Title:Polysynaptic connectivity mapping with single-neuron resolution and high throughput using evolving RNA barcodes.

The intricate brain functions rely on neuronal networks jointly processing information through connections known as synapses. Two neurons within a network can be connected directly by synapsing with each other or indirectly through other neurons. Therefore, mapping the connectivity of neuronal networks is critical for understanding how information is processed within the brain. However, current methods can only map a small fraction of the neurons with one-synapse connection, falling far short of mapping full network structures. I propose to address this gap by using an engineered synapse-hopping virus whose genome sequence changes slightly during the hop. Once it traverses an entire network, its genome sequence can used to infer the direct and indirect connectivity based on the amount of sequence change. This approach will identify neurons connected directly or with multiple synaptic intermediates and will be applicable to a large number of neurons. It will be a step-change advancements in our ability to map neuronal connectivity at scale.