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Translational changes upon aging and dietary restriction in progeroid DNA-repair-deficient mice

GSE288427 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/04/20 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 6 conditions, mostly with about 4 replicates eachGroups 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)
Aging is a complex multifactorial phenomenon largely driven by damaged macromolecules. We showed recently that with aging time- and exposure-dependent accumulation of DNA damage derails the basal process of transcription physically stalling RNA polymerase, lowering and skewing the transcriptional landscape in a gene-length-dependent fashion.
Read the full summary ↓
However, how this influences the translational output and whether translation is similarly affected is largely unknown. Here, we present a parallel analysis of transcriptional and translational liver profiles from the well-characterized Ercc1Δ/− progeroid, DNA repair-deficient mouse model compared to wildtype under ad libitum conditions and upon dietary restriction (DR), which strongly delays aging in this mutant. Using ribosome profiling, we found that transcriptional changes during accelerated, normal, and delayed aging are largely preserved at the translational level ruling out a major translational impact on gene expression in aging. Moreover, in both Ercc1Δ/− and aged wild-type mice there was a prioritization of inflammation, metabolic redesign, and expression of translation initiation factors, along with a shift in codon occupancy. While translation initiation factors were further increased by DR, codon occupancy was partially normalized showing a discordant response. Additionally, increased ribosomal pausing and a relative reduction of upstream open reading frame expression were both further intensified by DR. Together these data infer a finetuning of the translational output, e.g. by regulating upstream open reading frames under various cellular stress situations. This study uncovers a complex interplay between DR, DNA damage, aging, and translational regulation, highlighting the potential of DR to modify DNA damage-driven translational dynamics during aging.
This dataset
Open GSE288427 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 GSE288427_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 PRJNA1217452 and SRA study SRP560780. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 4 replicates each
Liver Ercc1 d/- 30% DR 16wks # ×4 Liver Ercc1 +/+ AL 16wks # ×4 Liver Ercc1 d/- AL 16wks # ×4 Liver Ercc1 d/- AL 7wks # ×4 Liver Ercc1 +/+ AL 104wks # ×4 Liver Ercc1 +/+ 30% DR 16wks # ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 sample titles; they account for 24 of them. 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
Datasets on a similar topic

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