GEO series

Integrative analysis of RNA binding proteins identifies DDX55 as a novel regulator of 3’UTR isoform diversity

GSE293802 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/08/19 Platform GPL34295

At a glance

RNA-seq (gene expression) · human · 18 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: 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: Integrative analysis of RNA binding proteins identifies DDX55 as a novel regulator of 3'UTR isoform diversitybioRxiv : the preprint server for biology · 2025

Summary (written by the submitters)

The 3’ untranslated regions (3’UTRs) of mRNAs play a critical role in controlling gene expression and function because they contain binding sites for microRNAs and RNA binding proteins (RBPs) that alter mRNA stability, localization, and translation. Most mRNA 3’ ends contain multiple polyadenylation sites (PAS) that can be utilized in condition-specific manners, a process known as alternative polyadenylation (APA), however the mechanisms driving the regulation of APA remain poorly characterized.

Read the full summary ↓

By integrating a large set of over 500 RNA binding protein (RBP) depletion and binding experiments across two cell lines generated by the ENCODE consortium, we uncovered a number of RBPs in each cell type whose depletion leads to widespread alteration of 3’ UTR patterns. These include not only known regulators of APA, but also many putative novel regulators of 3’UTR isoform expression. We focused analysis on the largely unstudied DEAD box RNA helicase, DDX55, and validate its novel role in 3’UTR isoform regulation using molecular assays and targeted 3’ end sequencing experiments (QuantSeq REV V2, Lexogen). Our findings identify DDX55 as a new regulator of APA, particularly at PAS that contain features of RNA secondary structure. Our data also suggest additional previously unrecognized regulators of 3’ UTR processing and differential stability.

Published in

Integrative analysis of RNA binding proteins identifies DDX55 as a novel regulator of 3'UTR isoform diversity

Gazzara MR, Cater T, Mallory MJ et al. · bioRxiv : the preprint server for biology 2025 · PMID 40654921 · doi:10.1101/2025.05.06.652471

This dataset

Open GSE293802 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 GSE293802_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 PRJNA1246408 and SRA study SRP576460. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40654921) ↗

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

GSM8890250 HepG2 siControl replicate 1 QuantSeq Rev V2 3'end seq of whole cell RNA
GSM8890251 HepG2 siControl replicate 2 QuantSeq Rev V2 3'end seq of whole cell RNA
GSM8890252 HepG2 siControl replicate 3 QuantSeq Rev V2 3'end seq of whole cell RNA
GSM8890253 HepG2 siDDX55 replicate 1 QuantSeq Rev V2 3'end seq of whole cell RNA
GSM8890254 HepG2 siDDX55 replicate 2 QuantSeq Rev V2 3'end seq of whole cell RNA
GSM8890255 HepG2 siDDX55 replicate 3 QuantSeq Rev V2 3'end seq of whole cell RNA
GSM8890256 HepG2 siControl replicate 1 QuantSeq Rev V2 3'end seq of nuclear RNA
GSM8890257 HepG2 siControl replicate 2 QuantSeq Rev V2 3'end seq of nuclear RNA
GSM8890258 HepG2 siControl replicate 3 QuantSeq Rev V2 3'end seq of nuclear RNA
GSM8890259 HepG2 siDDX55 replicate 1 QuantSeq Rev V2 3'end seq of nuclear RNA
GSM8890260 HepG2 siDDX55 replicate 2 QuantSeq Rev V2 3'end seq of nuclear RNA
GSM8890261 HepG2 siDDX55 replicate 3 QuantSeq Rev V2 3'end seq of nuclear RNA
GSM8890262 HepG2 siControl replicate 1 QuantSeq Rev V2 3'end seq of cytoplasmic RNA
GSM8890263 HepG2 siControl replicate 2 QuantSeq Rev V2 3'end seq of cytoplasmic RNA
GSM8890264 HepG2 siControl replicate 3 QuantSeq Rev V2 3'end seq of cytoplasmic RNA
GSM8890265 HepG2 siDDX55 replicate 1 QuantSeq Rev V2 3'end seq of cytoplasmic RNA
GSM8890266 HepG2 siDDX55 replicate 2 QuantSeq Rev V2 3'end seq of cytoplasmic RNA
GSM8890267 HepG2 siDDX55 replicate 3 QuantSeq Rev V2 3'end seq of cytoplasmic RNA

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