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Enhanced activities of OCT4 and SOX2 facilitates epigenetic reprogramming by modulating cell cycle [scRNA-Seq]

GSE222745 Mus musculus (mouse) Single-cell RNA-seq 422 samples Submitted 2026/01/01 Platform GPL19057

At a glance

Single-cell RNA-seq · mouse · 422 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 422 samples: 5 conditions, mostly with about 94 replicates eachGroups 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: Enhanced Activities of OCT4 and SOX2 Promote Epigenetic Reprogramming by Shortening G1 PhaseAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025

Summary (written by the submitters)

Fusing VP16 transcription activation domain with OCT4 and SOX2 (OvSvK) promoted the generation of induced pluripotency stem cells (iPSCs) by remodeling cell cycle and epigenetic modification. Multiomic analyses revealed that the other 80% upregulated genes experienced increase in H3K4me3 and decrease in H3K27me3 and were enriched with genes which undergo more intensive DNA demethylation during cell proliferation.

Read the full summary ↓

Consistent results were obtained when siCcnd1, siCdkn2a and Ccne1 were screened out and used to mimic the cell cycle remodeling. In summary, these studies set up a correlation between epigenetic modification during cell cycle remodeling and cell fate conversion.

Published in

Enhanced Activities of OCT4 and SOX2 Promote Epigenetic Reprogramming by Shortening G1 Phase

Guo L, Lin J, Ren Q et al. · Advanced science (Weinheim, Baden-Wurttemberg, Germany) 2025 · PMID 40448624 · doi:10.1002/advs.202415528

This dataset

Open GSE222745 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 GSE222745_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 PRJNA913303 and SRA study SRP416233. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40448624) ↗

Study design

5 conditions, mostly with about 94 replicates each

Single-cell RNA-seq day2 cell ×94 Single-cell RNA-seq day3 cell ×89 Single-cell RNA-seq day0 cell ×86 Single-cell RNA-seq day1 cell ×74 Single-cell RNA-seq day4 cell ×57

Supports a between-group comparison across 400 samples.

How we read this: 5 replicated groups read from the first 400 of 422 sample titles; they account for 400 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

GSM6930132 Single-cell RNA-seq day0 cell1 Single-cell RNA-seq day…
GSM6930133 Single-cell RNA-seq day0 cell2 Single-cell RNA-seq day…
GSM6930134 Single-cell RNA-seq day0 cell3 Single-cell RNA-seq day…
GSM6930135 Single-cell RNA-seq day0 cell4 Single-cell RNA-seq day…
GSM6930136 Single-cell RNA-seq day0 cell5 Single-cell RNA-seq day…
GSM6930137 Single-cell RNA-seq day0 cell6 Single-cell RNA-seq day…
GSM6930138 Single-cell RNA-seq day0 cell7 Single-cell RNA-seq day…
GSM6930139 Single-cell RNA-seq day0 cell8 Single-cell RNA-seq day…
GSM6930140 Single-cell RNA-seq day0 cell9 Single-cell RNA-seq day…
GSM6930141 Single-cell RNA-seq day0 cell10 Single-cell RNA-seq day…
GSM6930142 Single-cell RNA-seq day0 cell11 Single-cell RNA-seq day…
GSM6930143 Single-cell RNA-seq day0 cell12 Single-cell RNA-seq day…
GSM6930144 Single-cell RNA-seq day0 cell13 Single-cell RNA-seq day…
GSM6930145 Single-cell RNA-seq day0 cell14 Single-cell RNA-seq day…
GSM6930146 Single-cell RNA-seq day0 cell15 Single-cell RNA-seq day…
GSM6930147 Single-cell RNA-seq day0 cell16 Single-cell RNA-seq day…
GSM6930148 Single-cell RNA-seq day0 cell17 Single-cell RNA-seq day…
GSM6930149 Single-cell RNA-seq day0 cell18 Single-cell RNA-seq day…
GSM6930150 Single-cell RNA-seq day0 cell19 Single-cell RNA-seq day…
GSM6930151 Single-cell RNA-seq day0 cell20 Single-cell RNA-seq day…
GSM6930152 Single-cell RNA-seq day0 cell21 Single-cell RNA-seq day…
GSM6930153 Single-cell RNA-seq day0 cell22 Single-cell RNA-seq day…
GSM6930154 Single-cell RNA-seq day0 cell23 Single-cell RNA-seq day…
GSM6930155 Single-cell RNA-seq day0 cell24 Single-cell RNA-seq day…
GSM6930156 Single-cell RNA-seq day0 cell25 Single-cell RNA-seq day…
GSM6930157 Single-cell RNA-seq day0 cell26 Single-cell RNA-seq day…
GSM6930158 Single-cell RNA-seq day0 cell27 Single-cell RNA-seq day…
GSM6930159 Single-cell RNA-seq day0 cell28 Single-cell RNA-seq day…
GSM6930160 Single-cell RNA-seq day0 cell29 Single-cell RNA-seq day…
GSM6930161 Single-cell RNA-seq day0 cell30 Single-cell RNA-seq day…
GSM6930162 Single-cell RNA-seq day0 cell31 Single-cell RNA-seq day…
GSM6930163 Single-cell RNA-seq day0 cell32 Single-cell RNA-seq day…
GSM6930164 Single-cell RNA-seq day0 cell33 Single-cell RNA-seq day…
GSM6930165 Single-cell RNA-seq day0 cell34 Single-cell RNA-seq day…
GSM6930166 Single-cell RNA-seq day0 cell35 Single-cell RNA-seq day…
GSM6930167 Single-cell RNA-seq day0 cell36 Single-cell RNA-seq day…
GSM6930168 Single-cell RNA-seq day0 cell37 Single-cell RNA-seq day…
GSM6930169 Single-cell RNA-seq day0 cell38 Single-cell RNA-seq day…
GSM6930170 Single-cell RNA-seq day0 cell39 Single-cell RNA-seq day…
GSM6930171 Single-cell RNA-seq day0 cell40 Single-cell RNA-seq day…

+ 382 more — browse all 422 samples with per-sample file links →

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GSE269347 Daunorubicin-induced T cell remodeling facilitates a high antitumor response to PD-1 blockade therapy by promoting the expansion and effector function of CD8+ prolifeating T cells [scRNA-Seq] 16 samples shares facilitates, scrna-seq
GSE296768 Plaque-induced transcriptional reprogramming of microglia towards lymphoid receptor expression protects against Alzheimer's disease [scRNA-seq] 12 samples shares reprogramming, scrna-seq
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