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N6-methyladenosine and the NEXT complex direct Xist RNA turnover and X inactivation dynamics [ChrRNA-seq_XistDelm6A]

GSE300223 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/06/22 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 12 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
m(6)A and the NEXT complex direct Xist RNA turnover and X-inactivation dynamicsNature structural & molecular biology · 2025
Summary (written by the submitters)
X chromosome inactivation (XCI) in mammals is orchestrated by the non-coding RNA Xist which together with specific interacting proteins, functions in cis to silence an entire X chromosome. Defined sites on Xist RNA carry the N6-methyladenosine (m6A) modification, and perturbation of the m6A writer complex has been found to abrogate Xist-mediated gene-silencing.
Read the full summary ↓
However, the relative contribution of m6A and its mechanism of action remain unclear. Here we re-investigate the role of m6A in XCI by applying rapid degron-mediated depletion of METTL3, the catalytic subunit of the m6A writer complex, an approach that minimises indirect effects due to transcriptome-wide depletion of m6A. In contrast to prior studies, we find that acute loss of METTL3/m6A accelerates Xist-mediated gene silencing, and that this correlates with increased levels and stability of Xist transcripts. We show that Xist RNA turnover is mediated by the nuclear exosome targeting (NEXT) complex but is independent of the major nuclear m6A reader protein YTHDC1. Our findings demonstrate that the primary function of m6A on Xist RNA is to promote Xist RNA turnover which in turn regulates XCI dynamics.
Published in
m(6)A and the NEXT complex direct Xist RNA turnover and X-inactivation dynamics
Wei G, Coker H, Rodermund L et al. · Nature structural & molecular biology 2025 · PMID 40926104 · doi:10.1038/s41594-025-01663-w
This dataset
Open GSE300223 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 GSE300223_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 PRJNA1279867 and SRA study SRP593531. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40926104) ↗
Study design
12 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 12 sample titles: 12 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

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