The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop technology for single-cell RNA sequencing (scRNA-seq). Single-cell RNA-sequencing has emerged as one of the best tools to catalogue cell types and understand their function. The key advantage of scRNA-seq is that it provides transcriptome-wide information about individual cells in heterogeneous samples while alternative methods either provide information about only a limited set of genes (e.g., flow cytometry, qPCR) or cannot provide single-cell resolution (bulk RNA-seq, microarrays). However, current scRNA-seq approaches remain expensive, enable only limited sample multiplexing, and are not compatible with common sample storage conditions. This project will focus on the key technical challenges that are required to develop universally applicable scRNA-seq kits that meet customer needs. If successful, the end product will be a scRNA-seq kit that is ready for pilot testing with academic and pharmaceutical company customers. By reducing the cost and increasing sample size and sample multiplexing of scRNA-seq, the technology will improve the ability to understand multicellular systems and enhance workflows used in the pharmaceutical industry, such as drug screening and patient stratification.The intellectual merit of this SBIR Phase I project is to develop a single-cell RNA sequencing (scRNA-seq) method by using a combinatorial barcoding scheme that labels transcripts within fixed cells. The proposed technology makes it possible to measure the transcriptional profiles of hundreds of thousands of individual cells in parallel. Unlike previous scRNA-seq technologies, the technology also enables high sample multiplexing (up to 96 samples/experiment), is compatible with stored samples, and fixes cells before dissociation, reducing the risk of perturbations to gene expression during cell handling. Most importantly, the method requires no complex instruments, which contributes to making the technology an order of magnitude less expensive than existing technologies. The objectives of this project are to dramatically improve the number of molecules detected per cell and to simplify the workflow for users. Modifications to assay chemistry will be tested to increase molecular detection, and time-consuming steps in the workflow will be altered to shorten the overall experimental time and reduce the probability of user error.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
