A kit for massively parallel single cell gene expression analysis Abstract Interest in single cell gene expression analysis harnessing the capability of next- generation sequencing (NGS) has recently gained momentum in the academic community. Although sequencing has become cheaper, the ability to measure gene expression profile at the single cell level is extremely constrained by the limitation of technolog for preparing sequencing libraries from single cells. Currently available sample preparation techniques require expensive instruments and are brute-force and low-throughput. Single cell gene expression would be much more powerful if it can be scaled to examine tens of thousands of cells at a time and across many genes. Not only will such technology advance our knowledge in basic biology and medicine, it also has many potential clinical applications. We have recently developed a low-cost and high-resolution massively parallel method to prepare sequencing libraries from large number of single cells for gene expression analysis. The method is based on the concept of stochastic labeling, executed at the single cell and the single molecule level. We have successfully conducted expression analysis of ~100 genes of close to 1000 single cells per sample routinely, and have demonstrated the ability of our system to classify major cell types in heterogeneous cell mixtures such as human blood. The scalability, throughput, and economy of our technology far exceed existing commercial platforms. For this proposed Phase II project, we plan to further scale our technology to enable routine analysis of hundreds of genes across 10,000 cells per sample, and to convert the current working prototype into an exportable product that includes a reagent kit, a simple reagent-loading device, and supporting assay design and analysis software.

Public Health Relevance

A kit for massively parallel single cell gene expression analysis Narrative We aim to develop a commercial kit that enables low-cost, routine, sequencing-based digital gene expression measurement of 10,000 or more individual cells in a biological sample. Our technology would widen the adoption of large-scale single cell analysis by researchers, enabling researchers to gain better understanding of complex biological systems and their relationships to health and diseases. It also has a number of potential clinical applications, especially in situations when identification of rare cells is crucial. Examples inclue early cancer detection, monitoring of cancer therapy, and evaluating responses to drugs and vaccines.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
Project #
1R44HG008323-01
Application #
8832632
Study Section
Special Emphasis Panel (ZRG1-IMST-J (15))
Program Officer
Smith, Michael
Project Start
2014-12-10
Project End
2015-11-30
Budget Start
2014-12-10
Budget End
2015-11-30
Support Year
1
Fiscal Year
2015
Total Cost
$1,512,400
Indirect Cost
Name
Cellular Research, Inc.
Department
Type
DUNS #
078299220
City
Palo Alto
State
CA
Country
United States
Zip Code
94304