DOCSLIB.ORG

Identification of Endometrial Cancer Methylation Features Using a Combined

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Identification of Endometrial Cancer Methylation Features Using a Combined Identification of endometrial cancer methylation features using a combined methylation analysis method DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Michael P Trimarchi B.S. Biomedical Sciences Graduate Program The Ohio State University 2016 Dissertation Committee: Joanna L Groden, Advisor Paul Goodfellow Ralf A. Bundschuh Jeffrey Parvin Pearlly Yan Copyrighted by Michael P Trimarchi 2016 Abstract Introduction: DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation marks are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens. Widespread accumulation of methylation in regulatory elements in some cancers (termed the CpG island methylator phenotype, CIMP) can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA that are not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses have been performed for a limited number of cancer specimens. Yet methods for analyzing these large datasets and integrating findings from different studies have not been fully developed. An approach was developed to profile CIMP by combining the strengths of two different methylome profiling techniques. Methods: Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing (MethylCap-seq). Publically available data from The Cancer Genome Atlas (TCGA) for 203 endometrial cancers, analyzed using the Infinium HumanMethylation 450 beadchip, were compared to the MethylCap-seq data. A MethylCap-seq quality control module was ii developed to exclude sequencing samples with poor-quality methylation data from analysis. Additional MethylCap-seq datasets were also used to develop and validate the quality control module. Results: Analysis of total methylation in promoter CpG islands (CGIs) identified a subset of tumors with a methylator phenotype. I developed a 13- region methylation signature associated with a “hypermethylator state” using a training set of five highly methylated and eight lowly methylated tumors. The signature was validated using data from TCGA. High signature methylation score was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in TCGA test set. In addition, the methylation signature distinguished >90% of endometrioid endometrial tumors from normal controls in the test set. Furthermore, classification of tumors by signature methylation score proved highly robust, showing good agreement with previously published methylation clusters for the test set as well as consistent ranking of tumors across alternative signatures. Conclusion: I identified a methylation signature for a “hypermethylator phenotype” in endometrial cancer and developed methods that could prove useful for identifying extreme methylation phenotypes in other cancers. iii Acknowledgments My sincere thanks to my committee and my former advisor Tim H.M. Huang for making this project possible, as well as the current and former members of the Yan and Groden labs. Special thanks to Paul Goodfellow for helping reorient the project after my former advisor left, and to Ralf Bundschuh for his guidance in data analysis. iv Vita June 2002 ............................................... North Olmsted High School June 2006 ............................................... B.S. Microbiology, Minor in Chemistry, The Ohio State University June 2007 to present ............................. Graduate Research Associate, Biomedical Sciences Graduate Program, The Ohio State University Publications 2016 Michael P Trimarchi, Pearlly Yan, Joanna Groden, Ralf Bundschuh, Paul Goodfellow. Identification of endometrial cancer methylation features using a combined methylation analysis method. Manuscript in preparation. 2012 Michael P Trimarchi, Mark Murphy, David Frankhouser, Benjamin AT Rodriguez, John Curfman, Guido Marcucci, Pearlly Yan, Ralf Bundschuh. Enrichment-based DNA methylation analysis using next-generation sequencing: sample exclusion, estimating changes in global methylation, and the contribution of replicate lanes. BMC Genomics 2012, 13(Suppl 8):S6 (17 December 2012). v 2012 Rodriguez B, Tam HH, Frankhouser D, Trimarchi M, Murphy M, Kuo C, Parikh D, Ball B, Schwind S, Curfman J, Blum W, Marcucci G, Yan P, Bundschuh R. A Scalable, Flexible Workflow for MethylCap-Seq Data Analysis. BMC Genomics 2012, 13(Suppl 6):S14 (26 October 2012). 2012 Yan P, Frankhouser D, Murphy M, Tam HH, Rodriguez B, Curfman J, Trimarchi M, Geyer S, Wu YZ, Whitman SP, Metzeler K, Walker A, Klisovic R, Jacob S, Grever MR, Byrd JC, Bloomfield CD, Garzon R, Blum W, Caligiuri MA, Bundschuh R, Marcucci G. Genome-wide methylation profiling in decitabine- treated patients with acute myeloid leukemia. Blood. 2012 Jul 11. 2011 Trimarchi MP, Mouangsavanh M, Huang TH., Cancer epigenetics: a perspective on the role of DNA methylation in acquired endocrine resistance. Chin J Cancer. 2011 Nov;30(11):749-56. 2010 Cottrell, C. E., Bir, N., Varga, E., Alvarez, C. E., Bouyain, S., Zernzach, R., Thrush, D. L., Evans, J., Trimarchi, M., Butter, E. M., Cunningham, D., Gastier-Foster, J. M., McBride, K. L. and Herman, G. E. Contactin 4 as an autism susceptibility locus. Autism Res. 2011 Jun;4(3):189-99. vi Fields of Study Major Field: Biomedical Sciences Specialization: Cancer Research Interdisciplinary Specialization: Biomedical, Clinical & Translational Sciences vii Table of Contents Abstract ............................................................................................................ ii Acknowledgments ........................................................................................... iv Vita .................................................................................................................. v List of Figures ................................................................................................. xii List of Tables ................................................................................................. xiv Chapter 1. Background .................................................................................... 