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Establishment of sex-specific liver transcriptomes and H3K9me3 profiles during sexual maturity: the impact of maternal obesity [ChIP-seq]

GSE304113 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 36 samples Submitted 2025/11/01 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 36 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
36 samples: 36 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
Establishment of sex-specific liver transcriptomes and H3K9me3 profiles during sexual maturity: the impact of maternal obesityBiology of sex differences · 2025
Summary (written by the submitters)
The escalating prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is strongly linked to rising obesity rates. Maternal obesity (MO) increases offspring susceptibility to metabolic disorders, including MASLD. This elevated risk could be a consequence of epigenetic modifications established during fetal development, a period highly sensitive to the maternal diet.
Read the full summary ↓
H3K9me3, a heterochromatin hallmark, silences gene programs dispensable for differentiated cell types. This study investigated how MO influences sex-specific gene expression and chromatin architecture in offspring liver. Female mice consumed a Western-style or control diet pre-pregnancy and throughout gestation/lactation. Offspring were weaned at 3 weeks and transitioned to chow for five weeks. At 3 weeks, liver transcriptomes of control offspring were similar between sexes. However, MO significantly disrupted hepatic gene expression in both sexes, dysregulating hundreds of genes and altering H3K9me3 binding. By 8 weeks, with sexual maturity, control offspring showed substantial sex-based gene expression divergence, predominantly genes involved in immune response, cell adhesion, xenobiotic detoxification, cholesterol metabolism, and lipid partitioning. Thousands of differentially bound H3K9me3 peaks were also observed between 3 and 8 weeks, with many on the female X chromosome. Remarkably, by 8 weeks, MO offspring showed incomplete normalization of gene expression, H3K9me3 profiles, and hepatic lipid classes, emphasizing the persistent impact of maternal diet on the genomic and metabolic landscape. This study highlights inherent sex differences in liver gene expression and suggests H3K9me3's role in establishing sex-specific liver function during sexual maturation. Moreover, MO disrupts these patterns, which are not fully corrected by postnatal dietary normalization.
Published in
Establishment of sex-specific liver transcriptomes and H3K9me3 profiles during sexual maturity: the impact of maternal obesity
Yadav AK, Harris-Kawano A, Saxena R et al. · Biology of sex differences 2025 · PMID 41121265 · doi:10.1186/s13293-025-00767-8
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 GSE304113_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 PRJNA1298935 and SRA study SRP604665. Searching any of these in the dataset finder brings you back here.

Study design
36 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 36 sample titles: 36 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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