? No change from original application Brain functions emerge from highly nuanced spatiotemporal dynamics of neural circuit computation mediated by diverse and precisely interconnected neuron types. Specific and systematic experimental access to these cell types are prerequisites to deciphering brain circuit organization and function, but this has been a prohibitive bottleneck in neuroscience. Although powerful, current genetic approaches in mammals are mostly restricted to germline engineering in the mouse and have fundamental limitations in time, cost, scale, versatility and clinical application. What is urgently needed is the ability to identify and manipulate cell types in a way that is: 1) specific (to bona fide types defined by anatomical and physiological properties), 2) comprehensive (to many cell types), 3) fast (days instead of months to years), 4) inexpensive, and 5) across mammalian species. We propose to develop a paradigm-shifting platform that will enable rapid and comprehensive access for brain cell types across mammalian species by leveraging fundamental epigenomic and gene regulatory basis of cell types - the transcriptional enhancers. We will establish a cellular resolution and scalable pipeline for identifying cell type enhancers in the mouse brain that combines 1) chromatin landscape analysis (ATAC-seq) in genetic driver-defined neuronal subpopulations, 2) innovative AAV- and sequencing-based massively parallel reporter assays in these subpopulations, 3) high-throughput validation using a novel method of integrated spatial transcriptomics and sequencing-based projection mapping, and 4) high-resolution whole brain morphological imaging.
We aim for comprehensive coverage of neuron types of the cerebral cortex, including both glutamatergic pyramidal neurons and GABAergic interneurons, though our strategy and tools will be general to other brain regions and species. The Huang lab has systematically generated combinatorial genetic driver lines targeting major cortical neuron subpopulations and has discovered the transcriptional basis of cortical neuron types. Bing Ren is a leader in enhancer biology and has pioneered the technical advances in cell type and single cell chromatin analysis, including computational approaches. Tony Zador invented MAPseq, BARseq and other sequencing-based methods that enable high throughput, cellular resolution mapping of neuronal connectivity. Pavel Osten has pioneered developing high-resolution and high-throughput whole brain imaging pipelines with associated computational analysis. Together, our knowledge and expertise constitute a synergistic team focusing on an excellent experimental system for the systematic screening, discovery and validation of cell type enhancers and for generating cell census datasets that contribute to the BICCN goals. Our approach is grounded in fundamental genetic principles and mechanisms and has the potential to transform the scale and rate of discovery across neuroscience and biomedical fields.

Public Health Relevance

? No change from original application We will develop novel non-germline based viral tools to achieve specific and comprehensive targeting of neuronal cell types toward exploring neural circuit organization and function across mammalian species.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Multi-Year Funded Research Project Grant (RF1)
Project #
7RF1MH124612-02
Application #
10327151
Study Section
Special Emphasis Panel (ZMH1)
Program Officer
Yao, Yong
Project Start
2020-09-23
Project End
2023-09-22
Budget Start
2020-09-25
Budget End
2023-09-22
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Duke University
Department
Neurosciences
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705