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mRNA export factors store nascent transcripts within nuclear speckles as an adaptive response to transient global inhibition of transcription.

GSE183570 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2025/02/13 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 28 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
28 samples: 10 conditions, mostly in triplicateGroups 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
mRNA export factors store nascent transcripts within nuclear speckles as an adaptive response to transient global inhibition of transcriptionMolecular cell · 2025
Summary (written by the submitters)
Several transcription inhibitors have been developed as cancer therapies. However, they show modest clinical activity highlighting that our understanding of the cellular response to transcriptional inhibition remains incomplete. Here we report that potent inhibitors of transcription not only impact mRNA output, but also markedly impair mRNA transcript localisation and nuclear export.
Read the full summary ↓
We demonstrate that retention of newly transcribed mRNA in nuclear speckles is an adaptive response to chemically distinct transcriptional inhibitors. Retained transcripts are fully processed and accumulate in proportion to the expression level of the genes from which they emanate. The TREX mRNA export complex plays an integral role in directing nascent transcripts to nuclear speckles where they are bound to NXF1, protected from degradation, and poised for rapid export following re-initiation of transcription. Our findings provide new insights into the crosstalk between transcription and mRNA export, with important implications for drugs aiming to inhibit transcription for therapeutic gain.
Published in
mRNA export factors store nascent transcripts within nuclear speckles as an adaptive response to transient global inhibition of transcription
Williams TD, Michalak EM, Carey KT et al. · Molecular cell 2025 · PMID 39753105 · doi:10.1016/j.molcel.2024.12.008
This dataset
Open GSE183570 in finder → Find more human 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 GSE183570_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 PRJNA761339 and SRA study SRP335988. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39753105) ↗
Study design
10 conditions, mostly in triplicate
DMSO Nuc ×3 JQ1 Nuc ×3 JQ1-VHL Nuc ×3 IBET151-VHL Nuc ×3 DMSO Cyto ×3 JQ1 Cyto ×3 JQ1-VHL Cyto ×3 IBET151-VHL Cyto ×3 +2 more

Supports a between-group comparison across 28 samples.

How we read this: 10 replicated groups read from 28 sample titles; they account for 28 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
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