Project 1: UW-CNOF Mapping Technology Development

摘要-项目1：UW-CNOF地图技术开发 在过去的十年里，分析基因组结构的技术的进步导致了显著的 我们对4D核组，即真核生物的时空组织的理解进展 细胞核内的基因组。在最近出现的所有强大的实验工具中，染色体 构象捕获(3C)及其高通量衍生物已成为目前应用最广泛的构象捕获方法 描述本地和全球的基因组结构。然而，目前基于3C的曲目 方法在诸如特异性、分辨率和输入等关键参数方面受到严重限制 要求。最近，我们在使用DNase Hi-C解决这些限制方面取得了实质性进展， Hi-C方案的限制性无酶衍生物。在这里，我们建议进一步发展生化 用于表征动态4D核组的方法，所述动态4D核组在现有技术的基础上通过 根据输入要求(下至单个细胞)、分辨率(消除限制性内切酶偏向)、比例 (全基因组或有针对性的观点)和整合(结合转录组和 表观基因组)，同时还提高了敏感性、特异性、简单性和吞吐量。在目标1中，我们将继续 优化全基因组和靶向DNase Hi-C协议-包括简化的原位版本 DNase Hi-C-进一步最小化输入要求和偏差，同时提高分辨率。我们还将完善 这些协议以最大限度地提高健壮性、可扩展性和可输出性。在目标2中，我们将开发一种高- 在大量单细胞中常规测量基因组结构的吞吐量方法。我们的建议 以组合索引为基础并有大量初步数据支持的方法使例行公事 DNase Hi-C(核结构)或ATAC-seq(染色质可访问性)数据的生产从数百个到 每个实验有数千个单细胞。在目标3中，我们将整合DNase Hi-C和其他分析方法，用于 同时测量基因组结构、表观遗传状态和转录组 单细胞。我们相信，这种联合分析方法的成功发展将大大提高我们的能力。 开发连接基因组形式和功能的一体化模型。最后，在目标4中，我们将标准化， 基准测试，并导出由该项目开发的实验方法，目标是最大化其 对NOFIC调查人员、4DN网络和更广泛的科学界的影响和效用。

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.