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本文引用的文献

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Repitools: an R package for the analysis of enrichment-based epigenomic data.Repitools:一个用于分析基于富集的表观基因组学数据的 R 包。
Bioinformatics. 2010 Jul 1;26(13):1662-3. doi: 10.1093/bioinformatics/btq247. Epub 2010 May 10.
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Direct detection of DNA methylation during single-molecule, real-time sequencing.单分子实时测序中 DNA 甲基化的直接检测。
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Whole genome DNA methylation analysis based on high throughput sequencing technology.基于高通量测序技术的全基因组 DNA 甲基化分析。
Methods. 2010 Nov;52(3):203-12. doi: 10.1016/j.ymeth.2010.04.009. Epub 2010 Apr 27.
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Promoter DNA methylation patterns of differentiated cells are largely programmed at the progenitor stage.分化细胞的启动子 DNA 甲基化模式在很大程度上是在祖细胞阶段编程的。
Mol Biol Cell. 2010 Jun 15;21(12):2066-77. doi: 10.1091/mbc.e10-01-0018. Epub 2010 Apr 21.
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Genome-wide analysis of aberrant methylation in human breast cancer cells using methyl-DNA immunoprecipitation combined with high-throughput sequencing.采用甲基化 DNA 免疫沉淀联合高通量测序技术分析人类乳腺癌细胞中异常甲基化的全基因组。
BMC Genomics. 2010 Feb 25;11:137. doi: 10.1186/1471-2164-11-137.
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Consolidation of the cancer genome into domains of repressive chromatin by long-range epigenetic silencing (LRES) reduces transcriptional plasticity.通过长距离表观遗传沉默(LRES)将癌症基因组整合到抑制性染色质域中会降低转录可塑性。
Nat Cell Biol. 2010 Mar;12(3):235-46. doi: 10.1038/ncb2023. Epub 2010 Feb 21.
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Principles and challenges of genomewide DNA methylation analysis.全基因组 DNA 甲基化分析的原理和挑战。
Nat Rev Genet. 2010 Mar;11(3):191-203. doi: 10.1038/nrg2732.
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Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution.单核苷酸分辨率下临床样本的全基因组 DNA 甲基化图谱绘制。
Nat Methods. 2010 Feb;7(2):133-6. doi: 10.1038/nmeth.1414. Epub 2010 Jan 10.
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edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.edgeR:一个用于数字基因表达数据差异表达分析的 Bioconductor 包。
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MBD-isolated Genome Sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome.MBD 分离基因组测序为人类基因组中的 DNA 甲基化提供了高通量和全面的检测。
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基于亲和力的全基因组 DNA 甲基化数据评估:CpG 密度、扩增偏倚和拷贝数变异的影响。

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

机构信息

Epigenetics Laboratory, Cancer Research Program, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.

出版信息

Genome Res. 2010 Dec;20(12):1719-29. doi: 10.1101/gr.110601.110. Epub 2010 Nov 2.

DOI:10.1101/gr.110601.110
PMID:21045081
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2989998/
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.

摘要

DNA 甲基化是一种重要的表观遗传修饰,在分化过程中与基因表达的调控密切相关,但在癌症等疾病状态下,DNA 甲基化谱往往失调。现在有许多技术可用于靶向或全基因组方式检测 CpG 位点的 DNA 甲基化状态,但每种方法由于内在的偏倚,可能会检测到基因组的不同部分。在这项研究中,我们比较了两种流行的全基因组技术——甲基化 DNA 免疫沉淀(MeDIP)和基于甲基-CpG 结合域的捕获(MBDCap)——之间的甲基化 DNA 亲和纯化,结果表明每种技术都在 CpG 密度景观的不同区域发挥作用。我们探讨了全基因组扩增的影响,并表明它会降低检测基因组中富含 GC 区域 DNA 甲基化的敏感性。通过使用 MBDCap,我们比较和对比了基于微阵列和测序的读取,并强调了拷贝数变异(CNV)在差异甲基组比较中可能产生的影响。这些研究表明,DNA 甲基化数据分析和基因组覆盖度高度依赖于所采用的方法,必须考虑 GC 含量、DNA 扩增程度和拷贝数。