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      DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation

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          Abstract

          DNA methylation maintenance by DNMT1 is an essential process in mammals but molecular mechanisms connecting DNA methylation patterns and enzyme activity remain elusive. Here, we systematically analyzed the specificity of DNMT1, revealing a pronounced influence of the DNA sequences flanking the target CpG site on DNMT1 activity. We determined DNMT1 structures in complex with preferred DNA substrates revealing that DNMT1 employs flanking sequence-dependent base flipping mechanisms, with large structural rearrangements of the DNA correlating with low catalytic activity. Moreover, flanking sequences influence the conformational dynamics of the active site and cofactor binding pocket. Importantly, we show that the flanking sequence preferences of DNMT1 highly correlate with genomic methylation in human and mouse cells, and 5-azacytidine triggered DNA demethylation is more pronounced at CpG sites with flanks disfavored by DNMT1. Overall, our findings uncover the intricate interplay between CpG-flanking sequence, DNMT1-mediated base flipping and the dynamic landscape of DNA methylation.

          Abstract

          DNA methylation is one of the major epigenetic mechanisms that critically influence gene expression, genomic stability and cell differentiation. Here, the authors study DNMT1 in complex with DNA substrates and systematically analyze the mechanism and specificity of DNMT1.

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          Most cited references40

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          Manipulation of FASTQ data with Galaxy

          Summary: Here, we describe a tool suite that functions on all of the commonly known FASTQ format variants and provides a pipeline for manipulating next generation sequencing data taken from a sequencing machine all the way through the quality filtering steps. Availability and Implementation: This open-source toolset was implemented in Python and has been integrated into the online data analysis platform Galaxy (public web access: http://usegalaxy.org; download: http://getgalaxy.org). Two short movies that highlight the functionality of tools described in this manuscript as well as results from testing components of this tool suite against a set of previously published files are available at http://usegalaxy.org/u/dan/p/fastq Contact: james.taylor@emory.edu; anton@bx.psu.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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            DNA methylation aging clocks: challenges and recommendations

            Epigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.
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              DNA methylation loss in late-replicating domains is linked to mitotic cell division

              DNA methylation loss occurs frequently in cancer genomes, primarily within lamina-associated, late-replicating regions termed Partially Methylated Domains (PMDs). We profiled 39 diverse primary tumors and 8 matched adjacent tissues using Whole-Genome Bisulfite Sequencing (WGBS), and analyzed them alongside 343 additional human and 206 mouse WGBS datasets. We identified a local CpG sequence context associated with preferential hypomethylation in PMDs. Analysis of CpGs in this context (“Solo-WCGWs”) revealed previously undetected PMD hypomethylation in almost all healthy tissue types. PMD hypomethylation increased with age, beginning during fetal development, and appeared to track the accumulation of cell divisions. In cancer, PMD hypomethylation depth correlated with somatic mutation density and cell-cycle gene expression, consistent with its reflection of mitotic history, and suggesting its application as a mitotic clock. We propose that late replication leads to lifelong progressive methylation loss, which acts as a biomarker for cellular aging and which may contribute to oncogenesis.
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                Author and article information

                Contributors
                jikui.song@ucr.edu
                albert.jeltsch@ibtb.uni-stuttgart.de
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                24 July 2020
                24 July 2020
                2020
                : 11
                : 3723
                Affiliations
                [1 ]ISNI 0000 0004 1936 9713, GRID grid.5719.a, Department of Biochemistry, Institute of Biochemistry and Technical Biochemistry, , University of Stuttgart, ; Allmandring 31, 70569 Stuttgart, Germany
                [2 ]ISNI 0000 0001 2222 1582, GRID grid.266097.c, Department of Biochemistry, , University of California, ; Riverside, CA 92521 USA
                [3 ]ISNI 0000 0004 1936 9713, GRID grid.5719.a, Institute for Systems Theory and Automatic Control, , University of Stuttgart, ; Pfaffenwaldring 9, 70569 Stuttgart, Germany
                Author information
                http://orcid.org/0000-0002-6478-4081
                http://orcid.org/0000-0002-4958-1032
                http://orcid.org/0000-0001-6113-9290
                Article
                17531
                10.1038/s41467-020-17531-8
                7381644
                32709850
                69d81d41-1937-498d-92ee-d45c4e7fbf8c
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 February 2020
                : 6 July 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: EXC 2075 390740016
                Award ID: JE252/36
                Award ID: EXC 2075 390740016
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: 1R35GM119721
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                enzyme mechanisms,dna methylation,x-ray crystallography
                Uncategorized
                enzyme mechanisms, dna methylation, x-ray crystallography

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