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Characterization of translational dynamics during macrophage activation

GSE281922 Mus musculus (mouse) RNA-seq (gene expression) 22 samples Submitted 2025/09/07 Platform GPL21273Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 22 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
22 samples: 8 conditions, mostly in duplicateGroups 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)
Macrophages require rapid and tightly controlled regulatory mechanisms to respond rapidly to environmental disruptions while preventing excessive inflammatory responses. While transcriptional regulation has been well-characterized in macrophage activation, whether and how translational control contributes to macrophage activation remains less understood. Here, we investigate the dynamic landscape of translational regulation in macrophages across acute, intermediate, and prolonged LPS exposure.
This dataset
Open GSE281922 in finder → Find more mouse 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 GSE281922_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 PRJNA1186181 and SRA study SRP545296. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in duplicate
Riboseq of raw264.7 without LPS treatment, ×2 Riboseq of raw264.7 with 6h LPS treatment, ×2 Riboseq of raw264.7 with 12h LPS treatment, ×2 Riboseq of raw264.7 with 24h LPS treatment, ×2 RNAseq of raw264.7 without LPS treatment, ×2 RNAseq of raw264.7 with 6h LPS treatment, ×2 RNAseq of raw264.7 with 12h LPS treatment, ×2 RNAseq of raw264.7 with 24h LPS treatment, ×2 +6 more

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 22 sample titles; they account for 16 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
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