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High-throughput mapping of modular regulatory domains in human RNA-binding proteins

GSE303955 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 43 samples Submitted 2025/08/05 Platform GPL21697
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 43 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
43 samples: 13 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)
RNA regulation plays an integral role in tuning gene expression and is controlled by thousands of RNA-binding proteins (RBPs). While some RBPs require most of their sequence to accomplish their functions, some examples exist of modularity: small protein domains that serve as molecular glues to recruit larger RNA regulatory complexes. Mapping these RNA-regulatory effector domains is important for understanding RBP function and for developing compact synthetic tools for precisely tuning RNA levels.
Read the full summary ↓
We developed a high-throughput recruitment assay (HT-RNA-Recruit) to identify RNA-down-regulatory effector domains within human RBPs. By recruiting over 30,000 protein tiles from 367 RBPs to a reporter mRNA, we discovered over 100 unique RNA-down-regulatory effector domains in 86 distinct RBPs. We identified some domains that downregulate gene expression both when recruited to DNA and RNA, and dissected their mechanisms of regulation. Finally, we built inducible synthetic RNA regulators that can target endogenous RNAs or stably maintain reporter gene expression at desired levels, and developed a mathematical model to predict their dynamics. This work serves as a resource for human RNA regulators and expands the synthetic repertoire of RNA-based genetic control tools.
This dataset
Open GSE303955 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 GSE303955_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 PRJNA1112784 and SRA study SRP508324. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
13 conditions, mostly in duplicate
rTetR-KRAB H3K9me3 C+R ×2 MCP-KRAB d0 H3K9me3 C+R ×2 MCP-KRAB d1 H3K9me3 C+R ×2 MCP-NANOS H3K9me3 C+R ×2 RNA-seq MCP alone over expression, B ×2 RNA-seq synNANOS over expression, B ×2 RNA-seq RBFOX-NANOS over expression, B ×2 RNA-seq CPEB2 full-length overexpression, B ×2 +22 more

Supports a between-group comparison across 26 samples.

How we read this: 13 replicated groups read from 43 sample titles; they account for 26 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

+ 3 more — browse all 43 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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