PROJECT SUMMARY A major challenge in studying the mammalian brain is to characterize the integrative properties of individual neurons, such as molecular profiles, complete morphology (dendrites, axons, synapses), connectivity, and activity; furthermore, this must be done at a scale that is commensurate with the goal of understanding all the neurons and their circuitry in the brain. While current single-cell transcriptomic and epigenomic profiling techniques are highly quantitative, scalable and informative, the technologies to study other neuronal cell-type defining properties(e.g. single-neuron brain-wide morphology and synaptic connectivity) are low throughput, labor intensive, poorly scalable and often yield partial data. Emerging neuronal cell type classification studies in invertebrates (e.g. Drosophila) and in rodents suggest that the neuronal morphological data such as axonal projection patterns are correlated, but may also be independent to the cell classes defined by single-cell gene expression. Thus, a complete and unbiased survey of mammalian neuronal cell census should include orthogonal data types consisting of both molecular profiles and brainwide morphology of single neurons. Finally, for emerging new cell types defined by unique transcriptomic profiles, the causal links between the cell-type-defining “neuronal identity” genes and other cell-type-specific features, such as morphology, synaptic connectivity and activity, remain elusive and cannot be readily characterized in a scalable manner. In this proposal (in response to RFA MH-21-140), we will address these challenges by building upon a novel neurotechnology called Mosaicism with Repeat Frameshift, or MORF. MORF mice can confer cell- type specific, sparse and brightly labeling of neurons and glia to illuminate their complete morphologies in the mouse brain. The innovative aspect of the MORF mice is the use of an out-of-frame mononucleotide repeat as a stochastic translational switch; and its random frameshift leads to the expression of an extremely bright membrane-bound immunoreporter protein in 1-5% of genetically-defined neurons. In this proposal, we will generate four next-generation MORF mouse models that will allow: (1). precise and sparse labeling of neuronal cell types based on two genetic drivers (i.e. two molecular markers that define the neuronal cell type); (2). Cre-dependent labeling of endogenous presynaptic proteins in sparsely labeled GABAergic and cortical glutamatergic neurons; (3). selective expression of genome-editing tools in genetically and sparsely labeled neurons to support perturbation and multiplex subcellular labeling; and (4). development of an innovative and integrative multiscale imaging and registration pipeline to provide proof-of-concept data that analyzes brainwide morphology and connectivity of genetically-defined single neurons. Together, our grant may help to develop generalizable, scalable and democratizable tools to advance the study of ...