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RAPIDASH: Tag-free enrichment of ribosome-associated proteins reveals compositional dynamics in embryonic tissues, cancer cells, and macrophages [RNA-Seq and Ribo-Seq]

GSE274188 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/09/10 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
Samples
12 samples: 3 × H1 hiN D14, LLPHNterm/Nterm, Ribo-seq, vs 3 × H1 hiN D14, LLPHwt/wt, Ribo-seq, vs 3 × H1 hiN D14, LLPHNterm/Nterm, RNAseq, vs 3 × H1 hiN D14, LLPHwt/wt, RNAseq,Groups 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
RAPIDASH: Tag-free enrichment of ribosome-associated proteins reveals composition dynamics in embryonic tissue, cancer cells, and macrophagesMolecular cell · 2024
Summary (written by the submitters)
Ribosomes are emerging as direct regulators of gene expression, with ribosome-associated proteins (RAPs) allowing ribosomes to modulate translation. Nevertheless, a lack of technologies to enrich RAPs across sample types has prevented systematic analysis of RAP identities, dynamics, and functions. We have developed a label-free methodology called RAPIDASH to enrich ribosomes and RAPs from any sample.
Read the full summary ↓
We applied RAPIDASH to mouse embryonic tissues and identified hundreds of potential RAPs, including DHX30 and LLPH, two forebrain RAPs important for neurodevelopment. We identified a critical role of LLPH in neural development linked to the translation of genes with long coding sequences. In addition, we showed RAPIDASH can identify ribosome changes in cancer cells. Finally, we characterized ribosome composition remodeling during immune cell activation and observed extensive changes post-stimulation. RAPIDASH has therefore enabled the discovery of RAPs in multiple cell types, tissues, and stimuli and is adaptable to characterize ribosome remodeling in several contexts.
Published in
RAPIDASH: Tag-free enrichment of ribosome-associated proteins reveals composition dynamics in embryonic tissue, cancer cells, and macrophages
Susanto TT, Hung V, Levine AG et al. · Molecular cell 2024 · PMID 39260367 · doi:10.1016/j.molcel.2024.08.023
This dataset
Open GSE274188 in finder → Find more human 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 GSE274188_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 PRJNA1145378 and SRA study SRP524765. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39260367) ↗
Study design
3 × H1 hiN D14, LLPHNterm/Nterm, Ribo-seq, vs 3 × H1 hiN D14, LLPHwt/wt, Ribo-seq, vs 3 × H1 hiN D14, LLPHNterm/Nterm, RNAseq, vs 3 × H1 hiN D14, LLPHwt/wt, RNAseq,

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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