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      Landscape of DNA methylation on the X chromosome reflects CpG density, functional chromatin state and X-chromosome inactivation

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          Abstract

          X-chromosome inactivation (XCI) achieves dosage compensation between males and females through the silencing of the majority of genes on one of the female X chromosomes. Thus, the female X chromosomes provide a unique opportunity to study euchromatin and heterochromatin of allelic regions within the same nuclear environment. We examined the interplay of DNA methylation (DNAm) with CpG density, transcriptional activity and chromatin state at genes on the X chromosome using over 1800 female samples analysed with the Illumina Infinium Human Methylation450 BeadChip. DNAm was used to predict an inactivation status for 63 novel transcription start sites (TSSs) across 27 tissues. There was high concordance of inactivation status across tissues, with 62% of TSSs subject to XCI in all 27 tissues examined, whereas 9% escaped from XCI in all tissues, and the remainder showed variable escape from XCI between females in subsets of tissues. Inter-female and twin data supported a model of predominately cis-acting influences on inactivation status. The level of expression from the inactive X relative to the active X correlated with the amount of female promoter DNAm to a threshold of ∼30%, beyond which genes were consistently subject to inactivation. The inactive X showed lower DNAm than the active X at intragenic and intergenic regions for genes subject to XCI, but not at genes that escape from inactivation. Our categorization of genes that escape from X inactivation provides candidates for sex-specific differences in disease.

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          Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells.

          Cytosine methylation is required for mammalian development and is often perturbed in human cancer. To determine how this epigenetic modification is distributed in the genomes of primary and transformed cells, we used an immunocapturing approach followed by DNA microarray analysis to generate methylation profiles of all human chromosomes at 80-kb resolution and for a large set of CpG islands. In primary cells we identified broad genomic regions of differential methylation with higher levels in gene-rich neighborhoods. Female and male cells had indistinguishable profiles for autosomes but differences on the X chromosome. The inactive X chromosome (Xi) was hypermethylated at only a subset of gene-rich regions and, unexpectedly, overall hypomethylated relative to its active counterpart. The chromosomal methylation profile of transformed cells was similar to that of primary cells. Nevertheless, we detected large genomic segments with hypomethylation in the transformed cell residing in gene-poor areas. Furthermore, analysis of 6,000 CpG islands showed that only a small set of promoters was methylated differentially, suggesting that aberrant methylation of CpG island promoters in malignancy might be less frequent than previously hypothesized.
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            Epigenetic Predictor of Age

            From the moment of conception, we begin to age. A decay of cellular structures, gene regulation, and DNA sequence ages cells and organisms. DNA methylation patterns change with increasing age and contribute to age related disease. Here we identify 88 sites in or near 80 genes for which the degree of cytosine methylation is significantly correlated with age in saliva of 34 male identical twin pairs between 21 and 55 years of age. Furthermore, we validated sites in the promoters of three genes and replicated our results in a general population sample of 31 males and 29 females between 18 and 70 years of age. The methylation of three sites—in the promoters of the EDARADD, TOM1L1, and NPTX2 genes—is linear with age over a range of five decades. Using just two cytosines from these loci, we built a regression model that explained 73% of the variance in age, and is able to predict the age of an individual with an average accuracy of 5.2 years. In forensic science, such a model could estimate the age of a person, based on a biological sample alone. Furthermore, a measurement of relevant sites in the genome could be a tool in routine medical screening to predict the risk of age-related diseases and to tailor interventions based on the epigenetic bio-age instead of the chronological age.
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              Topological Organization of Multi-chromosomal Regions by Firre

              RNA is known to be an abundant and important structural component of the nuclear matrix, including long noncoding RNAs (lncRNA). Yet the molecular identities, functional roles, and localization dynamics of lncRNAs that influence nuclear architecture remain poorly understood. Here, we describe one lncRNA, Firre, that interacts with the nuclear matrix factor hnRNPU, through a 156 bp repeating sequence and Firre localizes across a ~5 Mb domain on the X-chromosome. We further observed Firre localization across at least five distinct trans-chromosomal loci, which reside in spatial proximity to the Firre genomic locus on the X-chromosome. Both genetic deletion of the Firre locus or knockdown of hnRNPU resulted in loss of co-localization of these trans-chromosomal interacting loci. Thus, our data suggest a model in which lncRNAs such as Firre can interface with and modulate nuclear architecture across chromosomes.
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                Author and article information

                Journal
                Hum Mol Genet
                Hum. Mol. Genet
                hmg
                hmg
                Human Molecular Genetics
                Oxford University Press
                0964-6906
                1460-2083
                15 March 2015
                07 November 2014
                07 November 2014
                : 24
                : 6
                : 1528-1539
                Affiliations
                [1 ]Department of Medical Genetics, University of British Columbia , Vancouver, BC, CanadaV6T 1Z3,
                [2 ]Molecular Epigenetics Group, Life Sciences Institute , Vancouver, BC, CanadaV6T 1Z3,
                [3 ]Department of Obstetrics and Gynaecology, University of British Columbia , Vancouver, BC, CanadaV5Z 4H4,
                [4 ]The Child and Family Research Institute , Vancouver, BC, CanadaV5Z 4H4
                [5 ]Centre for Molecular Medicine and Therapeutics , Vancouver, BC, CanadaV5Z 4H4
                Author notes
                [* ]To whom correspondence should be addressed at: Department of Medical Genetics, 2350 Health Sciences Mall, Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada V6T 1Z3. Tel: +1 6048220908; Fax: +1 6048221239; Email: carolyn.brown@ 123456ubc.ca
                Article
                ddu564
                10.1093/hmg/ddu564
                4381753
                25381334
                28552c5e-4021-42f5-8278-b2dc79193922
                © The Author 2014. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 29 July 2014
                : 1 October 2014
                : 3 November 2014
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                Genetics
                Genetics

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