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Distinct factors control histone variant H3.3 localization at specific genomic regions

GSE16893 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 38 samples Submitted 2010/03/04 Platform GPL9250
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 38 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
38 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 incorporation of histone H3 variants has been implicated in the epigenetic memory of cellular state. Using genome editing with zinc finger nucleases to tag endogenous H3.3, we report genome-wide profiles of H3 variants in mammalian embryonic stem (ES) cells and neuronal precursor cells. Genome-wide patterns of H3.3 are dependent on amino acid sequence, and change with cellular differentiation at developmentally regulated loci.
Read the full summary ↓
The H3.3 chaperone Hira is required for H3.3 enrichment at active and repressed genes. Strikingly, Hira is not essential for localization of H3.3 at telomeres and many transcription factor binding sites. Immunoaffinity purification and mass spectrometry reveal that the proteins Atrx and Daxx associate with H3.3 in a Hira-independent manner. Atrx is required for Hira-independent localization of H3.3 at telomeres, and for the repression of telomeric RNA. Our data demonstrate that multiple and distinct factors are responsible for H3.3 localization at specific genomic locations in mammalian cells.
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 GSE16893_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 PRJNA117667 and SRA study SRP001989. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 38 more — browse all 38 samples with per-sample file links →

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