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

编码百科全书中的基因组结构：以 3D 形式连接 DNA 元素、染色质状态和基因表达

• 批准号: 10241049
• 负责人: Christina S Leslie
• 金额: $ 74.25万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-01 至 2022-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10241049
• 关键词: 3-Dimensional; ATAC-seq; Architecture; Atlases; Cells; Chromatin; Chromatin Interaction Analysis by Paired-End Tag Sequencing; Chromatin Loop; Chromosomes; Clustered Regularly Interspaced Short Palindromic Repeats; Computing Methodologies; DNA; DNA Sequence; DNA Structure; DNase I hypersensitive sites sequencing; Data; Disease; Elements; Encyclopedias; Enhancers; Epigenetic Process; Gene Expression; Gene Expression Regulation; Genes; Genetic Transcription; Genome; Genomics; Goals; Grant; Guide RNA; Hi-C; Human; Human Genome; Hybrids; Individual; Learning; Light; Link; Mediating; Methods; Modeling; Output; Parents; Peptide Signal Sequences; Ploidies; Published Comment; Regulation; Regulator Genes; Regulatory Element; Resolution; Resources; Specificity; Statistical Data Interpretation; Structural Models; Structure; Technology; Training; Untranslated RNA; base; cell type; chromosome conformation capture; computerized tools; deep learning; density; epigenomics; experimental study; genome annotation; genome editing; genome wide association study; genomic data; histone modification; insight; learning strategy; member; next generation; predictive modeling; programs; sequence learning; supervised learning; three dimensional structure; three-dimensional modeling; tool; transcription factor; transcriptomics; unsupervised learning

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.

自提交母校 U01 拨款以来，本节未曾更改。 项目概要 ENCODE 生成的数千个测序实验中的大多数都提供表观遗传的一维读数 3D 基因组的景观或转录输出。新染色体构象捕获 (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：染色体划分为开放和封闭的区室； 定义为拓扑相关域 (TAD) 的结构亚基以及调节和域的存在； TAD 内的结构 DNA 环使用 CRISPR/Cas 介导的基因组编辑的新实验证据。 表明局部 3D 结构的破坏可以改变邻近基因的调节，并且已经有 早期尝试使用 3D DNA 循环数据来预测 GWAS 研究中非编码 SNP 的影响。 该提案的目标是开发新的综合计算方法来解释大规模 根据底层 3D 架构对 1D 表观基因组和转录组资源进行编码 我们团队的成员开创了从一维推断局部染色质状态的强大方法。 我们还通过 Segway 套件分析了染色质的一维组织。 元素及其谱系动态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 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。 结合分层 3D 基因组架构的信息，使我们能够预测个体如何 结构/调控元件有助于 3D DNA 循环和基因表达的机制预测。 将使用最先进的技术在其天然细胞类型特定染色质环境中进行实验验证 基因组编辑，利用我们团队开发的计算和实验 CRISPR/Cas 工具。

项目成果

Completing the ENCODE3 compendium yields accurate imputations across a variety of assays and human biosamples.

完成 ENCODE3 纲要可以对各种检测和人类生物样本进行准确的估算。

• 发表时间: 2020-03-30
• 影响因子: 12.3
• 作者: Schreiber, Jacob;Bilmes, Jeffrey;Noble, William Stafford
• 通讯作者: Noble, William Stafford

Prioritizing transcriptomic and epigenomic experiments using an optimization strategy that leverages imputed data.

使用利用估算数据的优化策略优先考虑转录组和表观基因组实验。

• 发表时间: 2021-05-01
• 作者: Schreiber, Jacob;Bilmes, Jeffrey;Noble, William Stafford
• 通讯作者: Noble, William Stafford

Epiphany: predicting Hi-C contact maps from 1D epigenomic signals.

Epiphany：根据一维表观基因组信号预测 Hi-C 接触图。

• 发表时间: 2023-06-06
• 影响因子: 12.3
• 作者: Yang, Rui;Das, Arnav;Gao, Vianne R;Karbalayghareh, Alireza;Noble, William S;Bilmes, Jeffery A;Leslie, Christina S
• 通讯作者: Leslie, Christina S

GuideScan software for improved single and paired CRISPR guide RNA design.

GuideScan 软件用于改进单个和配对 CRISPR 引导 RNA 设计。

• 发表时间: 2017
• 影响因子: 46.9
• 作者: Perez, Alexendar R;Pritykin, Yuri;Vidigal, Joana A;Chhangawala, Sagar;Zamparo, Lee;Leslie, Christina S;Ventura, Andrea
• 通讯作者: Ventura, Andrea

Avocado: a multi-scale deep tensor factorization method learns a latent representation of the human epigenome.

鳄梨：一种多尺度深度张量分解方法，学习人类表观基因组的潜在表示。

• 发表时间: 2020
• 影响因子: 12.3
• 作者: Schreiber, Jacob;Durham, Timothy;Bilmes, Jeffrey;Noble, William Stafford
• 通讯作者: Noble, William Stafford