BICCN

Dendritome Mapping of Genetically-Defined and Sparsely-Labeled Cortical and Striatal Projection Neurons

Neuronal morphology is one of the key features for unbiased classification of neuronal cell types in the mammalian brain. Here we propose a novel approach to perform comprehensive brain-wide profiling of the dendritic morphology of genetically-defined neurons in the mouse brain. We have developed an innovative mouse genetic tool, called Mosaicism with Repeat Frameshift (MORF), which enables sparse and stochastic labeling of genetically-defined neurons in mice. MORF reporter mice can label in exquisite detail single neurons from dendrite and spines to axons and axonal terminals at a labeling frequency of 1-5% of a given Cre+ neuronal lineage. We propose to cross our new MORF lines with Cre mouse lines for striatal medium spiny neurons (MSNs) of direct- (D1-MSNs) and indirect-pathways (D2-MSNs), and Layer 5 cortical pyramidal neurons (CPNs) and image the detailed dendritic morphology of thousands of these genetically-defined striatal and cortical neurons (i.e. dendritome). We will digitally reconstruct thousands of MORF-labeled neurons using our novel program called G-Cut and register the brain-wide single neuron morphological data onto a standard reference mouse brain atlas. Reconstructed neurons will subsequently be used for morphology based clustering to define new morphological subtypes. This dendritome data will be disseminated to the Brain Cell Data Center (BCDC) for data integration with those from other BRAIN Initiative Cell Census Network (BICCN) and for data access by the broader neuroscience research community. In addition to the dendritome data generation and analyses, we will further advance our MORF method by generating new MORF reporter mouse lines with logarithmic fold decrease in the Cre-dependent labeling frequencies, which will permit imaging of the complete, brain-wide morphology (i.e. both dendritic and axonal arborizations) of genetically-defined single neurons. Finally, we will develop integrated computer software and hardware (e.g. domain-specific computing) solutions for image processing and neuronal reconstruction, a major bottleneck in analyzing large-scale neuronal morphological datasets. In summary, we will provide rich dendritome information to enable unbiased, morphology-based neuronal cell type classification, and novel mouse genetic tools and computer software and hardware to advance the field of large-scale neuronal morphological studies in the mammalian brain.

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