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Identifying membrane-bound transcriptional regulatory proteins from rare but evolutionarily conserved domain combinations

GSE309766 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 18 samples Submitted 2025/12/18 Platform GPL17021Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 18 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
Mus musculus (mouse)
Samples
18 samples: 18 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
Identifying membrane-bound transcriptional regulatory proteins from rare but evolutionarily conserved domain combinationsbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Transcriptional regulatory proteins, including transcription factors (TFs) and chromatin modifiers, perform their crucial cellular functions inside cell nuclei. However, unlike most TFs, membrane-bound transcription factors (MBTFs) are first anchored in membranes before nuclear translocation. Known MBTFs are vital for processes from myelin expression (MYRF) to cholesterol homeostasis (SREBP), yet their overall diversity remains uncharted.
Read the full summary ↓
We hypothesized that additional membrane-bound transcriptional regulators (MBTRs) might exist and developed a bioinformatics screen that prioritizes membrane proteins likely to regulate transcription. Our approach leverages domain composition, assuming that surprising domain combinations suggest novel biological functions. We searched for rare but evolutionarily conserved combinations of transmembrane domains paired with domains likely involved in transcriptional regulation. Our method rediscovered known MBTFs and membrane-bound histone kinases, and identified novel MBTR candidates, including histone N-acetyltransferases and the prolactin regulatory element-binding protein PREB. Experimental validation indicates that PREB may undergo cleavage. Without its transmembrane domain, PREB exhibits nuclear localization and chromatin association in mouse embryonic stem cells. Furthermore, we identified a putative class of new MBTFs that share MYRF's DNA-binding domain. These findings underscore the utility of our method and provide a framework for investigating MBTRs that likely facilitate the integration of extracellular signals with transcriptional responses.
Published in
Identifying membrane-bound transcriptional regulatory proteins from rare but evolutionarily conserved domain combinations
Lee M, Jang Y, Guo Q et al. · bioRxiv : the preprint server for biology 2025 · PMID 41446247 · doi:10.64898/2025.12.20.695554
This dataset
Open GSE309766 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE309766_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1363143 and SRA study SRP644292. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41446247) ↗
Study design
18 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 18 sample titles: 18 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
Datasets on a similar topic

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