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Genome-wide profiling of 5-Formylcytosine reveals it roles in epigenetic priming

GSE41545 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 30 samples Submitted 2013/04/18 Platform GPL16173Platform GPL13112
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 30 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
30 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)
TET proteins oxidize 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC). 5fC and 5caC are excised by mammalian DNA glycosylase TDG, implicating 5mC oxidation in DNA demethylation. Here we show that the genomic locations of 5fC can be determined by coupling chemical reduction with biotin tagging.
Read the full summary ↓
Genome-wide mapping of 5fC in mouse embryonic stem cells (mESCs) reveals that 5fC preferentially occurs at poised enhancers among other gene regulatory elements. Application to Tdg null mESCs further suggests that 5fC production coordinates with p300 in remodeling epigenetic states of enhancers. This process, which is not influenced by 5hmC, appears to be associated with further oxidation of 5hmC and commitment to demethylation through 5fC. Finally, we resolved 5fC at base-resolution by hydroxylamine-based protection from bisulfite-mediated deamination, thereby confirming sites of 5fC accumulation. Our results reveal roles of active 5mC/5hmC oxidation and TDG-mediated demethylation in epigenetic tuning at regulatory elements.
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 GSE41545_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 PRJNA177422 and SRA study SRP016104. Searching any of these in the dataset finder brings you back here.

Samples in this study

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