Center for Genome Imaging

基因组成像中心

• 批准号: 10597684
• 负责人: CHAO-TING WU
• 金额: $ 250万
• 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/10597684
• 关键词: 3-Dimensional; Address; Aneuploidy; Biological; Biological Process; Cells; Chromosome Structures; 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; Homologous Gene; Human; Human Development; Human Genome; Image; Image Analysis; Imaging Device; Individual; Infection; Intervention; Knowledge; Laboratories; Malignant Neoplasms; Medical; Methods; Modeling; Molecular Genetics; Oligonucleotides; Onset of illness; Physics; Polymers; Predisposition; Repetitive Sequence; Research Personnel; Research Project Grants; Resolution; Resource Sharing; Resources; Solid; Sports; Structure; Technology; Training; Visualization; Work; advanced disease; computational pipelines; 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; superresolution microscopy; tool; transcriptome; ultra high resolution; 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

项目概要/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贡献者 然而，我们才刚刚开始发现其背后的结构特征 因此，拟议研究的目标是开发和应用能够实现自动化的工具。 人类基因组的整体序列特异性成像，具有高基因组分辨率。 lar，拟议的工作将创新使用衍射极限光进行固定和活细胞成像的方法 显微镜和超分辨率显微镜，以及开发图像分析和基因组的新工具 为此，它将涉及四个实验室的持续合作，它们的合作 选修的专业知识涵盖经典和分子遗传学、染色体动力学等领域 ICS、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 所提出的研究的一个同样重要的目标是确保生成重新生成的模型。 个人专业知识广度将与当前整个团队相匹配的搜索者。 健康相关性：对 3D 基因组组织的扎实掌握是否会对以下方面产生影响： 是否有助于保护人类健康？ 早期诊断的策略，甚至可能是新疗法的开发？ 这些问题几乎肯定是响亮的“是”，因为 3D 基因组组织的知识将使 提高我们解决基本生物过程和疾病的能力。 创新：大量研究认为基因组作为整合单元发挥作用，但目前还没有 现有技术能够以高基因组分辨率对整个基因组进行序列特异性成像。 因此，研究人员理解 3D 基因组组织和基因组之间相互作用的能力 nome 函数仅限于局部事件的脱节快照 因此，前三个目标。 将开发下一层工具，使整个基因组触手可及。他们将推进一种新方法， OligoFISSEQ，然后与OligoSTORM和OligoDNA-PAINT集成，最终实现高 他们还将解决两个基因组特征。 捕获极其困难的事实——二倍体细胞中存在同源物并且高度 重复序列——以及大容量数据存储、图像处理的创新策略 最后，第四个目标是实施传播我们的工具的方法。 1. 将技术扩展到全基因组成像 2. 填补空白以端到端可视化染色体——协商同源物和重复 3. 探针设计、图像分析、建模和表观遗传数据整合 4. 让同事参与全基因组成像的培训、资源和机会