1 I. Epigenetics in cancer, with a focus on DNA methylation .......................... 1 Chromatin model ...................................................................................... 1 DNA methylation ...................................................................................... 1 DNA methylation in cancer COMMENT: perhaps this is a better place for you to refer to the You and Jones Cancer Cell review. ....................... 2 Histone modifications ............................................................................... 3 DNA methylation interaction with histone modifications ........................... 4 DNA methylation as a biomarker and therapeutic target .......................... 5 II. Methylome Profiling ................................................................................. 6 Analysis methods ..................................................................................... 6 Methylome Profiling: The Biology ........................................................... 13 viii Chapter 2. Thesis Rationale and Research Objectives ................................ 19 Chapter 3. Enrichment-based DNA methylation analysis using next- generation sequencing: quality control, estimating changes in global methylation and the effects of increased sequencing depth. ......................... 21 I. Introduction ............................................................................................ 21 II. Results and Discussion ......................................................................... 23 Quality control exclusion criteria reduce noise in methylation signal and improve analytical power. ....................................................................... 23 The effect of additional sequencing lanes on quality control metrics ...... 27 The global methylation indicator (GMI) correlates inversely with an in vitro methylated tracer sequence. .................................................................. 31 III. Methods ............................................................................................... 34 Patient samples ...................................................................................... 34 Methylated-DNA capture (MethylCap-seq) ............................................. 35 MethylCap-seq experimental quality control and exclusion criteria ........ 36 Standard sequence file processing and alignment ................................. 37 Standard global methylation analysis workflow ...................................... 37 Calculation of noise in methylation signal ............................................... 38 Calculation of the Global Methylation Indicator (GMI) ............................ 39 Assessment of methylated fragment enrichment using an in vitro methylated construct .............................................................................. 39 ix IV. Conclusions ......................................................................................... 40 Chapter 4. Identification of endometrial cancer
Load more

Recommended publications
  • Dedifferentiation by Adenovirus E1A Due to Inactivation of Hippo Pathway Effectors YAP and TAZ
    Downloaded from genesdev.cshlp.org on October 3, 2021 - Published by Cold Spring Harbor Laboratory Press Dedifferentiation by adenovirus E1A due to inactivation of Hippo pathway effectors YAP and TAZ Nathan R. Zemke, Dawei Gou, and Arnold J. Berk Molecular Biology Institute, University of California at Los Angeles, Los Angeles, California 90095, USA Adenovirus transformed cells have a dedifferentiated phenotype. Eliminating E1A in transformed human embryonic kidney cells derepressed ∼2600 genes, generating a gene expression profile closely resembling mesenchymal stem cells (MSCs). This was associated with a dramatic change in cell morphology from one with scant cytoplasm and a globular nucleus to one with increased cytoplasm, extensive actin stress fibers, and actomyosin-dependent flat- tening against the substratum. E1A-induced hypoacetylation at histone H3 Lys27 and Lys18 (H3K27/18) was reversed. Most of the increase in H3K27/18ac was in enhancers near TEAD transcription factors bound by Hippo signaling-regulated coactivators YAP and TAZ. E1A causes YAP/TAZ cytoplasmic sequestration. After eliminating E1A, YAP/TAZ were transported into nuclei, where they associated with poised enhancers with DNA-bound TEAD4 and H3K4me1. This activation of YAP/TAZ required RHO family GTPase signaling and caused histone acetylation by p300/CBP, chromatin remodeling, and cohesin loading to establish MSC-associated enhancers and then superenhancers. Consistent results were also observed in primary rat embryo kidney cells, human fibroblasts, and human respiratory tract epithelial cells. These results together with earlier studies suggest that YAP/TAZ function in a developmental checkpoint controlled by signaling from the actin cytoskeleton that prevents differ- entiation of a progenitor cell until it is in the correct cellular and tissue environment.
