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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:
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