← BioTransfer GEO Dataset Finder
GEO series

The maternal X chromosome impairs cognition and accelerates brain aging through epigenetic modulation in female mice

GSE200461 Mus musculus (mouse) RNA-seq (gene expression) 30 samples Submitted 2024/11/06 Platform GPL21103Platform GPL21273
At a glance

RNA-seq (gene expression) · mouse · 30 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
30 samples: 30 samples, each with a distinct title — no replicated groupsGroups 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
The maternal X chromosome affects cognition and brain ageing in female miceNature · 2025
Summary (written by the submitters)
To compare gene expression between the materal X (Xm) and paternal X (Xp), we used a flurorescence-based cell sorting to separate the maternal X from the paternal X. Then we performed gene expression analysis using data obtained from RNA-seq of young Xm and Xp cells To compare gene expression between the materal X (Xm) and paternal X (Xp) in neurons from both young and old mice, we used a flurorescence-based cell sorting to separate the maternal X from the paternal X. Then we performed gene expression analysis using data obtained from RNA-seq of young and old Xm and Xp neurons.
Published in
The maternal X chromosome affects cognition and brain ageing in female mice
Abdulai-Saiku S, Gupta S, Wang D et al. · Nature 2025 · PMID 39843739 · doi:10.1038/s41586-024-08457-y
This dataset
Open GSE200461 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 GSE200461_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 PRJNA824602 and SRA study SRP368161. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39843739) ↗
Study design
30 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 30 sample titles: 30 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
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.