GEO series

Female-specific m6A remodeling in the liver correlates with post-transcriptional metabolic adaptation to high fat diet

GSE335522 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/06/19 Platform GPL34328

At a glance

RNA-seq (gene expression) · mouse · 16 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: 16 samples: 4 × male, normal diet, vs 4 × male, high fat diet, vs 4 × female, normal diet, vs 4 × female, high fat diet,Groups 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)

Sex differences strongly influence susceptibility to metabolic dysfunction-associated steatotic liver disease (MASLD), yet the regulatory mechanisms underlying these differences remain incompletely understood. To examine sex-specific hepatic adaptation to high-fat (HF) diet mouse model of MASLD, we integrated proteomics, transcriptomics, and Oxford Nanopore direct RNA sequencing for transcriptome-wide m6A profiling in male and female mouse livers.

Read the full summary ↓

Female mice were relatively protected from HF diet–induced hepatic steatosis and exhibited distinct proteome remodeling enriched for peroxisomal pathways. In contrast, transcriptomic responses in females were dominated by inflammatory signatures and did not recapitulate the metabolic adaptations observed at the protein level, revealing extensive RNA–protein discordance and post-transcriptional remodeling. Integrated RNA–protein analyses identified female-specific amplification of peroxisomal proteins despite modest transcript-level changes. HF diet also induced sex-specific remodeling of m6A RNA methylation and altered regulation of the m6A methylation system. Notably, reduced 3′ UTR m6A methylation in female peroxisomal transcripts inversely correlated with increased protein abundance relative to RNA expression. Together, these findings implicate m6A-associated post-transcriptional regulation in sex-specific hepatic adaptation to HF diet exposure and the basis for discordance between many of the mRNAs and proteins in the liver.

This dataset

Open GSE335522 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 GSE335522_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 PRJNA1478688 and SRA study SRP709769. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

4 × male, normal diet, vs 4 × male, high fat diet, vs 4 × female, normal diet, vs 4 × female, high fat diet,

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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

GSM9814986 male, normal diet, replicate 4 male, normal diet,
GSM9814987 male, normal diet, replicate 3 male, normal diet,
GSM9814988 male, normal diet, replicate 2 male, normal diet,
GSM9814989 male, normal diet, replicate 1 male, normal diet,
GSM9814990 male, high fat diet, replicate 4 male, high fat diet,
GSM9814991 male, high fat diet, replicate 3 male, high fat diet,
GSM9814992 male, high fat diet, replicate 2 male, high fat diet,
GSM9814993 male, high fat diet, replicate 1 male, high fat diet,
GSM9814994 female, normal diet, replicate 4 female, normal diet,
GSM9814995 female, normal diet, replicate 3 female, normal diet,
GSM9814996 female, normal diet, replicate 2 female, normal diet,
GSM9814997 female, normal diet, replicate 1 female, normal diet,
GSM9814998 female, high fat diet, replicate 4 female, high fat diet,
GSM9814999 female, high fat diet, replicate 3 female, high fat diet,
GSM9815000 female, high fat diet, replicate 2 female, high fat diet,
GSM9815001 female, high fat diet, replicate 1 female, high fat diet,

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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.