Encoding genomic architecture in the encyclopedia: linking DNA elements, chromatin state, and gene expression in 3D

这一部分自提交母公司U01奖助金以来没有变化。 项目摘要 ENCODE产生的数千个测序实验中的大多数提供了表观遗传学的一维读数 3D基因组的景观或转录输出。新的染色体构象捕捉(3C) 技术-特别是Hi-C和Chia-PET-已经开始提供对分层3D的洞察 基因组的组织：将染色体分成开放和封闭的隔间；存在 被定义为拓扑相关结构域(TADS)的结构亚基；以及调节性和 TADS内的结构DNA环。CRISPR/Cas介导的基因组编辑的新实验证据 这表明，局部3D结构的破坏可以改变邻近基因的调控，而且已经有 早期的努力是利用3D DNA循环的数据来预测来自GWAS研究的非编码SNP的影响。 这项提议的目标是开发新的综合计算方法来解释大尺度 根据底层的3D架构编码1D表观基因组和转录组资源 基因组。我们团队的成员已经开创了从一维图像推断局部染色质状态的强大方法 通过赛格威套装观看。我们还分析了染色质的一维组织 元素及其谱系动力学来定义调控复杂性的概念，我们提出了一个基因 从活性DNA含量预测分化过程中基因表达变化的调控模型 增强剂。在这里，我们将在这些努力的基础上学习染色质状态和基因调控模型 整合了关于分层3D基因组架构的信息，使我们能够预测个体 结构/调控元件有助于3D DNA循环和基因表达。机械论预测 将在其天然细胞类型的特定染色质环境中使用最先进的技术进行实验验证 基因组编辑，利用我们团队开发的计算和实验CRISPR/CAS工具。

This section has not changed since the submission of the parent U01 grant. Project Summary Most of the 1000s of sequencing experiments generated by ENCODE provide 1D readouts of the epigenetic landscape or transcriptional output of a 3D genome. New chromosome conformation capture (3C) technologies – in particular Hi-C and ChIA-PET – have begun to provide insight into the hierarchical 3D organization of the genome: the partition of chromosomes into open and closed compartments; the existence of structural subunits defined as topologically associated domains (TADs); and the presence of regulatory and structural DNA loops within TADs. New experimental evidence using CRISPR/Cas-mediated genome editing suggests that disruption of local 3D structure can alter regulation of neighboring genes, and there have been early efforts to use data on 3D DNA looping to predict the impact of non-coding SNPs from GWAS studies. The goal of this proposal is to develop new integrative computational methods to interpret large-scale ENCODE 1D epigenomic and transcriptomic resources in light of the underlying 3D architecture of the genome. Members of our team have pioneered powerful methods to infer local chromatin states from a 1D viewpoint through the Segway suite. We have also analyzed the 1D organization of chromatin accessible elements and their lineage dynamics to define the concept of regulatory complexity, and we presented a gene regulation model to predict gene expression changes in differentiation from the DNA content of active enhancers. Here we will build on these efforts to learn chromatin state and gene regulation models that incorporate information on hierarchical 3D genomic architecture, enabling us to predict how individual structural/regulatory elements contribute to 3D DNA looping and to gene expression. Mechanistic predictions will be experimentally validated in their native cell-type specific chromatin context using state-of-the-art genome editing, exploiting computational and experimental CRISPR/Cas tools developed by our team.