PT  - JOURNAL ARTICLE
AU  - Fred P. Davis
AU  - Aljoscha Nern
AU  - Serge Picard
AU  - Michael B. Reiser
AU  - Gerald M. Rubin
AU  - Sean R. Eddy
AU  - Gilbert L. Henry
TI  - A genetic, genomic, and computational resource for exploring neural circuit function
AID  - 10.1101/385476
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 385476
4099  - http://biorxiv.org/content/early/2018/08/05/385476.short
4100  - http://biorxiv.org/content/early/2018/08/05/385476.full
AB  - Abstract 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.HighlightsTranscriptomes reveal transmitters and receptors expressed in Drosophila visual neuronsTandem affinity purification of intact nuclei (TAPIN) enables neuronal genomicsTAPIN-seq and genetic drivers establish transcriptomes of 67 Drosophila cell typesProbabilistic modeling simplifies interpretation of large transcriptome catalogs