GSE116969
A GENETIC, GENOMIC, AND COMPUTATIONAL RESOURCE FOR EXPLORING NEURAL CIRCUIT FUNCTION
The anatomy of many neural circuits is being characterized with increasing resolution, but their molecular properties remain mostly unknown. Here, we characterize gene expression patterns in distinct neural cell types of the Drosophila visual system using genetic lines to access individual cell types, the TAPIN-seq method to measure their transcriptomes, and a probabilistic method to interpret these measurements. We used these tools to build a resource of high-resolution transcriptomes for 100 driver lines covering 67 cell types. Combining these transcriptomes with recently reported connectomes helps characterize how information is transmitted and processed across a range of scales, from individual synapses to circuit pathways. We describe examples that include identifying neurotransmitters, including cases of co-release, generating functional hypotheses based on receptor expression, as well as identifying strong commonalities between different cell types. Overall design: 266 RNA-seq samples including 242 nuclear RNA-seq libraries prepared from specific cell types using INTACT/TAPIN, 8 samples dissected from the optic lobe, and 16 control libraries to characterize the INTACT/TAPIN protocols.