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Genomic Convergence in Hibernating Mammals Elucidates the Genetics of Metabolic Regulation in the Hypothalamus [snATACseq]

GSE295866 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2025/08/04 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 20 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
20 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
Genomic convergence in hibernating mammals elucidates the genetics of metabolic regulation in the hypothalamusScience (New York, N.Y.) · 2025
Summary (written by the submitters)
Extreme metabolic adaptations can elucidate genetic programs governing mammalian metabolism. Here we used convergent evolutionary changes in hibernating lineages to define conserved cis-regulatory elements (CREs) and metabolic programs. We characterized mouse hypothalamus gene expression and chromatin dynamics across fed, fasted, and refed states, then used comparative genomics of hibernating versus non-hibernating lineages to identify cis-elements with convergent changes in hibernators.
Read the full summary ↓
Multi-omics approaches pinpointed CREs, hub genes, regulatory programs, and cell types underlying lineage divergence. Hibernators accumulated loss-of-function effects for CREs regulating hypothalamic responses, and the refeeding period after fasting served as a key phase for molecular processes with convergent evolutionary changes. This work provides a genetic framework for harnessing hibernator adaptations to understand human metabolic control.
Published in
Genomic convergence in hibernating mammals elucidates the genetics of metabolic regulation in the hypothalamus
Ferris E, Gonzalez Murcia JD, Rodriguez AC et al. · Science (New York, N.Y.) 2025 · PMID 40743333 · doi:10.1126/science.adp4025
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 GSE295866_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 PRJNA1238491 and SRA study SRP571763. Searching any of these in the dataset finder brings you back here.

Samples in this study

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