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Transcriptomic and epigenomic profiling of Tet TKO neural stem cells to study NSC specification and multipotency

GSE248933 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 36 samples Submitted 2024/07/23 Platform GPL19057Platform GPL28457Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 36 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
36 samples: 14 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.
Paper
Developmental DNA demethylation is a determinant of neural stem cell identity and gliogenic competenceScience advances · 2024
Summary (written by the submitters)
In this study we: (1) identify genes deregulated in wildtype (WT) and Tet triple knockout (TKO) mouse embryonic stem cells (ESC) and neural stem cells (NSC). (2) Profile genome-wide changes in DNA methylation in WT and TKO ESCs and NSCs. (3) Map histone marks H3K4me1 and H3K27ac in WT and TKO ESCs and NSCs. (4) Identify promoter-interacting chromatin loops in WT and TKO NSCs.
Published in
Developmental DNA demethylation is a determinant of neural stem cell identity and gliogenic competence
MacArthur IC, Ma L, Huang CY et al. · Science advances 2024 · PMID 39196941 · doi:10.1126/sciadv.ado5424
This dataset
Open GSE248933 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 GSE248933_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 PRJNA1046471 and SRA study SRP474956. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39196941) ↗
Study design
14 conditions, mostly in duplicate
Tet_WT_ESC_RNAseq ×3 Tet_WT_NSC_RNAseq ×3 Tet_TKO_ESC_RNAseq ×2 Tet_TKO_NSC_RNAseq ×2 Tet_WT_ESC_H3K4me1_CUT&Tag ×2 Tet_TKO_ESC_H3K4me1_CUT&Tag ×2 Tet_WT_ESC_H3K27ac_CUT&Tag ×2 Tet_TKO_ESC_H3K27ac_CUT&Tag ×2 +12 more

Supports a between-group comparison across 30 samples.

How we read this: 14 replicated groups read from 36 sample titles; they account for 30 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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