A key function of the brain is to categorize sensory cues as repulsive or attractive and respond accordingly. While we have some understanding of how sensory information is processed in the sensory periphery, the classification of cues according to valence in central brain circuits is less well understood. Here, we addressed this question in the Drosophila larva, where we could leverage the synaptic resolution connectome to determine where innate and learnt information from distinct aversive and appetitive sensory modalities converges; and combine this with imaging and manipulation of neural activity to determine how valence information is encoded and used to guide navigation. We found that information from multiple innately aversive and attractive sensory modalities converges onto a common output neuron of the learning circuit, specifically the Mushroom Body output neuron, MBON-m1. We discovered that this neuron is required for navigating both attractive odor and aversive temperature cues and is activated by attractive cues, such as food odour and sugar, and inhibited by different aversive cues, such as cooling, salt, or non-food odors. Together, our study reveals a neuron that bi-directionally encodes valence and controls actions.

Predicting adaptive phenotypic evolution depends on invariable selection gradients and on the stability of the genetic covariances between the component traits of the multivariate phenotype. We describe the evolution of six traits of locomotion behavior and body size in the nematode Caenorhabditis elegans for 50 generations of adaptation to a novel environment. We show that the direction of adaptive multivariate phenotypic evolution can be predicted from the ancestral selection differentials, particularly when the traits were measured in the new environment. Interestingly, the evolution of individual traits does not always occur in the direction of selection, nor are trait responses to selection always homogeneous among replicate populations. These observations are explained because the phenotypic dimension with most of the ancestral standing genetic variation only partially aligns with the phenotypic dimension under directional selection. These findings validate selection theory and suggest that the direction of multivariate adaptive phenotypic evolution is predictable for tens of generations.

Whether or not genetic divergence in the short-term of tens to hundreds of generations is compatible with phenotypic stasis remains a relatively unexplored problem. We evolved predominantly outcrossing, genetically diverse populations of the nematode Caenorhabditis elegans under a constant and homogeneous environment for 240 generations and followed individual locomotion behavior. Although founders of lab populations show highly diverse locomotion behavior, during lab evolution, the component traits of locomotion behavior - defined as the transition rates in activity and direction - did not show divergence from the ancestral population. In contrast, transition rates' genetic (co)variance structure showed a marked divergence from the ancestral state and differentiation among replicate populations during the final 100 generations and after most adaptation had been achieved. We observe that genetic differentiation is a transient pattern during the loss of genetic variance along phenotypic dimensions under drift during the last 100 generations of lab evolution. These results suggest that short-term stasis of locomotion behavior is maintained because of stabilizing selection, while the genetic structuring of component traits is contingent upon drift history.

1 Abstract Predicting phenotypic evolution on the short-term of tens to hundreds of generations, particularly in changing environments and under finite population sizes, is an important theoretical goal. Because organisms are not simply collections of independent traits, making headway into this goal requires understanding if the phenotypic plasticity of ancestral populations aligns with the phenotypic dimensions that contain more genetic variation for selection to be effective and eventually feedback on the maintenance of genetic variation and promote adaptation or rescue from extinction. By performing 50 generations of experimental evolution in a changing environment we show that ancestral phenotypic plasticity for locomotion behavior in the partially-outcrossing nematode Caenorhabditis elegans is nonadaptive because it does not align with the phenotypic dimension encompassing most genetic variance in the ancestral population and is of no consequence to future phenotypic divergence. Despite evolution of the genetic structure of locomotion behavior we are able to predict the direction of phenotypic divergence, but not the magnitude, based on the genetic covariances between the component traits of locomotion behavior and fitness of the ancestral population. We further demonstrate that indirect selection on the component traits of locomotion behavior with unobserved trait(s) is responsible for the observed phenotypic divergence on them. Our findings indicate that selection theory can predict the direction of short-term adaptive phenotypic evolution.

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 (MB) output neurons (encoding learned valences) and characterized their patterns of interaction with lateral horn (LH) neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent MB and LH 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.

