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Candida albicans induces monocyte training via epigenetic programming through a dectin 1-dependent pathway

GSE34260 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2012/12/21 Platform GPL9185Platform GPL9052
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 15 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
15 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)
Non-specific protective effects against reinfection have been described following infection with Candida albicans. Here we show that mice defective in functional T and B lymphocytes were protected against reinfection with C. albicans in a monocyte-dependent manner. C. albicans and beta glucans induced functional programming of monocytes, leading to enhanced cytokine production in vivo and in vitro.
Read the full summary ↓
The training required the beta glucan receptor dectin 1 and the non-canonical Raf 1 pathway. Monocyte training by beta-glucans was mediated by epigenetic mechanisms through genome-wide changes in histone trimethylation at H3K4. Pathway analysis showed specific induction of epigenetic changes in genes of innate immunity. The functional programming of monocytes, reminiscent of similar properties of NK cells, has been termed “trained immunity” and may be employed for the design of improved vaccination strategies.
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 GSE34260_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 PRJNA149747 and SRA study SRP009657. Searching any of these in the dataset finder brings you back here.

Samples in this study

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