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      Environment‐induced epigenetic reprogramming in genomic regulatory elements in smoking mothers and their children

      research-article
      1 , 2 , 1 , 3 , 2 , 1 , 15 , 2 , 1 , 3 , 1 , 3 , 4 , 5 , 2 , 2 , 6 , 4 , 2 , 2 , 2 , 7 , 1 , 1 , 8 , 2 , 9 , 1 , 10 , 10 , 11 , 12 , 4 , 5 , 6 , 1 , 13 , 1 , 3 , 13 , 14 , , 2 ,
      Molecular Systems Biology
      John Wiley and Sons Inc.
      environment, epigenetics, WGBS, histone modifications, enhancer deregulation, Chromatin, Epigenetics, Genomics & Functional Genomics, Genome-Scale & Integrative Biology, Systems Medicine

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          Abstract

          Epigenetic mechanisms have emerged as links between prenatal environmental exposure and disease risk later in life. Here, we studied epigenetic changes associated with maternal smoking at base pair resolution by mapping DNA methylation, histone modifications, and transcription in expectant mothers and their newborn children. We found extensive global differential methylation and carefully evaluated these changes to separate environment associated from genotype‐related DNA methylation changes. Differential methylation is enriched in enhancer elements and targets in particular “commuting” enhancers having multiple, regulatory interactions with distal genes. Longitudinal whole‐genome bisulfite sequencing revealed that DNA methylation changes associated with maternal smoking persist over years of life. Particularly in children prenatal environmental exposure leads to chromatin transitions into a hyperactive state. Combined DNA methylation, histone modification, and gene expression analyses indicate that differential methylation in enhancer regions is more often functionally translated than methylation changes in promoters or non‐regulatory elements. Finally, we show that epigenetic deregulation of a commuting enhancer targeting c‐Jun N‐terminal kinase 2 ( JNK2) is linked to impaired lung function in early childhood.

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          Most cited references30

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          Identifying ChIP-seq enrichment using MACS.

          Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.
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            A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.

            Chromatin states are the key to gene regulation and cell identity. Chromatin immunoprecipitation (ChIP) coupled with high-throughput sequencing (ChIP-Seq) is increasingly being used to map epigenetic states across genomes of diverse species. Chromatin modification profiles are frequently noisy and diffuse, spanning regions ranging from several nucleosomes to large domains of multiple genes. Much of the early work on the identification of ChIP-enriched regions for ChIP-Seq data has focused on identifying localized regions, such as transcription factor binding sites. Bioinformatic tools to identify diffuse domains of ChIP-enriched regions have been lacking. Based on the biological observation that histone modifications tend to cluster to form domains, we present a method that identifies spatial clusters of signals unlikely to appear by chance. This method pools together enrichment information from neighboring nucleosomes to increase sensitivity and specificity. By using genomic-scale analysis, as well as the examination of loci with validated epigenetic states, we demonstrate that this method outperforms existing methods in the identification of ChIP-enriched signals for histone modification profiles. We demonstrate the application of this unbiased method in important issues in ChIP-Seq data analysis, such as data normalization for quantitative comparison of levels of epigenetic modifications across cell types and growth conditions. http://home.gwu.edu/ approximately wpeng/Software.htm. Supplementary data are available at Bioinformatics online.
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              Prenatal and passive smoke exposure and incidence of asthma and wheeze: systematic review and meta-analysis.

              Exposure to passive smoke is a common and avoidable risk factor for wheeze and asthma in children. Substantial growth in the prospective cohort study evidence base provides an opportunity to generate new and more detailed estimates of the magnitude of the effect. A systematic review and meta-analysis was conducted to provide estimates of the prospective effect of smoking by parents or household members on the risk of wheeze and asthma at different stages of childhood. We systematically searched Medline, Embase, and conference abstracts to identify cohort studies of the incidence of asthma or wheeze in relation to exposure to prenatal or postnatal maternal, paternal, or household smoking in subjects aged up to 18 years old. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were estimated by using random effects model. We identified 79 prospective studies. Exposure to pre- or postnatal passive smoke exposure was associated with a 30% to 70% increased risk of incident wheezing (strongest effect from postnatal maternal smoking on wheeze in children aged ≤2 years, OR = 1.70, 95% CI = 1.24-2.35, 4 studies) and a 21% to 85% increase in incident asthma (strongest effect from prenatal maternal smoking on asthma in children aged ≤2 years, OR = 1.85, 95% CI = 1.35-2.53, 5 studies). Building upon previous findings, exposure to passive smoking increases the incidence of wheeze and asthma in children and young people by at least 20%. Preventing parental smoking is crucially important to the prevention of asthma.
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                Author and article information

