Research Assistant Professor
Ph.D., Princeton University, 2015
firstname.lastname@example.org | 516-367-5067
I develop novel high-throughput, multi-omics methods for single-cell analysis, and apply these methods to understanding complex physiology and disease, including cancer, immunology and neurobiology in humans and other organisms. In cancer, I am working on understanding how the host components interact with a tumor.
Single-cell analyses play an important and unique role in understanding the heterogeneity of a tissue and the interactions between cells. Li’s research focuses on developing high-throughput, multi-omics, single-cell methods and using them to understand the patterns of gene expression and genomic variation of cancer cells and tissues. In spite of rapid advances in single-cell protocols, existing methods still suffer from low coverage, cross-contamination, poor sampling, and high cost. To resolve these problems, Li developed a new platform for single-cell sequencing, in which single-cell nucleic acids are we polymerized into balls of polyacrylamide (BAG-seq). By customizing the choice of Acrydite-modified oligonucleotides, the BAGs can capture DNA or RNA. Once the polymerization is complete, the cell contents are captured and isolated within each BAG, enabling further manipulations without cross contamination. Split-pool barcoding assigns a unique tag to each BAG, enabling a high-throughput low-cost single-cell approach superior to existing single-cell methods. Using BAG-seq, the lab is working on characterizing the host elements in tumors and learning how the host components interact with tumors. In addition, by collaborating with Dr. Dan Levy, Li developed a method of using conventional short-read sequencing to obtain ultra-low-error-rate de novo haplotype-phased sequence assemblies of regions 10 KB in length without reliance on a reference genome.