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Genome-scale DNA methylation maps of pluripotent and differentiated cells

GSE11034 Mus musculus (mouse) DNA methylation 18 samples Submitted 2008/07/06 Platform GPL6677
At a glance

DNA methylation · mouse · 18 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Mus musculus (mouse)
Samples
18 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)
We report the generation and analysis of genome-scale DNA methylation profiles at nucleotide resolution in mammalian cells. Using high-throughput Reduced Representation Bisulfite Sequencing (RRBS) and single-molecule-based sequencing, we generated DNA methylation maps covering the vast majority of CpG islands, and a representative sampling of conserved non-coding elements, transposons and other genomic features, for murine embryonic stem (ES) cells, ES-derived and primary neural cells, and eight other primary tissues.
Read the full summary ↓
Several key findings emerge from the data. First, DNA methylation patterns are better correlated with histone methylation patterns than with the underlying genome sequence context. Second, methylation of CpGs are dynamic epigenetic marks that undergo extensive changes during cellular differentiation, particularly in regulatory regions outside of core promoters. Third, analysis of ES-derived and primary cells reveals that 'weak' CpG islands associated with a specific set of developmentally regulated genes undergo aberrant hypermethylation during extended proliferation in vitro, in a pattern reminiscent of that reported in some primary tumors. More generally, the results establish RRBS as a powerful technology for epigenetic profiling of cell populations relevant to developmental biology, cancer and regenerative medicine. Keywords: High-throughput Reduced Representation Bisulfite Sequencing (RRBS), Illumina, cell type comparison
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 GSE11034_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 PRJNA107127 and SRA study SRP000179. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 18 more — browse all 18 samples with per-sample file links →

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