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Depletion of individual dietary amino acids induces distinct metabolic and chromatin states

GSE314023 Mus musculus (mouse) RNA-seq (gene expression) 60 samples Submitted 2025/12/17 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 60 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
60 samples: 60 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
Depletion of individual dietary amino acids induce distinct metabolic and chromatin statesThe Journal of biological chemistry · 2026
Summary (written by the submitters)
Reducing dietary levels of protein or specific essential amino acids (EAAs) promotes favorable metabolic reprogramming, including improved glucose tolerance, increased insulin sensitivity and reduced fat mass. However, the extent to which shared or EAA-specific mechanisms facilitate diet-associated phenotypes remains unclear. Here, we compared the physiological and molecular responses to dietary levels of methionine, leucine, and isoleucine by feeding C57BL/6J mice diets in which each of these specific AAs is depleted.
Read the full summary ↓
Dietary depletion of Met, Leu, or Ile (Met-D, Leu-D, or Ile-D) elicited distinct, AA-specific physiological and hepatic molecular (transcriptome, metabolome, histone proteome) responses that were not phenocopied by mTORC1 inhibition via rapamycin treatment. Ile-D yielded the most distinct and dramatic responses, highlighted by expression of select chromatin modifying and metabolic enzymes that led to a prominent epigenetic state of histone H2A/H4 hypoacetylation and maintained hepatic acetyl-CoA levels despite downregulated β-oxidation. Multi-Omics Factor Analysis of 14,139 data points objectively affirmed Ile-D phenotypes are distinct from Met-D or Leu-D and identified metabolic and chromatin features as primary discriminators. We further demonstrated the metabolic and epigenetic responses to Ile-D can be recapitulated in vitro, suggesting that these responses are cell intrinsic. Together, these results demonstrate that dietary depletion of EAAs induce unique phenotypes and highlight distinct molecular mechanisms by which individual EAAs may control metabolic health.
Published in
Depletion of individual dietary amino acids induce distinct metabolic and chromatin states
Haws SA, Liu Y, Green CL et al. · The Journal of biological chemistry 2026 · PMID 41419194 · doi:10.1016/j.jbc.2025.111074
This dataset
Open GSE314023 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 GSE314023_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 PRJNA1389563 and SRA study SRP655784. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41419194) ↗
Study design
60 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 60 sample titles: 60 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

+ 20 more — browse all 60 samples with per-sample file links →

Datasets on a similar topic

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