    [Show full text]
  • DNA Methylation Regulates Discrimination of Enhancers From
    Sharifi-Zarchi et al. BMC Genomics (2017) 18:964 DOI 10.1186/s12864-017-4353-7 RESEARCHARTICLE Open Access DNA methylation regulates discrimination of enhancers from promoters through a H3K4me1-H3K4me3 seesaw mechanism Ali Sharifi-Zarchi1,2,3,4†, Daniela Gerovska5†, Kenjiro Adachi6, Mehdi Totonchi3, Hamid Pezeshk7,8, Ryan J. Taft9, Hans R. Schöler6,10, Hamidreza Chitsaz2, Mehdi Sadeghi8,11, Hossein Baharvand3,12* and Marcos J. Araúzo-Bravo5,13,14* Abstract Background: DNA methylation at promoters is largely correlated with inhibition of gene expression. However, the role of DNA methylation at enhancers is not fully understood, although a crosstalk with chromatin marks is expected. Actually, there exist contradictory reports about positive and negative correlations between DNA methylation and H3K4me1, a chromatin hallmark of enhancers. Results: We investigated the relationship between DNA methylation and active chromatin marks through genome- wide correlations, and found anti-correlation between H3K4me1 and H3K4me3 enrichment at low and intermediate DNA methylation loci. We hypothesized “seesaw” dynamics between H3K4me1 and H3K4me3 in the low and intermediate DNA methylation range, in which DNA methylation discriminates between enhancers and promoters, marked by H3K4me1 and H3K4me3, respectively. Low methylated regions are H3K4me3 enriched, while those with intermediate DNA methylation levels are progressively H3K4me1 enriched. Additionally, the enrichment of H3K27ac, distinguishing active from primed enhancers, follows a plateau in the lower range of the intermediate DNA methylation level, corresponding to active enhancers, and decreases linearly in the higher range of the intermediate DNA methylation. Thus, the decrease of the DNA methylation switches smoothly the state of the enhancers from a primed to an active state.
    [Show full text]
  • Modes of Interaction of KMT2 Histone H3 Lysine 4 Methyltransferase/COMPASS Complexes with Chromatin
    cells Review Modes of Interaction of KMT2 Histone H3 Lysine 4 Methyltransferase/COMPASS Complexes with Chromatin Agnieszka Bochy ´nska,Juliane Lüscher-Firzlaff and Bernhard Lüscher * ID Institute of Biochemistry and Molecular Biology, Medical School, RWTH Aachen University, Pauwelsstrasse 30, 52057 Aachen, Germany; [email protected] (A.B.); jluescher-fi[email protected] (J.L.-F.) * Correspondence: [email protected]; Tel.: +49-241-8088850; Fax: +49-241-8082427 Received: 18 January 2018; Accepted: 27 February 2018; Published: 2 March 2018 Abstract: Regulation of gene expression is achieved by sequence-specific transcriptional regulators, which convey the information that is contained in the sequence of DNA into RNA polymerase activity. This is achieved by the recruitment of transcriptional co-factors. One of the consequences of co-factor recruitment is the control of specific properties of nucleosomes, the basic units of chromatin, and their protein components, the core histones. The main principles are to regulate the position and the characteristics of nucleosomes. The latter includes modulating the composition of core histones and their variants that are integrated into nucleosomes, and the post-translational modification of these histones referred to as histone marks. One of these marks is the methylation of lysine 4 of the core histone H3 (H3K4). While mono-methylation of H3K4 (H3K4me1) is located preferentially at active enhancers, tri-methylation (H3K4me3) is a mark found at open and potentially active promoters. Thus, H3K4 methylation is typically associated with gene transcription. The class 2 lysine methyltransferases (KMTs) are the main enzymes that methylate H3K4. KMT2 enzymes function in complexes that contain a necessary core complex composed of WDR5, RBBP5, ASH2L, and DPY30, the so-called WRAD complex.
