Summary
The human genome contains several thousand genes that play a key role in the development of the brain’s connectome, a precise assembly of neural connections with billions of neurons and trillions of synapses. How is genomic information translated into synapse-specific connectivity underlying behavior and cognition? Answering this fundamental question will provide important insights about the principles underlying nervous system development and is relevant for neurodevelopmental disorders such as autism. However, current approaches to measure neuronal connectivity have intrinsic limitations that prevent combined analysis of connected neurons, and their gene expression profiles at a scale that matches the complexity of the mammalian nervous system. Here I propose to develop a novel approach for massively parallel neural circuit tracing with barcoded rabies virus and 3D intact-tissue RNA-sequencing. This will permit a comprehensive understanding about neural network architecture via the large-scale measurement of molecular, cellular, and circuit-level mechanisms in the mouse brain. Compared to current efforts that require vast scientific resources to map synaptic connectivity among a few cells or small tissue volumes, my approach will enable routine measurements of connections among thousands of single neurons with molecular detail. Based on my expertise in in vivo barcoding I will conduct a longitudinal study to reveal the wiring rules underlying the spatiotemporal development of neural circuits from diverse neuron types in the mouse prefrontal cortex, a brain region that plays a key role in cognition. I will follow a cross-sectional approach to unravel the effects of distinct mutations on neuronal wiring in the prefrontal cortex in two mouse models of autism (Cntnap2-/-, Syngap1+/-). My work will provide an innovative experimental platform and provide mechanistic insights into the developmental algorithms that the genome uses to encode the connectome.
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| Web resources: | https://cordis.europa.eu/project/id/101117989 |
| Start date: | 01-06-2024 |
| End date: | 31-05-2029 |
| Total budget - Public funding: | 1 500 000,00 Euro - 1 500 000,00 Euro |
Cordis data
Original description
The human genome contains several thousand genes that play a key role in the development of the brain’s connectome, a precise assembly of neural connections with billions of neurons and trillions of synapses. How is genomic information translated into synapse-specific connectivity underlying behavior and cognition? Answering this fundamental question will provide important insights about the principles underlying nervous system development and is relevant for neurodevelopmental disorders such as autism. However, current approaches to measure neuronal connectivity have intrinsic limitations that prevent combined analysis of connected neurons, and their gene expression profiles at a scale that matches the complexity of the mammalian nervous system. Here I propose to develop a novel approach for massively parallel neural circuit tracing with barcoded rabies virus and 3D intact-tissue RNA-sequencing. This will permit a comprehensive understanding about neural network architecture via the large-scale measurement of molecular, cellular, and circuit-level mechanisms in the mouse brain. Compared to current efforts that require vast scientific resources to map synaptic connectivity among a few cells or small tissue volumes, my approach will enable routine measurements of connections among thousands of single neurons with molecular detail. Based on my expertise in in vivo barcoding I will conduct a longitudinal study to reveal the wiring rules underlying the spatiotemporal development of neural circuits from diverse neuron types in the mouse prefrontal cortex, a brain region that plays a key role in cognition. I will follow a cross-sectional approach to unravel the effects of distinct mutations on neuronal wiring in the prefrontal cortex in two mouse models of autism (Cntnap2-/-, Syngap1+/-). My work will provide an innovative experimental platform and provide mechanistic insights into the developmental algorithms that the genome uses to encode the connectome.Status
SIGNEDCall topic
ERC-2023-STGUpdate Date
12-03-2024
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