Versatile, exponentially scalable methods for single cell molecular profiling

单细胞基因组学领域正在蓬勃发展。然而，绝大多数研究都局限于 定量mRNA转录，通常在几千个细胞中。我们最近开创了一种新的 基于单细胞组合索引（“SCI”）概念的方法，其中几轮分裂， 分子索引和合并用于唯一地标记细胞或细胞核的核酸，而不需要 每个细胞的分离或区室化。可唯一标记为刻度的像元数 指数地与索引的轮数，例如， 数百万个细胞可以用三个 循环索引。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共测定（sci-CAR）。在此，我们建议 开发更广泛的单细胞方法，所有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“单通道”科学分析， 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”科学分析，例如： RNA和DNA的共测定。在我们的第三个目标中，我们将调整科学分析，使大规模的化学和生物技术成为可能。 在单细胞中进行基因筛选在我们的最终目标，我们将努力使方法和相关的软件 广泛提供给研究界。作为一个多功能的、指数级可扩展的平台，我们预计， 单细胞组合索引将加深和扩大单细胞基因组学对不同目标的影响， 包括用于生物体的描述性分子图谱，用于基因和调节的功能研究， 元素，并用于建模基因调控。

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.