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Illumina’s MethylationEPIC array interrogates the methylation status of over 850,000 cytosines in the human genome. Since the MethylationEPIC array is closely related to the Infinium HumanMethylation450 BeadChip, the steps presented in this document can be applied to either platform. The analysis laid out in the tutorial is based on detection of differentially methylated CpG sites and their subsequent filtering and annotation.

 

 

Due to annotation changes, the results presented here may slightly differ over the time.

 

Description of the Data Set

The data set accompanying this document consists of eight human samples processed by Illumina MethylationEPIC  BeadChip arrays. The data set is taken from a study of DNA methylation in human pluripotent stem cells (hPCS) (Lee et al. Cell Rep 2017).

Naive hPSCs can be generated and cultured in vitro from somatic cells. While naive hPSCs have robust self-renewal ability and can be maintained in cell culture, their utility is limited because they can only differentiate into the neural fate in vitro. Multi-germ layer potential can be achieved by converting naive-state hPSCs to primed-state hPSCs; however, this process requires long-term serial passage of naive hPSCs under priming conditions making it an unattractive option. A faster and simpler method to expand the in vitro differentiation potential of naive hPSCs would greatly increase their utility.  The authors hypothesized that the higher expression of the core pluripotent genes POU5F1 and NANOG in naive vs. primed hPSCs is responsible for the reduced differentiation capacity of naive hPSCs by enhancing self-renewal at the expense of differentiation capacity. To test this hypothesis, the authors targeted POU5F1 and NANOG using shRNAs in naive hPCS. One of the effects they observed was restoration of a primed-like state of global DNA methylation in anti-POU5F1 and anti-NANOG shRNA treated naive cells on autosomal chromosomes. 

 

The data files can be downloaded from Gene Expression Omnibus using accession number GSE95531. To follow this tutorial, download the 16 .idat files associated with GSE95531 (note that two .idat files are generated for each array) and unzip them on your local computer using 7-zip, WinRAR, or a similar program. The .idat files can be downloaded individually by selecting the links for each sample or all together in one zipped folder by selecting the GSE95531_RAW.tar file at the bottom of the page. 

 

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