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Interplay between Genetic Variation and Nutrition Challenge Controls Hepatic Diurnal Rhythms [RNA-seq]

GSE278920 Mus musculus (mouse) RNA-seq (gene expression) 108 samples Submitted 2025/08/25 Platform GPL19057Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 108 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
108 samples
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
Genetics-nutrition interactions control diurnal enhancer-promoter dynamics and liver lipid metabolismCell metabolism · 2025
Summary (written by the submitters)
Variation in diurnal rhythms contributes to the risk of multiple diseases, yet the genomic and epigenomic basis remains largely unknown. Here, we show that SNPs in enhancer and promoter regions genome-wide contribute to variations in human diurnal rhythms. Differential rhythmic gene expression and physiological responses to diet-induced obesity in mice with different genetic backgrounds are linked to time-dependent enhancer-promoter interactions (EPI) regulated by cis-regulatory SNPs and transcription factors (TFs) like ESRRγ.
Read the full summary ↓
Hepatocyte-specific Esrrγ knockout alters rhythmic processes in liver, including triglyceride synthesis and lipid droplet formation, across mouse strains. Moreover, motifs of ESRRγ and other lipid metabolism-related TFs are enriched in individual-specific EPIs harboring SNPs to control rhythmic genes in patients with MAFLD. SNPs located in these sites are correlated with hepatic metabolic traits. Thus, SNPs and TFs interdependently form the genomic and epigenomic basis for diurnal rhythm variation, contributing to disease risk.
Published in
Genetics-nutrition interactions control diurnal enhancer-promoter dynamics and liver lipid metabolism
Zhou D, Chen Y, Liu P et al. · Cell metabolism 2025 · PMID 40858101 · doi:10.1016/j.cmet.2025.07.010
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 GSE278920_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: 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 PRJNA1169622 and SRA study SRP536901. Searching any of these in the dataset finder brings you back here.

Samples in this study

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