    [Show full text]
  • Enhancer Priming by H3K4 Methylation Safeguards Germline Competence
    bioRxiv preprint doi: https://doi.org/10.1101/2020.07.07.192427; this version posted July 7, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Title: Enhancer priming by H3K4 methylation safeguards germline competence 1* 1 1,2 Authors: Tore Bleckwehl ​ ,​ Kaitlin Schaaf ,​ Giuliano Crispatzu ,​ Patricia ​ ​ ​ ​ 1,3 1,4 5 5 Respuela ,​ Michaela Bartusel ,​ Laura Benson ,​ Stephen J. Clark ,​ Kristel M. ​ ​ ​ ​ 6 7 1,8 7,9 Dorighi ,​ Antonio Barral ,​ Magdalena Laugsch ,​ Miguel Manzanares ,​ Joanna ​ ​ ​ ​ 6,10,11 5,12,13 1,3,14* Wysocka ,​ Wolf Reik ,​ Álvaro Rada-Iglesias ​ ​ ​ ​ ​ ​ Affiliations: 1 Center for Molecular Medicine Cologne (CMMC), University of Cologne, Germany. 2 Department of Internal Medicine 2, University Hospital Cologne. 3 Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), CSIC/University of Cantabria, Spain. 4 Department of Biology, Massachusetts Institute of Technology, USA. 5 Epigenetics Programme, Babraham Institute, Cambridge CB22 3AT, UK. 6 Department of Chemical and Systems Biology, Stanford University School of Medicine, USA. 7 Centro Nacional de Investigaciones Cardiovasculares (CNIC), Spain. 8 Institute of Human Genetics, Heidelberg University Hospital, Germany. 9 Centro de Biología Molecular Severo Ochoa (CBMSO), CSIC-UAM, Spain. 10 Department of Developmental Biology, Stanford University School of Medicine, USA. 11 Howard Hughes Medical Institute, Stanford University School of Medicine, USA. 12 Centre for Trophoblast Research, University of Cambridge, CB2 3EG, UK 13 Wellcome Trust Sanger Institute, Cambridge CB10 1SA, UK.
    [Show full text]
  • Deciphering the Histone Code to Build the Genome Structure
    bioRxiv preprint doi: https://doi.org/10.1101/217190; this version posted November 20, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Deciphering the histone code to build the genome structure Kirti Prakasha,b,c,* and David Fournierd,* aPhysico-Chimie Curie, Institut Curie, CNRS UMR 168, 75005 Paris, France; bOxford Nanoimaging Ltd, OX1 1JD, Oxford, UK; cMicron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, Oxford, UK; dFaculty of Biology and Center for Computational Sciences, Johannes Gutenberg University Mainz, 55128 Mainz, Germany; *Correspondence: [email protected], [email protected] Histones are punctuated with small chemical modifications that alter their interaction with DNA. One attractive hypothesis stipulates that certain combinations of these histone modifications may function, alone or together, as a part of a predictive histone code to provide ground rules for chromatin folding. We consider four features that relate histone modifications to chromatin folding: charge neutrali- sation, molecular specificity, robustness and evolvability. Next, we present evidence for the association among different histone modi- fications at various levels of chromatin organisation and show how these relationships relate to function such as transcription, replica- tion and cell division. Finally, we propose a model where the histone code can set critical checkpoints for chromatin to fold reversibly be- tween different orders of the organisation in response to a biological stimulus. DNA | nucleosomes | histone modifications | chromatin domains | chro- mosomes | histone code | chromatin folding | genome structure Introduction The genetic information within chromosomes of eukaryotes is packaged into chromatin, a long and folded polymer of double-stranded DNA, histones and other structural and non- structural proteins.
