Stephan Beck

Analysis of the Protein-Coding Content of the Sequence of Human Cytomegalovirus Strain AD169

Large-scale sequence analysis of the AD169 strain of human cytomegalovirus (HCMV) began in this laboratory in 1984 when very little was known about the sequence or location of genetic information in the viral genome. At that time sequence analysis was confined to the major immediate-early gene (Stenberg et al. 1984), a region of the Colburn strain that contained CA tracts (Jeang and Hayward 1983), the L-S junction region (Tamashiro et al. 1984), and what has been termed the transforming region (Kouzarides et al. 1983). This chapter is being written in March 1989 when the sequence is complete except for some remaining polishing of certain areas which is still going on (manuscript in preparation). As far as we know there are no major discrepancies in the data which might lead to the sequence changing although of course this cannot be ruled out. We present a preliminary analysis of the HCMV genome and limit ourselves mainly to the potential protein-coding content of over 200 reading frames.

DNA methylation profiling of human chromosomes 6, 20 and 22

DNA methylation is the most stable type of epigenetic modification modulating the transcriptional plasticity of mammalian genomes. Using bisulfite DNA sequencing, we report high-resolution methylation profiles of human chromosomes 6, 20 and 22, providing a resource of about 1.9 million CpG methylation values derived from 12 different tissues. Analysis of six annotation categories showed that evolutionarily conserved regions are the predominant sites for differential DNA methylation and that a core region surrounding the transcriptional start site is an informative surrogate for promoter methylation. We find that 17% of the 873 analyzed genes are differentially methylated in their 5′ UTRs and that about one-third of the differentially methylated 5′ UTRs are inversely correlated with transcription. Despite the fact that our study controlled for factors reported to affect DNA methylation such as sex and age, we did not find any significant attributable effects. Our data suggest DNA methylation to be ontogenetically more stable than previously thought.

Complete sequence and gene map of a human major histocompatibility complex

Here we report the first complete sequence and gene map of a human major histocompatibility complex (MHC), a region on chromosome 6 which is essential to the immune system (reviewed in ref. 1). When it was discovered over 50 years ago the region was thought to specify histocompatibility genes, but their nature has been resolved only in the last two decades. Although many of the 224 identified gene loci (128 predicted to be expressed) are still of unknown function, we estimate that about 40% of the expressed genes have immune system function. Over 50% of the MHC has been sequenced twice, in different haplotypes, giving insight into the extraordinary polymorphism and evolution of this region. Several genes, particularly of the MHC class II and III regions, can be traced by sequence similarity and synteny to over 700 million years ago, clearly predating the emergence of the adaptive immune system some 400 million years ago. The sequence is expected to be invaluable for the identification of many common disease loci. In the past, the search for these loci has been hampered by the complexity of high gene density and linkage disequilibrium.Here we report the first complete sequence and gene map of a human major histocompatibility complex (MHC), a region on chromosome 6 which is essential to the immune system (reviewed in ref. 1). When it was discovered over 50 years ago the region was thought to specify histocompatibility genes, but their nature has been resolved only in the last two decades. Although many of the 224 identified gene loci (128 predicted to be expressed) are still of unknown function, we estimate that about 40% of the expressed genes have immune system function. Over 50% of the MHC has been sequenced twice, in different haplotypes, giving insight into the extraordinary polymorphism and evolution of this region. Several genes, particularly of the MHC class II and III regions, can be traced by sequence similarity and synteny to over 700 million years ago, dearly predating the emergence of the adaptive immune system some 400 million years ago. The sequence is expected to be invaluable for the identification of many common disease loci. In the past, the search for these loci has been hampered by the complexity of high gene density and linkage disequilibrium.Here we report the first complete sequence and gene map of a human major histocompatibility complex (MHC), a region on chromosome 6 which is essential to the immune system (reviewed in ref. 1). When it was discovered over 50 years ago the region was thought to specify histocompatibility genes, but their nature has been resolved only in the last two decades. Although many of the 224 identified gene loci (128 predicted to be expressed) are still of unknown function, we estimate that about 40% of the expressed genes have immune system function. Over 50% of the MHC has been sequenced twice, in different haplotypes, giving insight into the extraordinary polymorphism and evolution of this region. Several genes, particularly of the MHC class II and III regions, can be traced by sequence similarity and synteny to over 700 million years ago, clearly predating the emergence of the adaptive immune system some 400 million years ago. The sequence is expected to be invaluable for the identification of many common disease loci. In the past, the search for these loci has been hampered by the complexity of high gene density and linkage disequilibrium.

