Chronic kidney disease (CKD) is a major public health concern, characterized by an irreversible reduction in renal function. Currently, creatinine-based GFR estimation is predominantly used clinically to characterize CKD. However, this method is known to be an insensitive test for early losses of kidney function. Since patient prognosis relies heavily on slowing further decline of kidney function, uncovering novel biomarkers for kidney function, in conjunction with eGFR, will help improve patient outcome. Epigenetic-based biomarkers have been identified in numerous cancers, as DNA methylation changes alter cellular function. Thus, the objective of this study is to determine novel DNA methylation patterns reflecting altered kidney function. Five healthy participants that have undergone a nephrectomy have donated urine samples before and after their surgery, and global DNA methylation changes were analyzed through the 450K HumanMethylation microarray. Site- and region-level analyses were conducted to determine significant differentially methylated probes post-nephrectomy. The differential associations observed post-nephrectomy are statistically significant in both the site-level and regional analyses. Nineteen significant candidate probes have been systematically selected for validation, based on involvement in kidney function and consistent direction of methylation. Pyrosequencing assays have also been successfully designed and tested with control DNA, however replication of the microarray findings in participant DNA was unsuccessful. The inability to validate these candidate probes may be attributed to many influencing factors, and with this in mind, uncovering novel methylation patterns is still a promising biomarker for evaluating kidney function. / Thesis / Master of Science (MSc)

Leung Sau Ching. / Thesis submitted in: October 2003. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 142-165). / Abstracts in English and Chinese. / Acknowledgments --- p.ii / Abstract (English Version) --- p.iii / Abstract (Chinese Version) --- p.vi / Table of Contents --- p.viii / List of Tables --- p.xii / List of Figures --- p.xiii / List of Abbreviations --- p.xv / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- Multiple Myeloma (MM) --- p.1 / Chapter 1.1.1 --- Epidemiology --- p.3 / Chapter 1.1.2 --- Clinical and Pathologic Features of MM --- p.3 / Chapter 1.1.3 --- Diagnosis and Staging --- p.4 / Chapter 1.1.4 --- Prognosis --- p.6 / Chapter 1.1.5 --- Treatment --- p.7 / Chapter 1.2 --- Molecular Abnormalities of MM --- p.8 / Chapter 1.2.1 --- Genetic Alterations: Chromosomal Aberrations --- p.8 / Chapter 1.2.2 --- Genetic Alterations: Ras Mutations --- p.11 / Chapter CHAPTER 2 --- LITERATURE REVIEW --- p.12 / Chapter 2.1 --- Epigenetic Alterations: DNA Methylation --- p.12 / Chapter 2.1.1 --- Characteristics of CpG Island --- p.14 / Chapter 2.1.2 --- Mechanism of Methylation-Related Gene Silencing --- p.14 / Chapter 2.1.3 --- DNA Methylation Is Important for Normal Cellular Functions --- p.17 / Chapter 2.1.4 --- DNA Methylation Changes in Cancer Cells --- p.17 / Chapter 2.1.5 --- Global DNA Hypomethylation --- p.18 / Chapter 2.1.6 --- Regional DNA Hypermethylation --- p.20 / Chapter 2.1.6.1 --- De Novo Methylation --- p.21 / Chapter 2.1.6.2 --- DNA Hypermethylation Acts as a Third Pathway