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.
The human body is comprised of trillions of individual cells. Over 150 years ago, Rudolf Virchow famously stated that all diseases involve aberrations of normal cells, launching the modern field of pathology. Nonetheless, to date, most methods for measuring molecular biology in human tissues, and in particular the toolset of the rapidly advancing field of genomics, lack the ability to resolve differences between individual cells. The technologies developed by this project will allow us to scalably measure diverse aspects of molecular biology at single cell resolution. The adoption and application of these methods will broadly facilitate our understanding of human biology as well as of the pathophysiology of all human diseases.
