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Pcbp1 is crucial for Naïve-to-Primed pluripotency transition due to regulation of amino acid metabolism [RNA-seq]

GSE264035 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/06/04 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 × Naive cells, wild type, vs 3 × Naive cells, PCBP1 KO, vs 3 × EpiLC cells, wild type, vs 3 × EpiLC cells, PCBP1 KO,Groups 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)
Embryo implantation coincides with the Naïve-to-Primed pluripotency transition. From fertilization to implantation only a number of cleavages is observed without significant embryo growth. Embryo-uterine connection provides necessary nutrients for further development while metabolism intensification is occurred. We have found that in vitro Naïve-to-Primed pluripotency transition of ESCs with Pcbp1 knockout is worsened – reduction of proliferation and cell death is observed.
Read the full summary ↓
By using ChIP-seq, RNA-seq and Mass-spectrometry we show that Pcbp1 is detrimental for pluripotent properties, but is crucial for amino acid metabolism intensification. According to this, functional approaches showed protein synthesis decline, while embryos deficient for Pcbp1 demonstrated growth absence after implantation.
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 GSE264035_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: 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 PRJNA1100582 and SRA study SRP501905. Searching any of these in the dataset finder brings you back here.

Study design
3 × Naive cells, wild type, vs 3 × Naive cells, PCBP1 KO, vs 3 × EpiLC cells, wild type, vs 3 × EpiLC cells, PCBP1 KO,

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
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