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Generation of cellular diversity through temporal patterning of radial glia during mouse corticogenesis I

GSE276209 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 33 samples Submitted 2024/09/03 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 33 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
Mus musculus (mouse)
Samples
33 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)
Neural cell type diversity arises from both spatial and temporal patterning of neural stem cells. Although spatial patterning mechanisms have been extensively studied, temporal patterning mechanisms remain relatively unexplored. In this study, we addressed generation of diverse neural cell types through lineage progression of mouse cortical radial glia.
Read the full summary ↓
The time series scRNA-seq and snATAC-seq of mouse cortical development revealed that radial glia temporally transitioned from neurogenesis to gliogenesis. During gliogenic stages, various cell types were generated simultaneously along multidirectional lineage trajectories. We established comprehensive molecular maps for cortical lineage commitment and cellular diversification. The transcriptome and epigenome of cortical radial glia exhibit temporal dynamics, as revealed by scRNA-seq and snATAC-seq. Lhx2, a transcription factor with temporal dynamic chromatin binding activities, was identified as a key regulator of the neurogenesis-to-gliogenesis transition. It maintains neurogenic competence by establishing the active epigenetic state of its target genes.
This dataset
Open GSE276209 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 GSE276209_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 PRJNA1155709 and SRA study SRP530103. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
13 conditions, mostly in duplicate
E13_Lhx2 ×2 E15_Lhx2 ×2 E18_FT_Lhx2 ×2 E15_ATAC_WT ×2 E15_ATAC_Lhx2cKO ×2 E15_FT_ATAC_WT ×2 E15_FT_ATAC_Lhx2cKO ×2 E15_H3K4me3_WT ×2 +12 more

Supports a between-group comparison across 26 samples.

How we read this: 13 replicated groups read from 33 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
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.