Decoding the molecular identity of neurons

Regulated gene expression underlies the specification of cell fate and the maintenance of cell-specific function. Cellular diversity is of particular importance in the brain where neural circuits are assembled from cells with unique properties. Many neurological and psychiatric conditions arise from dysfunction in the brain, and although molecules are the targets of therapeutic drugs, we know relatively little about those that are critical for specific neural functions. Here we propose to generate a single-cell resolution transcriptome of the entire fly brain using Drop-seq. In a unique collaborative effort we will mine this data set to uncover molecules that contribute to an array of important neural processes, including: 1. How does Kenyon cell diversity support memory-guided decisions? 2. What is the extent of input specificity to functionally discrete dopaminergic neurons? 3. How do particular peptidergic neurons respond to internal states? 4. How does sex-specific neuronal identity emerge? 5. Is there a rational transcription factor logic for cell-specific gene expression? Our endeavour also possesses significant technological value. Transcriptomic information, and the design of synthetic regulatory sequences that decode cell-specific patterns of gene expression, will improve the precision and resolution with which experimental effector genes can be targeted to pre-determined groups of neurons.