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Distinct hepatocyte adaptations during gestation and lactation [pregnant_liver_mm10_CUT_RUN]

GSE294859 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2025/09/02 Platform GPL34290
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 10 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
10 samples: 3 × mouse hepatocyte,G14.5,WT,CUT&RUN, vs 3 × mouse hepatocyte,G14.5,Il6stHMKO,CUT&RUN, vs 2 × mouse hepatocyte,P4L,WT,CUT&RUN, vs 2 × mouse hepatocyte,P4L,Acss2HMKO,CUT&RUN,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.
Paper
Hepatocyte metabolic adaptations during pregnancy and lactationCell · 2025
Summary (written by the submitters)
Using high-resolution single-cell RNA sequencing, we systematically characterized hepatocyte adaptations in mice across pregnancy and postpartum stages. We discovered a cyclical hepatocyte trajectory (“pregnancy clock”) governing metabolic changes during gestation and postpartum recovery, which reverted to pregestational states in non-lactating mice.
Read the full summary ↓
Lactation induced a distinct branching trajectory characterized by elevated lipid synthesis and export. Deletion of gp130 disrupted hepatic adaptations during pregnancy, impairing fetal growth, whereas ACSS2 deficiency postpartum disrupted lipid export, affecting milk quality and offspring growth.
Published in
Hepatocyte metabolic adaptations during pregnancy and lactation
Yang L, Zhang Y, Yu XX et al. · Cell 2025 · PMID 40882627 · doi:10.1016/j.cell.2025.08.007
This dataset
Open GSE294859 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE294859_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1251711 and SRA study SRP579175. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40882627) ↗
Study design
3 × mouse hepatocyte,G14.5,WT,CUT&RUN, vs 3 × mouse hepatocyte,G14.5,Il6stHMKO,CUT&RUN, vs 2 × mouse hepatocyte,P4L,WT,CUT&RUN, vs 2 × mouse hepatocyte,P4L,Acss2HMKO,CUT&RUN,

Supports a between-group comparison across 10 samples.

How we read this: 4 replicated groups read from 10 sample titles; they account for 10 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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