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NELF prevents widespread transcriptional readthrough into DNA replication zones of cancer cells [TT-seq]

GSE254009 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/12/13 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: 6 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)
Regulation of RNA polymerase II (Pol II) transcription is closely associated with cell proliferation. However, it remains unclear how the Pol II transcription program is rewired in cancer to promote uncontrolled growth. Here, we find that gene expression of NELFCD, a known negative elongation factor, is up-regulated in colorectal tumours.
Read the full summary ↓
To dissect the direct role of NELF-C on Pol II transcription in such cancer, we employed an auxin-dependent protein degradation system for NELF-C in combination with nascent transcript sequencing technologies. Strikingly, we demonstrate that the acute loss of NELF-C protein globally redistributes termination factors and perturbs Pol II transcription termination. These changes drive pervasive Pol II transcription into DNA replication zones leading to transcription-replication conflict that may block the cell cycle in G1 or early S phase. Our findings reveal a previously unrecognised role of NELF in transcription termination and highlight NELF as a potential therapeutic target in colorectal cancer.
This dataset
Open GSE254009 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 GSE254009_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 PRJNA1068108 and SRA study SRP485475. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in duplicate
TT-seq-NELFCAID-DMSO4h-NVP2_0m ×2 TT-seq-NELFCAID-DMSO4h-NVP2_30m ×2 TT-seq-NELFCAID-DMSO4h-NVP2_60m ×2 TT-seq-NELFCAID-Auxin4h-NVP2_0m ×2 TT-seq-NELFCAID-Auxin4h-NVP2_30m ×2 TT-seq-NELFCAID-Auxin4h-NVP2_60m ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 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
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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.