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Redox Heterogeneity in Mouse Embryonic Stem Cells Individualizes Cell Fate Decisions I

GSE244777 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2024/07/07 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 27 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
27 samples: 9 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.
Summary (written by the submitters)
How cellular diversity is created is a key question in biology. Embryonic stem cells (ESCs) are pluripotent cells that can develop into any cell type in the body. Yet, the regulatory mechanisms that govern cell fate decisions remain largely unknown. Moreover, although genetically identical, individual ESCs are strikingly heterogeneous regarding their differentiation capacity but the molecular basis for this phenotypic heterogeneity is unclear.
Read the full summary ↓
We now demonstrate that pluripotent mouse ESCs (mESCs) display large natural variations in mitochondrial reactive oxygen species (ROS) levels that individualize their nuclear redox state and redox-sensitive H3K4me3 landscape. By using intracellular redox probes, we sorted pluripotent and differentiating mESCs based on their nuclear redox environments into subpopulations and analysed their differentiation capacity. We show that more reduced mESCs are biased towards the mesendodermal fate and form the primitive streak upon differentiation. This mesendodermal specification is due to increased Wnt signaling pathway activity, mediated via a ROS-specific regulatory mechanism of p53-dependent expression of the Wnt ligand Wnt3, and increased H3K4me3 levels. We demonstrate that formation of a primitive streak-like structure by differentiating mESCs is initiated by increased mitochondrial ROS and p53 stabilization, followed by antioxidant Nrf2 response pathway activation that leads to a reduced nuclear redox environment, allowing for the accumulation of ROS-sensitive H3K4me3 marks and activation of Wnt3 and other mesendoderm-related gene expression. In summary, our study shows that natural variations in endogenous ROS levels individualize the H3K4me3 landscape of mESCs, and through gene expression changes govern their cell fate decision at the onset of gastrulation.
This dataset
Open GSE244777 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 GSE244777_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 PRJNA1024535 and SRA study SRP464765. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 conditions, mostly in triplicate
Pluripotent E14Tg2a cells, untreated, timepoi… ×3 Pluripotent E14Tg2a cells, hydrogen peroxide … ×3 Pluripotent E14Tg2a cells, hydrogen peroxide … ×3 Pluripotent E14Tg2a cells, hydrogen peroxide … ×3 Pluripotent E14Tg2a cells, hydrogen peroxide … ×3 Pluripotent E14Tg2a cells, hydrogen peroxide … ×3 Pluripotent E14Tg2a cells, hydrogen peroxide … ×3 Pluripotent E14Tg2a cells, hydrogen peroxide … ×3 +1 more

Supports a between-group comparison across 27 samples.

How we read this: 9 replicated groups read from 27 sample titles; they account for 27 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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