Argentine tango has been shown to help psychological and physical health by reducing perceived levels of depression and stress, similar and at times better than meditation. An often reported experience in Argentine tango is "flow", which is described as total involvement from the dancers. While this state has been self-reported by experienced dancers while dancing, it has yet to be quantified in real-time. However, with the emergence of portable and wearable devices for the acquisition of physiological signals such as electroencephalography (EEG) and electrocardiography (ECG), and recent innovations in EEG artifact removal algorithms, this quantification may now be possible. In this work presents a case study where we aim to first validate the potential of recording usable EEG and ECG data from dancers while dancing, in an unobtrusive manner, as well as investigate the existence of neurophysiological correlates of Argentine tango flow.

Animal behavior is shaped both by evolution and by individual experience. In many species parallel brain pathways are thought to encode innate and learnt behavior drives and as a result may link the same sensory cue to different actions if innate and learnt drives are in opposition. How these opposing drives are integrated into a single coherent action is not well understood. In insects, the Mushroom Body Output Neurons (MBONs) and the Lateral Horn Neurons (LHNs) are thought to provide the learnt and innate drives, respectively. However their patterns of convergence and the mechanisms by which their outputs are used to select actions are not well understood. We used electron microscopy reconstruction to comprehensively map the downstream targets of all MBONs in Drosophila larva and characterise their patterns of convergence with LHNs. We discovered convergence neurons that receive direct input from MBONs and LHNs and compare opposite behaviour drives. Functional imaging and optogenetic manipulation suggest these convergence neurons compute the overall predicted value of approaching or avoiding an odor and mediate action selection. Our study describes the circuit mechanisms allowing integration of opposing drives from parallel olfactory pathways. ### Competing Interest Statement The authors have declared no competing interest.

Evolutionary theory suggests that phenotypic stasis is explained by natural selection and genetic drift, or by constraints imposed by mutation and recombination of standing genetic variation. We performed experimental evolution from standing genetic variation with the nematode Caenorhabditis elegans , measuring individual locomotion in outcrossing populations for 240 generations. We find that, in our constant environment, locomotion bias shows no directional divergence, due to both stabilizing and disruptive selection on specific combinations of component traits. Despite phenotypic stasis, the genetic variance-covariance structure between component traits shows clear divergence from the ancestral state and extensive differentiation among replicated populations facing the same environment. Analysis of mutation accumulation experiments and genome-sequenced recombinant inbred lines from the experimental populations indicates that the evolution of the genetic variance-covariance structure is independent of de novo mutation or major effect QTL; being instead explained by the joint action of selection and drift in generating subtle linkage disequilibrium differences between small effect QTL among replicate populations. These findings indicate that phenotypic evolution is repeatable because of selection, even if the genetic structuring of component traits within lineages is mostly contingent upon drift history.

Partial selfing, whereby self- and cross- fertilization occur in populations at intermediate frequencies, is generally thought to be evolutionarily unstable. Yet, it is found in natural populations. This could be explained if populations with partial selfing are able to reduce genetic loads and the possibility for inbreeding depression while keeping genetic diversity that may be important for future adaptation. To address this hypothesis, we compare the experimental evolution of Caenorhabditis elegans populations under partial selfing, exclusive selfing or predominant outcrossing, while they adapt to osmotically challenging conditions. We find that the ancestral genetic load, as measured by the risk of extinction upon inbreeding by selfing, is maintained as long as outcrossing is the main reproductive mode, but becomes reduced otherwise. Analysis of genome-wide single-nucleotide polymorphisms (SNPs) during experimental evolution and among the inbred lines that survived enforced inbreeding indicates that populations with predominant outcrossing or partial selfing maintained more genetic diversity than expected with neutrality or purifying selection. We discuss the conditions under which this could be explained by the presence of recessive deleterious alleles and/or overdominant loci. Taken together, our observations suggest that populations evolving under partial selfing can gain some of the benefits of eliminating unlinked deleterious recessive alleles and also the benefits of maintaining genetic diversity at partially dominant or overdominant loci that become associated due to variance of inbreeding levels.

