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Lifelong restriction of dietary valine has sex-specific benefits for health and lifespan in mice

GSE298741 Mus musculus (mouse) RNA-seq (gene expression) 105 samples Submitted 2026/05/11 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 105 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
105 samples: 105 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)
Dietary protein has emerged as a key regulator of metabolic health in humans and rodents. Many of the benefits of protein restriction (PR) are mediated by reduced consumption of dietary branched-chain amino acids (BCAAs; leucine, valine and isoleucine), and restriction of BCAAs is sufficient to extend healthspan and lifespan in mice. The metabolic benefits of BCAA restriction are mediated by isoleucine and valine, with isoleucine restriction being sufficient to extend lifespan in male mice.
Read the full summary ↓
However, the effect of valine restriction on healthy aging remains unknown. In this study, we placed young C57BL/6J mice of both sexes on either control or valine restricted (Val-R) diets and followed them longitudinally as they aged. We found that Val-R-fed male and female mice displayed significantly improved glucose regulation and increased energy expenditure, coinciding with decreased body weight and adiposity. These benefits are independent of FGF21, and mTORC1, signaling pathways associated with metabolism and aging. Further, we performed transcriptomic analysis on the liver, muscle and brown adipose tissue, and found tissue- and sex-specific changes in response to Val-R. Lastly, Val-R reduces frailty and extends the median lifespan of male, but not female, mice by 19%. Our results demonstrate that Val-R improves multiple aspects of health in mice of both sexes and extends lifespan in males, and suggests that interventions that mimic Val-R may have translational potential for aging and age-related diseases.
This dataset
Open GSE298741 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 GSE298741_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 PRJNA1271044 and SRA study SRP589299. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
105 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 105 sample titles: 105 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

+ 65 more — browse all 105 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.