    [Show full text]
  • Interplay Between P53 and Epigenetic Pathways in Cancer
    University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2016 Interplay Between P53 and Epigenetic Pathways in Cancer Jiajun Zhu University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Biology Commons, Cell Biology Commons, and the Molecular Biology Commons Recommended Citation Zhu, Jiajun, "Interplay Between P53 and Epigenetic Pathways in Cancer" (2016). Publicly Accessible Penn Dissertations. 2130. https://repository.upenn.edu/edissertations/2130 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/2130 For more information, please contact [email protected]. Interplay Between P53 and Epigenetic Pathways in Cancer Abstract The human TP53 gene encodes the most potent tumor suppressor protein p53. More than half of all human cancers contain mutations in the TP53 gene, while the majority of the remaining cases involve other mechanisms to inactivate wild-type p53 function. In the first part of my dissertation research, I have explored the mechanism of suppressed wild-type p53 activity in teratocarcinoma. In the teratocarcinoma cell line NTera2, we show that wild-type p53 is mono-methylated at Lysine 370 and Lysine 382. These post-translational modifications contribute ot the compromised tumor suppressive activity of p53 despite a high level of wild-type protein in NTera2 cells. This study provides evidence for an epigenetic mechanism that cancer cells can exploit to inactivate p53 wild-type function. The paradigm provides insight into understanding the modes of p53 regulation, and can likely be applied to other cancer types with wild-type p53 proteins. On the other hand, cancers with TP53 mutations are mostly found to contain missense substitutions of the TP53 gene, resulting in expression of full length, but mutant forms of p53 that confer tumor-promoting “gain-of-function” (GOF) to cancer.
    [Show full text]
  • Dynamics of Transcription-Dependent H3k36me3 Marking by the SETD2:IWS1:SPT6 Ternary Complex
    bioRxiv preprint doi: https://doi.org/10.1101/636084; this version posted May 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Dynamics of transcription-dependent H3K36me3 marking by the SETD2:IWS1:SPT6 ternary complex Katerina Cermakova1, Eric A. Smith1, Vaclav Veverka2, H. Courtney Hodges1,3,4,* 1 Department of Molecular & Cellular Biology, Center for Precision Environmental Health, and Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA 2 Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, Prague, Czech Republic 3 Center for Cancer Epigenetics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA 4 Department of Bioengineering, Rice University, Houston, TX, 77005, USA * Lead contact; Correspondence to: [email protected] Abstract The genome-wide distribution of H3K36me3 is maintained SETD2 contributes to gene expression by marking gene through various mechanisms. In human cells, H3K36 is bodies with H3K36me3, which is thought to assist in the mono- and di-methylated by eight distinct histone concentration of transcription machinery at the small portion methyltransferases; however, the predominant writer of the of the coding genome. Despite extensive genome-wide data trimethyl mark on H3K36 is SETD21,11,12. Interestingly, revealing the precise localization of H3K36me3 over gene SETD2 is a major tumor suppressor in clear cell renal cell bodies, the physical basis for the accumulation, carcinoma13, breast cancer14, bladder cancer15, and acute maintenance, and sharp borders of H3K36me3 over these lymphoblastic leukemias16–18. In these settings, mutations sites remains rudimentary.
