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A subcellular map of translational machinery composition and regulation at the single-molecule level [ALIBi_Lsg1_KD]

GSE283890 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/03/05 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 3 × ribosome-bound RNA, endoplasmic reticulum, scramble siRNA, biol vs 3 × whole-cell RNA, endoplasmic reticulum, scramble siRNA, biol vs 3 × ribosome-bound RNA, endoplasmic reticulum, Lsg1 siRNA, biol vs 3 × whole-cell RNA, endoplasmic reticulum, Lsg1 siRNA, biolGroups 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
A subcellular map of translational machinery composition and regulation at the single-molecule levelScience (New York, N.Y.) · 2025
Summary (written by the submitters)
Millions of ribosomes are packed within mammalian cells, yet we lack tools to visualize them in toto and characterize their subcellular composition. Here, we present ribosome expansion microscopy (RiboExM) to visualize individual ribosomes and an optogenetic proximity-labeling technique (ALIBi) to probe their composition. We generated a super-resolution ribosomal map, revealing unexpected subcellular translational hotspots and enrichment of 60S subunits near polysomes at the endoplasmic reticulum (ER).
Read the full summary ↓
We found that Lsg1 tethers 60S to the ER and regulates translation of select proteins. Additionally, we discovered ribosome heterogeneity at mitochondria guiding translation of metabolism-related transcripts. Finally, we visualized ribosomes in neurons, revealing a dynamic switch between monosomes and polysomes in neuronal translation. Together, these approaches enable exploration of ribosomal localization and composition at unprecedented resolution.
Published in
A subcellular map of translational machinery composition and regulation at the single-molecule level
Zhang Z, Xu A, Bai Y et al. · Science (New York, N.Y.) 2025 · PMID 40048539 · doi:10.1126/science.adn2623
This dataset
Open GSE283890 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 GSE283890_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 PRJNA1195974 and SRA study SRP550291. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40048539) ↗
Study design
3 × ribosome-bound RNA, endoplasmic reticulum, scramble siRNA, biol vs 3 × whole-cell RNA, endoplasmic reticulum, scramble siRNA, biol vs 3 × ribosome-bound RNA, endoplasmic reticulum, Lsg1 siRNA, biol vs 3 × whole-cell RNA, endoplasmic reticulum, Lsg1 siRNA, biol

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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