to Loss of Function in Carcinogenesis --- p.21 / Chapter 2.1.6.3 --- DNA Hypermethylation Contributes to Tumorigenesis --- p.25 / Chapter 2.1.6.4 --- Methodologies in the Study of DNA Hypermethylation --- p.26 / Chapter 2.1.6.5 --- Single Gene Hypermethylation --- p.28 / Chapter 2.1.6.6 --- Multiple Gene Hypermethylation --- p.30 / Chapter 2.1.6.7 --- Potential Clinical Applications of DNA Hypermethylation --- p.36 / Chapter 2.1.6.7.1 --- Tumor Cells Detection by 5'CpG Island Hypermethylation --- p.37 / Chapter 2.1.6.7.2 --- Prognostic and Predictive Significances of DNA Hypermethylation --- p.39 / Chapter 2.1.6.7.3 --- Therapeutic Intervention of CpG island Hypermethylation --- p.40 / Chapter 2.2 --- DNA Hypermethylation in MM and MGUS --- p.43 / Chapter 2.3 --- Six-Genes Panel for the Hypermethylation Study --- p.45 / Chapter 2.3.1 --- Apoptotic Pathway: DAP-kinase --- p.45 / Chapter 2.3.2 --- Retinoid Signaling Pathway: RARβ --- p.50 / Chapter 2.3.3 --- Angiogenic Pathway: THBS-1 --- p.52 / Chapter 2.3.4 --- Cell cycle Regulatory Pathway: pl6 and p15 --- p.57 / Chapter 2.3.5 --- Ras Signaling Pathway: RASSF1A --- p.62 / Chapter CHAPTER 3 --- BACKGROUND OF STUDY --- p.67 / Chapter 3.1 --- Rationale --- p.67 / Chapter 3.2 --- Hypothesis --- p.69 / Chapter 3.3 --- The Objectives of Study --- p.70 / Chapter CHAPTER 4 --- MATERIALS AND METHODS --- p.71 / Chapter 4.1 --- Culture of Human Multiple Myeloma (MM)-derived Cell Lines --- p.71 / Chapter 4.2 --- Demethylation Treatment --- p.72 / Chapter 4.3 --- Patient and Control Samples --- p.72 / Chapter 4.4 --- DNA Extraction --- p.73 / Chapter 4.5 --- MS-PCR --- p.73 / Chapter 4.6 --- Plasma Cell Isolation --- p.77 / Chapter 4.7 --- RNA Extraction and RT-PCR --- p.78 / Chapter 4.8 --- Statistics --- p.82 / Chapter CHAPTER 5 --- RESULTS --- p.84 / Chapter 5.1 --- Patient Characteristics --- p.84 / Chapter 5.2 --- Single Gene Hypermethylation --- p.87 / Chapter 5.2.1 --- Normal PB Did Not Show Methylation --- p.87 / Chapter 5.2.2 --- DNA Hypermethylation in Human MM-derived Cell Lines --- p.87 / Chapter 5.2.3 --- DNA Hypermethylation in Primary MM --- p.89 / Chapter 5.3 --- Demethylation Treatment --- p.93 / Chapter 5.4 --- Concurrent Hypermethylation --- p.96 / Chapter 5.5 --- Statistical Analyses of Primary MM --- p.101 / Chapter 5.5.1 --- Statistical Analyses Between Single Gene Hypermethylation and Clinical Parameters (Categorical) --- p.101 / Chapter 5.5.2 --- Statistical Analyses Between Single Gene Hypermethylation and Clinical Parameters (Non-Categorical) --- p.101 / Chapter 5.5.3 --- Survival Analyses of Single Gene Hypermethylation --- p.105 / Chapter 5.5.4 --- Correlation Analyses of Concurrent Hypermethylation --- p.107 / Chapter 5.5.5 --- Correlation Analyses Between Concurrent Hypermethylation and Clinical Parameters --- p.107 / Chapter CHAPTER 6 --- DISCUSSION --- p.110 / Chapter 6.1 --- Involvement of Cellular Pathways by Hypermethylation --- p.111 / Chapter 6.1.1 --- Apoptotic Pathway: DAP-kinase and RARβ --- p.111 / Chapter 6.1.2 --- "Cell Cycle Regulatory Pathway: p16, p15 and RASSF1A" --- p.113 / Chapter 6.1.3 --- Angiogenic Pathway: THBS-1 --- p.117 / Chapter 6.2 --- Hypermethylation-Associated Gene Silencing --- p.119 / Chapter 6.3 --- Hypermethylation in Cell Lines and Primary MM --- p.120 / Chapter 6.4 --- Concurrent