    [Show full text]
  • Genomic and Epigenomic EBF1 Alterations Modulate TERT Expression in Gastric Cancer
    Genomic and epigenomic EBF1 alterations modulate TERT expression in gastric cancer Manjie Xing, … , Bin Tean Teh, Patrick Tan J Clin Invest. 2020;130(6):3005-3020. https://doi.org/10.1172/JCI126726. Research Article Gastroenterology Oncology Graphical abstract Find the latest version: https://jci.me/126726/pdf The Journal of Clinical Investigation RESEARCH ARTICLE Genomic and epigenomic EBF1 alterations modulate TERT expression in gastric cancer Manjie Xing,1,2,3 Wen Fong Ooi,2 Jing Tan,4,5 Aditi Qamra,2,3 Po-Hsien Lee,6 Zhimei Li,5 Chang Xu,1,6 Nisha Padmanabhan,1 Jing Quan Lim,7 Yu Amanda Guo,8 Xiaosai Yao,9 Mandoli Amit,1 Ley Moy Ng,6 Taotao Sheng,1,10 Jing Wang,1 Kie Kyon Huang,1 Chukwuemeka George Anene-Nzelu,11,12 Shamaine Wei Ting Ho,1,6 Mohana Ray,13 Lijia Ma,13 Gregorio Fazzi,14 Kevin Junliang Lim,1 Giovani Claresta Wijaya,5 Shenli Zhang,1 Tannistha Nandi,2 Tingdong Yan,1 Mei Mei Chang,8 Kakoli Das,1 Zul Fazreen Adam Isa,2 Jeanie Wu,1 Polly Suk Yean Poon,2 Yue Ning Lam,2 Joyce Suling Lin,2 Su Ting Tay,1 Ming Hui Lee,1 Angie Lay Keng Tan,1 Xuewen Ong,1 Kevin White,13,15 Steven George Rozen,1,16 Michael Beer,17,18 Roger Sik Yin Foo,11,12 Heike Irmgard Grabsch,14,19 Anders Jacobsen Skanderup,8 Shang Li,1,20 Bin Tean Teh,1,5,6,9,16,20 and Patrick Tan1,2,6,16,21,22,23 1Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore.
    [Show full text]
  • Chromatin Dynamics During DNA Replication Raz Bar-Ziv*, Yoav Voichek* and Naama Barkai†
    Downloaded from genome.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press Chromatin Dynamics during DNA Replication Raz Bar-Ziv*, Yoav Voichek* and Naama Barkai† Affiliations: Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel. *these authors contributed equally to the manuscript †Correspondence to: [email protected] Keywords: Chromatin; Replication; Summary: Chromatin is composed of DNA and histones, which provide a unified platform for regulating DNA-related processes, mostly through their post translational modification. During DNA replication, histone arrangement is perturbed, to first allow progression of DNA polymerase and then during repackaging of the replicated DNA. To study how DNA replication influences the pattern of histone modification, we followed the cell-cycle dynamics of ten histone marks in budding yeast. We find that histones deposited on newly replicated DNA are modified at different rates; while some marks appear immediately upon replication (e.g. H4K16ac, H3K4me1), others increase with transcription-dependent delays (e.g. H3K4me3, H3K36me3). Notably, H3K9ac was deposited as a wave preceding the replication fork by ~5-6 kb. This replication-guided H3K9ac was fully dependent on the acetyltransferase Rtt109, while expression-guided H3K9ac was deposited by Gcn5. Further, topoisomerase depletion intensified H3K9ac in front of the replication fork, and in sites where RNA polymerase II was trapped, suggesting supercoiling stresses trigger H3K9 acetylation. Our results assign complementary roles for DNA replication and gene expression in defining the pattern of histone modification. Introduction: In eukaryotic cells, DNA is wrapped around histone octamers to form nucleosomes, the basic building blocks of the chromatin structure.
    [Show full text]
  • Association of Cnvs with Methylation Variation
    www.nature.com/npjgenmed ARTICLE OPEN Association of CNVs with methylation variation Xinghua Shi1,8, Saranya Radhakrishnan2, Jia Wen1, Jin Yun Chen2, Junjie Chen1,8, Brianna Ashlyn Lam1, Ryan E. Mills 3, ✉ ✉ Barbara E. Stranger4, Charles Lee5,6,7 and Sunita R. Setlur 2 Germline copy number variants (CNVs) and single-nucleotide polymorphisms (SNPs) form the basis of inter-individual genetic variation. Although the phenotypic effects of SNPs have been extensively investigated, the effects of CNVs is relatively less understood. To better characterize mechanisms by which CNVs affect cellular phenotype, we tested their association with variable CpG methylation in a genome-wide manner. Using paired CNV and methylation data from the 1000 genomes and HapMap projects, we identified genome-wide associations by methylation quantitative trait locus (mQTL) analysis. We found individual CNVs being associated with methylation of multiple CpGs and vice versa. CNV-associated methylation changes were correlated with gene expression. CNV-mQTLs were enriched for regulatory regions, transcription factor-binding sites (TFBSs), and were involved in long- range physical interactions with associated CpGs. Some CNV-mQTLs were associated with methylation of imprinted genes. Several CNV-mQTLs and/or associated genes were among those previously reported by genome-wide association studies (GWASs). We demonstrate that germline CNVs in the genome are associated with CpG methylation. Our findings suggest that structural variation together with methylation may affect cellular phenotype. npj Genomic Medicine (2020) 5:41 ; https://doi.org/10.1038/s41525-020-00145-w 1234567890():,; INTRODUCTION influence transcript regulation is DNA methylation, which involves The extent of genetic variation that exists in the human addition of a methyl group to cytosine residues within a CpG population is continually being characterized in efforts to identify dinucleotide.
