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Reduction of H3K9 methylation by G9a inhibitor improves development of mouse SCNT embryos

GSE248499 Mus musculus (mouse) DNA methylation 25 samples Submitted 2024/09/18 Platform GPL21273
At a glance

DNA methylation · mouse · 25 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Mus musculus (mouse)
Samples
25 samples: 11 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.
Paper
Reduction of H3K9 methylation by G9a inhibitors improves the development of mouse SCNT embryosStem cell reports · 2024
Summary (written by the submitters)
Inefficient mammalian cloning can be improved by removal of somatic H3K9me3 from the embryonic genome. However, this strategy involves injection of histone demethylase mRNA into embryos, which itself is a limiting step due to the invasive and labor-consuming nature. Here we report that treatment with an inhibitor against G9a (G9ai), the major histone methyltransferase that introduces H3K9me1/2 in mammals, greatly improved development of cloned embryos in mice.
Read the full summary ↓
Intriguingly, G9ai treatment resulted in immediate reduction of H3K9me1/2 and secondary loss of H3K9me3 in SCNT embryos. By G9ai treatment, the birth rate of cloned pups increased about fivefold (up to 3.9%) and, when combined with trichostatin A, a histone deacetylase inhibitor, it was further improved to 14.5%. Mechanistically, G9ai and TSA synergistically enhanced H3K9me3 demethylation and boosted zygotic activation of Obox family genes. Thus, we established an easy, highly effective SCNT protocol that would enhance future cloning research and applications.
Published in
Reduction of H3K9 methylation by G9a inhibitors improves the development of mouse SCNT embryos
Matoba S, Shikata D, Shirai F et al. · Stem cell reports 2024 · PMID 38729154 · doi:10.1016/j.stemcr.2024.04.003
This dataset
Open GSE248499 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 GSE248499_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: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1044134 and SRA study SRP473756. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38729154) ↗
Study design
11 conditions, mostly in duplicate
IVF, ×4 SCNT, LatA&R701-treated, ×3 SCNT, cont, ×2 SCNT, LatA-treated control, ×2 SCNT, LatA&TSA-treated, ×2 SCNT, Kdm3a-injected, ×2 SCNT, Kdm4d-injected, ×2 SCNT, LatA&A366-treated, ×2 +3 more

Supports a between-group comparison across 25 samples.

How we read this: 11 replicated groups read from 25 sample titles; they account for 25 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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