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The past decade of social insect research has seen rapid development in automated behavioral tracking and molecular profiling of the nervous system, two distinct but complementary lines of inquiry into phenotypic variation across individuals, colonies, populations, and species. These experimental strategies have developed largely in parallel, as automated tracking generates a continuous stream of behavioral data while, in contrast, 'omics-based profiling provides a single "snapshot" of the brain. Better integration of these approaches applied to studying variation in social behavior will reveal the underlying genetic and neurobiological mechanisms that shape the evolution and diversification of social life. In this review, we discuss relevant advances in both fields and propose new strategies to better elucidate the molecular and behavioral innovations that generate social life.

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The evolution of eusociality in Hymenoptera-encompassing bees, ants, and wasps-is characterized by multiple gains and losses of social living, making this group a prime model to understand the mechanisms that underlie social behavior and social complexity. Our review synthesizes insights into the evolutionary history and molecular basis of eusociality. We examine new evidence for key evolutionary hypotheses and molecular pathways that regulate social behaviors, highlighting convergent evolution on a shared molecular toolkit that includes the insulin/insulin-like growth factor signaling (IIS) and target of rapamycin (TOR) pathways, juvenile hormone and ecdysteroid signaling, and epigenetic regulation. We emphasize how the crosstalk among these nutrient-sensing and endocrine signaling pathways enables social insects to integrate external environmental stimuli, including social cues, with internal physiology and behavior. We argue that examining these pathways as an integrated regulatory circuit and exploring how the regulatory architecture of this circuit evolves alongside eusociality can open the door to understanding the origin of the complex life histories and behaviors of this group.

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Season length and its associated variables can influence the expression of social behaviors, including the occurrence of eusociality in insects. Eusociality can vary widely across environmental gradients, both within and between different species. Numerous theoretical models have been developed to examine the life history traits that underlie the emergence and maintenance of eusociality, yet the impact of seasonality on this process is largely uncharacterized. Here, we present a theoretical model that incorporates season length and offspring development time into a single, individual-focused model to examine how these factors can shape the costs and benefits of social living. We find that longer season lengths and faster brood development times are sufficient to favor the emergence and maintenance of a social strategy, while shorter seasons favor a solitary one. We also identify a range of season lengths where social and solitary strategies can coexist. Moreover, our theoretical predictions are well-matched to the natural history and behavior of two flexibly-eusocial bee species, suggesting our model can make realistic predictions about the evolution of different social strategies. Broadly, this work reveals the crucial role that environmental conditions can have in shaping social behavior and its evolution and underscores the need for further models that explicitly incorporate such variation to study evolutionary trajectories of eusociality.

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Natural variation can provide important insights into the genetic and environmental factors that shape social behaviour and its evolution. The sweat bee, Lasioglossum baleicum, is a socially flexible bee capable of producing both solitary and eusocial nests. We demonstrate that within a single nesting aggregation, soil temperatures are a strong predictor of the social structure of nests. Sites with warmer temperatures in the spring have a higher frequency of social nests than cooler sites, perhaps because warmer temperatures provide a longer reproductive window for those nests. To identify the molecular correlates of this behavioural variation, we generated a de novo genome assembly for L. baleicum, and we used transcriptomic profiling to compare adults and developing offspring from eusocial and solitary nests. We find that adult, reproductive females have similar expression profiles regardless of social structure in the nest, but that there are strong differences between reproductive females and workers from social nests. We also find substantial differences in the transcriptomic profiles of stage-matched pupae from warmer, social-biased sites compared to cooler, solitary-biased sites. These transcriptional differences are strongly predictive of adult reproductive state, suggesting that the developmental environment may set the stage for adult behaviours in L. baleicum. Together, our results help to characterize the molecular mechanisms shaping variation in social behaviour and highlight a potential role of environmental tuning during development as a factor shaping adult behaviour and physiology in this socially flexible bee.

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Here, we reveal an unanticipated role of the blood-brain barrier (BBB) in regulating complex social behavior in ants. Using scRNA-seq, we find localization in the BBB of a key hormone-degrading enzyme called juvenile hormone esterase (Jhe), and we show that this localization governs the level of juvenile hormone (JH3) entering the brain. Manipulation of the Jhe level reprograms the brain transcriptome between ant castes. Although ant Jhe is retained and functions intracellularly within the BBB, we show that Drosophila Jhe is naturally extracellular. Heterologous expression of ant Jhe into the Drosophila BBB alters behavior in fly to mimic what is seen in ants. Most strikingly, manipulation of Jhe levels in ants reprograms complex behavior between worker castes. Our study thus uncovers a remarkable, potentially conserved role of the BBB serving as a molecular gatekeeper for a neurohormonal pathway that regulates social behavior.

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Natural variation can provide important insights into the genetic and environmental factors that shape social behavior and its evolution. The sweat bee, Lasioglossum baleicum , is a socially flexible bee capable of producing both solitary and eusocial nests. We demonstrate that within a single nesting aggregation, soil temperatures are a strong predictor of the social structure of nests. Sites with warmer temperatures in the spring have a higher frequency of social nests than cooler sites, perhaps because warmer temperatures provide a longer reproductive window for those nests. To identify the molecular correlates of this behavioral variation, we generated a de novo genome assembly for L. baleicum , and we used transcriptomic profiling to compare adults and developing offspring from eusocial and solitary nests. We find that adult, reproductive females have similar expression profiles regardless of social structure in the nest, but that there are strong differences between reproductive females and workers from social nests. We also find substantial differences in the transcriptomic profiles of stage-matched pupae from warmer, social-biased sites compared to cooler, solitary-biased sites. These transcriptional differences are strongly predictive of adult reproductive state, suggesting that the developmental environment may set the stage for adult behaviors in L. baleicum . Together, our results help to characterize the molecular mechanisms shaping variation in social behavior and highlight a potential role of environmental tuning during development as a factor shaping adult behavior and physiology in this socially flexible bee.

