Literature DB >> 21045081

Evaluation of affinity-based genome-wide DNA methylation data: effects of CpG density, amplification bias, and copy number variation.

Mark D Robinson1, Clare Stirzaker, Aaron L Statham, Marcel W Coolen, Jenny Z Song, Shalima S Nair, Dario Strbenac, Terence P Speed, Susan J Clark.   

Abstract

DNA methylation is an essential epigenetic modification that plays a key role associated with the regulation of gene expression during differentiation, but in disease states such as cancer, the DNA methylation landscape is often deregulated. There are now numerous technologies available to interrogate the DNA methylation status of CpG sites in a targeted or genome-wide fashion, but each method, due to intrinsic biases, potentially interrogates different fractions of the genome. In this study, we compare the affinity-purification of methylated DNA between two popular genome-wide techniques, methylated DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain-based capture (MBDCap), and show that each technique operates in a different domain of the CpG density landscape. We explored the effect of whole-genome amplification and illustrate that it can reduce sensitivity for detecting DNA methylation in GC-rich regions of the genome. By using MBDCap, we compare and contrast microarray- and sequencing-based readouts and highlight the impact that copy number variation (CNV) can make in differential comparisons of methylomes. These studies reveal that the analysis of DNA methylation data and genome coverage is highly dependent on the method employed, and consideration must be made in light of the GC content, the extent of DNA amplification, and the copy number.

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Year:  2010        PMID: 21045081      PMCID: PMC2989998          DOI: 10.1101/gr.110601.110

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  48 in total

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Authors:  Pamela L Paris
Journal:  Methods Mol Biol       Date:  2009

2.  Continuous base identification for single-molecule nanopore DNA sequencing.

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3.  Methylated DNA immunoprecipitation and microarray-based analysis: detection of DNA methylation in breast cancer cell lines.

Authors:  Yu-I Weng; Tim H-M Huang; Pearlly S Yan
Journal:  Methods Mol Biol       Date:  2009

4.  Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.

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5.  Inherent signals in sequencing-based Chromatin-ImmunoPrecipitation control libraries.

Authors:  Vinsensius B Vega; Edwin Cheung; Nallasivam Palanisamy; Wing-Kin Sung
Journal:  PLoS One       Date:  2009-04-15       Impact factor: 3.240

6.  High-resolution genome-wide cytosine methylation profiling with simultaneous copy number analysis and optimization for limited cell numbers.

Authors:  Mayumi Oda; Jacob L Glass; Reid F Thompson; Yongkai Mo; Emmanuel N Olivier; Maria E Figueroa; Rebecca R Selzer; Todd A Richmond; Xinmin Zhang; Luke Dannenberg; Roland D Green; Ari Melnick; Eli Hatchwell; Eric E Bouhassira; Amit Verma; Masako Suzuki; John M Greally
Journal:  Nucleic Acids Res       Date:  2009-04-22       Impact factor: 16.971

7.  Impact of chromatin structures on DNA processing for genomic analyses.

Authors:  Leonid Teytelman; Bilge Ozaydin; Oliver Zill; Philippe Lefrançois; Michael Snyder; Jasper Rine; Michael B Eisen
Journal:  PLoS One       Date:  2009-08-20       Impact factor: 3.240

8.  Optimization of experimental design parameters for high-throughput chromatin immunoprecipitation studies.

Authors:  Romina Ponzielli; Paul C Boutros; Sigal Katz; Angelina Stojanova; Adam P Hanley; Fereshteh Khosravi; Christina Bros; Igor Jurisica; Linda Z Penn
Journal:  Nucleic Acids Res       Date:  2008-10-21       Impact factor: 16.971

9.  CNV-seq, a new method to detect copy number variation using high-throughput sequencing.

Authors:  Chao Xie; Martti T Tammi
Journal:  BMC Bioinformatics       Date:  2009-03-06       Impact factor: 3.169

10.  Impact of whole genome amplification on analysis of copy number variants.

Authors:  T J Pugh; A D Delaney; N Farnoud; S Flibotte; M Griffith; H I Li; H Qian; P Farinha; R D Gascoyne; M A Marra
Journal:  Nucleic Acids Res       Date:  2008-06-17       Impact factor: 16.971

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  64 in total

Review 1.  Statistical approaches for the analysis of DNA methylation microarray data.

