Many neurons in the central nervous system produce a single primary cilium that serves as a specialized signaling organelle. Several neuromodulatory G-protein-coupled receptors (GPCRs) localize to primary cilia in neurons, although it is not understood how GPCR signaling from the cilium impacts circuit function and behavior. We find that the vertebrate ancient long opsin A (VALopA), a G-coupled GPCR extraretinal opsin, targets to cilia of zebrafish spinal neurons. In the developing 1-d-old zebrafish, brief light activation of VALopA in neurons of the central pattern generator circuit for locomotion leads to sustained inhibition of coiling, the earliest form of locomotion. We find that a related extraretinal opsin, VALopB, is also G-coupled, but is not targeted to cilia. Light-induced activation of VALopB also suppresses coiling, but with faster kinetics. We identify the ciliary targeting domains of VALopA. Retargeting of both opsins shows that the locomotory response is prolonged and amplified when signaling occurs in the cilium. We propose that ciliary localization provides a mechanism for enhancing GPCR signaling in central neurons.

The mating decisions of Drosophila melanogaster females are primarily revealed through either of two discrete actions: opening of the vaginal plates to allow copulation, or extrusion of the ovipositor to reject the male. Both actions are triggered by the male courtship song, and both are dependent upon the female's mating status. Virgin females are more likely to open their vaginal plates in response to song; mated females are more likely to extrude their ovipositor. Here, we examine the neural cause and behavioral consequence of ovipositor extrusion. We show that the DNp13 descending neurons act as command-type neurons for ovipositor extrusion, and that ovipositor extrusion is an effective deterrent only when performed by females that have previously mated. The DNp13 neurons respond to male song via direct synaptic input from the pC2l auditory neurons. Mating status does not modulate the song responses of DNp13 neurons, but rather how effectively they can engage the motor circuits for ovipositor extrusion. We present evidence that mating status information is mediated by ppk sensory neurons in the uterus, which are activated upon ovulation. Vaginal plate opening and ovipositor extrusion are thus controlled by anatomically and functionally distinct circuits, highlighting the diversity of neural decision-making circuits even in the context of closely related behaviors with shared exteroceptive and interoceptive inputs.

The formation and consolidation of memories are complex phenomena involving synaptic plasticity, microcircuit reorganization, and the formation of multiple representations within distinct circuits. To gain insight into the structural aspects of memory consolidation, we focus on the calyx of the Drosophila mushroom body. In this essential center, essential for olfactory learning, second- and third-order neurons connect through large synaptic microglomeruli, which we dissect at the electron microscopy level. Focusing on microglomeruli that respond to a specific odor, we reveal that appetitive long-term memory results in increased numbers of precisely those functional microglomeruli responding to the conditioned odor. Hindering memory consolidation by non-coincident presentation of odor and reward, by blocking protein synthesis, or by including memory mutants suppress these structural changes, revealing their tight correlation with the process of memory consolidation. Thus, olfactory long-term memory is associated with input-specific structural modifications in a high-order center of the fly brain.

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all Mushroom Body output neurons (encoding learned valences) and characterized their patterns of interaction with Lateral Horn neurons (encoding innate valences) in larva. The connectome revealed multiple types that receive convergent Mushroom Body and Lateral Horn inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate valences to modify behavior.

The world view of rodents is largely determined by sensation on two length scales. One is within the animal's peri-personal space. Sensorimotor control on this scale involves active movements of the nose, tongue, head, and vibrissa, along with sniffing to determine olfactory clues. The second scale involves the detection of more distant space through vision and audition; these detection processes also impact repositioning of the head, eyes, and ears. Here we focus on orofacial motor actions, primarily vibrissa-based touch but including nose twitching, head bobbing, and licking, that control sensation at short, peri-personal distances. The orofacial nuclei for control of the motor plants, as well as primary and secondary sensory nuclei associated with these motor actions, lie within the hindbrain. The current data support three themes: First, the position of the sensors is determined by the summation of two drive signals, i.e., a fast rhythmic component and an evolving orienting component. Second, the rhythmic component is coordinated across all orofacial motor actions and is phase-locked to sniffing as the animal explores. Reverse engineering reveals that the preBötzinger inspiratory complex provides the reset to the relevant premotor oscillators. Third, direct feedback from somatosensory trigeminal nuclei can rapidly alter motion of the sensors. This feedback is disynaptic and can be tuned by high-level inputs. The elucidation of synergistic coordination of orofacial motor actions to form behaviors, beyond that of a common rhythmic component, represents a work in progress that encompasses feedback through the midbrain and forebrain as well as hindbrain areas.

