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Maf1 cooperates with progesterone receptors to repress RNA polymerase III transcription of select tRNAs

GSE283978 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 54 samples Submitted 2025/09/29 Platform GPL24676Platform GPL34284
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 54 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
54 samples: 54 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.
Paper
Maf1 cooperates with progesterone receptor to repress RNA polymerase III transcription of select tRNAsNucleic acids research · 2025
Summary (written by the submitters)
Progesterone receptors (PR) can regulate transcription by RNA Polymerase III (Pol III), which transcribes small non-coding RNAs, including all transfer RNAs (tRNAs). Previous work demonstrated that PR associates with the Pol III complex at tRNA genes and that progestins downregulate tRNA transcripts in breast tumor models. To further elucidate the mechanism of PR-mediated regulation of Pol III, we performed ChIP-seq for PR, the Pol III subunit POLR3A, the TFIIIB component Brf1, and the Pol III repressor Maf1 in breast cancer cells with or without progestin treatment.
Read the full summary ↓
Upon progestin exposure, PR localized to approximately half of POLR3A-occupied tRNA genes, with Maf1 co-recruited to many of these PR-POLR3A sites. While progestin treatment did not significantly alter the number of tRNA genes occupied by Pol III or Brf1, Brf1 occupancy was stabilized, as indicated by increased peak amplitudes. Analysis of nascent tRNA transcription revealed a specific progestin-induced downregulation of approximately one-third of highly expressed tRNA genes. This repression was significantly reduced by Maf1 knockdown, indicating that Maf1 is necessary for PR-mediated tRNA downregulation. Additionally, PR co-immunoprecipitated with Maf1 along with Brf1 and POLR3A. Overall, these findings demonstrate a ligand-dependent PR-mediated repression of tRNA transcription through Maf1.
Published in
Maf1 cooperates with progesterone receptor to repress RNA polymerase III transcription of select tRNAs
Finlay-Schultz J, Vinod Paul K, Erickson B et al. · Nucleic acids research 2025 · PMID 41206048 · doi:10.1093/nar/gkaf1176
This dataset
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.

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 GSE283978_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1196441 and SRA study SRP550589. Searching any of these in the dataset finder brings you back here.

Study design
54 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 54 sample titles: 54 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

+ 14 more — browse all 54 samples with per-sample file links →

Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag 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.