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The RNA-binding E3 ligase MKRN2 selectively disrupts IL-6 translation to restrain inflammation [RNA-seq]

GSE291859 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/04/27 Platform GPL28330
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples
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)
Dysregulation of proinflammatory cytokine production leads to autoimmune and inflammatory diseases. Although E3 ligases and RNA-binding proteins (RBPs) are critical in autoimmunity and inflammation, whether RNA-binding E3 ligases (E3-RBPs) can regulate proinflammatory cytokine expression to be involved in autoimmune disorders remains unclear.
Read the full summary ↓
Here, we found that MKRN2, an E3-RBP, selectively inhibits IL-6 expression in LPS-activated macrophages. MKRN2-deficient mice have increased IL-6 serum levels at the untreated stage or after LPS treatment, and exhibit increased severity of experimental colitis which is associated with increased IL-6 levels. MKRN2 is negatively correlated with IL-6 expression in clinical samples from patients with ulcerative colitis and rheumatoid arthritis. Mechanistically, upon encountering Il6 mRNA, MKRN2 links K29 polyubiquitin to Lys179 of PAIP1 which blocks PAIP1-eIF4A interaction, thus inhibiting the translational efficiency of Il6 mRNA. Our findings provide new mechanistic insight and potential therapeutic strategies for inflammatory autoimmune diseases by disrupting translation process of specific proinflammatory cytokines.
This dataset
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.

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 GSE291859_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1235663 and SRA study SRP570214. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 18 more — browse all 18 samples with per-sample file links →

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