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NUDT21 Shapes Macrophage Transcriptomes through alternative polyadenylation in ARDS

GSE292996 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/08/11 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
16 samples: 4 × Lysm_Con vs 4 × Lysm_LPS_3h vs 4 × Nudt21-Lysm_Con vs 4 × Nudt21-Lysm_LPS_3hGroups 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
NUDT21 Regulates Macrophage Cytokine Responses via Alternative Polyadenylation in ARDSResearch square · 2025
Summary (written by the submitters)
Defining the molecular mechanisms governing macrophage-driven inflammation is essential for developing targeted interventions for ARDS. One such mechanism could be alternative polyadenylation (APA), a post-transcriptional regulatory process that plays a critical role in gene regulation. Most mammalian genes, including key proinflammatory mediators, contain multiple polyadenylation sites (PAS).
Read the full summary ↓
APA regulates the addition of poly(A) tails at alternative PAS, generating transcripts with different 3' UTR lengths. One key regulator of APA is Nudix Hydrolase 21 (NUDT21), a critical cleavage factor Im (CFIm) component. However, whether NUDT21-mediated APA plays a role in inflammation during ARDS is not known. Thus, the goal of this study is to identify the APA genes regulated by NUDT21 in macrophages.
Published in
NUDT21 Regulates Macrophage Cytokine Responses via Alternative Polyadenylation in ARDS
Mills T, Liu H, Wang Y et al. · Research square 2025 · PMID 41282183 · doi:10.21203/rs.3.rs-7810883/v1
This dataset
Open GSE292996 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 GSE292996_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 PRJNA1242320 and SRA study SRP573321. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41282183) ↗
Study design
4 × Lysm_Con vs 4 × Lysm_LPS_3h vs 4 × Nudt21-Lysm_Con vs 4 × Nudt21-Lysm_LPS_3h

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 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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