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Effects of type I IFN signaling on gene expression of Mycobacterium tuberculosis-infected bone marrow-derived macrophages (BMDMs)

GSE289356 Mus musculus (mouse) RNA-seq (gene expression) 34 samples Submitted 2025/02/13 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 34 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
34 samples: 34 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
ACOD1-mediated lysosomal membrane permeabilization contributes to Mycobacterium tuberculosis-induced macrophage deathProceedings of the National Academy of Sciences of the United States of America · 2025
Summary (written by the submitters)
Our previous work identified that type I IFNs mediate macrophage death after infection of Mycobacterium tuberculosis (Mtb) through a novel mechanism.Type I IFN signaling relies on its several hundred ISGs to execute various functions. In order to delineate the downstream mechanism of type I IFN-mediating cell death, we adopted RNA-seq experiments to identify which gene(s) are differentially expressed in WT or Ifnar1-/- bone marrow-derived macrophages (BMDMs).
Read the full summary ↓
In the meantime, we're also interested in how genetic background affects transcriptomics in BMDMs infected with Mtb. Thus a transcriptomics analysis of C57BL/6, 129S2 and 129X1 infected with Mtb were also conducted.
Published in
ACOD1-mediated lysosomal membrane permeabilization contributes to Mycobacterium tuberculosis-induced macrophage death
Yang Z, Zhang L, Ottavi S et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 40100622 · doi:10.1073/pnas.2425309122
This dataset
Open GSE289356 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 GSE289356_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 PRJNA1222774 and SRA study SRP563392. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40100622) ↗
Study design
34 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 34 sample titles: 34 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.