Building the Foundation of Epigenomics Roadmaps

建立表观基因组学路线图的基础

• 批准号: 8812480
• 负责人: Yan W. Asmann
• 金额: $ 31.3万
• 依托单位: MAYO CLINIC JACKSONVILLE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-11 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8812480
• 关键词: Address; Adult; Algorithms; Architecture; BMP4; Base Pairing; Breast Epithelial Cells; Cell Differentiation process; Cells; ChIP-seq; Chromatin; Data; Data Analyses; Data Set; Databases; Deposition; Epigenetic Process; Formaldehyde; Foundations; Galaxy; Gene Expression Profile; Gene Targeting; Genome; Genomics; Goals; Histones; Human; Imagery; Individual; Liver; Location; MCF7 cell; Malignant Neoplasms; Maps; Modification; Noise; Normal Cell; Normal tissue morphology; Nucleosomes; Pathway interactions; Peptide Signal Sequences; Play; Positioning Attribute; Process; Protocols documentation; Regulation; Resolution; Role; Sampling; Signal Transduction; Sonication; Technology; Testing; Therapeutic Studies; Tissues; United States National Institutes of Health; Variant; base; cancer cell; cancer initiation; cell type; chromatin immunoprecipitation; crosslink; embryonic stem cell; epigenome; epigenomics; genome-wide; histone modification; human embryonic stem cell; novel; public health relevance; research study; simulation; stem; tool; transcriptome sequencing; tumor progression

DESCRIPTION (provided by applicant): The NIH Roadmap Epigenomics project has generated substantial genome-wide histone modification maps in a large number of human normal cells and tissues using the chromatin immunoprecipitation and sequencing (ChIP-Seq) approach. The comparison of these "reference" epigenomic profiles with those in human cancer cells (e.g., from ENCODE) will greatly advance our understanding of the mechanisms of cancer initiation and progression and will guide therapeutic studies on human cancers. However, there are substantial analytic challenges for such comparisons: (1) the "peaks" called from the ChIP-Seq data are usually broad regions, ranging from several hundred to several million base pairs for a single histone marker; (2) the peaks from ChIP-Seq are limited in resolution due to the sonication process, so the precise locations and sizes of the peaks for the same marker vary from experiment to experiment; (3) the cross-linking protocol by formaldehyde introduces noise or non-specific signals of histone markers. We have previously demonstrated that histone modification at the resolution of the single nucleosome is critical for the comparison of epigenomic profiles between different cells or tissues. Here, we propose a genomic and computational approach to decompose the ChIP-Seq signals to the resolution of individual nucleosomes and then compare histone modifications of each nucleosome between samples. Given that nucleosome mapping is not the focus for either the Roadmap Epigenomics project or the ENCODE project, we will generate high-resolution nucleosome maps for human normal and cancer cells and incorporate these nucleosome data and also histone modification data at the resolution of the single nucleosome into both projects by building a nucleosome genome browser.

描述（由申请人提供）：NIH路线图表观基因组学项目使用染色质免疫沉淀和测序（ChIP-Seq）方法在大量人类正常细胞和组织中生成了大量全基因组组蛋白修饰图。将这些“参考”表观基因组图谱与人类癌细胞（例如，来自ENCODE）的表观基因组图谱进行比较，将极大地促进我们对癌症发生和进展机制的理解，并将指导人类癌症的治疗研究。然而，这种比较存在大量的分析挑战：(1)ChIP-Seq数据的“峰值”通常是广泛的区域，单个组蛋白标记的范围从几百到几百万个碱基对；(2)由于超声处理过程的限制，ChIP-Seq的峰值分辨率有限，因此同一标记物的峰值精确位置和大小在不同的实验中有所不同；(3)甲醛交联方案引入了组蛋白标记物的噪声或非特异性信号。我们之前已经证明，单核小体分辨率下的组蛋白修饰对于不同细胞或组织之间表观基因组谱的比较至关重要。在这里，我们提出了一种基因组和计算方法，将ChIP-Seq信号分解为单个核小体的分辨率，然后比较样品之间每个核小体的组蛋白修饰。鉴于核小体图谱绘制不是Roadmap表观基因组学项目或ENCODE项目的重点，我们将生成人类正常细胞和癌细胞的高分辨率核小体图谱，并通过构建核小体基因组浏览器，将这些核小体数据以及单核小体分辨率下的组蛋白修饰数据整合到两个项目中。