GEO series

PAF1C-dependent activation of CDK12 is required for RNA polymerase II phosphorylation and transcript elongation

GSE281924 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2025/05/19 Platform GPL30173

At a glance

RNA-seq (gene expression) · human · 15 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: 15 samples: 5 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: PAF1C-mediated activation of CDK12/13 kinase activity is critical for CTD phosphorylation and transcript elongationMolecular cell · 2025

Summary (written by the submitters)

The RNA polymerase II (RNAPII) transcription cycle is regulated by dynamic changes in RNAPII C-terminal domain (CTD) phosphorylation, and such modification is crucial for gene expression. However, the mechanisms regulating the transcription-specific cyclin-dependent kinases (CDKs) during the transcription cycle remain poorly understood.

Read the full summary ↓

Here, we show that human CDK12 co-phosphorylates CTD Serine2 and Serine5. This di-phosphorylated Serine2-Serine5 CTD mark can then act as a precursor for Serine2 mono-phosphorylated CTD through Serine5 de-phosphorylation. Notably, CDK12 is specifically regulated by association with the elongation-specific factor PAF1C, in which the CDC73 subunit contains a metazoan-specific peptide motif, capable of allosteric CDK12/Cyclin K activation. This motif is essential for cell proliferation and required for normal cellular levels of CTD phosphorylation. It is also crucial for transcript elongation, particularly across long human genes. Together, these findings provide new insight into the mechanisms governing RNAPII phospho-CTD dynamics that ensure progression through the human transcription cycle.

Published in

PAF1C-mediated activation of CDK12/13 kinase activity is critical for CTD phosphorylation and transcript elongation

Lopez Martinez D, Todorovski I, Noe Gonzalez M et al. · Molecular cell 2025 · PMID 40315851 · doi:10.1016/j.molcel.2025.04.012

This dataset

Open GSE281924 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 GSE281924_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 PRJNA1186184 and SRA study SRP545290. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40315851) ↗

Study design

5 conditions, mostly in triplicate

CON ×3 SI73_DELTA ×3 SI73 ×3 SI73_WT ×3 SI73_YY ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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

GSM8632884 CON_REP1 CON
GSM8632885 CON_REP2 CON
GSM8632886 CON_REP3 CON
GSM8632887 SI73_DELTA_REP1 SI73_DELTA
GSM8632888 SI73_DELTA_REP2 SI73_DELTA
GSM8632889 SI73_DELTA_REP3 SI73_DELTA
GSM8632890 SI73_REP1 SI73
GSM8632891 SI73_REP2 SI73
GSM8632892 SI73_REP3 SI73
GSM8632893 SI73_WT_REP1 SI73_WT
GSM8632894 SI73_WT_REP2 SI73_WT
GSM8632895 SI73_WT_REP3 SI73_WT
GSM8632896 SI73_YY_REP1 SI73_YY
GSM8632897 SI73_YY_REP2 SI73_YY
GSM8632898 SI73_YY_REP3 SI73_YY

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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.