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Stable maintenance of MERVL-positive embryonic stem cells reveals sustained transcriptional programs and enhancer remodeling

GSE268173 Mus musculus (mouse) Single-cell RNA-seq 24 samples Submitted 2026/05/12 Platform GPL21273
At a glance

Single-cell RNA-seq · mouse · 24 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
24 samples: 8 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)
Mouse embryonic stem cells (ESCs) occasionally transit into a rare two-cell-like (2C) state characterized by transient activation of endogenous retroviruses such as MERVL and expression of 2C-specific genes including the Zscan4 cluster. These 2C-like cells (2CLCs) resemble early blastomeres and display expanded developmental potential, but their unstable and sporadic nature has hindered mechanistic studies.
Read the full summary ↓
Here, we demonstrate the transiently stable maintenance of MERVL-positive ESCs that exhibit persistent MERVL expression and activation of 2C-associated genes. Live-cell imaging revealed uniform and sustained MERVL activity in these MERVL-positive ESCs, contrasting with the heterogeneous and transient expression observed in conventional ESCs. Transcriptome profiling demonstrated robust induction of 2C-specific regulatory networks, and embryoid body differentiation combined with machine learning uncovered increased lineage variability and altered developmental trajectories. Single-cell RNA sequencing revealed clear separation of control ESCs from MERVL-positive populations and redistribution across distinct transcriptional states, with Red and Mosaic lines showing graded shifts within a shared transcriptional manifold. Epigenomic profiling further revealed distinct chromatin states, specialized super-enhancer landscapes, and active enhancer marking at MERVL loci. Together, these findings demonstrate that stable maintenance of MERVL-positive ESCs is achievable in vitro, providing a powerful model to dissect ERV-driven transcriptional regulation, epigenomic remodeling, and 2C-like transcriptional and epigenetic programs.
This dataset
Open GSE268173 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 GSE268173_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1114869 and SRA study SRP509313. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
1-19 red, ZHBTc4-2c-tcTomato-HisD, RNA-Seq, ×3 1-5 red, ZHBTc4-2c-tcTomato-HisD, RNA-Seq, ×3 2-10 red, ZHBTc4-2c-tcTomato-HisD, RNA-Seq, ×3 2-1 mosaic, ZHBTc4-2c-tcTomato-HisD, RNA-Seq, ×3 3-2 mosaic, ZHBTc4-2c-tcTomato-HisD, RNA-Seq, ×3 3-1 mosaic, ZHBTc4-2c-tcTomato-HisD, RNA-Seq, ×3 ZHBTc4 mESC Dox noLIF 48h RNA-Seq, ×3 ZHBTc4 mESC noDox RNA-Seq, ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 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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