DNA methylation profiling of the human major histocompatibility complex: A pilot study for the Human Epigenome Project

The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine-guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data

Increased DNA methylation variability in type 1 diabetes across three immune effector cell types

The incidence of type 1 diabetes (T1D) has substantially increased over the past decade, suggesting a role for non-genetic factors such as epigenetic mechanisms in disease development. Here we present an epigenome-wide association study across 406,365 CpGs in 52 monozygotic twin pairs discordant for T1D in three immune effector cell types. We observe a substantial enrichment of differentially variable CpG positions (DVPs) in T1D twins when compared with their healthy co-twins and when compared with healthy, unrelated individuals. These T1D-associated DVPs are found to be temporally stable and enriched at gene regulatory elements. Integration with cell type-specific gene regulatory circuits highlight pathways involved in immune cell metabolism and the cell cycle, including mTOR signalling. Evidence from cord blood of newborns who progress to overt T1D suggests that the DVPs likely emerge after birth. Our findings, based on 772 methylomes, implicate epigenetic changes that could contribute to disease pathogenesis in T1D.This work was funded by the EU-FP7 project BLUEPRINT (282510) and the Wellcome Trust (99148). We thank all twins for taking part in this study; Kerra Pearce and Mark Kristiansen (UCL Genomics) for processing the Illumina Infinium HumanMethylation450 BeadChips; Rasmus Bennet for technical assistance; and Laura Phipps for proofreading the manuscript. The BMBF Pediatric Diabetes Biobank recruits patients from the National Diabetes Patient Documentation System (DPV), and is financed by the German Ministry of Education and Research within the German Competence Net Diabetes Mellitus (01GI1106 and 01GI1109B). It was integrated into the German Center for Diabetes Research in January 2015. We thank the Swedish Research Council and SUS Funds for support. We gratefully acknowledge the participation of all NIHR Cambridge BioResource volunteers, and thank the Cambridge BioResource staff for their help with volunteer recruitment. We thank members of the Cambridge BioResource SAB and Management Committee for their support of our study and the NIHR Cambridge Biomedical Research Centre for funding. The Cardiovascular Epidemiology Unit is supported by the UK Medical Research Council (G0800270), BHF (SP/09/002), and NIHR Cambridge Biomedical Research Centre. Research in the Ouwehand laboratory is supported by the NIHR, BHF (PG-0310-1002 and RG/09/12/28096) and NHS Blood and Transplant. K.D. is funded as a HSST trainee by NHS Health Education England. M.F. is supported by the BHF Cambridge Centre of Excellence (RE/13/6/30180). A.D., E.L., L.C. and P.F. receive additional support from the European Molecular Biology Laboratory. A.K.S. is supported by an ADA Career Development Award (1-14-CD-17). B.O.B. and R.D.L. acknowledge support from the Deutsche Forschungsgemeinschaft (DFG) and European Federation for the Study of Diabetes, respectively

Transcriptome Analysis Describing New Immunity and Defense Genes in Peripheral Blood Mononuclear Cells of Rheumatoid Arthritis Patients

Background: Large-scale gene expression profiling of peripheral blood mononuclear cells from Rheumatoid Arthritis (RA) patients could provide a molecular description that reflects the contribution of diverse cellular responses associated with this disease. The aim of our study was to identify peripheral blood gene expression profiles for RA patients, using Illumina technology, to gain insights into RA molecular mechanisms. Methodology/Principal Findings: The Illumina Human-6v2 Expression BeadChips were used for a complete genome-wide transcript profiling of peripheral blood mononuclear cells (PBMCs) from 18 RA patients and 15 controls. Differential analysis per gene was performed with one-way analysis of variance (ANOVA) and P values were adjusted to control the False Discovery Rate (FDR < 5%). Genes differentially expressed at significant level between patients and controls were analyzed using Gene Ontology (GO) in the PANTHER database to identify biological processes. A differentially expression of 339 Reference Sequence genes (238 down-regulated and 101 up-regulated) between the two groups was observed. We identified a remarkably elevated expression of a spectrum of genes involved in Immunity and Defense in PBMCs of RA patients compared to controls. This result is confirmed by GO analysis, suggesting that these genes could be activated systemically in RA. No significant down-regulated ontology groups were found. Microarray data were validated by real time PCR in a set of nine genes showing a high degree of correlation. Conclusions/Significance: Our study highlighted several new genes that could contribute in the identification of innovative clinical biomarkers for diagnostic procedures and therapeutic interventions

