In a complex tissue, the fate and function of individual cells are strongly influenced by the local environment. Understanding the transcriptome-wide gene expression profiles of different cells residing in different microenvironment would help us understand the origin of celf-to-cell variation and their fate decision making mechanisms. Current in situ RNA detection methods only assay a small number of genes. While single cell RNA-seq methods provide a global survey of transcription profiles, spatial location information of individual cells is lost in the sample preparation process. This project aims to develop a novel experimental paradigm, in which thousands of cells will be unambiguously labeled and imaged in the tissue, and be subjected to retrospective single-cell mRNA sequencing. We will use this multifaceted, multiplex experimental paradigm to reveal the morphological and transcriptomic dynamics with unprecedented resolutions and scales in the developing Drosophila brain.
The MICHR Promoting Progress in Statistics (ProPS) Award aims to further develop single-cell transcriptome analysis methods, which will help us more accurately determine the key genes and pathways affecting neuronal subtypes and developmental stages...
Efficient molecular evolution to generate enantioselective enzymes using a dual-channel microfluidic droplet screening platform
Directed evolution has long been a key strategy to generate enzymes with desired properties like high selectivity, but experimental barriers and analytical costs of screening enormous mutant libraries have limited such efforts. Here, we describe an...
Deterministic droplet-based co-encapsulation and pairing of microparticles via active sorting and downstream merging
Published in the Royal Society of Chemistry, 2017
Presented at the University of Michigan Single-Cell Genomic Data Analytics Symposium
Sort 'N Merge: A Deterministic Microfluidic Platform for Co-Encapsulating Distinct Particles in Microdroplets
Published in Micro Electro Mechanical Systems