Versatile, exponentially scalable methods for single cell molecular profiling

单细胞基因组学领域正在爆炸式增长。然而，绝大多数研究仅限于 量化信使核糖核酸转录，通常在几千个细胞。我们最近开创了一个新的班级 方法基于单细胞组合标引(SCI)的概念，其中多轮分裂， 分子索引和汇集用于唯一地标记细胞或核的核酸，而不需要 对每个细胞进行隔离或分隔。可以唯一标注比例的像元数 随着索引的循环次数呈指数级增长，​例如​可以用最少的三个细胞来分析数以百万计的细胞 一轮一轮的索引。自2015年以来，我们开发了量化染色质可及性的SCI方法 (SCI-ATAC-seq)、转录(sci-RNA-seq)、染色质结构(sci-Hi-C)和基因组序列 (SCI-LIANTI)，以及染色质可及性和转录的联合分析(SCI-CAR)。在此，我们建议 开发更广泛的单细胞方法，所有这些方法都基于单细胞的统一概念 组合标引。在我们的第一个目标中，我们将开发更多的不同类型的“单通道”SCI分析 分子状态的各个方面。在我们的第二个目标中，我们将开发额外的“双通道”SCI分析方法，例如​。 RNA和DNA的联合检测。在我们的第三个目标中，我们将采用SCI分析来实现大规模的化学和 在单细胞中进行基因筛选。在我们的最终目标中，我们将致力于制作方法和相关软件 广泛提供给研究界。作为一个多功能、指数级可扩展的平台，我们预计 单细胞组合索引将深化和扩大单细胞基因组学对不同目标的影响， 包括用于生物的描述性分子图谱、用于基因功能研究和调控 元素，以及对基因调控进行建模。

The field of single cell genomics is exploding. However, the vast majority of studies restrict themselves to quantifying mRNA transcription, typically in a few thousand cells. We have recently pioneered a new class of methods based on the concept of single cell combinatorial indexing (“sci”), wherein several rounds of splitting, molecular indexing, and pooling are used to uniquely label nucleic acids of cells or nuclei, without requiring the isolation or compartmentalization of each cell. The number of cells that can be uniquely labeled scales exponentially with the number of rounds of indexing, ​e.g. ​millions of cells can be profiled with as few as three rounds of indexing. Since 2015, we have developed sci- methods for quantifying chromatin accessibility (sci-ATAC-seq), transcription (sci-RNA-seq), chromatin architecture (sci-Hi-C), and genome sequence (sci-LIANTI), as well as a co-assay of chromatin accessibility and transcription (sci-CAR). Here, we propose to develop a much broader range of single cell methods, all based on the unifying concept of single cell combinatorial indexing. In our first aim, we will develop additional “single channel” sci- assays of various aspects of molecular state. In our second aim, we will develop additional “two channel” sci- assays, ​e.g. co-assays of RNA and DNA. In our third aim, we will adapt sci- assays to enable large-scale chemical and genetic screens in single cells. In our final aim, we will work to make the methods and associated software widely available to the research community. As a versatile, exponentially scalable platform, we anticipate that single cell combinatorial indexing will deepen and broaden the impact of single cell genomics for diverse goals, including for descriptive molecular atlases of organisms, for functional studies of genes and regulatory elements, and for modeling gene regulation.