Hypermethylation --- p.122 / Chapter 6.4.1 --- DNA Hypermethylation is Common in MM --- p.122 / Chapter 6.4.2 --- Extent of Hypermethylation --- p.123 / Chapter 6.4.3 --- Involvement of Cellular Pathways by DNA Hypermethylation --- p.124 / Chapter 6.4.4 --- Concurrent p16 and DAP-kinase Hypermethylation --- p.126 / Chapter 6.5 --- Clinical Applications of DNA Hypermethylation --- p.129 / Chapter 6.5.1 --- Methylation As Tumor Markers for MM --- p.129 / Chapter 6.5.2 --- Prognostic Implications of DNA Hypermethylation in MM --- p.130 / Chapter 6.5.3 --- Correlations Between DNA Hypermethylation and Clinical Parameters --- p.131 / Chapter 6.6 --- MS-PCR --- p.136 / Chapter CHAPTER 7 --- CONCLUSION --- p.137 / Chapter CHAPTER 8 --- FURTHER STUDIES --- p.140 / References --- p.142

Zhong, Yangliu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 50-57). / Abstracts in English and Chinese. / Title Page --- p.i / Thesis Committee --- p.ii / Abstract (English Version) --- p.iv / Abstract (Chinese Version) --- p.V / Acknowledgement --- p.vi / Table of Contents --- p.viii / List of Tables --- p.X / List of Figures --- p.xii / List of Abbreviations and Symbols --- p.xiii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- DNA methylation --- p.1 / Chapter 1.2 --- Repair of m3T --- p.2 / Chapter 1.3 --- Objectives of this work --- p.3 / Chapter 1.4 --- DNA structure --- p.3 / Chapter 1.4.1 --- Nomenclature scheme for DNA --- p.3 / Chapter 1.4.2 --- Base pair scheme --- p.4 / Chapter 1.4.3 --- Sugar conformation --- p.5 / Chapter 1.4.4 --- Backbone conformation --- p.7 / Chapter 2 --- Materials and Methods --- p.9 / Chapter 2.1 --- Sample design --- p.9 / Chapter 2.2 --- Sample preparation --- p.10 / Chapter 2.3 --- NMR analysis --- p.10 / Chapter 2.3.1 --- Resonance assignment --- p.12 / Chapter 2.3.2 --- Determination of sugar conformation --- p.13 / Chapter 2.3.3 --- Determination of backbone conformation --- p.14 / Chapter 2.4 --- UV melting study --- p.15 / Chapter 3 --- Effect of m3T on Double-Helical Structures and Stabilities --- p.17 / Chapter 3.1 --- Resonance assignments --- p.17 / Chapter 3.2 --- Effect of m3T on double-helical DNA structures --- p.19 / Chapter 3.2.1 --- Base pairing mode --- p.19 / Chapter 3.2.2 --- Sugar conformation --- p.21 / Chapter 3.2.3 --- Backbone conformation --- p.22 / Chapter 3.3 --- Effect of m3T on double-helical DNA stabilities --- p.25 / Chapter 3.4 --- Discussion --- p.26 / Chapter 3.4.1 --- Single-strand requirement in FTO repair --- p.26 / Chapter 3.4.2 --- Relationship between m3T pairing structure and stability --- p.27 / Chapter 4 --- Effect of m3T Mispair on Double-Helical DNA Structures and Stabilities --- p.28 / Chapter 4.1 --- Resonance assignments --- p.28 / Chapter 4.2 --- Effect of m3T mispair on double-helical DNA structures --- p.32 / Chapter 4.2.1 --- Pairing mode of T m3T --- p.34 / Chapter 4.2.2 --- Pairing mode of G m3T --- p.35 / Chapter 4.2.3 --- Pairing mode of C.m3T --- p.35 / Chapter 4.3 --- Effect of m3T mispair on double-helical DNA stabilities --- p.36 / Chapter 4.4 --- Discussion --- p.36 / Chapter 4.4.1 --- Predominant mutation --- p.37 / Chapter 4.4.2 --- Relationship between m3T pairing structure and stabilities --- p.37 / Chapter 5 --- Conclusion and Future Work --- p.39 / Chapter Appendix I --- Proton chemical shift values (ppm) of AmT --- p.40 / Chapter Appendix II --- Proton chemical shift values (ppm) of RefAT --- p.41 / Chapter Appendix III --- Proton chemical shift values of NmT samples --- p.42 / Chapter Appendix IV --- "Σ1' and %S of TmT, GmT and CmT" --- p.45 / Chapter Appendix V --- "1H-31P HSQC spectra of (a) TmT, (b) GmT and (c) CmT" --- p.46 / Chapter Appendix VI --- "1H-31P COSY spectra of (a) TmT, (b) GmT and (c) CmT" --- p.47 / Chapter Appendix VII --- "31P chemical shifts, 3JH3'P and %Bi of TmT, GmT and CmT" --- p.48 / Chapter Appendix VIII --- "UV melting curves of RefAT, AmT, TmT, GmT and CmT" --- p.49 / References --- p.50

Change of DNA methylation is a hallmark of cancer. It is frequently associated with cancer progression. Testicular germ cell tumor (TGCT) is the most common malignant tumor in young males. Currently, only a limited number of genes are known to be epigenetically changed in TGCT. Genome-wide analysis of differential methylation in a previously established testicular cell line is documented here. A total of 35,208 differentially methylated regions (DMR) were identified. However, only a small number of DMRs mapped to gene promoters. Genome-wide analysis of gene expression revealed a group of differentially expressed genes that were regulated by DNA methylation. Several candidate genes ( APOLD1, PCDH10 and RGAG1) were found to be dysregulated in TGCT patients. Surprisingly, APOLD1 was mapped to the TGCT susceptibility locus at 12p13.1, suggesting that it may be important in TGCT pathogenesis. / The majority of DMRs are located in introns or intergenic regions, but their functions are not well understood. Some of these DMRs were found to regulate non-coding RNAs (ncRNAs). In this study, differential methylation of 3 small nucleolar RNAs (snoRNA) and 3 microRNAs (miRNA) were identified. One of the miRNAs, miR-199a, is embedded in a conserved region in intron-14 of dynamin 3 at 1q24.3. Hypermethylation of miR-199a correlated with testicular cancer progression, and silencing of miR-199a. Re-expression of miR-199a in testicular cancer cells suppressed cell growth, cancer migration, invasion, and metastasis. miR-199a-5p, one of two mature miRNA species derived from miR-199a, is associated with cancer progression. An embryonal carcinoma antigen, podocalyxin-like protein 1 (PODXL), was identified to be a target of miR-199a-sp. PODXL is an anti-adhesive protein overexpressed in aggressive testicular cancer. Knockdown of PODXL suppressed cancer invasion. The inverse relationship between PODXL and miR-199a-5p expression suggests that PODXL is one of the downstream effectors mediating cancer invasion and metastasis. This study links DNA methylation, miR-199a dysregulation, and PODXL expression as a mechanism to explain testicular cancer progression. / Cheung, Hoi Hung. / Adviser: Woi-Yee Chan. / Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 165-192). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Zhan, Yingqian. