eLifeNeurosciencePeer-reviewed journal article
A genetic, genomic, and computational resource for exploring neural circuit function
Fred P. DavisiD, Aljoscha NerniD, Serge Picard, Michael B. ReiseriD, Gerald M. RubiniD, Sean R. EddyiD, Gilbert Lee HenryiD
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, available at http://www.opticlobe.com. 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.\n\nHighlightsO_LITranscriptomes reveal transmitters and receptors expressed in Drosophila visual neurons\nC_LIO_LITandem affinity purification of intact nuclei (TAPIN) enables neuronal genomics\nC_LIO_LITAPIN-seq and genetic drivers establish transcriptomes of 67 Drosophila cell types\nC_LIO_LIProbabilistic modeling simplifies interpretation of large transcriptome catalogs\nC_LI
- organism: Drosophila
- assay: scRNA-seq
- research focus: cell type annotation
- approach: experimental assay
- Citations
- 268
- FWCI
- 15.92
- Field percentile
- top 1%
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