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Intermolecular 3′UTR-3′UTR interactions drive Wnt gene activation through heteromeric protein assembly

GSE329836 Homo sapiens (human) RNA-seq (gene expression) 29 samples Submitted 2026/05/05 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 29 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
29 samples: 29 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)
Stem cell differentiation depends on transcription factors that are often encoded by mRNAs with highly conserved 3′UTRs. To determine their functional roles, we performed 3′UTR loss-of-function studies. Partial deletion of endogenous 3′UTRs altered stem cell differentiation efficiency in 7/10 cases. As 6/7 3′UTR deletions did not affect expression level of the encoded proteins, we reveal widespread abundance-independent regulatory roles of 3′UTRs.
Read the full summary ↓
For example, 3′UTR deletion of CTNNB1, an mRNA that encodes the essential Wnt co-activator β-catenin, keeps β-catenin levels unaffected but impairs zebrafish embryogenesis and induction of the Wnt transcriptional program during human stem cell differentiation. We show that long intermolecular 3′UTR-3′UTR interactions between Wnt transcription factor mRNAs and CTNNB1 enable co-translational protein complex assembly of these transcription factors with β-catenin. As antisense oligonucleotide-mediated blocking of 3′UTR interactions impairs Wnt program induction, our findings indicate that transcriptional regulators can form functional units during protein biogenesis to be fully active.
This dataset
Open GSE329836 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 GSE329836_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 PRJNA1461925 and SRA study SRP697215. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
29 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 29 sample titles: 29 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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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.