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Sox4 is a master regulator of epithelial-mesenchymal transition (EMT) by controlling Ezh2 expression and epigenetic reprogramming

GSE45579 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 13 samples Submitted 2013/06/20 Platform GPL9250
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 13 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
13 samples: 6 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.
Summary (written by the submitters)
Gene expression profiling has uncovered the transcription factor Sox4 with up-regulated activity during TGFβ-induced EMT in normal and cancerous breast epithelial cells. Sox4 is indispensable for EMT and cell survival in vitro and for primary tumor growth and metastasis in vivo. Among several EMT-relevant genes, Sox4 directly regulates the expression of Ezh2, encoding the Polycomb group histone methyltransferase that trimethylates histone 3 lysine 27 (H3K27me3) for gene repression.
Read the full summary ↓
Ablation of Ezh2 expression prevents EMT, while forced expression of Ezh2 restores EMT in Sox4-deficient cells. Ezh2-mediated H3K27me3 marks associate with key EMT genes, representing an epigenetic EMT signature that predicts patient survival. Our results identify Sox4 as a master regulator of EMT by governing the expression of the epigenetic modifier Ezh2.
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 GSE45579_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA194616 and SRA study SRP020232. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in duplicate
NMuMG_day00_H3K27me3, ×2 NMuMG_day01_H3K27me3, ×2 NMuMG_day04_H3K27me3, ×2 NMuMG_day07_H3K27me3, ×2 NMuMG_day10_H3K27me3, ×2 NMuMG_day20_H3K27me3, ×2 NMuMG_Input_DNA ×1

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 13 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
Datasets on a similar topic

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