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

  1. Fred P Davis  Is a corresponding author
  2. Aljoscha Nern
  3. Serge Picard
  4. Michael B Reiser
  5. Gerald M Rubin
  6. Sean R Eddy
  7. Gilbert L Henry  Is a corresponding author
  1. Janelia Research Campus, Howard Hughes Medical Institute, United States

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 apparent co-release, generating functional hypotheses based on receptor expression, as well as identifying strong commonalities between different cell types.

Data availability

All raw and processed transcriptome data is available from NCBI GEO (accession GSE116969).

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Fred P Davis

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    For correspondence
    fredpdavis@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8294-1610
  2. Aljoscha Nern

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3822-489X
  3. Serge Picard

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Michael B Reiser

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4108-4517
  5. Gerald M Rubin

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8762-8703
  6. Sean R Eddy

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6676-4706
  7. Gilbert L Henry

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    For correspondence
    henry@cshl.edu
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institute of Arthritis and Musculoskeletal and Skin Diseases (Intramural Research Program)

  • Fred P Davis

Howard Hughes Medical Institute

  • Fred P Davis
  • Aljoscha Nern
  • Serge Picard
  • Michael B Reiser
  • Gerald M Rubin
  • Sean R Eddy

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Metrics

  • 9,813
    views
  • 1,079
    downloads
  • 185
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Fred P Davis
  2. Aljoscha Nern
  3. Serge Picard
  4. Michael B Reiser
  5. Gerald M Rubin
  6. Sean R Eddy
  7. Gilbert L Henry
(2020)
A genetic, genomic, and computational resource for exploring neural circuit function
eLife 9:e50901.
https://doi.org/10.7554/eLife.50901

Share this article

https://doi.org/10.7554/eLife.50901

Further reading

    1. Genetics and Genomics
    2. Neuroscience
    Thomas P Spargo, Lachlan Gilchrist ... Alfredo Iacoangeli
    Research Article

    Continued methodological advances have enabled numerous statistical approaches for the analysis of summary statistics from genome-wide association studies. Genetic correlation analysis within specific regions enables a new strategy for identifying pleiotropy. Genomic regions with significant ‘local’ genetic correlations can be investigated further using state-of-the-art methodologies for statistical fine-mapping and variant colocalisation. We explored the utility of a genome-wide local genetic correlation analysis approach for identifying genetic overlaps between the candidate neuropsychiatric disorders, Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia, Parkinson’s disease, and schizophrenia. The correlation analysis identified several associations between traits, the majority of which were loci in the human leukocyte antigen region. Colocalisation analysis suggested that disease-implicated variants in these loci often differ between traits and, in one locus, indicated a shared causal variant between ALS and AD. Our study identified candidate loci that might play a role in multiple neuropsychiatric diseases and suggested the role of distinct mechanisms across diseases despite shared loci. The fine-mapping and colocalisation analysis protocol designed for this study has been implemented in a flexible analysis pipeline that produces HTML reports and is available at: https://github.com/ThomasPSpargo/COLOC-reporter.

    1. Developmental Biology
    2. Genetics and Genomics
    Subhradip Das, Sushmitha Hegde ... Girish S Ratnaparkhi
    Research Article

    Repurposing of pleiotropic factors during execution of diverse cellular processes has emerged as a regulatory paradigm. Embryonic development in metazoans is controlled by maternal factors deposited in the egg during oogenesis. Here, we explore maternal role(s) of Caspar (Casp), the Drosophila orthologue of human Fas-associated factor-1 (FAF1) originally implicated in host-defense as a negative regulator of NF-κB signaling. Maternal loss of either Casp or it’s protein partner, transitional endoplasmic reticulum 94 (TER94) leads to partial embryonic lethality correlated with aberrant centrosome behavior, cytoskeletal abnormalities, and defective gastrulation. Although ubiquitously distributed, both proteins are enriched in the primordial germ cells (PGCs), and in keeping with the centrosome problems, mutant embryos display a significant reduction in the PGC count. Moreover, the total number of pole buds is directly proportional to the level of Casp. Consistently, it’s ‘loss’ and ‘gain’ results in respective reduction and increase in the Oskar protein levels, the master determinant of PGC fate. To elucidate this regulatory loop, we analyzed several known components of mid-blastula transition and identify the translational repressor Smaug, a zygotic regulator of germ cell specification, as a potential critical target. We present a detailed structure-function analysis of Casp aimed at understanding its novel involvement during PGC development.