Aims: Studies of DNA methylomes hold enormous promise for biomedicine but are hampered by the technological challenges of analyzing many samples cost-effectively. Recently, a major extension of the previous Infinium HumanMethylation27 BeadChip ® (Illumina, Inc. CA, USA), called Infinium HumanMethylation450 (Infinium Methylation 450K; Illumina, Inc. CA, USA) was developed. This upgraded technology is a hybrid of two different chemical assays, the Infinium I and Infinium II assays, allowing (for 12 samples in parallel) assessment of the methylation status of more than 480,000 cytosines distributed over the whole genome. In this article, we evaluate Infinium Methylation 450K on cell lines and tissue samples, highlighting some of its advantages but also some of its limitations. In particular, we compare the methylation values of the Infinium I and Infinium II assays. Materials & methods: We used Infinium Methylation 450K to profile: first, the well-characterized HCT116 wild-type and double-knockout cell lines and then, 16 breast tissue samples (including eight normal and eight primary tumor samples). Absolute methylation values (b-values) were extracted with the GenomeStudio TM software and then subjected to detailed analysis. Results: While this technology appeared highly robust as previously shown, we noticed a divergence between the b-values retrieved from the type I and type II Infinium assays. Specifically, the b-values obtained from Infinium II probes were less accurate and reproducible than those obtained from Infinium I probes. This suggests that data from the type I and type II assays should be considered separately in any downstream bioinformatic analysis. To be able to deal with the Infinium I and Infinium II data together, we developed and tested a new correction technique, which we called 'peak-based correction'. The idea was to rescale the Infinium II data on the basis of the Infinium I data. While this technique should be viewed as an approximation method, it significantly improves the quality of Infinium II data. Conclusion: Infinium 450K is a powerful technique in terms of reagent costs, time of labor, sample throughput and coverage. It holds great promise for the better understanding of the epigenetic component in health and disease. Yet, due to the nature of its design comprising two different chemical assays, analysis of the whole set of data is not as easy as initially anticipated. Correction strategies, such as the peak-based approach proposed here, are a step towards adequate output data analysis. keywoRds: bisulfite-based method n dNA methylation n dNA methylome n epigenetics n epigenomics n Infinium I n Infinium II n Infinium Methylation 450k n peak-based correction

This paper identifies the N-acetylglucosamine transferase OGT as binding partner for TET2/3 proteins. Their genome-wide chromatin binding and the characterization of the Set1/COMPASS complex as OGT target implies coordinated gene regulation.

#Hydroxymethylcytosine, well described in DNA, occurs also in RNA. Here, we show that hydroxymethylcytosine preferentially marks polyadenylated RNAs and is deposited by Tet in Drosophila. We map the transcriptome-wide hydroxymethylation landscape, revealing hydroxymethylcytosine in the transcripts of many genes, notably in coding sequences, and identify consensus sites for hydroxymethylation. We found that RNA hydroxymethylation can favor mRNA translation. Tet and hydroxymethylated RNA are found to be most abundant in the Drosophila brain, and Tet-deficient fruitflies suffer impaired brain development, accompanied by decreased RNA hydroxymethylation. This study highlights the distribution, localization, and function of cytosine hydroxymethylation and identifies central roles for this modification in Drosophila.

DNA methylation profiling identifies epigenetic dysregulation in pancreatic islets from type 2 diabetic patientsThe first genome-scale DNA methylation study on pancreatic islets from type 2 diabetic patients identifies disease-associated DNA methylation pattern that translate into aberrant gene expression in novel factors relevant for β-cell function and survival.

Breast cancer is a molecularly, biologically and clinically heterogeneous group of disorders. Understanding this diversity is essential to improving diagnosis and optimizing treatment. Both genetic and acquired epigenetic abnormalities participate in cancer, but the involvement of the epigenome in breast cancer and its contribution to the complexity of the disease are still poorly understood. By means of DNA methylation profiling of 248 breast tissues, we have highlighted the existence of previously unrecognized breast cancer groups that go beyond the currently known ‘expression subtypes’. Interestingly, we showed that DNA methylation profiling can reflect the cell type composition of the tumour microenvironment, and in particular a T lymphocyte infiltration of the tumours. Further, we highlighted a set of immune genes having high prognostic value in specific tumour categories. The immune component uncovered here by DNA methylation profiles provides a new perspective for the importance of the microenvironment in breast cancer, holding implications for better management of breast cancer patients.

Infinium HumanMethylation450 beadarray is a popular technology to explore DNA methylomes in health and disease, and there is a current explosion in the use of this technique. Despite experience acquired from gene expression microarrays, analyzing Infinium Methylation arrays appeared more complex than initially thought and several difficulties have been encountered, as those arrays display specific features that need to be taken into consideration during data processing. Here, we review several issues that have been highlighted by the scientific community, and we present an overview of the general data processing scheme and an evaluation of the different normalization methods available to date to guide the 450K users in their analysis and data interpretation.

Comprehensive analysis of the lncRNA landscape in breast cancers and its relationship with key clinical features and functional pathways.

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