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Development of a Multiplexed Sequencing Methodology (VECTORseq) to Elucidate Neuronal Molecular Identity and Connectivity Information

  • Author(s): Cheung, Victoria
  • Advisor(s): Edwards, Robert
  • et al.
Abstract

A fundamental goal of neurobiology is to understand how the structure and function of neurons tie into their molecular identity. The advent of single-cell RNA sequencing has made it possible to profile the gene expression of neurons which were traditionally difficult to access. However, many techniques lose connectivity information between neurons because tissue dissociation is involved. Optimization of current sequencing techniques can also be very slow, requiring iterative rounds of sequencing, and expensive. Here, we propose a method of exploiting the properties of commercially available, genetically engineered viruses to track neuronal connectivity and provide insight into their baseline gene expression: Virally Encoded Connectivity Transgenic Overlay RNA sequencing (VECTORseq). These unique viral transgenes are treated as barcodes in the single-cell dataset, and they are traceable since its transcript lengths are adequate for detection during sequencing. I injected retrogradely trafficked viruses encoding unique gene transcripts into outputs of a specific region of interest (ROI). I then dissected this ROI, dissociated it, and performed single-cell or single-nuclei sequencing. These transgenes delivered by retrogradely infecting viruses are resolved in the sequencing data—providing insight into which neurons in that ROI have projections to the injected locations. Colocalization of viral transgenes with known biomarkers provide validation of this technique so that it can be applied to other brain regions where good biomarkers have not been identified. This allows us to map the relationship between connectivity, structure, and function in a high-throughput, systematic way. We have shown the feasibility of this technique in cortical and subcortical populations of neurons as well as discovering new biomarkers.

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