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Identification of a set of transcriptional regulators involved in the temporal regulation of neuron subtype differentiation [RNA-Seq]

GSE310706 Mus musculus (mouse) RNA-seq (gene expression) 23 samples Submitted 2026/03/31 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 23 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
Mus musculus (mouse)
Samples
23 samples: 8 conditions, mostly in triplicateGroups 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
Identification of a set of transcriptional regulators involved in the temporal regulation of neuronal subtype differentiationDevelopmental biology · 2026
Summary (written by the submitters)
The sequential generation of various types of neurons and glia from neural stem /progenitor cells (NSPCs) during development is a major part to build complex central nervous system. Here, we identify PHF21b, ZFP7 and ZFP57 as crucial factors that regulate the transition from early-born neuron to late-born neuron generation by NSPCs in the developing mouse cortex and ganglionic eminence.
Read the full summary ↓
Combinatorial overexpression of these three factors in the stage progressed NSPCs generating late-born neurons resulted in prolonged generation of early-born neurons. Conversely, simultaneous knockdown of these genes suppressed generation of early-born neurons.
Published in
Identification of a set of transcriptional regulators involved in the temporal regulation of neuronal subtype differentiation
Hisamatsu D, Hasegawa H, Naka-Kaneda H et al. · Developmental biology 2026 · PMID 42000103 · doi:10.1016/j.ydbio.2026.04.003
This dataset
Open GSE310706 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 GSE310706_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 PRJNA1366964 and SRA study SRP647230. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42000103) ↗
Study design
8 conditions, mostly in triplicate
cortical NSPCs, 3FOE, Day5, ×3 ganglionic eminence NSPCs, control EGFP, Day5, ×3 ganglionic eminence NSPCs, 3FOE, Day5, ×3 cortical cells, shControl, Day5, ×3 cortical cells, sh3F, Day5, ×3 ganglionic eminence cells, shControl, Day5, ×3 ganglionic eminence cells, sh3F, Day5, ×3 cortical NSPCs, control EGFP, Day5, ×2

Supports a between-group comparison across 23 samples.

How we read this: 8 replicated groups read from 23 sample titles; they account for 23 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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