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Dcp1a, a novel Mek substrate, regulates the self-renewal and differentiation of mouse embryonic stem cells [RNA-seq]

GSE267668 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/11/19 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples
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)
Mek inhibitor is widely applied to maintain pluripotency, while prolonged Mek inhibition compromises the developmental potential of mouse embryonic stem cells (ESCs). To better understand the mechanism of Mek in pluripotency maintenance, we first demonstrated that Mek regulates gene expression at post-transcriptional steps. Consistently, many of the 66 Mek substrates identified by quantitative phosphoproteomic analysis are involved in RNA processing.
Read the full summary ↓
We further confirmed that S563 of Dcp1a, a mRNA decapping cofactor and P-body component, is phosphorylated by Mek1. Dcp1a, as well as two other P-body components Edc4 and Dcp2, are required for the proper self-renewal and differentiation of ESCs, indicating the role of P-bodies in ESCs. Dephosphorylation of Dcp1a S563 facilitates both self-renewal and differentiation of ESCs, through promoting P-body formation and RNA storage. In summary, our study identified 66 Mek substrates supporting the Erk-independent function of Mek, and revealed that Dcp1a, phosphorylated by Mek, regulates ESC self-renewal and differentiation, through modulating P-body formation.
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 GSE267668_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 PRJNA1112373 and SRA study SRP508148. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 18 more — browse all 18 samples with per-sample file links →

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