Epigenome-wide association studies for common human diseases

Despite the success of genome-wide association studies (GWASs) in identifying loci associated with common diseases, a substantial proportion of the causality remains unexplained. Recent advances in genomic technologies have placed us in a position to initiate large-scale studies of human disease-associated epigenetic variation, specifically variation in DNA methylation. Such epigenome-wide association studies (EWASs) present novel opportunities but also create new challenges that are not encountered in GWASs. We discuss EWAS design, cohort and sample selections, statistical significance and power, confounding factors and follow-up studies. We also discuss how integration of EWASs with GWASs can help to dissect complex GWAS haplotypes for functional analysis.

A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC

The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and are essential in self versus non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune diseases. Yet identification of causal variants is problematic owing to linkage disequilibrium that extends across multiple HLA and non-HLA genes in the MHC. We therefore set out to characterize the linkage disequilibrium patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common SNPs and deletion-insertion polymorphisms across four population samples. The analysis provides informative tag SNPs that capture much of the common variation in the MHC region and that could be used in disease association studies, and it provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.

The chicken B locus is a minimal essential major histocompatibility complex.

Here we report the sequence of the region that determines rapid allograft rejection in chickens, the chicken major histocompatibility complex (MHC). This 92-kilobase region of the B locus contains only 19 genes, making the chicken MHC roughly 20-fold smaller than the human MHC. Virtually all the genes have counterparts in the human MHC, defining a minimal essential set of MHC genes conserved over 200 million years of divergence between birds and mammals. They are organized differently, with the class III region genes located outside the class II and class I region genes. The absence of proteasome genes is unexpected and might explain unusual peptide-binding specificities of chicken class I molecules. The presence of putative natural killer receptor gene(s) is unprecedented and might explain the importance of the B locus in the response to the herpes virus responsible for Mareks disease. The small size and simplicity of the chicken MHC allows co-evolution of genes as haplotypes over considerable periods of time, and makes it possible to study the striking MHC-determined pathogen-specific disease resistance at the molecular level.

Age-dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer

Polycomb group proteins (PCGs) are involved in repression of genes that are required for stem cell differentiation. Recently, it was shown that promoters of PCG target genes (PCGTs) are 12-fold more likely to be methylated in cancer than non-PCGTs. Age is the most important demographic risk factor for cancer, and we hypothesized that its carcinogenic potential may be referred by irreversibly stabilizing stem cell features. To test this, we analyzed the methylation status of over 27,000 CpGs mapping to promoters of approximately 14,000 genes in whole blood samples from 261 postmenopausal women. We demonstrate that stem cell PCGTs are far more likely to become methylated with age than non-targets (odds ratio = 5.3 [3.8-7.4], P < 10(-10)), independently of sex, tissue type, disease state, and methylation platform. We identified a specific subset of 69 PCGT CpGs that undergo hypermethylation with age and validated this methylation signature in seven independent data sets encompassing over 900 samples, including normal and cancer solid tissues and a population of bone marrow mesenchymal stem/stromal cells (P < 10(-5)). We find that the age-PCGT methylation signature is present in preneoplastic conditions and may drive gene expression changes associated with carcinogenesis. These findings shed substantial novel insights into the epigenetic effects of aging and support the view that age may predispose to malignant transformation by irreversibly stabilizing stem cell features.

A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis

DNA methylation is an indispensible epigenetic modification required for regulating the expression of mammalian genomes. Immunoprecipitation-based methods for DNA methylome analysis are rapidly shifting the bottleneck in this field from data generation to data analysis, necessitating the development of better analytical tools. In particular, an inability to estimate absolute methylation levels remains a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling. To address this issue, we developed a cross-platform algorithm—Bayesian tool for methylation analysis (Batman)—for analyzing methylated DNA immunoprecipitation (MeDIP) profiles generated using oligonucleotide arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). We developed the latter approach to provide a high-resolution whole-genome DNA methylation profile (DNA methylome) of a mammalian genome. Strong correlation of our data, obtained using mature human spermatozoa, with those obtained using bisulfite sequencing suggest that combining MeDIP-seq or MeDIP-chip with Batman provides a robust, quantitative and cost-effective functional genomic strategy for elucidating the function of DNA methylation.

A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data

Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs. Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform. Availability: BMIQ is freely available from http://code.google.com/p/bmiq/. Contact: a.teschendorff@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online

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.