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Sahoo K, Sundararajan V. Methods in DNA methylation array dataset analysis: A review. Comput Struct Biotechnol J 2024; 23:2304-2325. [PMID: 38845821 PMCID: PMC11153885 DOI: 10.1016/j.csbj.2024.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 04/25/2024] [Accepted: 05/08/2024] [Indexed: 06/09/2024] Open
Abstract
Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.
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Affiliation(s)
| | - Vino Sundararajan
- Correspondence to: Department of Bio Sciences, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore 632 014, Tamil Nadu, India.
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2
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Górczak K, Burzykowski T, Claesen J. A varying-coefficient model for the analysis of methylation sequencing data. Comput Biol Chem 2024; 111:108094. [PMID: 38781748 DOI: 10.1016/j.compbiolchem.2024.108094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 05/06/2024] [Accepted: 05/08/2024] [Indexed: 05/25/2024]
Abstract
DNA methylation is an important epigenetic modification involved in gene regulation. Advances in the next generation sequencing technology have enabled the retrieval of DNA methylation information at single-base-resolution. However, due to the sequencing process and the limited amount of isolated DNA, DNA-methylation-data are often noisy and sparse, which complicates the identification of differentially methylated regions (DMRs), especially when few replicates are available. We present a varying-coefficient model for detecting DMRs by using single-base-resolved methylation information. The model simultaneously smooths the methylation profiles and allows detection of DMRs, while accounting for additional covariates. The proposed model takes into account possible overdispersion by using a beta-binomial distribution. The overdispersion itself can be modeled as a function of the genomic region and explanatory variables. We illustrate the properties of the proposed model by applying it to two real-life case studies.
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Affiliation(s)
- Katarzyna Górczak
- Data Science Institute, Hasselt University, Belgium; Open Analytics NV, Antwerp, Belgium
| | - Tomasz Burzykowski
- Data Science Institute, Hasselt University, Belgium; Department of Biostatistics and Medical Informatics, Medical University of Bialystok, Poland; International Drug Development Institute (IDDI), Belgium
| | - Jürgen Claesen
- Data Science Institute, Hasselt University, Belgium; Department of Epidemiology and Data Science, Amsterdam UMC, VU Amsterdam, The Netherlands.
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3
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Geens B, Goossens S, Li J, Van de Peer Y, Vanden Broeck J. Untangling the gordian knot: The intertwining interactions between developmental hormone signaling and epigenetic mechanisms in insects. Mol Cell Endocrinol 2024; 585:112178. [PMID: 38342134 DOI: 10.1016/j.mce.2024.112178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/30/2024] [Accepted: 02/04/2024] [Indexed: 02/13/2024]
Abstract
Hormones control developmental and physiological processes, often by regulating the expression of multiple genes simultaneously or sequentially. Crosstalk between hormones and epigenetics is pivotal to dynamically coordinate this process. Hormonal signals can guide the addition and removal of epigenetic marks, steering gene expression. Conversely, DNA methylation, histone modifications and non-coding RNAs can modulate regional chromatin structure and accessibility and regulate the expression of numerous (hormone-related) genes. Here, we provide a review of the interplay between the classical insect hormones, ecdysteroids and juvenile hormones, and epigenetics. We summarize the mode-of-action and roles of these hormones in post-embryonic development, and provide a general overview of epigenetic mechanisms. We then highlight recent advances on the interactions between these hormonal pathways and epigenetics, and their involvement in development. Furthermore, we give an overview of several 'omics techniques employed in the field. Finally, we discuss which questions remain unanswered and possible avenues for future research.
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Affiliation(s)
- Bart Geens
- Molecular Developmental Physiology and Signal Transduction, KU Leuven, Naamsestraat 59 box 2465, B-3000 Leuven, Belgium.
| | - Stijn Goossens
- Molecular Developmental Physiology and Signal Transduction, KU Leuven, Naamsestraat 59 box 2465, B-3000 Leuven, Belgium.
| | - Jia Li
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium; VIB Center for Plant Systems Biology, VIB, Ghent, Belgium.
| | - Yves Van de Peer
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium; VIB Center for Plant Systems Biology, VIB, Ghent, Belgium.
| | - Jozef Vanden Broeck
- Molecular Developmental Physiology and Signal Transduction, KU Leuven, Naamsestraat 59 box 2465, B-3000 Leuven, Belgium.
