Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brain’s volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the fly’s visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the 53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.

Mitochondria are an integral part of the metabolism of a neuron. EM images of fly brain volumes, taken for connectomics, contain mitochondria as well as the cells and synapses that have already been reported. Here, from the Drosophila hemibrain dataset, we extract, classify, and measure approximately 6 million mitochondria among roughly 21 thousand neurons of more than 5500 cell types. Each mitochondrion is classified by its appearance - dark and dense, light and sparse, or intermediate - and the location, orientation, and size (in voxels) are annotated. These mitochondria are added to our publicly available data portal, and each synapse is linked to its closest mitochondrion. Using this data, we show quantitative evidence that mitochodrial trafficing extends to the smallest dimensions in neurons. The most basic characteristics of mitochondria - volume, distance from synapses, and color - vary considerably between cell types, and between neurons with different neurotransmitters. We find that polyadic synapses with more post-synaptic densities (PSDs) have closer and larger mitochondria on the pre-synaptic side, but smaller and more distant mitochondria on the PSD side. We note that this relationship breaks down for synapses with only one PSD, suggesting a different role for such synapses.Competing Interest StatementThe authors have declared no competing interest.

Comprehensive high-resolution structural maps are central to functional exploration and understanding in biology. For the nervous system, in which high resolution and large spatial extent are both needed, such maps are scarce as they challenge data acquisition and analysis capabilities. Here we present for the mouse inner plexiform layer–the main computational neuropil region in the mammalian retina–the dense reconstruction of 950 neurons and their mutual contacts. This was achieved by applying a combination of crowd-sourced manual annotation and machine-learning-based volume segmentation to serial block-face electron microscopy data. We characterize a new type of retinal bipolar interneuron and show that we can subdivide a known type based on connectivity. Circuit motifs that emerge from our data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglion cell is motion sensitive.

Many animals use visual information to navigate, but how such information is encoded and integrated by the navigation system remains incompletely understood. In Drosophila melanogaster, EPG neurons in the central complex compute the heading direction by integrating visual input from ER neurons, which are part of the anterior visual pathway (AVP). Here we densely reconstruct all neurons in the AVP using electron-microscopy data. The AVP comprises four neuropils, sequentially linked by three major classes of neurons: MeTu neurons, which connect the medulla in the optic lobe to the small unit of the anterior optic tubercle (AOTUsu) in the central brain; TuBu neurons, which connect the AOTUsu to the bulb neuropil; and ER neurons, which connect the bulb to the EPG neurons. On the basis of morphologies, connectivity between neural classes and the locations of synapses, we identify distinct information channels that originate from four types of MeTu neurons, and we further divide these into ten subtypes according to the presynaptic connections in the medulla and the postsynaptic connections in the AOTUsu. Using the connectivity of the entire AVP and the dendritic fields of the MeTu neurons in the optic lobes, we infer potential visual features and the visual area from which any ER neuron receives input. We confirm some of these predictions physiologically. These results provide a strong foundation for understanding how distinct sensory features can be extracted and transformed across multiple processing stages to construct higher-order cognitive representations.

Animals exhibit innate and learned preferences for temperature and humidity-conditions critical for their survival and reproduction. Leveraging a whole-brain electron microscopy volume, we studied the adult Drosophila melanogaster circuitry associated with antennal thermo- and hygrosensory neurons. We have identified two new target glomeruli in the antennal lobe, in addition to the five known ones, and the ventroposterior projection neurons (VP PNs) that relay thermo- and hygrosensory information to higher brain centers, including the mushroom body and lateral horn, seats of learned and innate behavior. We present the first connectome of a thermo- and hygrosensory neuropil, the lateral accessory calyx (lACA), by reconstructing neurons downstream of heating- and cooling-responsive VP PNs. A few mushroom body-intrinsic neurons solely receive thermosensory input from the lACA, while most receive additional olfactory and thermo- and/or hygrosensory PN inputs. Furthermore, several classes of lACA-associated neurons form a local network with outputs to other brain neuropils, suggesting that the lACA serves as a hub for thermo- and hygrosensory circuitry. For example, DN1a neurons link thermosensory PNs in the lACA to the circadian clock via the accessory medulla. Finally, we survey strongly connected downstream partners of VP PNs across the protocerebrum; these include a descending neuron targeted by dry-responsive VP PNs, meaning that just two synapses might separate hygrosensory inputs from motor circuits. These data provide a comprehensive first- and second-order layer analysis of Drosophila thermo- and hygrosensory systems and an initial survey of third-order neurons that could directly modulate behavior.