To integrate changing environmental cues with high spatial and temporal resolution is critical for animals to orient themselves. Drosophila larvae show an effective motor program to navigate away from light sources. How the larval visual circuit processes light stimuli to control navigational decision remains unknown. The larval visual system is composed of two sensory input channels, Rhodopsin5 (Rh5) and Rhodopsin6 (Rh6) expressing photoreceptors (PRs). We here characterize how spatial and temporal information are used to control navigation. Rh6-PRs are required to perceive temporal changes of light intensity during head casts, while Rh5-PRs are required to control behaviors that allow navigation in response to spatial cues. We characterize how distinct behaviors are modulated and identify parallel acting and converging features of the visual circuit. Functional features of the larval visual circuit highlight the principle of how early in a sensory circuit distinct behaviors may be computed by partly overlapping sensory pathways.

ABSTRACTUnderstanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty is problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here we report a recombinant inbred line (RIL) quantitative trait locus (QTL) mapping panel for the hermaphroditic nematodeCaenorhabditis elegans, theC. elegansmultiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs, was created by hybridization of 16 wild isolates, experimental evolution at moderate population sizes and predominant outcrossing for 140-190 generations, and inbreeding by selfing for 13-16 generations. The panel contains 22% of single nucleotide polymorphisms known to segregate in natural populations, and complements existing mapping resources forC. elegansby providing high nucleotide diversity across >95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad sense heritability in the CeMEE. While simulations show we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits does not feature such alleles. We instead find that a significant fraction of trait variance, particularly for fertility, can be explained by sign epistasis with weak main effects. In congruence, phenotype prediction, while generally poor (r2< 10%), requires modeling epistasis for optimal accuracy, with most variance attributed to the highly recombinant, rapidly evolving chromosome arms.

Classical theory on the origin and evolution of selfing and outcrossing relies on the role of inbreeding depression created by unlinked partially-deleterious recessive alleles to predict that individuals from natural populations predominantly self or outcross. Comparative data indicates, however, that maintenance of partial selfing and outcrossing at intermediate frequencies is common in nature. In part to explain the presence of mixed reproductive modes within populations, several hypotheses regarding the evolution of inbreeding depression have been put forward based on the complex interaction of linkage and identity disequilibrium among fitness loci, together with Hill-Robertson effects. We here ask what is the genetic basis of inbreeding depression so that populations with intermediate selfing rates can eliminate it while maintain potentially adaptive genetic diversity. For this, we use experimental evolution in the nematode C. elegans under partial selfing and compare it to the experimental evolution of populations evolved under exclusive selfing and predominant outcrossing. We find that the ancestral risk of extinction upon enforced inbreeding by selfing is maintained when populations evolve under predominant outcrossing, but reduced when populations evolve under partial or exclusive selfing. Analysis of genome-wide single-nucleotide polymorphism (SNP) during experimental evolution and after enforced inbreeding suggests that, under partial selfing, populations were purged of unlinked deleterious recessive alleles that segregate in the ancestral population, which in turn allowed the expression of unlinked overdominant fitness loci. Taken together, these observations indicate that populations evolving under partial selfing gain the short-term benefits of selfing, in purging deleterious recessive alleles, but also the long-term benefits of outcrossing, in maintaining genetic diversity that may important for future adaptation.

Complex animal behaviors are built from dynamical relationships between sensory inputs, neuronal activity, and motor outputs in patterns with strategic value. Connecting these patterns illuminates how nervous systems compute behavior. Here, we study Drosophila larva navigation up temperature gradients toward preferred temperatures (positive thermotaxis). By tracking the movements of animals responding to fixed spatial temperature gradients or random temperature fluctuations, we calculate the sensitivity and dynamics of the conversion of thermosensory inputs into motor responses. We discover three thermosensory neurons in each dorsal organ ganglion (DOG) that are required for positive thermotaxis. Random optogenetic stimulation of the DOG thermosensory neurons evokes behavioral patterns that mimic the response to temperature variations. In vivo calcium and voltage imaging reveals that the DOG thermosensory neurons exhibit activity patterns with sensitivity and dynamics matched to the behavioral response. Temporal processing of temperature variations carried out by the DOG thermosensory neurons emerges in distinct motor responses during thermotaxis.

