GEO series

Targeting CDK12/CYCLIN K induces a gene activation program which is mediated by P-TEFb

GSE316689 Homo sapiens (human) RNA-seq (gene expression) 8 samples Submitted 2026/08/07 Platform GPL30173

At a glance

RNA-seq (gene expression) · human · 8 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: 8 samples: 8 samples, each with a distinct title — no replicated groupsGroups 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 transcription in human cells is a multistep process controlled by coordinated actions of host transcription factors and their associated kinases. Despite major advances, fundamental gaps still remain in understanding how transcriptional programs are dynamically regulated. Gene expression of Human immunodeficiency virus (HIV) is tightly controlled by the cellular transcription machinery, providing a powerful model for studying transcription regulation.

Read the full summary ↓

Such gene expression regulation is clinically significant, as HIV persists in long-lived reservoirs even under antiretroviral therapy. Here, we show that selective targeting of CDK12/CYCLIN K (CCNK) induces a global gene activation program, which is mediated by positive transcription elongation factor b (P-TEFb). CDK12/CCNK targeting reshapes promoter-proximal and gene bodies landscape at chromatin, and promotes release of P-TEFb from its inhibitory 7SK snRNP complex. Additional transcriptomic profiling reveals preferential upregulation of P-TEFb-target genes, accompanied by induction of relatively short genes and repression of CDK12-regulated DNA damage response pathways. In HIV- infected cells, targeting CDK12/CCNK activates a robust viral gene expression, accompanied with latency reversal and importantly, synergistic reactivation effects when combined with latency- reversing agents. Together, these results uncover a previously unrecognized compensatory interplay between transcriptional kinases that rewires the cellular gene expression program with implications for HIV latency reversal and cancer biology.

This dataset

Open GSE316689 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 GSE316689_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 PRJNA1403602 and SRA study SRP662880. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

8 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 8 sample titles: 8 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

GSM9458362 Sample 1 Untreated
GSM9458363 Sample 2 Untreated
GSM9458364 Sample 3 Untreated
GSM9458365 Sample 4 Untreated
GSM9458366 Sample 1 Treated
GSM9458367 Sample 2 Treated
GSM9458368 Sample 3 Treated
GSM9458369 Sample 4 Treated

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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.