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4
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Zhao N, Lai C, Wang Y, Dai S, Gu H. Understanding the role of DNA methylation in colorectal cancer: Mechanisms, detection, and clinical significance. Biochim Biophys Acta Rev Cancer 2024; 1879:189096. [PMID: 38499079 DOI: 10.1016/j.bbcan.2024.189096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 02/18/2024] [Accepted: 03/13/2024] [Indexed: 03/20/2024]
Abstract
Colorectal cancer (CRC) is one of the deadliest malignancies worldwide, ranking third in incidence and second in mortality. Remarkably, early stage localized CRC has a 5-year survival rate of over 90%; in stark contrast, the corresponding 5-year survival rate for metastatic CRC (mCRC) is only 14%. Compounding this problem is the staggering lack of effective therapeutic strategies. Beyond genetic mutations, which have been identified as critical instigators of CRC initiation and progression, the importance of epigenetic modifications, particularly DNA methylation (DNAm), cannot be underestimated, given that DNAm can be used for diagnosis, treatment monitoring and prognostic evaluation. This review addresses the intricate mechanisms governing aberrant DNAm in CRC and its profound impact on critical oncogenic pathways. In addition, a comprehensive review of the various techniques used to detect DNAm alterations in CRC is provided, along with an exploration of the clinical utility of cancer-specific DNAm alterations.
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Affiliation(s)
- Ningning Zhao
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei 230031, China
| | - Chuanxi Lai
- Division of Colorectal Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310016, China
| | - Yunfei Wang
- Zhejiang ShengTing Biotech. Ltd, Hangzhou 310000, China
| | - Sheng Dai
- Division of Colorectal Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310016, China.
| | - Hongcang Gu
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei 230031, China.
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5
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Wang R, Yang Y, Lu T, Cui Y, Li B, Liu X. Circulating cell-free DNA-based methylation pattern in plasma for early diagnosis of esophagus cancer. PeerJ 2024; 12:e16802. [PMID: 38313016 PMCID: PMC10838104 DOI: 10.7717/peerj.16802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 12/26/2023] [Indexed: 02/06/2024] Open
Abstract
With the increased awareness of early tumor detection, the importance of detecting and diagnosing esophageal cancer in its early stages has been underscored. Studies have consistently demonstrated the crucial role of methylation levels in circulating cell-free DNA (cfDNA) in identifying and diagnosing early-stage cancer. cfDNA methylation pertains to the methylation state within the genomic scope of cfDNA and is strongly associated with cancer development and progression. Several research teams have delved into the potential application of cfDNA methylation in identifying early-stage esophageal cancer and have achieved promising outcomes. Recent research supports the high sensitivity and specificity of cfDNA methylation in early esophageal cancer diagnosis, providing a more accurate and efficient approach for early detection and improved clinical management. Accordingly, this review aims to present an overview of methylation-based cfDNA research with a focus on the latest developments in the early detection of esophageal cancer. Additionally, this review summarizes advanced analytical technologies for cfDNA methylation that have significantly benefited from recent advancements in separation and detection techniques, such as methylated DNA immunoprecipitation sequencing (MeDIP-seq). Recent findings suggest that biomarkers based on cfDNA methylation may soon find successful applications in the early detection of esophageal cancer. However, large-scale prospective clinical trials are required to identify the potential of these biomarkers.
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Affiliation(s)
- Rui Wang
- School of Public Health, Jilin University, Changchun, Jilin, China
| | - Yue Yang
- Department of Thoracic Surgery, First Hospital of Jilin University, Changchun, Jilin, China
| | - Tianyu Lu
- Department of Thoracic Surgery, First Hospital of Jilin University, Changchun, Jilin, China
| | - Youbin Cui
- Department of Thoracic Surgery, First Hospital of Jilin University, Changchun, Jilin, China
| | - Bo Li
- School of Public Health, Jilin University, Changchun, Jilin, China
| | - Xin Liu
- Department of Thoracic Surgery, First Hospital of Jilin University, Changchun, Jilin, China
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Hu Y, Shen F, Yang X, Han T, Long Z, Wen J, Huang J, Shen J, Guo Q. Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity. Clin Epigenetics 2023; 15:161. [PMID: 37821906 PMCID: PMC10568863 DOI: 10.1186/s13148-023-01574-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 09/27/2023] [Indexed: 10/13/2023] Open
Abstract
BACKGROUND Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies. RESULTS The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development. CONCLUSION This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.
