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      Meta-analysis of human methylation data for evidence of sex-specific autosomal patterns

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          Abstract

          Background

          Several individual studies have suggested that autosomal CpG methylation differs by sex both in terms of individual CpG sites and global autosomal CpG methylation. However, these findings have been inconsistent and plagued by spurious associations due to the cross reactivity of CpG probes on commercial microarrays. We collectively analysed 76 published studies (n = 6,795) for sex-associated differences in both autosomal and sex chromosome CpG sites.

          Results

          Overall autosomal methylation profiles varied substantially by study, and we encountered substantial batch effects. We accounted for these by conducting random effects meta-analysis for individual autosomal CpG methylation associations. After excluding non-specific probes, we found 184 autosomal CpG sites differentially methylated by sex after correction for multiple testing. In line with previous studies, average beta differences were small. Many of the most significantly associated CpG probes were new. Of note was differential CpG methylation in the promoters of genes thought to be involved in spermatogenesis and male fertility, such as SLC9A2, SPESP1, CRISP2, and NUPL1. Pathway analysis revealed overrepresentation of genes differentially methylated by sex in several broad Gene Ontology biological processes, including RNA splicing and DNA repair.

          Conclusions

          This study represents a comprehensive analysis of sex-specific methylation patterns. We demonstrate the existence of sex-specific methylation profiles and report a large number of novel DNA methylation differences in autosomal CpG sites between sexes.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1471-2164-15-981) contains supplementary material, which is available to authorized users.

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          Most cited references23

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          DNA methylation profiling of human chromosomes 6, 20 and 22

          DNA methylation constitutes the most stable type of epigenetic modifications modulating the transcriptional plasticity of mammalian genomes. Using bisulfite DNA sequencing, we report high-resolution methylation reference 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 6 annotation categories, revealed evolutionary conserved regions to be the predominant sites for differential DNA methylation and a core region surrounding the transcriptional start site as informative surrogate for promoter methylation. We find 17% of the 873 analyzed genes differentially methylated in their 5′-untranslated regions (5′-UTR) and about one third of the differentially methylated 5′-UTRs to be inversely correlated with transcription. While our study was 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.
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            A Language and Environment for Statistical Computing

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              High-throughput DNA methylation profiling using universal bead arrays.

              We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.
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                Author and article information

                Contributors
                nina.mccarthy@uwa.edu.au
                phillip.melton@uwa.edu.au
                gemma.cadby@uwa.edu.au
                seyhanyazar@gmail.com
                mariafranchina77@gmail.com
                eric.moses@uwa.edu.au
                David.Mackey@lei.org.au
                hewitt.alex@gmail.com
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                18 November 2014
                18 November 2014
                2014
                : 15
                : 1
                : 981
                Affiliations
                [ ]Centre for the Genetic Origins of Health and Disease (GOHaD), University of Western Australia, Perth, Australia
                [ ]Centre for Ophthalmology and Vision Science, University of Western Australia and the Lions Eye Institute, Perth, Australia
                [ ]Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
                Article
                6710
                10.1186/1471-2164-15-981
                4255932
                25406947
                31e133a7-d2ca-4e57-9650-c75038f7c417
                © McCarthy et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 13 February 2014
                : 8 October 2014
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Genetics
                methylation,genome,sex,cpg,illumina infinium humanmethylation27k,meta- analysis
                Genetics
                methylation, genome, sex, cpg, illumina infinium humanmethylation27k, meta- analysis

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