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中文摘要
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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的全基因组组蛋白修饰图谱。将这些“参考”表观基因组图谱与人类癌细胞中的表观基因组图谱(例如来自 ENCODE)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,这种比较存在巨大的分析挑战:(1) ChIP-Seq 数据调用的“峰”通常是广泛的区域,对于单个组蛋白标记来说,范围从数百到数百万个碱基对; (2) 由于超声处理过程,ChIP-Seq 的峰分辨率有限,因此同一标记的峰的精确位置和大小因实验而异; (3)甲醛交联方案引入了组蛋白标记的噪音或非特异性信号。我们之前已经证明,单个核小体分辨率下的组蛋白修饰对于比较不同细胞或组织之间的表观基因组谱至关重要。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,然后比较样本之间每个核小体的组蛋白修饰。鉴于核小体作图不是Roadmap Epigenomics项目或ENCODE项目的重点,我们将为人类正常细胞和癌细胞生成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个核小体分辨率的组蛋白修饰数据合并到这两个项目中。
英文摘要
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.
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NUCLIZE for quantifying epigenome: generating histone modification data at single-nucleosome resolution using genuine nucleosome positions.
NUCLIZE 用于量化表观基因组:使用真正的核小体位置以单核小体分辨率生成组蛋白修饰数据。
DOI: 10.1186/s12864-019-5932-6
发表时间: 2019
期刊: BMC genomics
影响因子: 4.4
作者: [Zheng,Daoshan, Trynda,Justyna, Sun,Zhifu, Li,Zhaoyu]
通讯作者: Li,Zhaoyu
Cancer Adoptive Cell Therapy (Can-ACT) Network Coordinating Center at Mayo Clinic
  • 批准号:
    10730805
  • 项目类别:
  • 资助金额:
    $48.03万
  • 财政年份:
    2023
  • 负责人:
    Yan W. Asmann
  • 依托单位:
Bioinformatics, Biostatistics, and Data Management Core
  • 批准号:
    10407942
  • 项目类别:
  • 资助金额:
    $55.43万
  • 财政年份:
    2021
  • 负责人:
    Yan W. Asmann
  • 依托单位:
Bioinformatics, Biostatistics, and Data Management Core
  • 批准号:
    10667458
  • 项目类别:
  • 资助金额:
    $55.11万
  • 财政年份:
    2021
  • 负责人:
    Yan W. Asmann
  • 依托单位:
Building the Foundation of Epigenomics Roadmaps
  • 批准号:
    8812480
  • 项目类别:
  • 资助金额:
    $31.3万
  • 财政年份:
    2014
  • 负责人:
    Yan W. Asmann
  • 依托单位:
海外基金