                Journal
                Mol Syst Biol
                Mol. Syst. Biol
                10.1002/(ISSN)1744-4292
                MSB
                msb
                Molecular Systems Biology
                John Wiley and Sons Inc. (Hoboken )
                1744-4292
                24 March 2016
                March 2016
                : 12
                : 3 ( doiID: 10.1002/msb.v12.3 )
                : 861
                Affiliations
                [ 1 ] Division of Theoretical BioinformaticsGerman Cancer Research Center (DKFZ) HeidelbergGermany
                [ 2 ] Department of Environmental ImmunologyHelmholtz Centre for Environmental Research Leipzig ‐ UFZ LeipzigGermany
                [ 3 ] Heidelberg Center for Personalized Oncology DKFZ‐HIPODKFZ HeidelbergGermany
                [ 4 ] Division of Epigenomics and Cancer Risk FactorsGerman Cancer Research Center (DKFZ) HeidelbergGermany
                [ 5 ] Research Group Genome Organization & FunctionGerman Cancer Research Center (DKFZ) and Bioquant HeidelbergGermany
                [ 6 ] Department of ImmunologyTokyo Medical University TokyoJapan
                [ 7 ] Department MetabolomicsHelmholtz Centre for Environmental Research Leipzig ‐ UFZ LeipzigGermany
                [ 8 ]Municipal Hospital “St Georg” Children's Hospital LeipzigGermany
                [ 9 ] Department of Dermatology, Venerology and AllerologyLeipzig University Medical Center LeipzigGermany
                [ 10 ] Genomics and Proteomics Core FacilityGerman Cancer Research Center (DKFZ) HeidelbergGermany
                [ 11 ] Sample Processing LabNational Center for Tumor Disease and German Cancer Research Center (DKFZ) HeidelbergGermany
                [ 12 ] Department of Molecular Biology Faculty of ScienceRadboud University NijmegenThe Netherlands
                [ 13 ] Institute of Pharmacy and Molecular Biotechnology and Bioquant CenterUniversity of Heidelberg HeidelbergGermany
                [ 14 ] Translational Lung Research Center Heidelberg (TLRC) German Center for Lung Research (DZL)University of Heidelberg HeidelbergGermany
                [ 15 ]Present address: Division of Newborn Medicine Children's Hospital Boston and Department of Cell BiologyHarvard Medical School BostonUSA
                Author notes
                [*] [* ] Corresponding author. E‐mail: r.eils@ 123456dkfz-heidelberg.de

                Corresponding author. E‐mail: irina.lehmann@ 123456ufz.de

                [†]

                These authors contributed equally to this work

                Author information
                http://orcid.org/0000-0002-4961-3639
                http://orcid.org/0000-0002-0034-4036
                Article
                MSB156520
                10.15252/msb.20156520
                4812527
                27013061
                1597f4b1-ecac-462a-8183-6b162b8c79f4
                © 2016 The Authors. Published under the terms of the CC BY 4.0 license

                This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 August 2015
                : 25 February 2016
                : 04 March 2016
                Page count
                Pages: 18
                Funding
                Funded by: Personalized Medicine (iMed)
                Funded by: BMBF
                Award ID: 01ZX1305A
                Funded by: German Cancer Research Center—Heidelberg Center for Personalized Oncology (DKFZ‐HIPO)
                Categories
                Article
                Articles
                Custom metadata
                2.0
                msb156520
                March 2016
                Converter:WILEY_ML3GV2_TO_NLMPMC version:4.8.5 mode:remove_FC converted:30.03.2016

                Quantitative & Systems biology
                environment,epigenetics,wgbs,histone modifications,enhancer deregulation,chromatin, epigenetics, genomics & functional genomics,genome-scale & integrative biology,systems medicine

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