Authors:  Kimberly D Siegmund
Journal:  Hum Genet       Date:  2011-04-26       Impact factor: 4.132

2.  Clinical and public health research using methylated DNA immunoprecipitation (MeDIP): a comparison of commercially available kits to examine differential DNA methylation across the genome.

Authors:  Priscilla Brebi-Mieville; Carmen Ili-Gangas; Pamela Leal-Rojas; Maartje G Noordhuis; Ethan Soudry; Jimena Perez; Juan Carlos Roa; David Sidransky; Rafael Guerrero-Preston
Journal:  Epigenetics       Date:  2012-01-01       Impact factor: 4.528

3.  Associations with early-life socio-economic position in adult DNA methylation.

Authors:  Nada Borghol; Matthew Suderman; Wendy McArdle; Ariane Racine; Michael Hallett; Marcus Pembrey; Clyde Hertzman; Chris Power; Moshe Szyf
Journal:  Int J Epidemiol       Date:  2011-10-20       Impact factor: 7.196

4.  Methyl-CpG/MBD2 Interaction Requires Minimum Separation and Exhibits Minimal Sequence Specificity.

Authors:  Blythe Moreland; Kenji Oman; John Curfman; Pearlly Yan; Ralf Bundschuh
Journal:  Biophys J       Date:  2016-12-20       Impact factor: 4.033

5.  DNA methylation marker to estimate the breast cancer cell fraction in DNA samples.

Authors:  Hiroki Ishihara; Satoshi Yamashita; Satoshi Fujii; Kazunari Tanabe; Hirofumi Mukai; Toshikazu Ushijima
Journal:  Med Oncol       Date:  2018-09-14       Impact factor: 3.064

Review 6.  Analysing and interpreting DNA methylation data.

Authors:  Christoph Bock
Journal:  Nat Rev Genet       Date:  2012-10       Impact factor: 53.242

7.  A metabolic labeling method detects m6A transcriptome-wide at single base resolution.

Authors:  Xiao Shu; Jie Cao; Mohan Cheng; Siying Xiang; Minsong Gao; Ting Li; Xiner Ying; Fengqin Wang; Yanan Yue; Zhike Lu; Qing Dai; Xiaolong Cui; Lijia Ma; Yizhen Wang; Chuan He; Xinhua Feng; Jianzhao Liu
Journal:  Nat Chem Biol       Date:  2020-04-27       Impact factor: 15.040

8.  Promoter hypomethylation of EpCAM-regulated bone morphogenetic protein gene family in recurrent endometrial cancer.

Authors:  Ya-Ting Hsu; Fei Gu; Yi-Wen Huang; Joseph Liu; Jianhua Ruan; Rui-Lan Huang; Chiou-Miin Wang; Chun-Liang Chen; Rohit R Jadhav; Hung-Cheng Lai; David G Mutch; Paul J Goodfellow; Ian M Thompson; Nameer B Kirma; Tim Hui-Ming Huang
Journal:  Clin Cancer Res       Date:  2013-09-27       Impact factor: 12.531

9.  A novel algorithm for network-based prediction of cancer recurrence.

Authors:  Jianhua Ruan; Md Jamiul Jahid; Fei Gu; Chengwei Lei; Yi-Wen Huang; Ya-Ting Hsu; David G Mutch; Chun-Liang Chen; Nameer B Kirma; Tim H-M Huang
Journal:  Genomics       Date:  2016-07-21       Impact factor: 5.736

10.  Exploring genome-wide DNA methylation profiles altered in hepatocellular carcinoma using Infinium HumanMethylation 450 BeadChips.

Authors:  Jing Shen; Shuang Wang; Yu-Jing Zhang; Hui-Chen Wu; Muhammad G Kibriya; Farzana Jasmine; Habibul Ahsan; David P H Wu; Abby B Siegel; Helen Remotti; Regina M Santella
Journal:  Epigenetics       Date:  2012-12-03       Impact factor: 4.528

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