER stress in macrophages fuels age-related inflammation and vulnerability to infection

GSE304706 Mus musculus (mouse) RNA-seq (gene expression) 8 samples Submitted 2026/08/08 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 8 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
8 samples: 4 × Peritoneal macrophages from young mouse, vs 4 × Peritoneal macrophages from aged mouse,Groups 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 is accompanied by a state of chronic, low-grade inflammation known as inflammaging that underlies increased susceptibility to infection and many age-related pathologies. Although macrophages are central to immune regulation and inflammation, the molecular mechanisms driving their age-associated dysfunction remain incompletely defined.
Read the full summary ↓
Here, we performed bulk RNA-sequencing on FACS-sorted peritoneal macrophages from young and aged mice. Analysis of differentially expressed genes revealed that genes upregulated in aged macrophages were significantly enriched for pathways related to "response to interferon-beta" and "response to interferon-gamma". Further investigation of our RNA-seq data for upstream mediators of these genes showed that Stat1 was markedly upregulated in aged macrophages. These transcriptomic findings suggest that the chronic activation of ER UPR in aged macrophages drives an enhanced ISG program, representing a potential mechanism for inflammaging.
This dataset
Open GSE304706 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 GSE304706_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 PRJNA1302373 and SRA study SRP606958. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
4 × Peritoneal macrophages from young mouse, vs 4 × Peritoneal macrophages from aged mouse,

Supports a between-group comparison across 8 samples.

How we read this: 2 replicated groups read from 8 sample titles; they account for 8 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

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