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Sigurpalsdottir BD, Stefansson OA, Holley G, Beyter D, Zink F, Hardarson MÞ, Sverrisson SÞ, Kristinsdottir N, Magnusdottir DN, Magnusson OÞ, Gudbjartsson DF, Halldorsson BV, Stefansson K. A comparison of methods for detecting DNA methylation from long-read sequencing of human genomes. Genome Biol 2024; 25:69. [PMID: 38468278 PMCID: PMC10929077 DOI: 10.1186/s13059-024-03207-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 02/28/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Long-read sequencing can enable the detection of base modifications, such as CpG methylation, in single molecules of DNA. The most commonly used methods for long-read sequencing are nanopore developed by Oxford Nanopore Technologies (ONT) and single molecule real-time (SMRT) sequencing developed by Pacific Bioscience (PacBio). In this study, we systematically compare the performance of CpG methylation detection from long-read sequencing. RESULTS We demonstrate that CpG methylation detection from 7179 nanopore-sequenced DNA samples is highly accurate and consistent with 132 oxidative bisulfite-sequenced (oxBS) samples, isolated from the same blood draws. We introduce quality filters for CpGs that further enhance the accuracy of CpG methylation detection from nanopore-sequenced DNA, while removing at most 30% of CpGs. We evaluate the per-site performance of CpG methylation detection across different genomic features and CpG methylation rates and demonstrate how the latest R10.4 flowcell chemistry and base-calling algorithms improve methylation detection from nanopore sequencing. Additionally, we show how the methylation detection of 50 SMRT-sequenced genomes compares to nanopore sequencing and oxBS. CONCLUSIONS This study provides the first systematic comparison of CpG methylation detection tools for long-read sequencing methods. We compare two commonly used computational methods for the detection of CpG methylation in a large number of nanopore genomes, including samples sequenced using the latest R10.4 nanopore flowcell chemistry and 50 SMRT sequenced samples. We provide insights into the strengths and limitations of each sequencing method as well as recommendations for standardization and evaluation of tools designed for genome-scale modified base detection using long-read sequencing.
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Affiliation(s)
- Brynja D Sigurpalsdottir
- deCODE Genetics/Amgen Inc., Sturlugata 8, Reykjavík, Iceland.
- School of Technology, Reykjavík University, Reykjavík, Iceland.
| | | | | | - Doruk Beyter
- deCODE Genetics/Amgen Inc., Sturlugata 8, Reykjavík, Iceland
| | - Florian Zink
- deCODE Genetics/Amgen Inc., Sturlugata 8, Reykjavík, Iceland
| | - Marteinn Þ Hardarson
- deCODE Genetics/Amgen Inc., Sturlugata 8, Reykjavík, Iceland
- School of Technology, Reykjavík University, Reykjavík, Iceland
| | | | | | | | | | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, Reykjavík, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavík, Iceland
| | - Bjarni V Halldorsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, Reykjavík, Iceland.
- School of Technology, Reykjavík University, Reykjavík, Iceland.
| | - Kari Stefansson
- deCODE Genetics/Amgen Inc., Sturlugata 8, Reykjavík, Iceland
- Faculty of Medicine, School of Health Science, University of Iceland, Reykjavík, Iceland
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Sun S, Zane A, Fulton C, Philipoom J. Statistical and bioinformatic analysis of hemimethylation patterns in non-small cell lung cancer. BMC Cancer 2021; 21:268. [PMID: 33711952 PMCID: PMC7953768 DOI: 10.1186/s12885-021-07990-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 03/01/2021] [Indexed: 12/22/2022] Open
Abstract
Background DNA methylation is an epigenetic event involving the addition of a methyl-group to a cytosine-guanine base pair (i.e., CpG site). It is associated with different cancers. Our research focuses on studying non-small cell lung cancer hemimethylation, which refers to methylation occurring on only one of the two DNA strands. Many studies often assume that methylation occurs on both DNA strands at a CpG site. However, recent publications show the existence of hemimethylation and its significant impact. Therefore, it is important to identify cancer hemimethylation patterns. Methods In this paper, we use the Wilcoxon signed rank test to identify hemimethylated CpG sites based on publicly available non-small cell lung cancer methylation sequencing data. We then identify two types of hemimethylated CpG clusters, regular and polarity clusters, and genes with large numbers of hemimethylated sites. Highly hemimethylated genes are then studied for their biological interactions using available bioinformatics tools. Results In this paper, we have conducted the first-ever investigation of hemimethylation in lung cancer. Our results show that hemimethylation does exist in lung cells either as singletons or clusters. Most clusters contain only two or three CpG sites. Polarity clusters are much shorter than regular clusters and appear less frequently. The majority of clusters found in tumor samples have no overlap with clusters found in normal samples, and vice versa. Several genes that are known to be associated with cancer are hemimethylated differently between the cancerous and normal samples. Furthermore, highly hemimethylated genes exhibit many different interactions with other genes that may be associated with cancer. Hemimethylation has diverse patterns and frequencies that are comparable between normal and tumorous cells. Therefore, hemimethylation may be related to both normal and tumor cell development. Conclusions Our research has identified CpG clusters and genes that are hemimethylated in normal and lung tumor samples. Due to the potential impact of hemimethylation on gene expression and cell function, these clusters and genes may be important to advance our understanding of the development and progression of non-small cell lung cancer. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-07990-7.