RD-Connect: An Integrated Platform Connecting Databases, Registries, Biobanks and Clinical Bioinformatics for Rare Disease Research

Research into rare diseases is typically fragmented by data type and disease. Individual efforts often have poor interoperability and do not systematically connect data across clinical phenotype, genomic data, biomaterial availability, and research/trial data sets. Such data must be linked at both an individual-patient and whole-cohort level to enable researchers to gain a complete view of their disease and patient population of interest. Data access and authorization procedures are required to allow researchers in multiple institutions to securely compare results and gain new insights. Funded by the European Union’s Seventh Framework Programme under the International Rare Diseases Research Consortium (IRDiRC), RD-Connect is a global infrastructure project initiated in November 2012 that links genomic data with registries, biobanks, and clinical bioinformatics tools to produce a central research resource for rare diseases

The International Human Epigenome Consortium: A Blueprint for Scientific Collaboration and Discovery

The International Human Epigenome Consortium (IHEC) coordinates the generation of a catalog of high-resolution reference epigenomes of major primary human cell types. The studies now presented (see the Cell Press IHEC web portal at http://www.cell.com/consortium/IHEC) highlight the coordinated achievements of IHEC teams to gather and interpret comprehensive epigenomic datasets to gain insights in the epigenetic control of cell states relevant for human health and disease

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Whole-Genome Bisulfite Sequencing of Two Distinct Interconvertible DNA Methylomes of Mouse Embryonic Stem Cells.

"The use of two kinase inhibitors (2i) enables derivation of mouse embryonic stem cells (ESCs) in the pluripotent ground state. Using whole-genome bisulfite sequencing (WGBS), we show that male 2i ESCs are globally hypomethylated compared to conventional ESCs maintained in serum. In serum, female ESCs are hypomethyated similarly to male ESCs in 2i, and DNA methylation is further reduced in 2i. Regions with elevated DNA methylation in 2i strongly correlate with the presence of H3K9me3 on endogenous retroviruses (ERVs) and imprinted loci. The methylome of male ESCs in serum parallels postimplantation blastocyst cells, while 2i stalls ESCs in a hypomethylated, ICM-like state. WGBS analysis during adaptation of 2i ESCs to serum suggests that deposition of DNA methylation is largely random, while loss of DNA methylation during reversion to 2i occurs passively, initiating at TET1 binding sites. Together, our analysis provides insight into DNA methylation dynamics in cultured ESCs paralleling early developmental processes.

Framework for quality assessment of whole genome cancer sequences

Bringing together cancer genomes from different projects increases power and allows the investigation of pan-cancer, molecular mechanisms. However, working with whole genomes sequenced over several years in different sequencing centres requires a framework to compare the quality of these sequences. We used the Pan-Cancer Analysis of Whole Genomes cohort as a test case to construct such a framework. This cohort contains whole cancer genomes of 2832 donors from 18 sequencing centres. We developed a non-redundant set of five quality control (QC) measurements to establish a star rating system. These QC measures reflect known differences in sequencing protocol and provide a guide to downstream analyses and allow for exclusion of samples of poor quality. We have found that this is an effective framework of quality measures. The implementation of the framework is available at: https://dockstore.org/containers/quay.io/jwerner_dkfz/pancanqc:1.2.2.</a