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Diurnal control of iron responsive element containing mRNAs through iron regulatory proteins IRP1 and IRP2 is mediated by feeding rhythms

GSE243134 Mus musculus (mouse) RNA-seq (gene expression) 77 samples Submitted 2024/05/01 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 77 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
77 samples: 77 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.
Summary (written by the submitters)
Background: Cellular iron homeostasis is regulated by iron regulatory proteins (IRP1 and IRP2) that sense iron levels (and other metabolic cues) and modulate mRNA translation or stability via interaction with iron regulatory elements (IREs). IRP2 is viewed as the primary regulator in liver, yet our previous datasets showing diurnal rhythms for certain IRE-containing mRNAs suggest a nuanced temporal control mechanism.
Read the full summary ↓
The purpose of this study is to gain insights into the daily regulatory dynamics across IRE-bearing mRNAs, specific IRP involvement, and underlying systemic and cellular rhythmicity cues in mouse liver. Results: We uncover high-amplitude diurnal oscillations in the regulation of key IRE containing transcripts in liver, compatible with maximal IRP activity at the onset of the dark phase. Although IRP2 protein levels also exhibit some diurnal variations and peak at the light-dark transition, ribosome profiling in IRP2-deficient mice reveals that maximal repression of target mRNAs at this time-point still occurs. We further find that diurnal regulation of IRE-containing mRNAs can continue in the absence of a functional circadian clock as long as feeding is rhythmic. Conclusions: Our findings suggest temporally controlled redundancy in IRP activities, with IRP2 mediating regulation of IRE-containing transcripts in the light phase and redundancy, conceivably with IRP1, at dark onset. Moreover, we highlight the significance of feeding-associated signals in driving rhythmicity. Our work highlights the dynamic nature and regulatory complexity in a metabolic pathway that had previously been considered well-understood.
This dataset
Open GSE243134 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 GSE243134_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 PRJNA1016416 and SRA study SRP460298. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
77 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 77 sample titles: 77 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

+ 37 more — browse all 77 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.