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Affiliation(s)
- Shuying Sun
- Department of Mathematics, Texas State University, San Marcos, TX, USA.
| | - Austin Zane
- Department of Statistics, Texas A&M University, College Station, TX, USA
| | - Carolyn Fulton
- Department of Mathematics, Schreiner University, Kerrville, TX, USA
| | - Jasmine Philipoom
- Department of Mathematics, Applied Mathematics, and Statistics, Case Western Reserve University, Cleveland, OH, USA
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Sun S, Lee YR, Enfield B. Hemimethylation Patterns in Breast Cancer Cell Lines. Cancer Inform 2019; 18:1176935119872959. [PMID: 31496635 PMCID: PMC6716185 DOI: 10.1177/1176935119872959] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 08/05/2019] [Indexed: 02/01/2023] Open
Abstract
DNA methylation is an epigenetic event that involves adding a methyl group to the cytosine (C) site, especially the one that pairs with a guanine (G) site (ie, CG or CpG site), in a human genome. This event plays an important role in both cancerous and normal cell development. Previous studies often assume symmetric methylation on both DNA strands. However, asymmetric methylation, or hemimethylation (methylation that occurs only on 1 DNA strand), does exist and has been reported in several studies. Due to the limitation of previous DNA methylation sequencing technologies, researchers could only study hemimethylation on specific genes, but the overall genomic hemimethylation landscape remains relatively unexplored. With the development of advanced next-generation sequencing techniques, it is now possible to measure methylation levels on both forward and reverse strands at all CpG sites in an entire genome. Analyzing hemimethylation patterns may potentially reveal regions related to undergoing tumor growth. For our research, we first identify hemimethylated CpG sites in breast cancer cell lines using Wilcoxon signed rank tests. We then identify hemimethylation patterns by grouping consecutive hemimethylated CpG sites based on their methylation states, methylation "M" or unmethylation "U." These patterns include regular (or consecutive) hemimethylation clusters (eg, "MMM" on one strand and "UUU" on another strand) and polarity (or reverse) clusters (eg, "MU" on one strand and "UM" on another strand). Our results reveal that most hemimethylation clusters are the polarity type, and hemimethylation does occur across the entire genome with notably higher numbers in the breast cancer cell lines. The lengths or sizes of most hemimethylation clusters are very short, often less than 50 base pairs. After mapping hemimethylation clusters and sites to corresponding genes, we study the functions of these genes and find that several of the highly hemimethylated genes may influence tumor growth or suppression. These genes may also indicate a progressing transition to a new tumor stage.
