![]() We applied scRNA-seq using droplet microfluidics (10x Chromium) on dissociated adult brains from animals precisely aged to eight different time points ( Figure S1G Table S1). Single-Cell RNA-Seq of the Adult Brain Identifies Discrete Cell Types We make this resource of 157,000 single-cell transcriptional profiles of two Drosophila strains available in a new single-cell visualization tool, called SCope, alongside other Drosophila and mammalian single-cell atlases ( ). Finally, we use machine-learning methods to accurately predict the age of a cell based on its gene expression profile. In addition, we map brain-wide cell-state changes that occur during aging. Here, we built a comprehensive atlas of cell types in the entire adult Drosophila brain, yielding nearly 1× “cell-coverage.” We also developed a Drosophila database for SCENIC ( Aibar et al., 2017), allowing us to map the gene regulatory networks underlying neuronal and glial types in the fly brain. Thus, comprehensive, unbiased brain-wide single-cell sequencing is expected to facilitate understanding of the cellular and regulatory basis of a brain and to provide insights on the gradual loss of fitness and cognition in aging ( Tulving and Craik, 2005, Wyss-Coray, 2016). Furthermore, during the lifetime of an animal, cell types and regulatory states may change, and the timing of normal and pathological loss of cell identity remains poorly described. Beyond the transcriptomes that underlie individual cell types, it is unknown whether brain-wide “regulatory states” exist that may be shared across multiple neuronal subtypes. It is an open question as to what extent neurons that build circuits with different spatial complexities, connections, and behavioral functions are controlled by different regulatory programs or whether they act as neutral building blocks in a circuit, committed to canonical neuronal communication. ![]() However, the molecular underpinnings of these cell types, such as the active gene regulatory networks and genes expressed in each cell type, have been less studied. Hundreds of neuronal types have been functionally characterized based on the morphology of their projections, their connectivity with other neurons, or their role in controlling behavior ( Robie et al., 2017). The Drosophila brain is ideal to build an atlas of cell types of a complex functioning brain because it encodes an extensive array of intricate behaviors ( Owald et al., 2015) while only consisting of approximately 100,000 cells, of which 85%–90% are neurons ( Kremer et al., 2017). However, a compendium of all cell types in a complete adult brain during the lifespan of an animal has not yet been reported. Single-cell technologies allow mapping of this diverse cellular landscape, and single-cell RNA sequencing (scRNA-seq) performed on developing mouse and zebrafish brains ( Han et al., 2018, Raj et al., 2018) and on parts of the adult fly brain ( Croset et al., 2018, Konstantinides et al., 2018) have already revealed unique cell types. These results, together with SCope, allow comprehensive exploration of all transcriptional states of an entire aging brain.īrain function depends on a complex network of specialized neuronal and glial cell types. This single-cell brain atlas covers nearly all cells in the normal brain and provides the tools to study cellular diversity alongside other Drosophila and mammalian single-cell datasets in our unique single-cell analysis platform: SCope ( ). During aging, RNA content declines exponentially without affecting neuronal identity in old brains. Gene network analyses using SCENIC revealed regulatory heterogeneity linked to energy consumption. Our data show high granularity and identify a wide range of cell types. Cell clustering identified 87 initial cell clusters that are further subclustered and validated by targeted cell-sorting. We present a single-cell transcriptome atlas of the entire adult Drosophila melanogaster brain sampled across its lifespan. The diversity of cell types and regulatory states in the brain, and how these change during aging, remains largely unknown.
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