Cellular diversity in the Drosophila midbrain revealed by single-cell transcriptomics
- University of Oxford, United Kingdom
Abstract
To understand the brain, molecular details need to be overlaid onto neural wiring diagrams so that synaptic mode, neuromodulation and critical signaling operations can be considered. Single-cell transcriptomics provide a unique opportunity to collect this information. Here we present an initial analysis of thousands of individual cells from Drosophila midbrain, that were acquired using Drop-Seq. A number of approaches permitted the assignment of transcriptional profiles to several major brain regions and cell-types. Expression of biosynthetic enzymes and reuptake mechanisms allows all the neurons to be typed according to the neurotransmitter or neuromodulator that they produce and presumably release. Some neuropeptides are preferentially co-expressed in neurons using a particular fast-acting transmitter, or monoamine. Neuromodulatory and neurotransmitter receptor subunit expression illustrates the potential of these molecules in generating complexity in neural circuit function. This cell atlas dataset provides an important resource to link molecular operations to brain regions and complex neural processes.
Data availability
Sequencing data have been deposited in SRA under accession code SRP128516. Digital Expression Matrix is provided as supplementary file.
Article and author information
Author details
Christoph Daniel Treiber
Funding
Wellcome (200846/Z/16/Z)
- Scott Waddell
Bettencourt Schueller Foundation
- Scott Waddell
Wellcome
- Vincent Croset
Wellcome
- Christoph Daniel Treiber
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Croset et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Cellular diversity in the Drosophila midbrain revealed by single-cell transcriptomics
eLife 7:e34550.
https://doi.org/10.7554/eLife.34550