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Affiliation(s)
- Shuying Sun
- Department of Mathematics, Texas State University, San Marcos, TX, USA
| | - Yu Ri Lee
- Department of Mathematics, Texas State University, San Marcos, TX, USA
| | - Brittany Enfield
- Global Engineering Systems, Cypress Semiconductor, Austin, TX, USA
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Taka N, Karube I, Yoshida W. Direct Detection of Hemi-methylated DNA by SRA-fused Luciferase Based on Bioluminescence Resonance Energy Transfer. ANAL LETT 2018. [DOI: 10.1080/00032719.2018.1533022] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Natsumi Taka
- School of Bioscience and Biotechnology, Graduate School of Bionics, Tokyo University of Technology, Hachioji, Tokyo, Japan
| | - Isao Karube
- School of Bioscience and Biotechnology, Graduate School of Bionics, Tokyo University of Technology, Hachioji, Tokyo, Japan
| | - Wataru Yoshida
- School of Bioscience and Biotechnology, Graduate School of Bionics, Tokyo University of Technology, Hachioji, Tokyo, Japan
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Zhang Z, Yu W, Chen S, Chen Y, Chen L, Zhang S. Methylation of the claudin‑3 promoter predicts the prognosis of advanced gastric adenocarcinoma. Oncol Rep 2018; 40:49-60. [PMID: 29749528 PMCID: PMC6059754 DOI: 10.3892/or.2018.6411] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 04/13/2018] [Indexed: 02/07/2023] Open
Abstract
Claudin-3 expression is associated with gastric cancer progression, but the role of epigenetic modifications remains unclear. We investigated methylation of the claudin-3 promoter and expression profiles in gastric adenocarcinoma and their associations with clinicopathological characteristics and prognosis of the patients. A total of 122 patients with advanced gastric cancer [stage IIB-IV, with lymph node (LN) metastasis] were enrolled. Each patient provided 4 tissue samples: normal gastric epithelium, intestinal metaplasia, primary tumor and metastatic LN. Claudin-3 protein expression was examined by immunohistochemistry. Claudin-3 promoter methylation was determined by methylation-specific PCR and verified by bisulfite sequencing PCR. Claudin-3 mRNA expression was measured by real-time PCR in a subset of cases, and its correlation with protein expression was analyzed using Spearman correlation. Kaplan-Meier survival analysis was performed (log-rank test). Factors associated with survival were identified by Cox regression. The strong expression rate of claudin-3 in intestinal metaplasia, primary tumor, metastatic LN and normal gastric epithelium was 91.8, 58.2, 30.3 and 13.9%, respectively. The promoter hypermethylation rate in intestinal metaplasia, primary tumor, normal gastric epithelium and metastatic LN was 5.7, 27.9, 36.9 and 49.2%, respectively. Claudin-3 mRNA and protein expression were positively correlated (P<0.001) with normal gastric epithelium (rs=0.745), intestinal metaplasia (rs=0.876), primary gastric adenocarcinoma (rs=0.915) and metastatic LN (rs=0.819). Claudin-3 mRNA expression was negatively correlated with claudin-3 promoter methylation. Median patient survival was 38, 22 and 11 months in the hypomethylated, partially methylated and hypermethylated groups, respectively (P<0.001). Claudin-3 promoter methylation status (HR: 5.67; 95% CI: 2.27–14.17) but not claudin-3 expression was an independent predictor of survival. Claudin-3 promoter hypermethylation reduces claudin-3 expression and independently predicts poor prognosis.
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Affiliation(s)
- Zhenzhen Zhang
- Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fujian, Fuzhou 350005, P.R. China
| | - Weixing Yu
- Institute of Translational Medicine, Fujian Medical University, Fujian, Fuzhou 350122, P.R. China
| | - Shuqin Chen
- Department of Pathology, Fujian Medical University, Fujian, Fuzhou 350122, P.R. China
| | - Yupeng Chen
- Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fujian, Fuzhou 350005, P.R. China
| | - Linying Chen
- Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fujian, Fuzhou 350005, P.R. China
| | - Sheng Zhang
- Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fujian, Fuzhou 350005, P.R. China
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Tian S, Bertelsmann K, Yu L, Sun S. DNA Methylation Heterogeneity Patterns in Breast Cancer Cell Lines. Cancer Inform 2016; 15:1-9. [PMID: 27688708 PMCID: PMC5032785 DOI: 10.4137/cin.s40300] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Revised: 08/07/2016] [Accepted: 08/13/2016] [Indexed: 12/25/2022] Open
Abstract
Heterogeneous DNA methylation patterns are linked to tumor growth. In order to study DNA methylation heterogeneity patterns for breast cancer cell lines, we comparatively study four metrics: variance, I2 statistic, entropy, and methylation state. Using the categorical metric methylation state, we select the two most heterogeneous states to identify genes that directly affect tumor suppressor genes and high- or moderate-risk breast cancer genes. Utilizing the Gene Set Enrichment Analysis software and the ConsensusPath Database visualization tool, we generate integrated gene networks to study biological relations of heterogeneous genes. This analysis has allowed us to contribute 19 potential breast cancer biomarker genes to cancer databases by locating “hub genes” – heterogeneous genes of significant biological interactions, selected from numerous cancer modules. We have discovered a considerable relationship between these hub genes and heterogeneously methylated oncogenes. Our results have many implications for further heterogeneity analyses of methylation patterns and early detection of breast cancer susceptibility.
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Affiliation(s)
- Sunny Tian
- Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Linda Yu
- St. John's School, Houston, TX, USA
| | - Shuying Sun
- Department of Mathematics, Texas State University, San Marcos, TX, USA
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