Partially Methylated Domains Are Hypervariable In Breast Cancer And Fuel Widespread Cpg Island Hypermethylation

This dataset contains supplemental tables and tracks for the study entitled: "Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation". Files PMDs_CGIs.zip The included files contain Genome positions of detected PMDs with their mean methylation (weighted mean, see Methods) Genome positions of CpG islands with their mean methylation (weighted mean) The "Brinkman" directory contains files from breast cancer data produced in this study The "normals" directory contains files from normal tissues (external data) analyzed in this study The "tumors" directory contains files from tumors (external data) analyzed in this study All genome positions are based on GRCh37/hg19 All files are TAB-delimited text files (.tsv) DNAme_bigwigs.zip The included files are BIGWIG files (http://genome.ucsc.edu/goldenPath/help/bigWig.html) for viewing the DNA methylation profiles in a genome browser such as UCSC (http://genome.ucsc.edu). Each file represents a whole-Genome Bisulfite Sequencing (WGBS) DNA methylation profile from one tumor used in this study. The used genome build was GRCh37/hg19. For every CpG with a coverage of at least 4 reads, the DNA methylation value (range: 0-1) is included. Methods Detection of partially methylated domains (PMDs) in all whole-genome bisulfite sequencing (WGBS) methylation profiles throughout this study was done using the MethylSeekR package for R (1). Before PMD calling, CpGs overlapping common SNPs (dbSNP build 137) were removed. The alpha distribution (1) was used to determine whether PMDs were present at all, along with visual inspection of WGBS profiles. After PMD calling, the resulting PMDs were further filtered by removing regions overlapping with centromers (undetermined sequence content). Mean methylation values from WGBS inside CGIs were calculated using the ‘weighted methylation level’ (2). Mean methylation values from WGBS inside PMDs were calculated using the ‘weighted methylation level’ (2). Calculation of mean methylation within PMDs involved removing all CpGs overlapping with CpG island(-shores) and promoters, as the high CpG densities within these elements yield unbalanced mean methylation values, not representative of PMD methylation. References (1) Burger, L., Gaidatzis, D., Schübeler, D. & Stadler, M. B. Identification of active regulatory regions from DNA methylation data. Nucleic Acids Research 41, (2013). (2) Schultz, M. D., Schmitz, R. J. & Ecker, J. R. ’Leveling’ the playing field for analyses of single-base resolution DNA methylomes. Trends in Genetics 28, 583–585 (2012).本数据集为题为《部分甲基化结构域在乳腺癌中呈高度可变且驱动广泛CpG岛高甲基化》的研究提供补充表格与基因组轨迹文件。 ## 文件 ### PMDs_CGIs.zip 该压缩包内含以下文件： 1. 已检测到的部分甲基化结构域（Partially methylated domains, PMDs）的基因组位置信息及其平均甲基化水平（加权均值，详见方法部分） 2. CpG岛（CpG island）的基因组位置信息及其平均甲基化水平（加权均值） 3. 「Brinkman」文件夹包含本研究生成的乳腺癌相关数据文件 4. 「normals」文件夹包含本研究分析的正常组织相关外部数据集文件 5. 「tumors」文件夹包含本研究分析的肿瘤组织相关外部数据集文件 6. 所有基因组位置信息均基于人类参考基因组GRCh37/hg19 7. 所有文件均为制表符分隔文本文件（.tsv） ### DNAme_bigwigs.zip 该压缩包内含BIGWIG格式文件，可通过UCSC基因组浏览器等工具查看DNA甲基化谱（详见UCSC官方帮助文档：http://genome.ucsc.edu/goldenPath/help/bigWig.html）。每个文件对应本研究中使用的一例肿瘤样本的全基因组亚硫酸氢盐测序（Whole-Genome Bisulfite Sequencing, WGBS）甲基化谱。所用参考基因组版本为GRCh37/hg19，文件包含所有测序深度≥4条reads的CpG位点的DNA甲基化数值（取值范围0~1）。 ## 方法 本研究中所有全基因组亚硫酸氢盐测序（WGBS）甲基化谱的部分甲基化结构域（PMDs）检测，均通过R语言的MethylSeekR包完成（参考文献1）。在PMD调用前，需移除与常见单核苷酸多态性（dbSNP数据库版本137）重叠的CpG位点。研究通过α分布结合WGBS谱的可视化检查，判断样本中是否存在PMDs。PMD调用完成后，进一步过滤掉与着丝粒（序列内容未确定）重叠的区域。 CpG岛内的WGBS平均甲基化水平采用「加权甲基化水平」计算（参考文献2）。 PMD区域内的WGBS平均甲基化水平同样采用「加权甲基化水平」计算（参考文献2），但计算过程中需移除与CpG岛（及CpG岛岸）和启动子重叠的CpG位点，因为这些区域的CpG密度极高，会导致平均甲基化数值失衡，无法代表PMD的真实甲基化水平。 ## 参考文献 (1) Burger, L., Gaidatzis, D., Schübeler, D. & Stadler, M. B. 基于DNA甲基化数据识别活性调控区域. 核酸研究, 41, (2013). (2) Schultz, M. D., Schmitz, R. J. & Ecker, J. R. 为单碱基分辨率DNA甲基组分析建立公平可比的基准. 遗传学趋势, 28, 583–585 (2012).