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      Adult monozygotic twins discordant for intra-uterine growth have indistinguishable genome-wide DNA methylation profiles

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          Abstract

          Background

          Low birth weight is associated with an increased adult metabolic disease risk. It is widely discussed that poor intra-uterine conditions could induce long-lasting epigenetic modifications, leading to systemic changes in regulation of metabolic genes. To address this, we acquire genome-wide DNA methylation profiles from saliva DNA in a unique cohort of 17 monozygotic monochorionic female twins very discordant for birth weight. We examine if adverse prenatal growth conditions experienced by the smaller co-twins lead to long-lasting DNA methylation changes.

          Results

          Overall, co-twins show very similar genome-wide DNA methylation profiles. Since observed differences are almost exclusively caused by variable cellular composition, an original marker-based adjustment strategy was developed to eliminate such variation at affected CpGs. Among adjusted and unchanged CpGs 3,153 are differentially methylated between the heavy and light co-twins at nominal significance, of which 45 show sensible absolute mean β-value differences. Deep bisulfite sequencing of eight such loci reveals that differences remain in the range of technical variation, arguing against a reproducible biological effect. Analysis of methylation in repetitive elements using methylation-dependent primer extension assays also indicates no significant intra-pair differences.

          Conclusions

          Severe intra-uterine growth differences observed within these monozygotic twins are not associated with long-lasting DNA methylation differences in cells composing saliva, detectable with up-to-date technologies. Additionally, our results indicate that uneven cell type composition can lead to spurious results and should be addressed in epigenomic studies.

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          Most cited references41

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          High density DNA methylation array with single CpG site resolution.

          We have developed a new generation of genome-wide DNA methylation BeadChip which allows high-throughput methylation profiling of the human genome. The new high density BeadChip can assay over 480K CpG sites and analyze twelve samples in parallel. The innovative content includes coverage of 99% of RefSeq genes with multiple probes per gene, 96% of CpG islands from the UCSC database, CpG island shores and additional content selected from whole-genome bisulfite sequencing data and input from DNA methylation experts. The well-characterized Infinium® Assay is used for analysis of CpG methylation using bisulfite-converted genomic DNA. We applied this technology to analyze DNA methylation in normal and tumor DNA samples and compared results with whole-genome bisulfite sequencing (WGBS) data obtained for the same samples. Highly comparable DNA methylation profiles were generated by the array and sequencing methods (average R2 of 0.95). The ability to determine genome-wide methylation patterns will rapidly advance methylation research. Copyright © 2011 Elsevier Inc. All rights reserved.
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            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.
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              Genome-wide DNA methylation profiling using Infinium® assay.

              Bisulfite sequence analysis of individual CpG sites within genomic DNA is a powerful approach for methylation analysis in the genome. The major limitation of bisulfite-based methods is parallelization. Both array and next-generation sequencing technology are capable of addressing this bottleneck. In this report, we describe the application of Infinium® genotyping technology to analyze bisulfite-converted DNA to simultaneously query the methylation state of over 27,000 CpG sites from promoters of consensus coding sequences (CCDS) genes. We adapted the Infinium genotyping assay to readout an array of over 27,000 pairs of CpG methylation-specific query probes complementary to bisulfite-converted DNA. Two probes were designed to each CpG site: a 'methylated' and an 'unmethylated' query probe. The probe design assumed that all underlying CpG sites were 'in phase' with the queried CpG site due to their close proximity. Bisulfite conversion was performed with a modified version of the Zymo EZ DNA Methylation™ kit. We applied this technology to measuring methylation levels across a panel of 14 different human tissues, four Coriell cell lines and six cancer cell lines. We observed that CpG sites within CpG islands (CGIs) were largely unmethylated across all tissues (~80% sites unmethylated, β < 0.2), whereas CpG sites in non-CGIs were moderately to highly methylated (only ~12% sites unmethylated, β < 0.2). Within CGIs, only approximately 3-6% of the loci were highly methylated; in contrast, outside of CGIs approximately 25-40% of loci were highly methylated. Moreover, tissue-specific methylation (variation in methylation across tissues) was much more prevalent in non-CGIs than within CGIs. Our results demonstrate a genome-wide scalable array-based methylation readout platform that is both highly reproducible and quantitative. In the near future, this platform should enable the analysis of hundreds of thousands to millions of CpG sites per sample.
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                Author and article information

                Contributors
                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2013
                26 May 2013
                : 14
                : 5
                : R44
                Affiliations
                [1 ]Laboratory of EpiGenetics, FR 8.3 Life Sciences, Saarland University, Saarbrücken, 66123, Saarland, Germany
                [2 ]Department of Genetics and Cell Biology, Maastricht University, Maastricht, 6200 MD, Limburg, The Netherlands
                [3 ]Nutrition and Toxicology Research Institute Maastricht (NUTRIM), Maastricht University, Maastricht, 6200 MD, Limburg, The Netherlands
                [4 ]Department of Psychiatry and Psychotherapy, Saarland University Hospital, Homburg, 66424, Saarland, Germany
                [5 ]Department of Human Genetics, University Hospital Gasthuisberg, Katholieke Universiteit Leuven, Leuven, B-3000, Vlaams-Brabant, Belgium
                [6 ]Unit of Urologic and Genetic Epidemiology, Department of Public Health and Epidemiology, University of Birmingham, Birmingham, B15 2TT, West Midlands, UK
                Article
                gb-2013-14-5-r44
                10.1186/gb-2013-14-5-r44
                4054831
                23706164
                0cccf3ab-3b3d-4dcf-93b2-8775091f9dc0
                Copyright © 2013 Souren et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 March 2013
                : 13 May 2013
                : 26 May 2013
                Categories
                Research

                Genetics
                Genetics

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