The cerebral cortex contains an astonishing diversity of neuronal cell types distributed across dozens of functional areas, which emerge during early development for an apparently uniform neuroepithelium, and the radial glia cells, which act as neural stem cells. Neurogenesis in the cortex follows highly orchestrated and carefully controlled programs that establish a highly reproducible patterns of the six cortical layers. It has long been hypothesized that developmental histories of the cells are instrumental for establishing normal patterns of neuronal connectivity necessary for establishing the primitives of cortical transformation of sensory information. Many genetic mutations underlying brain development abnormalities and neurodevelopmental psychiatric disorders have long been hypothesized to affect early stages of brain development, including neuronal differentiation and circuit formation. However, we currently lack scalable tools for interrogating the developmental processes, especially the lineage relationships, and relating them to the adult brain cell types atlas, which would serve as a framework for interrogating the impact of disease mutations or developmental perturbations on brain development in a highly scalable manner. Here, we propose to leverage two emerging technologies for developmental lineage tracing that are amenable with single cell RNA sequencing. We will deploy these methods in the context of developing mouse cerebral cortex to survey the developmental lineage relationships in distinct functional areas of the cortex for which reference adult cortical single cell data are readily accessible through the BRAIN Initiative Cell Census Network, to address the hypothesis that distinct neurogenesis patterns underlie the development of area- specific excitatory cortical neurons. Most scalable developmental lineage tracing studies do not preserve the spatial position information, which is traditionally critical for the understanding of cellular organization in the brain, including the cortex. To overcome this limitation, we will contextualize the developmental lineage information in situ by performing spatial transcriptomics analysis in primary tissue. We will focus this effort on mapping lineage relationships in the primary visual cortex. We expect that this approach will enable mapping of the tangential dispersion of clonally related neurons. This innovative research program will, if successful, contribute to the development of scalable technologies for mapping developmental lineage relationships in the cerebral cortex by comparing two scalable methods for developmental lineage tracing, and serve as a step towards integrating developmental lineage tracing technologies with spatial tissue mapping, which will facilitate integration of developmental lineage data into the mouse brain cell atlas.
We seek to develop and integrate scalable technologies for connecting neuronal cell identity in the cerebral cortex with developmental origin information. We will compare two technologies that track the developmental origins of cortical neurons and combines scalable recovery of transcriptomic cell identity. In addition, we will compare two scalable methods for mapping lineage information and marker gene expression in brain tissue sections, to establish a framework for contextualizing developmental lineage relationships in the common coordinate framework.
