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Targeted CRISPR-Cas9 screening identifies core transcription factors controlling murine haemato-endothelial fate commitment [RNA-seq]

GSE302791 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/10/12 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 3 × DN vs 3 × PD_SP vs 3 × DP_priMes vs 3 × F_SP_HEMGroups 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
Targeted CRISPR-Cas9 screening identifies core transcription factors controlling murine haemato-endothelial fate commitmentNature communications · 2025
Summary (written by the submitters)
During development, blood generation begins in the yolk sac with the differentiation of haemato-endothelial mesoderm generating haematopoietic progenitors. This study aimed to identify the crucial molecular regulators of haemato-endothelial mesoderm formation and to extend our knowledge of the process in an unbiased way.
Read the full summary ↓
We employed a murine embryonic stem cell model that recapitulates embryonic blood development, and performed targeted CRISPR-Cas9 knock out screens focusing on transcription factors and chromatin regulators, which highlighted the transcription factors Smad1, Ldb1, Six4 and Zbtb7b. Embryonic stem cells lacking these regulators gave rise to mesodermal subsets with a defined lineage differentiation bias, while transcriptome analysis of these cells uncovered the precise impact of each factor on gene expression in the developing mesoderm. Our study reveals novel molecular pathways governing mesodermal development crucial to allow endothelial and haematopoietic lineage specification and paves the way for future advances in haematopoietic stem cell applications.
Published in
Targeted CRISPR-Cas9 screening identifies core transcription factors controlling murine haemato-endothelial fate commitment
Teske M, Wertheimer T, Butz S et al. · Nature communications 2025 · PMID 41390669 · doi:10.1038/s41467-025-66230-9
This dataset
Open GSE302791 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 GSE302791_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 PRJNA1292167 and SRA study SRP601325. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41390669) ↗
Study design
3 × DN vs 3 × PD_SP vs 3 × DP_priMes vs 3 × F_SP_HEM

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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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.