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Affiliation(s)
- Yuhua Hu
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
- Graduate School, Dalian Medical University, Dalian, 116044, Liaoning, China
| | - Feng Shen
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
- Department of Neurosurgery, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
| | - Xi Yang
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Tingting Han
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
- Graduate School, Dalian Medical University, Dalian, 116044, Liaoning, China
| | - Zhuowen Long
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
| | - Jiale Wen
- Graduate School, Dalian Medical University, Dalian, 116044, Liaoning, China
- Department of Cardiology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
| | - Junxing Huang
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
| | - Jiangfeng Shen
- Department of Thoracic Surgery, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
| | - Qing Guo
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
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Bian Y, Gao Y, Lu C, Tian B, Xin L, Lin H, Zhang Y, Zhang X, Zhou S, Wan K, Zhou J, Li Z, Chen H, Wang L. Genome-wide methylation profiling identified methylated KCNA3 and OTOP2 as promising diagnostic markers for esophageal squamous cell carcinoma. Chin Med J (Engl) 2023:00029330-990000000-00789. [PMID: 37650127 DOI: 10.1097/cm9.0000000000002832] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Indexed: 09/01/2023] Open
Abstract
BACKGROUND Early detection of esophageal squamous cell carcinoma (ESCC) can considerably improve the prognosis of patients. Aberrant cell-free DNA (cfDNA) methylation signatures are a promising tool for detecting ESCC. However, available markers based on cell-free DNA methylation are still inadequate. This study aimed to identify ESCC-specific cfDNA methylation markers and evaluate the diagnostic performance in the early detection of ESCC. METHODS We performed whole-genome bisulfite sequencing (WGBS) for 24 ESCC tissues and their normal adjacent tissues. Based on the WGBS data, we identified 21,469,837 eligible CpG sites (CpGs). By integrating several methylation datasets, we identified several promising ESCC-specific cell-free DNA methylation markers. Finally, we developed a dual-marker panel based on methylated KCNA3 and OTOP2, and then, we evaluated its performance in our training and validation cohorts. RESULTS The ESCC diagnostic model constructed based on KCNA3 and OTOP2 had an AUC of 0.91 [95% CI: 0.85-0.95], and an optimal sensitivity and specificity of 84.91% and 94.32%, respectively, in the training cohort. In the independent validation cohort, the AUC was 0.88 [95% CI: 0.83-0.92], along with an optimal sensitivity of 81.5% and specificity of 92.9%. The model sensitivity for stage I-II ESCC was 78.4%, which was slightly lower than the sensitivity of the model (85.7%) for stage III-IV ESCC. CONCLUSIONS The dual-target panel based on cfDNA showed excellent performance for detecting ESCC and might be an alternative strategy for screening ESCC.
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Affiliation(s)
- Yan Bian
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Ye Gao
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Chaojing Lu
- Department of Thoracic Surgery, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Bo Tian
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Lei Xin
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Han Lin
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Yanhui Zhang
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Xun Zhang
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Siwei Zhou
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Kangkang Wan
- Wuhan Ammunition Life-tech Co., Ltd., Wuhan, Hubei430000, China
| | - Jun Zhou
- Wuhan Ammunition Life-tech Co., Ltd., Wuhan, Hubei430000, China
| | - Zhaoshen Li
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Hezhong Chen
- Department of Thoracic Surgery, Changhai Hospital, Naval Medical University, Shanghai200433, China
| | - Luowei Wang
- Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai200433, China
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Colicchio JM, Amstutz CL, Garcia N, Prabhu KN, Cairns TM, Akman M, Gottilla T, Gollery T, Stricklin SL, Bayer TS. A tool for rapid, automated characterization of population epigenomics in plants. Sci Rep 2023; 13:12915. [PMID: 37591855 PMCID: PMC10435466 DOI: 10.1038/s41598-023-38356-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 07/06/2023] [Indexed: 08/19/2023] Open
Abstract
Epigenetic variation in plant populations is an important factor in determining phenotype and adaptation to the environment. However, while advances have been made in the molecular and computational methods to analyze the methylation status of a given sample of DNA, tools to profile and compare the methylomes of multiple individual plants or groups of plants at high resolution and low cost are lacking. Here, we describe a computational approach and R package (sounDMR) that leverages the benefits of long read nanopore sequencing to enable robust identification of differential methylation from complex experimental designs, as well as assess the variability within treatment groups and identify individual plants of interest. We demonstrate the utility of this approach by profiling a population of Arabidopsis thaliana exposed to a demethylating agent and identify genomic regions of high epigenetic variability between individuals. Given the low cost of nanopore sequencing devices and the ease of sample preparation, these results show that high resolution epigenetic profiling of plant populations can be made more broadly accessible in plant breeding and biotechnology.