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 49-54). / Abstracts in English and Chinese. / Title Page --- p.i / Thesis Committee --- p.ii / Abstract (English version) --- p.iv / Abstract (Chinese version) --- p.v / Acknowledgment --- p.vi / Table of Contents --- p.vii / List of Tables --- p.ix / List of Figures --- p.x / List of Abbreviations and Symbols --- p.xiii / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- DNA Methylation --- p.1 / Chapter 1.2 --- DNA Structure --- p.2 / Chapter 1.2.1 --- Nomenclature Scheme for DNA --- p.2 / Chapter 1.2.2 --- Conformations of DNA --- p.5 / Chapter 1.2.3 --- Base Pair Scheme --- p.5 / Chapter 1.2.4 --- Sugar Conformation --- p.7 / Chapter 1.2.5 --- Backbone Conformation --- p.7 / Chapter 1.3 --- DNA Melting --- p.7 / Chapter 1.4 --- Objective of this Work --- p.8 / Chapter 2. --- Materials and Methodology --- p.9 / Chapter 2.1 --- Sequence Design --- p.9 / Chapter 2.2 --- Sample Preparation --- p.10 / Chapter 2.3 --- Resonance Assignment --- p.10 / Chapter 2.3.1 --- Proton Resonance Assignment --- p.11 / Chapter 2.3.2 --- Phosphorous Resonance Assignment --- p.14 / Chapter 2.4 --- Determination of Sugar Conformation --- p.15 / Chapter 2.5 --- Determination of Backbone Conformation --- p.16 / Chapter 2.6 --- Thermodynamic study on DNA --- p.18 / Chapter 3. --- Effects of N1-methylated Adenine on DNA Structure and Stability --- p.21 / Chapter 3.1 --- Overview --- p.21 / Chapter 3.2 --- Resonance Assignment Results --- p.21 / Chapter 3.2.1 --- 1H Resonance Assignments --- p.21 / Chapter 3.2.2 --- 31P Resonance Assignments --- p.23 / Chapter 3.3 --- Base Pair Structures --- p.24 / Chapter 3.4 --- Sugar Conformation --- p.26 / Chapter 3.5 --- Backbone Conformation --- p.27 / Chapter 3.6 --- Thermodynamic Stability Study --- p.29 / Chapter 4. --- Effects of N1-methylated Guanine on DNA Structure and Stability --- p.31 / Chapter 4.1 --- Overview --- p.31 / Chapter 4.2 --- Resonance Assignment Results --- p.31 / Chapter 4.2.1 --- 1H Resonance Assignments --- p.31 / Chapter 4.2.2 --- 31P Resonance Assignments --- p.33 / Chapter 4.3 --- Base Pair Structures --- p.34 / Chapter 4.4 --- Sugar Conformation --- p.36 / Chapter 4.5 --- Backbone Conformation --- p.39 / Chapter 4.6 --- Thermodynamic Stability Study --- p.41 / Chapter 5. --- Conclusion and Future work --- p.43 / Appendix I H1'-H6/H8 region of NOESY spectra of TmeA at 25 °C with different mixing times --- p.44 / "Appendix II 3JH1'h2"", 3JH1'h2"", and %S of TmeA and refTA" --- p.45 / "Appendix III 3JH1' h2'，3JH1'-H2"", and %S of CmeG and refCG" --- p.46 / "Appendix IV 31P chemical shifts, 3JH3'p and %B1 of TmeA, and refTA" --- p.47 / "Appendix V 31P chemical shifts, 3JH3'P and %B1of CmeG, and refCG" --- p.48 / References --- p.49

published_or_final_version / abstract / Medicine / Master / Master of Philosophy

Asthma is a heterogeneous group of conditions that typically begin in early life and result in recurrent, reversible bronchial obstruction. The role played by epigenetic mechanisms in the pathogenesis of childhood asthma is understood only in part. Here we discuss asthma epigenetics within a developmental perspective based on our recent demonstration that the epigenetic trajectory to childhood asthma begins at birth. We next discuss how this trajectory may be affected by prenatal environmental exposures. Finally, we examine in vitro studies that model the impact of asthma-associated exposures on the epigenome. All of these studies specifically surveyed human DNA methylation and involved a genome-wide component. In combination, their results broaden our understanding of asthma pathogenesis and the role the methylome plays in this process.

