This webinar discusses a study that used spatial transcriptomics to gain insight into the molecular mechanisms of amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease.
Mounting evidence indicates that dysfunction in signaling between motor neurons and glia is a key component of ALS, but limitations of traditional gene expression profiling technologies, such as low throughput or lack of spatial resolution, have so far stymied efforts to understand how this dysfunction participates in the onset and spread of ALS pathology in the spinal cord.
Our speaker, Silas Maniatis of the New York Genome Center, shares how his team sought to gain a spatially resolved view of disease-driven gene expression changes that order these events.
Dr. Maniatis discusses how the NYGC team and collaborators from the Flatiron Institute, SciLifeLab, and the Broad used spatial transcriptomics — which generates quantitative transcriptome-wide RNA sequencing data through the capture of polyadenylated RNA on arrays of spatially barcoded DNA capture probes — to obtain gene expression measurements of mouse spinal cords over the course of disease, as well as of postmortem tissue from ALS patients.
The study resulted in a comprehensive spatiotemporal, transcriptome-wide gene expression dataset combining resolution, replication, and biological perturbation. Dr. Maniatis discusses data from the study as well as the broader potential of the work for future studies of central nervous system disorders.