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Chromatin remodeler CHD4 establishes chromatin states required for ovarian reserve formation, maintenance, and germ cell survival [RNA-seq]

GSE273306 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2024/09/27 Platform GPL21273
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 10 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
Chromatin remodeler CHD4 establishes chromatin states required for ovarian reserve formation, maintenance, and germ cell survivalbioRxiv : the preprint server for biology · 2024
Summary (written by the submitters)
To understand the functional role of CHD4, a member of the Nucleosome Remodeling and Deacetylase (NuRD) complex, in establishing chromatin states in the formation and maintenance of ovarian reserve and the maintenance of female and male germ cells, we eliminated CHD4 function in germ cells using Ddx4-Cre and Gdf9-iCre to generate CHD4 conditional knockout (Chd4 DcKO and GcKO) mice.
Read the full summary ↓
We discover that CHD4 defines the chromatin state that ensures germ cell survival, thereby enabling the long-term maintenance of female and male germ cells. We then performed gene expression profiling analysis using data obtained from RNA-seq of Chd4 Dctrl and Chd4 DcKO non-growing oocytes and undifferentiated spermatogonia, and Chd4 Gctrl and Chd4 GcKO non-growing and growing oocytes.
Published in
Chromatin remodeler CHD4 establishes chromatin states required for ovarian reserve formation, maintenance, and germ cell survival
Munakata Y, Hu M, Kitamura Y et al. · bioRxiv : the preprint server for biology 2024 · PMID 39185217 · doi:10.1101/2024.08.12.607691
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 GSE273306_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 PRJNA1141405 and SRA study SRP522808. Searching any of these in the dataset finder brings you back here.

Study design
10 conditions, mostly in duplicate
RNA-seq_P1_NGO_Dctrl ×2 RNA-seq_P1_NGO_DcKO ×2 RNA-seq_P5_NGO_Dctrl ×2 RNA-seq_P5_NGO_DcKO ×2 RNA-seq_P10_NGO_Gctrl ×2 RNA-seq_P10_NGO_GcKO ×2 RNA-seq_P10_GO_Gctrl ×2 RNA-seq_P10_GO_GcKO ×2 +2 more

Supports a between-group comparison across 20 samples.

How we read this: 10 replicated groups read from 20 sample titles; they account for 20 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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