← BioTransfer GEO Dataset Finder
GEO series

Altering metabolism to program cell identity via NAD+ dependent deacetylation [RNA-seq]

GSE173532 Mus musculus (mouse) RNA-seq (gene expression) 30 samples Submitted 2025/04/01 Platform GPL30172Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 30 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
30 samples: 6 conditions, mostly in triplicateGroups 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
Altering metabolism programs cell identity via NAD(+)-dependent deacetylationThe EMBO journal · 2025
Summary (written by the submitters)
Cells change their metabolic profiles in response to an underling gene regulatory network, but how can alterations in metabolism encode specific transcriptional instructions?  Here we show that forcing metabolic change in embryonic stem cells (ESCs) promotes a developmental identity that better approximates the inner cell mass (ICM) of the mammalian blastocyst in cultures we refer to as enhanced metabolic ESCs (EMESCs).
Read the full summary ↓
The creation of EMESCs depends on the inhibition of glycolysis and stimulation of oxidative phosphorylation (OXPHOS), that in turns activates NAD+-dependent deacetlylases of the Sirtuin family.  The activation of this pathway leads to the deacetylation of histones and key transcription factors leading to a revised ICM-like gene regulatory network.  The exploitation of the NAD+/NADH coenzyme normally coupled to elevated OXPHOS to program lineage specific transcription suggests new paradigms for how cells respond to alterations in their environment.
Published in
Altering metabolism programs cell identity via NAD(+)-dependent deacetylation
Bone RA, Lowndes MP, Raineri S et al. · The EMBO journal 2025 · PMID 40281356 · doi:10.1038/s44318-025-00417-0
This dataset
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.

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 GSE173532_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA725905 and SRA study SRP316790. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in triplicate
P10_2iL ×3 P10_EMM ×3 P10_SL ×3 P20_2iL ×3 P20_EMM ×3 P20_SL ×3 Serum_LIF_rep1 (RNA-seq) ×1 Serum_LIF_rep2 (RNA-seq) ×1 +10 more

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 30 sample titles; they account for 18 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

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.