For more than 100 years, the fruit fly Drosophila melanogaster has been one of the most studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula Drosophilae , that includes 580,000 nuclei from 15 individually dissected sexed tissues as well as the entire head and body, annotated to >250 distinct cell types. We provide an in-depth analysis of cell type–related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types between tissues, such as blood and muscle cells, reveals rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the Drosophila community and serves as a reference to study genetic perturbations and disease models at single-cell resolution.

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Taste detection and hunger state dynamically regulate the decision to initiate feeding. To study how context-appropriate feeding decisions are generated, we combined synaptic resolution circuit reconstruction with targeted genetic access to specific neurons to elucidate a gustatory sensorimotor circuit for feeding initiation in adult Drosophila melanogaster. This circuit connects gustatory sensory neurons to proboscis motor neurons through three intermediate layers. Most neurons in this pathway are necessary and sufficient for proboscis extension, a feeding initiation behavior, and respond selectively to sugar taste detection. Pathway activity is amplified by hunger signals that act at select second-order neurons to promote feeding initiation in food-deprived animals. In contrast, the feeding initiation circuit is inhibited by a bitter taste pathway that impinges on premotor neurons, illuminating a local motif that weighs sugar and bitter taste detection to adjust behavioral outcome. Together, these studies reveal central mechanisms for the integration of external taste detection and internal nutritive state to flexibly execute a critical feeding decision.

Summary RNA interference (RNAi) is a potent mechanism for down-regulating gene expression. Conserved RNAi pathway components are found in animals, plants, fungi and other eukaryotes [1–3]. In C. elegans, the RNAi response is greatly amplified by the synthesis of abundant secondary siRNAs [4–6]. Exogenous double stranded RNA is processed by Dicer and RDE-1/Argonaute into primary siRNA that guides target mRNA recognition. The RDE-10/RDE-11 complex and the RNA dependent RNA polymerase RRF-1 then engage the target mRNA for secondary siRNA synthesis [7, 8]. However, the molecular link between primary siRNA production and secondary siRNA synthesis remains largely unknown. Furthermore, it is unclear if the sub-cellular sites for target mRNA recognition and degradation coincide with sites where siRNA synthesis and amplification occur. In the C. elegans germline, cytoplasmic P granules at the nuclear pores and perinuclear Mutator foci contribute to target mRNA surveillance and siRNA amplification, respectively [9–11]. We report that RDE-12, a conserved FG domain containing DEAD-box helicase, localizes in P-granules and cytoplasmic foci that are enriched in RSD-6 but are excluded from the Mutator foci. Our results suggest that RDE-12 promotes secondary siRNA synthesis by orchestrating the recruitment of RDE-10 and RRF-1 to primary siRNA targeted mRNA in distinct cytoplasmic compartments.

The forthcoming assembly of the adult Drosophila melanogaster central brain connectome, containing over 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain. Here, we create a leaky integrate-and-fire computational model of the entire Drosophila brain, based on neural connectivity and neurotransmitter identity, to study circuit properties of feeding and grooming behaviors. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation. Computational activation of neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing, a testable hypothesis that we validate by optogenetic activation and behavioral studies. Moreover, computational activation of different classes of gustatory neurons makes accurate predictions of how multiple taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Our computational model predicts that the sugar and water pathways form a partially shared appetitive feeding initiation pathway, which our calcium imaging and behavioral experiments confirm. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit that do not overlap with gustatory circuits, and accurately describes the circuit response upon activation of different mechanosensory subtypes. Our results demonstrate that modeling brain circuits purely from connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can accurately describe complete sensorimotor transformations.

Summary RNA interference (RNAi) has enabled researchers to study the function of many genes. However, it is not understood why some RNAi experiments succeed, while others do not. Here, we show in C. elegans that pharyngeal muscle is resistant to RNAi when initially exposed to dsRNA by feeding, but sensitive to RNAi in the next generation. Investigating this observation, we find that pharyngeal muscle cells as well as vulval muscle cells require nuclear rather than cytoplasmic RNAi. Further, we find in these cell types that nuclear RNAi silencing is most efficiently triggered during early development, defining a critical period for initiating nuclear RNAi. Finally, using heat-shock induced dsRNA expression, we show that synMuv B class mutants act in part to extend this critical window. The synMuv B-dependent early development associated critical period for initiating nuclear RNAi suggests that mechanisms that restrict developmental plasticity may also restrict the initiation of nuclear RNAi.

Taste detection and hunger state dynamically regulate the decision to initiate feeding. To study how context-appropriate feeding decisions are generated, we combined synaptic resolution circuit reconstruction with targeted genetic access to specific neurons to elucidate a gustatory sensorimotor circuit for feeding initiation in Drosophila melanogaster. This circuit connects gustatory sensory neurons to proboscis motor neurons through three intermediate layers. Most of the neurons in this pathway are necessary and sufficient for proboscis extension, a feeding initiation behavior, and respond selectively to sugar taste detection. Hunger signals act at select second-order neurons to increase feeding initiation in food-deprived animals. In contrast, a bitter taste pathway inhibits premotor neurons, illuminating a central mechanism that weighs sugar and bitter tastes to promote or inhibit feeding. Together, these studies reveal the neural circuit basis for the integration of external taste detection and internal nutritive state to flexibly execute a critical feeding decision.

Summary Ever since the discovery of the first microRNAs in C. elegans, increasing numbers of endogenous small RNAs have been discovered. Endogenous siRNAs (endo-siRNAs) have emerged in the last few years as a largely independent class of small RNAs that regulate endogenous gene expression, with mechanisms distinct from those of piRNAs and miRNAs. Quantification of these small RNAs and their effect on target RNAs is a powerful tool for the analysis of RNAi; however, detection of small RNAs can be difficult due to their small size and relatively low abundance. Here, we describe the novel FirePlex assay for directly detecting endo-siRNA levels in bulk, as well as an optimized qPCR method for detecting the effect of endo-siRNAs on gene targets. Intriguingly, the loss of endo-siRNAs frequently results in enhanced experimental RNAi. Thus, we also present an optimized method to assess the indirect impact of endo-siRNAs on experimental RNAi efficiency.