A dissertation submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Medicine / Fetal Alcohol Syndrome (F AS), the most severe form of Fetal Alcohol Spectrum Disorder (F ASD), has traditionally been associated with maternal alcohol consumption during pregnancy. However, a number of animal studies have shown an association between paternal preconception alcohol consumption and developmental abnormalities in the offspring that resemble the features of F AS. Dysregulation of epigenetic factors (such as DNA methylation) in the presence of alcohol may provide a plausible mechanism by which paternal alcohol consumption could result in offspring affected with features of F AS. Imprinted genes are expressed in a parentof- origin manner due to DNA methylation at distinct differentially methylated regions (DMRs) and are essential for normal embryonic development. There are only two known paternally methylated DMRs in humans, with an additional one described in mice - associated with Rasgrfl. The first aim of this study was to determine whether the human RASGRFl gene contains a DMR and whether this DMR is paternally methylated. In order to assess the imprint status of RASGRF 1, a number of computational assessments were done to identify key features of imprinted loci. Pyrosequencing analysis was used to assess the methylation status of various CpO islands surrounding RASGRFi in peripheral blood and sperm DNA samples. The RASGRF i-associated CpO regions were not found to exhibit differential methylation in a parent-of-origin manner. The second aIm of the study was to examine the effect of paternal alcohol consumption on the methylation status of the IG-DMR locus in male gametes and to detennine whether alcohol is correlated with methylation in a dose-dependant manner. Methylation assessment was done using the quantitative pyrosequencing technology. While an overall reduction in methylation was noted in males who consumed alcohol after adjusting for confounding variables, the amount of alcohol consumed did not correlate with overall methylation. When analyzed by individual CpG sites, alcohol consumption was found to correlate preferentially with demethylation at CpG 3 while alcohol-dosage preferentially correlated with demethylation at CpG 7. Age was significantly correlated with an increase in the overall methylation at JG-DMR and at individual sites within JG-DMR. In conclusion, these findings support the hypothesis that paternal preconception alcohol consumption can lead to hypomethylation of nonnally hypennethylated DMRs of specific imprinted genes in human spenn. This in tum could have significant implications with regard to the regulation of developmentally significant genes in the zygote and fetus, resulting in developmental, behavioral and neurocognitive disorders.

DNA methylation plays a crucial role in human health, especially cancer. Traditional DNA methylation analysis aims to identify CpGs/genes with differential methylation (DM) between experimental groups. Differential variability (DV) was recently observed that contributes to cancer heterogeneity and was also shown to be essential in detecting early DNA methylation alterations, notably epigenetic field defects. Moreover, studies have demonstrated that environmental factors may modify the effect of DNA methylation on health outcomes, or vice versa. Therefore, this dissertation seeks to develop new statistical methods for epigenetic data focusing on DV and interactions when efficient analytical tools are lacking. First, as neighboring CpG sites are usually highly correlated, we introduced a new method to detect differentially methylated regions (DMRs) that uses combined DM and DV signals between diseased and non-diseased groups. Next, using both DM and DV signals, we considered the problem of identifying epigenetic field defects, when CpG-site-level DM and DV signals are minimal and hard to be detected by existing methods. We proposed a weighted epigenetic distance-based method that accumulates CpG-site-level DM and DV signals in a gene. Here DV signals were captured by a pseudo-data matrix constructed using centered quadratic methylation measures. CpG-site-level association signal annotations were introduced as weights in distance calculations to up-weight signal CpGs and down-weight noise CpGs to further boost the study power. Lastly, we extended the weighted epigenetic distance-based method to incorporate DNA methylation by environment interactions in the detection of overall association between DNA methylation and health outcomes. A pseudo-data matrix was constructed with cross-product terms between DNA methylation and environmental factors that is able to capture their interactions. The superior performance of the proposed methods were shown through intensive simulation studies and real data applications to multiple DNA methylation data.

Transcriptional repression is maintained by many molecular processes, including DNA methylation and polycomb repression. These two systems are both associated with chromatin modification at the promoters of silent genes, and are both essential for mammalian development. Previous work has shown that DNMT proteins are required for correct targeting of polycomb repressive complexes (PRCs). In this thesis, I investigate whether targeting of DNA modification has a reciprocal dependence on the polycomb machinery by mapping DNA modification in wild-type and PRC-mutant ES cells (Ring1B null, EED null, and Ring1B/EED duble null). I find that the loss of PRCs results in increased DNA modification at sites normally targeted by de novo DNA methyltransferase which lose H3K4 methylation upon PRC removal. This increased DNA modificaiton is associated with increased gene expression when found at CpG island shores of genes marked by the PRC-mediated histone modifications H3K27me3 and H2AK119ub, but not genes lacking these marks. Gene misregulation may be further linked to DNA modification changes by increased DNA modification at enhancers. While loss of either Ring1B or EED led primarily to increases in DNA modification at regions dependant on DNMT3A/DNMT3B, the combined loss of Ring1B and EED results in widespread loss of DNA modification at sites more dependent on DNMT1 activity. This thesis suggests an interplay between PRCs and DNA modification placement which is relevant to the cntrol of gene expression.