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Affiliation(s)
| | | | | | | | | | - Melis Akman
- Sound Agriculture Company, Emeryville, CA, USA
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Drewell RA, Cormier TC, Steenwyk JL, Denis JS, Tabima J, Dresch J, Larochelle D. The Dictyostelium discoideum genome lacks significant DNA methylation and uncovers palindromic sequences as a source of false positives in bisulfite sequencing. NAR Genom Bioinform 2023; 5:lqad035. [PMID: 37081864 PMCID: PMC10111430 DOI: 10.1093/nargab/lqad035] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/13/2023] [Accepted: 03/30/2023] [Indexed: 04/22/2023] Open
Abstract
DNA methylation, the addition of a methyl (CH3) group to a cytosine residue, is an evolutionarily conserved epigenetic mark involved in a number of different biological functions in eukaryotes, including transcriptional regulation, chromatin structural organization, cellular differentiation and development. In the social amoeba Dictyostelium, previous studies have shown the existence of a DNA methyltransferase (DNMA) belonging to the DNMT2 family, but the extent and function of 5-methylcytosine in the genome are unclear. Here, we present the whole genome DNA methylation profile of Dictyostelium discoideum using deep coverage replicate sequencing of bisulfite-converted gDNA extracted from post-starvation cells. We find an overall very low number of sites with any detectable level of DNA methylation, occurring at significant levels in only 303-3432 cytosines out of the ∼7.5 million total cytosines in the genome depending on the replicate. Furthermore, a knockout of the DNMA enzyme leads to no overall decrease in DNA methylation. Of the identified sites, significant methylation is only detected at 11 sites in all four of the methylomes analyzed. Targeted bisulfite PCR sequencing and computational analysis demonstrate that the methylation profile does not change during development and that these 11 cytosines are most likely false positives generated by protection from bisulfite conversion due to their location in hairpin-forming palindromic DNA sequences. Our data therefore provide evidence that there is no significant DNA methylation in Dictyostelium before fruiting body formation and identify a reproducible experimental artifact from bisulfite sequencing.
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Affiliation(s)
- Robert A Drewell
- Biology Department, Clark University, 950 Main Street, Worcester, MA 01610, USA
| | - Tayla C Cormier
- Biology Department, Clark University, 950 Main Street, Worcester, MA 01610, USA
| | - Jacob L Steenwyk
- Biology Department, Clark University, 950 Main Street, Worcester, MA 01610, USA
- Howard Hughes Medical Institute and Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - James St Denis
- Biology Department, Clark University, 950 Main Street, Worcester, MA 01610, USA
| | - Javier F Tabima
- Biology Department, Clark University, 950 Main Street, Worcester, MA 01610, USA
| | - Jacqueline M Dresch
- Biology Department, Clark University, 950 Main Street, Worcester, MA 01610, USA
| | - Denis A Larochelle
- Biology Department, Clark University, 950 Main Street, Worcester, MA 01610, USA
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Yu X, Che Y, Li W, Zhang P, Yu Y, Chen J, Gong T, Cao F. DNA5mC Regulator-Mediated Molecular Clusters and Tumor Microenvironment Signatures in Glioblastoma. Front Cell Dev Biol 2022; 10:1055567. [DOI: 10.3389/fcell.2022.1055567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 10/20/2022] [Indexed: 11/10/2022] Open
Abstract
Growing evidence links DNA methylation to tumor immunity. The impact of DNA methylation (5 mC) on the microenvironment surrounding tumors and immunotherapy remains to be clarified. Through clustering gene expression of 20 DNA methylation regulators, this study aimed at systematically analyzing DNA methylation regulator patterns and tumor microenvironment characteristics of TCGA-GBM patients. Various subtypes of glioblastoma exhibit different tumor microenvironments and DNA methylation patterns. Each DNA methylation modification was then assigned a DNA methylation score (DMS). High DMS was associated with a good prognosis. In contrast, the low DMS group had a relatively low survival rate. A correlation was also found between high DMS and enhanced immunotherapy efficacy in two immune checkpoint blocking treatment cohorts. To conclude, identifying DNA methylation regulation patterns may prove critical to understanding glioblastoma progression and differentiation, as well as future therapeutic targets.
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