Project 1: UW-CNOF Mapping Technology Development

项目1：UW-CNOF测绘技术开发

• 批准号: 9021412
• 负责人: Jay Ashok Shendure
• 金额: $ 63.73万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-30 至 2020-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9021412
• 关键词: ATAC-seq; Address; Architecture; Benchmarking; Biochemical; Biological Assay; Cell Nucleus; Cells; Chromatin; Chromosomes; Communities; Coupled; Data; Data Quality; Deoxyribonucleases; Dependence; Dependency; Development; Epigenetic Process; Event; Gene Expression Profile; Generations; Genome; Genome Mappings; Goals; Heterogeneity; Hybrids; In Situ; Individual; Investigation; Maps; Measurement; Measures; Methods; Modeling; Molecular Conformation; Nuclear; Persons; Policies; Population; Problem Solving; Process; Production; Protocols documentation; Regulatory Element; Reporting; Research; Research Personnel; Resolution; Role; Sampling; Scheme; Sensitivity and Specificity; Specificity; Structure; Technology; Time; Training; Universities; Washington; Work; abstracting; base; combinatorial; cost; cost effective; epigenome; genome-wide; improved; in vivo; indexing; interest; research study; restriction enzyme; spatiotemporal; technology development; tool; transcriptome sequencing

ABSTRACT – PROJECT 1: UW-CNOF MAPPING TECHNOLOGY DEVELOPMENT Over the past decade, advances in technologies for assaying genome architecture have led to remarkable progress in our understanding of the 4D nucleome, i.e. the spatiotemporal organization of the eukaryotic genomes within nuclei. Among all of the powerful experimental tools that have recently emerged, chromosome conformation capture (3C) and its high-throughput derivatives have become the most widely used methods for characterizing genome architecture both locally and globally. However, the current repertoire of 3C-based methods is crucially limited with respect to key parameters such as specificity, resolution and input requirements. Recently, we have made substantial progress in addressing these limitations with DNase Hi-C, a restriction enzyme-free derivative of the Hi-C protocol. Here, we propose to further develop biochemical methods for characterizing the dynamic 4D nucleome that substantially improve upon the state of the art with respect to input requirements (down to single cell), resolution (eliminating restriction enzyme bias), scale (genome-wide or targeted views) and integration (combined measurements with the transcriptome and epigenome), while also improving sensitivity, specificity, simplicity and throughput. In Aim 1, we will continue to optimize genome-wide and targeted DNase Hi-C protocols – including a much simplified, in situ version of DNase Hi-C – to further minimize input requirements and bias while improving resolution. We will also refine these protocols in order to maximize robustness, scalability and exportability. In Aim 2, we will develop a high- throughput method for routinely measuring genome architecture in large numbers of single cells. Our proposed approach, based on combinatorial indexing and supported by substantial preliminary data, enables the routine production of DNase Hi-C (nuclear architecture) or ATAC-seq (chromatin accessibility) data from hundreds to thousands of single cells per experiment. In Aim 3, we will integrate DNase Hi-C and other assays for the concurrent measurement of genome architecture, epigenetic state, and the transcriptome, in each of many single cells. We believe that the successful development of such co-assays will profoundly advance our ability to develop integrative models connecting genome form and function. Finally, in Aim 4, we will standardize, benchmark, and export the experimental methods developed by this project, with the goal of maximizing their impact and utility for NOFIC investigators, the 4DN Network, and the broader scientific community.

摘要 - 项目1：UW-CNOF映射技术开发 在过去的十年中，主张基因组建筑的技术进步导致了非凡的 我们对4D核心的理解的进展，即真核的时空组织 核内的基因组。在最近出现的所有强大实验工具中，染色体 构象捕获（3C）及其高通量衍生物已成为最广泛使用的方法 在本地和全球范围内表征基因组建筑。但是，目前基于3C的曲目 对于特异性，分辨率和输入等关键参数，方法完全受到限制 要求。最近，我们在解决这些局限性的限制方面取得了重大进展， HI-C方案的无限制酶衍生物。在这里，我们建议进一步发展生化 表征动态4D核心的方法 尊重输入需求（直至单元），分辨率（消除限制酶偏见），尺度 （全基因组或有针对性的视图）和集成（与转录组结合测量和 表观基因组），同时还提高了灵敏度，特异性，简单性和吞吐量。在AIM 1中，我们将继续 优化全基因组和有针对性的DNase HI-C协议 - 包括一个备受简化的原位版本 DNase Hi-C - 进一步最大程度地减少输入要求和偏差，同时改善分辨率。我们还将完善 这些协议是为了最大程度地提高鲁棒性，可伸缩性和导出性。在AIM 2中，我们将发展一个高级 用于常规测量大量单细胞的基因组结构的吞吐量方法。我们提出的 基于组合索引并得到大量初步数据支持的方法，启用例程 从数百至 每个实验数千个单元格。在AIM 3中，我们将集成DNase Hi-C和其他测定法 同时测量基因组结构，表观遗传状态和转录组的同时测量 单细胞。我们认为，这种共同测定的成功发展将深刻提高我们的能力 开发连接基因组形式和功能的集成模型。最后，在AIM 4中，我们将标准化， 基准，并导出该项目开发的实验方法，目的是使其最大化 诺弗研究者，4DN网络和更广泛的科学界的影响力和实用性。