Epigenomic profiling of complex tissues with single-cell CUT&RUN

摘要 人类基因调控因素仍然定义不清，这在很大程度上是由于技术上的原因 已经被用来绘制染色质景观的特定组成部分的方法的局限性。 到目前为止，这些方法中最受欢迎的是CHIP-SEQ，它在数千个实验室和 是大型基础设施项目的主要项目，如NIH的ENCODE和表观基因组路线图 财团。然而，自推出以来的一年半里，我们的小说在目标和释放下进行了切割 使用核酸酶(切割和运行)抗体拴住的核酸酶方法超过了标准的芯片序列 在效率和分辨率方面都是数量级的。我们已经开发了Cut&Run扩展 这使得它更普遍地适用于生物问题，并引入了一种高度- 用于研究和临床应用的吞吐量自动化格式。 为了将Cut&Run的应用扩展到异种细胞和组织，我们建议开发两个 具有明显优势的单电池切割和运行策略。在这两种情况下，我们都应用原位结扎术 批量剪切和运行片段，我们为其提供初步的概念验证数据。一种策略 使用直接条形码放大纳米晶片阵列中的切割和运行片段，以及其他 使用拆分池组合条形码。帮助指导技术发展，并进一步推动我们的 了解重要的发育途径，我们将应用单细胞切割和运行 人CD34原代造血细胞和果蝇生殖系组织。我们还将发展 为利用碱基对的切割和运行数据定制的新型计算工具 利用片段长度和位置进行高峰呼唤和鉴定的精密度 活跃的基因调控元件。我们将使用标准的计算工具 是为单细胞rna-seq数据开发的，以描绘细胞类型，我们将为 相邻转录因子、组蛋白标记和RNA聚合酶II的同时定位 在单个细胞内推断增强子-启动子-基因组合。最后，我们将利用 检测我们最近发现的一个新的一般核小体特征的能力 这些调控元件是由不对称展开的核小体标记的。 综上所述，我们的方案将引入低成本、高通量的单细胞表观基因组 适用于各种基础研究和临床应用的表征策略 这需要从基因调控元件的活动中获得信息。

Summary Human genetic regulatory elements remain poorly defined, in large part owing to technical limitations of methods that have been used to map specific components of the chromatin landscape. By far the most popular of these methods is ChIP-seq, which is used in thousands of laboratories and is a staple of large infrastructural projects such as NIH's ENCODE and Epigenomic Roadmap consortia. However, in 1½ years since its introduction, our novel Cleavage Under Targets & Release Using Nuclease (CUT&RUN) antibody-tethered nuclease method has surpassed standard ChIP-seq in efficiency and resolution by orders of magnitude. We have developed extensions to CUT&RUN that make it more generally applicable to biological problems, and have introduced a high- throughput automated format for research and clinical applications. To extend the utility of CUT&RUN to heterogeneous cells and tissues, we propose to develop two single-cell CUT&RUN strategies with distinct advantages. In both cases, we apply in situ ligation to CUT&RUN fragments in bulk, for which we present preliminary proof-of-concept data. One strategy uses direct barcoded amplification of CUT&RUN fragments in nanowell chip arrays and the other uses split-pool combinatorial barcoding. To help guide technology development and to further our understanding of important developmental pathways, we will apply single-cell CUT&RUN to human CD34+ primary hematopoietic cells and Drosophila germline tissues. We will also develop novel computational tools customized for CUT&RUN data that take advantage of the base-pair precision of cleavages by using fragment length and position for peak-calling and for identification of active genetic regulatory elements. We will use standard computational tools that have been developed for single-cell RNA-seq data to delineate cell-type, and we will develop software for simultaneous mapping of adjacent transcription factors, histone marks and RNA Polymerase II within single cells to deduce enhancer-promoter-gene combinations. Finally, we will exploit the ability of CUT&RUN to detect a new general nucleosome feature that we recently discovered in which regulatory elements are marked by asymmetrically unwrapped nucleosomes. Taken together, our proposal will introduce a low-cost high-throughput single-cell epigenome characterization strategy that applies to the wide variety of basic research and clinical applications that require information from the activity of genetic regulatory elements.