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Mecp2 acts as a key stabilizer of glucocorticoid-induced genes in active chromatin regions [scATAC-Seq]

GSE298162 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 81 samples Submitted 2026/07/31 Platform GPL28330
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 81 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
81 samples: 58 distinct titles, 12 of them repeatedGroups 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)
Mutations in methyl-CpG-binding protein 2 (MECP2) constitute the primary cause of Rett syndrome (RTT). Although Mecp2 is ubiquitously expressed throughout the body, its functional profiling at the pan-tissue and multi-omics levels remains lacking. Here, we obtained transcriptomic and epigenomic profiles of various tissues from wild-type and RTT mice; revealed global hyperactivation of the glucocorticoid (GC)-induced genes (GIGs) following Mecp2 KO.
Read the full summary ↓
Further analysis of the nervous system revealed that non-neuronal cells were more susceptible to abnormalities of the GC system, playing a crucial role in the neurological disturbances of RTT mice. Mechanistically, we found that MECP2 binds to the regulatory elements of active GIGs to suppress their hyperactivation; and competitively inhibits the binding between NR3C1 and NCOA1 to maintain GC system homeostasis. Our study dissects the critical functions of Mecp2 at the epigenomic, transcriptomic, and protein levels, providing new insights into the pathomechanisms of RTT.
This dataset
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.

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 GSE298162_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1257593 and SRA study SRP582582. Searching any of these in the dataset finder brings you back here.

Study design
58 distinct titles, 12 of them repeated
neural_BrainStem_KO ×3 neural_BrainStem_WT ×3 neural_Cerebellum_KO ×3 neural_Cerebellum_WT ×3 neural_Diencephalon_KO ×3 neural_Diencephalon_WT ×3 neural_Pituitary_KO ×3 neural_SpinalCord_KO ×3 +4 more

How we read this: Read from 81 sample titles: 58 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

+ 41 more — browse all 81 samples with per-sample file links →

Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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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.