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Single cell 3'UTR sequencing of neural stem cells

GSE156767 Mus musculus (mouse) Single-cell RNA-seq 14 samples Submitted 2026/05/01 Platform GPL16417Platform GPL21103Platform GPL24247Platform GPL13112
At a glance

Single-cell RNA-seq · mouse · 14 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
14 samples: 2 × Neuro Sphere RIP - WT Input vs 2 × Neuro Sphere RIP - WT IgG vs 2 × Neuro Sphere RIP - WT CPEB4 IP vs 2 × Neuro Sphere RIP - KO CPEB4 IPGroups 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)
In cultured neural stem cells (NSCs) we report 3'UTR shortening in active neural stem cells (NSCs) versus quiescent NSCs. NSCs were treated either with BMP4 or EGF to obtain an equivalent of in vivo active and quiescent NSCs. In addition, we see differential 3'UTR usage between APLP1-/- NSCs and neuroblasts versus wildtype. (In this second experiment hash tag oligos were used to assign single cells to biological replicates.) The sequencing strategy allwos a paired-end mapping approach enabeling 3' peak calling with single cell resolution.
Read the full summary ↓
To access CPEB4 binding to mRNAs, an RNA immunoprecipitation (RIP) assay was carried out in cultured NSCs. Here, CPEB4-bound mRNAs were pulled down with a CPEB4 antibody.
This dataset
Open GSE156767 in finder → Find more mouse 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 GSE156767_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA658998 and SRA study SRP278635. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
2 × Neuro Sphere RIP - WT Input vs 2 × Neuro Sphere RIP - WT IgG vs 2 × Neuro Sphere RIP - WT CPEB4 IP vs 2 × Neuro Sphere RIP - KO CPEB4 IP

Supports a between-group comparison across 8 samples.

How we read this: 4 replicated groups read from 14 sample titles; they account for 8 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
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.