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Klf5 functions as a multi-lineage reprogramming transcription factor

GSE281941 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 30 samples Submitted 2025/06/01 Platform GPL24247Platform GPL28330
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 30 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
30 samples: 14 conditions, mostly in duplicateGroups 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)
The transcription factor Klf5 is indispensable for both embryonic (redundantly with Klf4) and extra-embryonic development during pre-implantation, yet its role in re-establishing these different fates in vitro remains largely unexplored.
Read the full summary ↓
Here, we demonstrate that in the absence of WNT signaling activation at the beginning, ectopic expression of Klf5 in post-implantation epiblast stem cells (EpiSCs) not only induces naïve pluripotency, but also exclusively drives reprogramming into trophoblast stem cells (TSCs) and primordial germ cells (PGCs) by directly reactivating key lineage-specific determinants. Single-cell transcriptome analysis reveals distinct reprogramming trajectories toward these three fates, alongside a non-reprogramming trajectory that driven by Klf5-mediated BMP signaling activation. Moreover, endogenous Klf5 is crucial for establishing TSC and PGC fates from embryonic stem cells driven by other inducers. Our findings highlight Klf5’s multipotent reprogramming capacity and its pivotal role in early TSC and PGC fate specification, offering new insights into its versatile functions during embryonic development.
This dataset
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.

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 GSE281941_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1070353 and SRA study SRP486406. Searching any of these in the dataset finder brings you back here.

Study design
14 conditions, mostly in duplicate
EpiSCs_WT ×2 TSC_WT ×2 ESC_WT ×2 ESC_Klf5_KO ×2 iTSC_Epi2-1_No5 ×2 iTSC_OC-Epi_No2 ×2 iEmpty_D2_LIF ×2 iKlf5_D2_LIF ×2 +8 more

Supports a between-group comparison across 28 samples.

How we read this: 14 replicated groups read from 30 sample titles; they account for 28 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
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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.