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Novel Single-Cell Multiomics Approach to Analyze Replication Timing and Gene Expression in Mouse Preimplantation Embryos

GSE284010 Mus musculus (mouse) Single-cell RNA-seq 248 samples Submitted 2025/06/16 Platform GPL30172
At a glance

Single-cell RNA-seq · mouse · 248 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
248 samples: 248 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
Single cell multiomics approach to analyze replication timing and gene expression in mouse preimplantation embryosCommunications biology · 2025
Summary (written by the submitters)
Analysis of a cell’s replication timing (RT) provides insight into how genes replicate, early or late, during the S-phase of the cell cycle. RT is cell-type specific, inheritable, and has been correlated to gene expression in normal and diseased states. However, most studies have been limited to somatic cells. Very little is known about RT in early mouse embryos, and how it correlates with the start of transcription during zygote gene activation (ZGA), at the 2-cell stage.
Read the full summary ↓
In this study, we used a novel in-house single-cell multiomics approach to simultaneously analyze RT and gene expression in individual cells of the mouse 1-cell, 2-cell, and 4-cell embryos. We demonstrated that RT was established at the 1-cell stage prior to ZGA. Surprisingly, we observed RT and gene expression correlation trends that were different in early totipotent embryos, compared to previously published studies in somatic cells. Late replicating regions correlated with higher gene expression and open chromatin in the early developing embryos. Lastly, we performed an integrated pseudo time trajectory analysis combining RT and gene expression information per cell.
Published in
Single cell multiomics approach to analyze replication timing and gene expression in mouse preimplantation embryos
Shetty AV, Steer CJ, Low WC · Communications biology 2025 · PMID 40830419 · doi:10.1038/s42003-025-08694-5
This dataset
Open GSE284010 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 GSE284010_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 PRJNA1196829 and SRA study SRP550933. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40830419) ↗
Study design
248 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 248 sample titles: 248 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

+ 208 more — browse all 248 samples with per-sample file links →

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.