Despite considerable progress in recent decades in dissecting the genetic causes of natural morphological variation, there is limited understanding of how variation within species ultimately contributes to species differences. We have studied patterning of the non-sensory hairs, commonly known as "trichomes," on the dorsal cuticle of first-instar larvae of Drosophila. Most Drosophila species produce a dense lawn of dorsal trichomes, but a subset of these trichomes were lost in D. sechellia and D. ezoana due entirely to regulatory evolution of the shavenbaby (svb) gene. Here, we describe intraspecific variation in dorsal trichome patterns of first-instar larvae of D. virilis that is similar to the trichome pattern variation identified previously between species. We found that a single large effect QTL, which includes svb, explains most of the trichome number difference between two D. virilis strains and that svb expression correlates with the trichome difference between strains. This QTL does not explain the entire difference between strains, implying that additional loci contribute to variation in trichome numbers. Thus, the genetic architecture of intraspecific variation exhibits similarities and differences with interspecific variation that may reflect differences in long-term and short-term evolutionary processes.

We have developed new open-source software calledTEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging.TEM features a graphical user interface that is used to submit jobs, monitor their progress, and display results. It implements a full processing pipeline including movie processing, image defocus determination, automatic particle picking, 2D classification, ab-initio 3D map generation from random parameters, 3D classification, and high-resolution refinement and reconstruction. Some of these steps implement newly-developed algorithms; others were adapted from previously published algorithms. The software is optimized to enable processing of typical datasets (2000 micrographs, 200k - 300k particles) on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing. Jobs can also be scheduled on large computer clusters using flexible run profiles that can be adapted for most computing environments.TEM is available for download from cistem.org.

We present CLADES (Cell Lineage Access Driven by an Edition Sequence), a technology for cell lineage studies based on CRISPR/Cas9. CLADES relies on a system of genetic switches to activate and inactivate reporter genes in a pre-determined order. Targeting CLADES to progenitor cells allows the progeny to inherit a sequential cascade of reporters, coupling birth order with reporter expression. This gives us temporal resolution of lineage development that can be used to deconstruct an extended cell lineage by tracking the reporters expressed in the progeny. When targeted to the germ line, the same cascade progresses across animal generations, marking each generation with the corresponding combination of reporters. CLADES thus offers an innovative strategy for making programmable cascades of genes that can be used for genetic manipulation or to record serial biological events.

Neural circuits carry out complex computations that allow animals to evaluate food, select mates, move toward attractive stimuli, and move away from threats. In insects, the subesophageal zone (SEZ) is a brain region that receives gustatory, pheromonal, and mechanosensory inputs and contributes to the control of diverse behaviors, including feeding, grooming, and locomotion. Despite its importance in sensorimotor transformations, the study of SEZ circuits has been hindered by limited knowledge of the underlying diversity of SEZ neurons. Here, we generate a collection of split-GAL4 lines that provides precise genetic targeting of 138 different SEZ cell types in adult , comprising approximately one third of all SEZ neurons. We characterize the single cell anatomy of these neurons and find that they cluster by morphology into six supergroups that organize the SEZ into discrete anatomical domains. We find that the majority of local SEZ interneurons are not classically polarized, suggesting rich local processing, whereas SEZ projection neurons tend to be classically polarized, conveying information to a limited number of higher brain regions. This study provides insight into the anatomical organization of the SEZ and generates resources that will facilitate further study of SEZ neurons and their contributions to sensory processing and behavior.

Detecting meaningful structure in neural activity and connectivity data is challenging in the presence of hidden nonlinearities, where traditional eigenvalue-based methods may be misleading. We introduce a novel approach to matrix analysis, called clique topology, that extracts features of the data invariant under nonlinear monotone transformations. These features can be used to detect both random and geometric structure, and depend only on the relative ordering of matrix entries. We then analyzed the activity of pyramidal neurons in rat hippocampus, recorded while the animal was exploring a 2D environment, and confirmed that our method is able to detect geometric organization using only the intrinsic pattern of neural correlations. Remarkably, we found similar results during nonspatial behaviors such as wheel running and rapid eye movement (REM) sleep. This suggests that the geometric structure of correlations is shaped by the underlying hippocampal circuits and is not merely a consequence of position coding. We propose that clique topology is a powerful new tool for matrix analysis in biological settings, where the relationship of observed quantities to more meaningful variables is often nonlinear and unknown.