Human brain specimens are one of few available opportunities to directly investigate the molecular underpinnings of neuropsychiatric diseases. Assays of gene and protein expression in situ have revolutionized our understanding of many of these diseases, but despite these advances, for many brain disorders, the tissue changes that give rise to clinical symptoms are poorly understood. Ascertaining the full set of molecular change(s) and the cell type(s) in which each change resides would inform the laboratory models used to study these illnesses, and offer hypotheses for potential new treatments. This proposal outlines a novel technology, Slide-seq, capable of performing whole-transcriptome analysis of intact brain tissue sections at single-cell (~7 ?m) resolution. The method applies my recent development of a novel DNA barcoding scheme, based upon split-and-pool DNA synthesis, to construct a microscope slide adorned with a high-diversity bead array capable of recording fine spatial coordinates for each gene, transcriptome-wide. In this proposal, we: (1) describe the molecular, computational, and cell biological innovations necessary to transfer RNA from tissue sections onto this array, and successfully report their spatial positions; (2) outline three core assays for unambiguously measuring the success of each crucial technical step; (3) critically evaluate the single-cell resolution of Slide- seq by profiling the mouse adult hippocampus; and (4) apply Slide-seq to a mouse model of Alzheimer's disease to uncover how surrounding cell populations respond to neuronal amyloid accumulation in the early stages of disease. Together, these experiments will produce a well-validated tool with broad applicability to problems in biology, most especially the analysis of pathological brain tissue.
For most neuropsychiatric diseases, the tissue changes that cause clinical symptoms are poorly understood. This project outlines the development and validation of a novel technology, Slide-seq, which will enable genome-wide expression analysis of brain tissue sections at single-cell resolution. This tool should find broad application not only to the study of pathological tissue specimens, but also to a wide range of biological problems that would benefit from the unbiased assessment of single-cell gene expression in situ.