Center for Genome Imaging

基因组成像中心

• 批准号: 10177498
• 负责人: CHAO-TING WU
• 金额: $ 324.82万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-07 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10177498
• 关键词: 3-Dimensional; Address; Aneuploidy; Biological; Biological Process; Cells; Chromosomes; Collaborations; Complement; Cues; Data; Data Storage and Retrieval; Development; Diagnostic; Diploid Cells; Disease; Ensure; Epigenetic Process; Etiology; Event; Generations; Genes; Genetic; Genome; Genomic Segment; Genomics; Goals; Health; Hi-C; Human; Human Development; Human Genome; Image; Image Analysis; Imaging Device; Individual; Infection; Intervention; Knowledge; Laboratories; Malignant Neoplasms; Medical; Methods; Microscopy; Modeling; Molecular Genetics; Physics; Polymers; Predisposition; Repetitive Sequence; Research Personnel; Research Project Grants; Resolution; Resource Sharing; Resources; Solid; Sports; Structure; Technology; Training; Visualization; Work; advanced disease; base; convolutional neural network; cost; design; disease diagnosis; epigenome; falls; genome-wide; grasp; human imaging; image processing; imaging study; innovation; light microscopy; live cell imaging; novel therapeutics; restraint; senescence; tool; transcriptome; whole genome

Project Summary/Abstract Center for genome imaging (CGI) Objectives: Three-dimensional (3D) genome organization is a major contributor to genome func- tion, and yet, we are only at the very dawn of discovering the structural signatures that underlie that organization. Thus, the goal of the proposed studies is to develop and apply tools that will enable se- quence-specific imaging of human genomes, in their entirety, with high genomic resolution. In particu- lar, the proposed work will innovate methods for fixed and live cell imaging using diffraction-limited light microscopy and super-resolution microscopy as well as develop new tools for image analysis and ge- nome modeling. To this end, it will involve the continued collaboration of four laboratories, whose col- lective breadth of expertise covers the fields of classical and molecular genetics, chromosome dynam- ics, imaging, Hi-C analysis, convolutional neural networks, and polymer physics-based and restraint- based modeling. An equally important objective of the proposed studies is to ensure a generation of re- searchers whose personal breadth of expertise will come to match that of the entire current team. Health relatedness: Will a solid grasp of 3D genome organization have implications for under- standing human development? Will it contribute to the protection of human health? Will it contribute to strategies for early diagnostics and perhaps even the development of new therapies? The answer to all these questions is almost certainly a resounding Yes, as knowledge of 3D genome organization will en- hance our capacity to address both fundamental biological processes as well as disease. Innovation: An abundance of studies argue that genomes function as integrated units and, yet, no extant technologies enable sequence-specific imaging of entire genomes at high genomic resolution. Thus, the capacity of researchers to fathom the interplay between 3D genome organization and ge- nome function has been limited to disjointed snapshots of localized events. Accordingly, first three aims will develop the next tier of tools to put entire genomes within reach. They will advance a new method, OligoFISSEQ, and then integrate it with OligoSTORM and OligoDNA-PAINT to finally achieve high- throughput imaging at both conventional and super-resolution. They will also tackle two genomic fea- tures that have been prohibitively difficult to capture – presence of homologs in diploid cells and highly repeated sequences – as well as innovate strategies for high volume data storage, image processing and analysis, and modeling. Finally, a fourth aim will implement methods for disseminating our tools. 1. Scaling technologies toward whole genome imaging 2. Filling in gaps to visualize chromosomes end-to-end – tackling homologs and repeats 3. Probe design, image analysis, modeling, and integration of epigenetic data 4. Training, resources, and opportunities for engaging colleagues in whole genome imaging

项目摘要/摘要 基因组成像中心（CGI） 目标：三维（3D）基因组组织是基因组功能的主要因素 但是，我们只是在发现构成的结构签名的曙光 组织。这是拟议的研究的目标是开发和应用工具，以使能力 具有高基因组分辨率的人类基因组的特异性成像。在特定 lar，提议的工作将使用衍射限制的光创新用于固定和活细胞成像的方法 显微镜和超分辨率显微镜以及开发新工具以进行图像分析和GE- Nome建模。为此，它将涉及四个实验室的持续合作，他们的合作 专业知识的讲座广度涵盖了经典和分子遗传学的领域，染色体动态 - IC，成像，HI-C分析，卷积神经网络以及基于聚合物物理和约束的聚合物 基于建模。拟议的研究同样重要的目标是确保产生一系列 搜索者的个人专业知识将与整个当前团队相匹配。 健康相关性：3D基因组组织的牢固掌握是否对不足有影响 站立的人类发展？它会促进保护人类健康吗？它会贡献吗 早期诊断的策略，甚至是新疗法的发展？所有人的答案 这些问题几乎可以肯定是肯定的，因为3D基因组组织的知识将纳入 Hance我们解决了两个基本生物过程和疾病的能力。 创新：大量的研究表明，基因组起着综合单位的作用，但没有 现有的技术可以在高基因组分辨率下对整个基因组进行序列特异性成像。 这，研究人员围攻3D基因组组织与GE-之间的相互作用的能力 Nome功能仅限于局部事件的脱节快照。彼此之间，前三个目标 将开发下一级工具，以使整个基因组触及。他们将推进一种新方法， 寡素，然后将其与寡素和寡素 - 粉刺整合在一起，最终达到了高 常规和超分辨率的吞吐量成像。他们还将解决两个基因组FEA- 被禁止难以捕获的调查 - 二倍体细胞中同源物的存在和高度 重复序列 - 以及用于大量数据存储的创新策略，图像处理 和分析和建模。最后，第四个目标将实施传播我们的工具的方法。 1。针对整个基因组成像的缩放技术 2。填充空白以可视化终端染色体 - 处理同源物和重复 3。探针设计，图像分析，建模和表观遗传数据的集成 4。培训，资源和机会，使同事参与整个基因组成像