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A genetic, genomic, and computational resource for exploring neural circuit function

Fred P. Davis, Aljoscha Nern, Serge Picard, Michael B. Reiser, Gerald M. Rubin, Sean R. Eddy, Gilbert L. Henry
doi: https://doi.org/10.1101/385476
Fred P. Davis
1Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
2Molecular Immunology and Inflammation Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD 20892, USA
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  • For correspondence: fredpdavis@gmail.com henry@cshl.edu
Aljoscha Nern
1Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
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Serge Picard
1Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
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Michael B. Reiser
1Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
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Gerald M. Rubin
1Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
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Sean R. Eddy
1Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
4Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
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Gilbert L. Henry
1Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
4Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
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  • For correspondence: fredpdavis@gmail.com henry@cshl.edu
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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.

Highlights

  1. Transcriptomes reveal transmitters and receptors expressed in Drosophila visual neurons

  2. Tandem affinity purification of intact nuclei (TAPIN) enables neuronal genomics

  3. TAPIN-seq and genetic drivers establish transcriptomes of 67 Drosophila cell types

  4. Probabilistic modeling simplifies interpretation of large transcriptome catalogs

Footnotes

  • http://www.opticlobe.com

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.
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Posted August 13, 2019.
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A genetic, genomic, and computational resource for exploring neural circuit function
Fred P. Davis, Aljoscha Nern, Serge Picard, Michael B. Reiser, Gerald M. Rubin, Sean R. Eddy, Gilbert L. Henry
bioRxiv 385476; doi: https://doi.org/10.1101/385476
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A genetic, genomic, and computational resource for exploring neural circuit function
Fred P. Davis, Aljoscha Nern, Serge Picard, Michael B. Reiser, Gerald M. Rubin, Sean R. Eddy, Gilbert L. Henry
bioRxiv 385476; doi: https://doi.org/10.1101/385476

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