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.

The regulatory sequence analysis tools (RSAT, http://rsat.ulb.ac.be/rsat/) is a software suite that integrates a wide collection of modular tools for the detection of cis-regulatory elements in genome sequences. The suite includes programs for sequence retrieval, pattern discovery, phylogenetic footprint detection, pattern matching, genome scanning and feature map drawing. Random controls can be performed with random gene selections or by generating random sequences according to a variety of background models (Bernoulli, Markov). Beyond the original word-based pattern-discovery tools (oligo-analysis and dyad-analysis), we recently added a battery of tools for matrix-based detection of cis-acting elements, with some original features (adaptive background models, Markov-chain estimation of P-values) that do not exist in other matrix-based scanning tools. The web server offers an intuitive interface, where each program can be accessed either separately or connected to the other tools. In addition, the tools are now available as web services, enabling their integration in programmatic workflows. Genomes are regularly updated from various genome repositories (NCBI and EnsEMBL) and 682 organisms are currently supported. Since 1998, the tools have been used by several hundreds of researchers from all over the world. Several predictions made with RSAT were validated experimentally and published.