Molecular exploration of the brain at single-cell resolution
Description
Exciting developments in next generation sequencing, microfluidics, and microscopy have spurned an era of new technologies to measure gene expression in individual cells and in tissues. I will discuss our technological contributions—in the space of single-cell gene expression analysis, as well as a new technology we developed, in collaboration with Fei Chen’s lab, called Slide-seq, which quantifies genome-wide expression at 10 micron spatial resolution. I’ll also highlight some areas of biology in which we are particularly focused on deploying these new tools.
Speaker Bio
My lab develops and applies novel technologies to uncover the molecular bases of neuropsychiatric illnesses. I trained in molecular neuroscience (with Cori Bargmann), clinical psychiatry (Massachusetts General Hospital), and both experimental and computational genomics (with Steven McCarroll). My postdoctoral work combined molecular technology development, microfluidics, bioinformatics, and machine learning to develop Drop-seq, a novel, high-throughput approach to single-cell gene expression analysis, and applied it to systematically characterize the cell types that are resident within complex neural tissues. In my newly established lab (founded Dec 2016), we have been leveraging the technological insights that made Drop-seq possible to develop new technologies for making additional high-throughput and unbiased measurements of the brain. Our recent demonstration, together with the Chen lab, of Slide-seq opens exciting opportunities to build a scalable and multi-modal platform for making high-resolution molecular measurements in situ.