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Dux promotes metabolism-lactylation-MET cascaded network during early iPSC reprogramming with Brg1 as the histone lactylation reader [RNA-Seq]

GSE251640 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/03/01 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 × MEF vs 3 × D4 vs 3 × D4_DUX vs 3 × iPSCGroups 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
Dux activates metabolism-lactylation-MET network during early iPSC reprogramming with Brg1 as the histone lactylation readerNucleic acids research · 2024
Summary (written by the submitters)
The process of reprogramming induced pluripotent stem cells (iPSCs) involves several crucial events, including the shutdown of somatic genes, the mesenchymal-epithelial transition (MET), activation of pluripotent genes, metabolic reprogramming, and epigenetic rewiring. These events intricately interact and influence each other, ultimately leading to the formation of iPSCs.
Read the full summary ↓
However, the specific element that regulates the reprogramming network remains unclear. Dux, a factor known to promote totipotency during the transition from embryonic stem cells (ESCs) to 2C-like ESCs (2CLC), has not been extensively studied in the context of iPSC reprogramming. In this study, we demonstrate that the modification of H3K18la induced by Dux overexpression controls the metabolism-H3K18la-MET network, enhancing the efficiency of iPSC reprogramming through a metabolic switch and the recruitment of P300 via its C-terminal domain. Through the utilization of H3K18la regulators, we discover that H3K18la plays crucial roles in promoting MET. Furthermore, our proteomic analysis of H3K18la IP experiment uncover the specific recruitment of Brg1 during reprogramming, with both H3K18la and Brg1 being enriched on the promoters of genes associated with epithelial and pluripotency. In summary, our study has demonstrated the significant role of Dux-induced H3K18la in the early reprogramming process, highlighting its function as a potent trigger. Additionally, our research has revealed, for the first time, the binding of Brg1 to H3K18la, indicating its role as a reader of histone lactylation.
Published in
Dux activates metabolism-lactylation-MET network during early iPSC reprogramming with Brg1 as the histone lactylation reader
Hu X, Huang X, Yang Y et al. · Nucleic acids research 2024 · PMID 38512058 · doi:10.1093/nar/gkae183
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 GSE251640_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 PRJNA1055002 and SRA study SRP479154. Searching any of these in the dataset finder brings you back here.

Study design
3 × MEF vs 3 × D4 vs 3 × D4_DUX vs 3 × iPSC

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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