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Misaligned feeding uncouples daily rhythms within brown adipose tissue and between peripheral clocks

GSE266543 Mus musculus (mouse) RNA-seq (gene expression) 144 samples Submitted 2024/07/25 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 144 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
144 samples: 144 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
Misaligned feeding uncouples daily rhythms within brown adipose tissue and between peripheral clocksCell reports · 2024
Summary (written by the submitters)
Extended consumption of food into the rest period perturbs the phase relationship between circadian clocks in the periphery and the brain and has deleterious effects on health through mechanisms that remain incompletely understood. Beyond the liver, how other metabolic organs respond to hypocaloric diet (amount and timing) is largely unexplored.
Read the full summary ↓
We investigated how feeding time impacts circadian gene expression in white (eWAT) and brown (BAT) adipose tissues in comparison to liver and hypothalamus. With automated feeders, we restricted food to either daytime or nighttime in C57BL/6J male mice, with or without caloric restriction. We found tissue-specific changes in the phase and amplitude of genome-wide mRNA expression patterns induced by daytime feeding in liver and eWAT, whereas BAT exhibited resilience and remained predominately entrained to the light-dark cycle, similar to hypothalamus. We uncovered an internal split within the BAT in response to conflicting environmental cues, displaying inverted oscillations on a subset of metabolic genes without modifying its local core circadian machinery. Integrating intra- and inter-tissue disruptions in circadian clock-controlled transcriptional networks with metabolic outcomes may help elucidate the mechanism underlying the health burden of eating at the wrong time of the day.
Published in
Misaligned feeding uncouples daily rhythms within brown adipose tissue and between peripheral clocks
Acosta-Rodríguez VA, Rijo-Ferreira F, van Rosmalen L et al. · Cell reports 2024 · PMID 39046875 · doi:10.1016/j.celrep.2024.114523
This dataset
Open GSE266543 in finder → Find more mouse RNA-seq 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 GSE266543_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: 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 PRJNA1107553 and SRA study SRP505572. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39046875) ↗
Study design
144 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 144 sample titles: 144 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

+ 104 more — browse all 144 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.