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Ribo-Tweezer: rapid removal of ribosomal proteins reveals new layers of post-transcriptional gene-regulation

GSE327296 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/05/18 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 12 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)
The ribosome is a ribozyme, but it may also act as a dynamic regulator of gene expression. Although ribosomal protein (RP) composition varies, dissecting the functional contributions of individual RPs beyond their housekeeping roles is challenging by the lack of tools for their selective manipulation in situ. Here, we developed Ribo-Tweezer, a degron-based system directly tethered to mature ribosomes that enables rapid, reversible, and selective depletion of specific RPs.
Read the full summary ↓
Using Ribo-Tweezer, we find a new role for RACK1 in stem cell fate control via translational regulation of zinc-finger transcriptional networks and in turn LINE1 expression. This translation-transcription coupling provides a mechanism by which translation control is further amplified in gene regulation. Distinct translational programs induced by RPLP0 and RPLP1 depletion further demonstrate RP-specific regulatory functions in translating the genome. Together, these findings establish Ribo-Tweezer as a powerful platform that has illuminated selective functions for RPs in gene regulation.
This dataset
Open GSE327296 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 GSE327296_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 PRJNA1450202 and SRA study SRP689973. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in duplicate
Polysome sequencing library of RACK1 FreeTir1… ×2 Polysome sequencing library of RACK1 FreeTir1… ×2 Polysome sequencing library of RACK1 FreeTir1… ×2 Polysome sequencing library of RACK1 FreeTir1… ×2 Polysome sequencing library of RACK1 FreeTir1… ×2 Polysome sequencing library of RACK1 FreeTir1… ×2 Polysome sequencing library of RACK1 Rps26Tir… ×2 Polysome sequencing library of RACK1 Rps26Tir… ×2 +4 more

Supports a between-group comparison across 24 samples.

How we read this: 12 replicated groups read from 24 sample titles; they account for 24 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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