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MeCP2 binds to 5hmC enriched within active genes and accessible chromatin in the nervous system

GSE42880 Mus musculus (mouse) DNA methylation 50 samples Submitted 2013/01/14 Platform GPL9250Platform GPL13112
At a glance

DNA methylation · mouse · 50 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Mus musculus (mouse)
Samples
50 samples
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 high level of 5-hydroxymethylcytosine (5hmC) present in neuronal genomes suggests that mechanisms interpreting 5hmC in the central nervous system (CNS) may differ from those present in embryonic stem cells. Here we present quantitative, genome-wide analysis of 5hmC, 5- methylcytosine (5mC) and gene expression in differentiated CNS cell types in vivo.
Read the full summary ↓
We report that 5hmC is enriched in active genes, and that surprisingly strong depletion of 5mC is observed over these regions. The contribution of these epigenetic marks to gene expression depends critically on cell type. We identify methyl-CpG binding protein 2 (MeCP2) as the major 5hmC binding protein in the brain, and demonstrate that MeCP2 binds 5hmC and 5mC containing DNA with similar high affinities. The Rett Syndromecausing mutation R133C preferentially inhibits 5hmC binding. These findings support a model in which 5hmC and MeCP2 constitute a cell specific epigenetic mechanism for regulation of chromatin structure and gene expression.
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 GSE42880_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 beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA186546 and SRA study SRP017936. Searching any of these in the dataset finder brings you back here.

Samples in this study

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