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EZH2 is required for germinal center formation and somatic EZH2 mutations promote lymphoid transformation

GSE45982 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 61 samples Submitted 2013/05/13 Platform GPL13112Platform GPL11154Platform GPL10999
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 61 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
61 samples: 20 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)
The EZH2 histone methyltransferase is highly expressed in germinal center (GC) B-cells and targeted by somatic mutations in B-cell lymphomas. Here we find that EZH2 deletion or pharmacologic inhibition suppresses GC formation and functions in mice. EZH2 represses proliferation checkpoint genes and helps establish bivalent chromatin domains at key regulatory loci to transiently suppress GC B-cell differentiation.
Read the full summary ↓
Somatic mutations reinforce these physiological effects through enhanced silencing of EZH2 targets in B-cells, and in human B-cell lymphomas. Conditional expression of mutant EZH2 in mice induces GC hyperplasia and accelerated lymphomagenesis in cooperation with BCL2. GCB-type DLBCLs are mostly addicted to EZH2, regardless of mutation status, but not the more differentiated ABC-type DLBCLs, thus clarifying the therapeutic scope of EZH2 targeting.
This dataset
Open GSE45982 in finder → Find more 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 GSE45982_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 peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA198866 and SRA study SRP021509. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 23680150) ↗
Study design
20 conditions, mostly in duplicate
NB ×4 GCB ×4 OCI-Ly7 GSK ×2 Farage GSK ×2 SUDHL5 GSK ×2 OCI-Ly1 GSK ×2 WSUDLCL2 GSK ×2 Pfeiffer GSK ×2 +29 more

Supports a between-group comparison across 44 samples.

How we read this: 20 replicated groups read from 61 sample titles; they account for 44 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

+ 21 more — browse all 61 samples with per-sample file links →

Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.