    [Show full text]
  • Epigenetics Changes in Breast Cancer
    ering & B ne io gi m n e e d io i c B a f l Behera P, J Bioengineer & Biomedical Sci 2017, S Journal of o l c a i e n n r 7:2 c u e o J DOI: 10.4172/2155-9538.1000223 ISSN: 2155-9538 Bioengineering & Biomedical Science Review Article Open Access Epigenetics Changes in Breast Cancer: Current Aspects in India Behera P* Department of Biotechnology, Amity University, Lucknow, India *Corresponding author: Behera P, Department of Biotechnology, Amity University, Lucknow, India, Tel: 9703466651; E-mail: [email protected] Received date: March 25, 2017; Accepted date: April 4, 2017; Published date: April 15, 2017 Copyright: © 2017 Behera P. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited. Abstract Epigenetics is turning out to be one of the promising studies in cancer research. This review focuses mainly on how genetic and epigenetic factors like DNA methylation, histone modifications and various other genes can assess the promoter region of cancer related genes and provides a tool for cancer diagnosis and research. The objective of the review is to provide an overview of the literature with some recent developments providing insights into the important question of co-evolution of epigenetic changes in breast cancer progression and tumorigenesis. This review also comply study of different genetic changes existing in breast cancer. Further in this review focus on functioning of DNA methylation, including both normal, disruptions or abnormal role in human disease, and changes in DNA methylation during human breast cancer is also noted.
    [Show full text]
  • Enhancer Priming by H3K4 Methyltransferase MLL4 Controls Cell Fate Transition
    Enhancer priming by H3K4 methyltransferase MLL4 controls cell fate transition Chaochen Wanga, Ji-Eun Leea, Binbin Laia, Todd S. Macfarlanb, Shiliyang Xua, Lenan Zhuanga, Chengyu Liuc, Weiqun Pengd,e, and Kai Gea,1 aLaboratory of Endocrinology and Receptor Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892; bDivision of Developmental Biology, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD 20892; cTransgenic Core, Center for Molecular Medicine, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892; dDepartment of Physics, The George Washington University, Washington, DC 20052; and eDepartment of Anatomy and Regenerative Biology, The George Washington University, Washington, DC 20052 Edited by Eric N. Olson, University of Texas Southwestern Medical Center, Dallas, TX, and approved August 26, 2016 (received for review April 29, 2016) Transcriptional enhancers control cell-type–specific gene expres- excellent models for studying cell fate transition and the underlying sion. Primed enhancers are marked by histone H3 lysine 4 (H3K4) molecular mechanism. mono/di-methylation (H3K4me1/2). Active enhancers are further MLL4 is a major enhancer H3K4 mono- and di-methyltransfer- marked by H3K27 acetylation (H3K27ac). Mixed-lineage leukemia ase with partial functional redundancy with MLL3 in mammalian 4 (MLL4/KMT2D) is a major enhancer H3K4me1/2 methyltransferase cells (7, 8). MLL4 colocalizes with lineage-determining TFs on AEs with functional redundancy with MLL3 (KMT2C). However, its role in during adipogenesis and myogenesis. Furthermore, MLL4 is re- cell fate maintenance and transition is poorly understood. Here, we quired for enhancer activation, cell-type–specific gene expression, show in mouse embryonic stem cells (ESCs) that MLL4 associates and cell differentiation during adipogenesis and myogenesis (8).
    [Show full text]