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Non-destructive transcriptomics via vesicular export (NTVE)

GSE283136 Homo sapiens (human) RNA-seq (gene expression) 412 samples Submitted 2025/09/01 Platform GPL34281Platform GPL34328Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 412 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
412 samples: 348 distinct titles, 29 of them repeatedGroups 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
Non-destructive transcriptomics via vesicular exportNature communications · 2026
Summary (written by the submitters)
Transcriptomics is a valuable technique for multiplexed monitoring of cellular states. Using an engineered RNA adapter, NTVE exports cellular transcripts from inducible human and murine reporter cell lines with high concordance to conventional lysate-derived RNA-seq. NTVE allows monitoring of transcriptome changes in response to genetic and chemical perturbations (Interferon gamma; ASCL1 transactivation) in the same cells over time using standard sequencing workflows.
Published in
Non-destructive transcriptomics via vesicular export
Armbrust N, Grosshauser M, Geilenkeuser J et al. · Nature communications 2026 · PMID 42034633 · doi:10.1038/s41467-026-72072-w
This dataset
Open GSE283136 in finder → Find more 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 GSE283136_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 PRJNA1192227 and SRA study SRP548345. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42034633) ↗
Study design
348 distinct titles, 29 of them repeated
30) ×9 HEK-293T technical control, ×4 Purified Neuro2a (ISBM-095) NTVE from co-cult… ×3 Purified HEK293T (ISBM-083) NTVE from co-cult… ×3 Total RNA HEK-293T lysate, HIV-gag WT, ×3 MCP, ×3 00) ×3 45) ×3 +21 more

Supports a case/control comparison: 32 samples read as cases, 86 as controls.

How we read this: Read from the first 400 of 412 sample titles: 348 distinct titles with little repetition. 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

+ 372 more — browse all 412 samples with per-sample file links →

Datasets on a similar topic

Search all RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.