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A repeatedly evolved mutation in Cryptochrome-1 of subterranean animals alters behavioral and molecular circadian rhythms

GSE277611 Mus musculus (mouse) RNA-seq (gene expression) 85 samples Submitted 2025/07/23 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 85 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
85 samples: 85 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
A repeatedly evolved mutation in Cryptochrome-1 of subterranean animals alters behavioral and molecular circadian rhythmsiScience · 2025
Summary (written by the submitters)
The repeated evolution of similar phenotypes in independent lineages often occurs in response to similar environmental pressures, through similar or different molecular pathways. Recently, a repeatedly occurring mutation R263Q in a conserved domain of the protein Cryptochrome-1 (CRY1) was reported in multiple species inhabiting subterranean environments.
Read the full summary ↓
Cryptochromes regulate circadian rhythms, and glucose and lipid metabolism. Subterranean species show changes to their circadian rhythm and metabolic pathways, making it likely that this mutation in CRY1 contributes to adaptive phenotypic changes. To identify the functional consequences of the CRY1 R263Q mutation, we generated a mouse model homozygous for this mutation. Indirect calorimetry experiments revealed delayed locomotor activity, energy expenditure and feeding patterns of mutant mice in the dark phase, but no further metabolic phenotypes – unlike a full loss of function of CRY1. Gene expression analyses showed altered expression of several canonical circadian genes in the livers of the mutant mice, fortifying the notion that CRY1 R263Q impacts metabolism. Our data provide the first characterization of a novel mutation that has repeatedly evolved in subterranean environments, supporting the idea that shared environmental constraints can drive the evolution of similar phenotypes through similar genetic changes.
Published in
A repeatedly evolved mutation in Cryptochrome-1 of subterranean animals alters behavioral and molecular circadian rhythms
Swaminathan A, Kenzior A, Price A et al. · iScience 2025 · PMID 40678503 · doi:10.1016/j.isci.2025.112874
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 GSE277611_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 PRJNA1162904 and SRA study SRP533658. Searching any of these in the dataset finder brings you back here.

Study design
85 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 85 sample titles: 85 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

+ 45 more — browse all 85 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.