The avoidance of light by fly larvae is a classic paradigm for sensorimotor behavior. Here, we use behavioral assays and video microscopy to quantify the sensorimotor structure of phototaxis using the Drosophila larva. Larval locomotion is composed of sequences of runs (periods of forward movement) that are interrupted by abrupt turns, during which the larva pauses and sweeps its head back and forth, probing local light information to determine the direction of the successive run. All phototactic responses are mediated by the same set of sensorimotor transformations that require temporal processing of sensory inputs. Through functional imaging and genetic inactivation of specific neurons downstream of the sensory periphery, we have begun to map these sensorimotor circuits into the larval central brain. We find that specific sensorimotor pathways that govern distinct light-evoked responses begin to segregate at the first relay after the photosensory neurons.

When tracking and segmenting multiple objects under heavy occlusion, a large class of algorithms can greatly benefit from a preprocessing that reliably assesses the number of individuals in each cluster. This is a difficult task when relying on local information only, due to scarcity of training examples and lack of strongly predictive features. In this paper, we develop a deterministic graphical model to address the problem of counting the number of objects in each foreground region as global inference across the entire video sequence. We show that global inference improves over local predictions, and is able to produce an accurate and coherent output within an useful runtime.

The spatial and temporal control of chromosome duplication and segregation is crucial for proper cell division. While this process is well studied in eukaryotic and some prokaryotic organisms, relatively little is known about it in prokaryotic polyploids such as Synechococcus elongatus PCC 7942, which is known to possess one to eight copies of its single chromosome. Using a fluorescent repressor-operator system, S. elongatus chromosomes and chromosome replication forks were tagged and visualized. We found that chromosomal duplication is asynchronous and that the total number of chromosomes is correlated with cell length. Thus, replication is independent of cell cycle and coupled to cell growth. Replication events occur in a spatially random fashion. However, once assembled, replisomes move in a constrained manner. On the other hand, we found that segregation displays a striking spatial organization in some cells. Chromosomes transiently align along the major axis of the cell and timing of alignment was correlated to cell division. This mechanism likely contributes to the non-random segregation of chromosome copies to daughter cells.

Bacterial microcompartments are proteinaceous complexes that catalyze metabolic pathways in a manner reminiscent of organelles. Although microcompartment structure is well understood, much less is known about their assembly and function in vivo. We show here that carboxysomes, CO2-fixing microcompartments encoded by 10 genes, can be heterologously produced in Escherichia coli. Expression of carboxysomes in E. coli resulted in the production of icosahedral complexes similar to those from the native host. In vivo, the complexes were capable of both assembling with carboxysomal proteins and fixing CO2. Characterization of purified synthetic carboxysomes indicated that they were well formed in structure, contained the expected molecular components, and were capable of fixing CO2 in vitro. In addition, we verify association of the postulated pore-forming protein CsoS1D with the carboxysome and show how it may modulate function. We have developed a genetic system capable of producing modular carbon-fixing microcompartments in a heterologous host. In doing so, we lay the groundwork for understanding these elaborate protein complexes and for the synthetic biological engineering of self-assembling molecular structures.

Cyanobacterial carbon fixation is a major component of the global carbon cycle. This process requires the carboxysome, an organelle-like proteinaceous microcompartment that sequesters the enzymes of carbon fixation from the cytoplasm. Here, fluorescently tagged carboxysomes were found to be spatially ordered in a linear fashion. As a consequence, cells undergoing division evenly segregated carboxysomes in a nonrandom process. Mutation of the cytoskeletal protein ParA specifically disrupted carboxysome order, promoted random carboxysome segregation during cell division, and impaired carbon fixation after disparate partitioning. Thus, cyanobacteria use the cytoskeleton to control the spatial arrangement of carboxysomes and to optimize the metabolic process of carbon fixation.