Wiring a complex brain requires many neurons with intricate cell specificity, generated by a limited number of neural stem cells. central brain lineages are a predetermined series of neurons, born in a specific order. To understand how lineage identity translates to neuron morphology, we mapped 18 central brain lineages. While we found large aggregate differences between lineages, we also discovered shared patterns of morphological diversification. Lineage identity plus Notch-mediated sister fate govern primary neuron trajectories, whereas temporal fate diversifies terminal elaborations. Further, morphological neuron types may arise repeatedly, interspersed with other types. Despite the complexity, related lineages produce similar neuron types in comparable temporal patterns. Different stem cells even yield two identical series of dopaminergic neuron types, but with unrelated sister neurons. Together, these phenomena suggest that straightforward rules drive incredible neuronal complexity, and that large changes in morphology can result from relatively simple fating mechanisms.

During postembryonic development, the nervous system must adapt to a growing body. How changes in neuronal structure and connectivity contribute to the maintenance of appropriate circuit function remains unclear. In a previous paper (Schneider-Mizell et al., 2016), we measured the cellular neuroanatomy underlying synaptic connectivity in Drosophila. Here, we examined how neuronal morphology and connectivity change between 1st instar and 3rd instar larval stages using serial section electron microscopy. We reconstructed nociceptive circuits in a larva of each stage and found consistent topographically arranged connectivity between identified neurons. Five-fold increases in each size, number of terminal dendritic branches, and total number of synaptic inputs were accompanied by cell-type specific connectivity changes that preserved the fraction of total synaptic input associated with each presynaptic partner. We propose that precise patterns of structural growth act to conserve the computational function of a circuit, for example determining the location of a dangerous stimulus.

Similar morphological, physiological, and behavioral features have evolved independently in different species, a pattern known as convergence. It is known that morphological convergence can occur through changes in orthologous genes. In some cases of convergence, cis-regulatory changes generate parallel modifications in the expression patterns of orthologous genes. Our understanding of how changes in cis-regulatory regions contribute to convergence is hampered, usually, by a limited understanding of the global cis-regulatory structure of the evolving genes. Here we examine the genetic causes of a case of precise phenotypic convergence between Drosophila sechellia and Drosophila ezoana, species that diverged ~40 Mya. Previous studies revealed that changes in multiple transcriptional enhancers of shavenbaby (svb, a transcript of the ovo locus) caused phenotypic evolution in the D. sechellia lineage. It has also been shown that the convergent phenotype of D. ezoana was likely caused by cis-regulatory evolution of svb. Here we show that the large-scale cis-regulatory architecture of svb is conserved between these Drosophila species. Furthermore, we show that the D. ezoana orthologs of the evolved D. sechellia enhancers have also evolved expression patterns that correlate precisely with the changes in the phenotype. Our results suggest that phenotypic convergence resulted from multiple noncoding changes that occurred in parallel in the D. sechellia and D. ezoana lineages.

Numerous efforts to generate "connectomes," or synaptic wiring diagrams, of large neural circuits or entire nervous systems are currently underway. These efforts promise an abundance of data to guide theoretical models of neural computation and test their predictions. However, there is not yet a standard set of tools for incorporating the connectivity constraints that these datasets provide into the models typically studied in theoretical neuroscience. This article surveys recent approaches to building models with constrained wiring diagrams and the insights they have provided. It also describes challenges and the need for new techniques to scale these approaches to ever more complex datasets.

"Regulatory evolution," that is, changes in a gene's expression pattern through changes at its regulatory sequence, rather than changes at the coding sequence of the gene or changes of the upstream transcription factors, has been increasingly recognized as a pervasive evolution mechanism. Many somatic sexually dimorphic features of Drosophila melanogaster are the results of gene expression regulated by the doublesex (dsx) gene, which encodes sex-specific transcription factors (DSX(F) in females and DSX(M) in males). Rapid changes in such sexually dimorphic features are likely a result of changes at the regulatory sequence of the target genes. We focused on the Flavin-containing monooxygenase-2 (Fmo-2) gene, a likely direct dsx target, to elucidate how sexually dimorphic expression and its evolution are brought about. We found that dsx is deployed to regulate the Fmo-2 transcription both in the midgut and in fat body cells of the spermatheca (a female-specific tissue), through a canonical DSX-binding site in the Fmo-2 regulatory sequence. In the melanogaster group, Fmo-2 transcription in the midgut has evolved rapidly, in contrast to the conserved spermathecal transcription. We identified two cis-regulatory modules (CRM-p and CRM-d) that direct sexually monomorphic or dimorphic Fmo-2 transcription, respectively, in the midguts of these species. Changes of Fmo-2 transcription in the midgut from sexually dimorphic to sexually monomorphic in some species are caused by the loss of CRM-d function, but not the loss of the canonical DSX-binding site. Thus, conferring transcriptional regulation on a CRM level allows the regulation to evolve rapidly in one tissue while evading evolutionary constraints posed by other tissues.