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Mecp2 stabilizes the glucocorticoid system in active chromatin regions [scRNA-Seq]

GSE299346 Mus musculus (mouse) Single-cell RNA-seq 36 samples Submitted 2026/07/31 Platform GPL28330
At a glance

Single-cell RNA-seq · mouse · 36 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
36 samples: 12 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.
Summary (written by the submitters)
Methyl-CpG-binding protein 2 (MECP2), a key epigenetic factor regulating gene expression via DNA/chromatin interactions, causes multisystem disorders when dysfunctional. However, its epigenetic regulatory mechanisms at the pan-tissue and multi-omics levels remain poorly understood. Here, we established comprehensive pan-tissue expression profiles in wild-type and Mecp2-knockout mice, revealing a crucial role for MECP2 in maintaining glucocorticoid (GC) signaling homeostasis.
Read the full summary ↓
Single-cell epigenomic analyses demonstrated widespread increases in chromatin accessibility at GC-induced genes (GIGs) upon Mecp2 deficiency. Through innovative single-cell multi-omics profiling of the nervous system, we further revealed that GIG dysregulation primarily disrupts neural homeostasis via non-neuronal cells. Mechanistically, we identified a dual regulatory mode of MECP2: (1) competitively inhibiting NR3C1 binding to the cis-regulatory elements of GIGs in active chromatin regions, and (2) specifically disrupting NR3C1-NCOA1 coactivator interactions. These findings not only elucidate a novel MECP2-NR3C1-NCOA1 axis in GC system regulation but also suggest potential therapeutic targets for Rett syndrome.
This dataset
Open GSE299346 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 GSE299346_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 PRJNA1270653 and SRA study SRP589102. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
BrainStem_KO ×3 BrainStem_WT ×3 Cerebellum_KO ×3 Cerebellum_WT ×3 Diencephalon_KO ×3 Diencephalon_WT ×3 Pituitary_KO ×3 Pituitary_WT ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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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