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Sweat bees have repeatedly gained and lost eusociality, a transition from individual to group reproduction. Here we generate chromosome-length genome assemblies for 17 species and identify genomic signatures of evolutionary trade-offs associated with transitions between social and solitary living. Both young genes and regulatory regions show enrichment for these molecular patterns. We also identify loci that show evidence of complementary signals of positive and relaxed selection linked specifically to the convergent gains and losses of eusociality in sweat bees. This includes two pleiotropic proteins that bind and transport juvenile hormone (JH)-a key regulator of insect development and reproduction. We find that one of these proteins is primarily expressed in subperineurial glial cells that form the insect blood-brain barrier and that brain levels of JH vary by sociality. Our findings are consistent with a role of JH in modulating social behaviour and suggest that eusocial evolution was facilitated by alteration of the proteins that bind and transport JH, revealing how an ancestral developmental hormone may have been co-opted during one of life's major transitions. More broadly, our results highlight how evolutionary trade-offs have structured the molecular basis of eusociality in these bees and demonstrate how both directional selection and release from constraint can shape trait evolution.

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1. Significant advances in computational ethology have allowed the quantification of behaviour in unprecedented detail. Tracking animals in social groups, however, remains challenging as most existing methods can either capture pose or robustly retain individual identity over time but not both. 2. To capture finely resolved behaviours while maintaining individual identity, we built NAPS (NAPS is ArUco Plus SLEAP), a hybrid tracking framework that combines state-of-the-art, deep learning-based methods for pose estimation (SLEAP) with unique markers for identity persistence (ArUco). We show that this framework allows the exploration of the social dynamics of the common eastern bumblebee (Bombus impatiens). 3. We provide a stand-alone Python package for implementing this framework along with detailed documentation to allow for easy utilization and expansion. We show that NAPS can scale to long timescale experiments at a high frame rate and that it enables the investigation of detailed behavioural variation within individuals in a group. 4. Expanding the toolkit for capturing the constituent behaviours of social groups is essential for understanding the structure and dynamics of social networks. NAPS provides a key tool for capturing these behaviours and can provide critical data for understanding how individual variation influences collective dynamics.

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Social isolation, particularly in early life, leads to deleterious physiological and behavioral outcomes. Here, we leverage new high-throughput tools to comprehensively investigate the impact of isolation in the bumblebee, Bombus impatiens, from behavioral, molecular, and neuroanatomical perspectives. We reared newly emerged bumblebees in complete isolation, in small groups, or in their natal colony, and then analyzed their behaviors while alone or paired with another bee. We find that when alone, individuals of each rearing condition show distinct behavioral signatures. When paired with a conspecific, bees reared in small groups or in the natal colony express similar behavioral profiles. Isolated bees, however, showed increased social interactions. To identify the neurobiological correlates of these differences, we quantified brain gene expression and measured the volumes of key brain regions for a subset of individuals from each rearing condition. Overall, we find that isolation increases social interactions and disrupts gene expression and brain development. Limited social experience in small groups is sufficient to preserve typical patterns of brain development and social behavior.

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The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimation in individual animals, extending these to multiple animals presents unique challenges for studies of social behaviors or animals in their natural environments. Here we present Social LEAP Estimates Animal Poses (SLEAP), a machine learning system for multi-animal pose tracking. This system enables versatile workflows for data labeling, model training and inference on previously unseen data. SLEAP features an accessible graphical user interface, a standardized data model, a reproducible configuration system, over 30 model architectures, two approaches to part grouping and two approaches to identity tracking. We applied SLEAP to seven datasets across flies, bees, mice and gerbils to systematically evaluate each approach and architecture, and we compare it with other existing approaches. SLEAP achieves greater accuracy and speeds of more than 800 frames per second, with latencies of less than 3.5 ms at full 1,024 × 1,024 image resolution. This makes SLEAP usable for real-time applications, which we demonstrate by controlling the behavior of one animal on the basis of the tracking and detection of social interactions with another animal.

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The evolutionary origins of eusociality represent increases in complexity from individual to caste-based, group reproduction. These behavioural transitions have been hypothesized to go hand in hand with an increased ability to regulate when and where genes are expressed. Bees have convergently evolved eusociality up to five times, providing a framework to test this hypothesis. To examine potential links between putative gene regulatory elements and social evolution, we compare alignable, non-coding sequences in 11 diverse bee species, encompassing three independent origins of reproductive division of labour and two elaborations of eusocial complexity. We find that rates of evolution in a number of non-coding sequences correlate with key social transitions in bees. Interestingly, while we find little evidence for convergent rate changes associated with independent origins of social behaviour, a number of molecular pathways exhibit convergent rate changes in conjunction with subsequent elaborations of social organization. We also present evidence that many novel non-coding regions may have been recruited alongside the origin of sociality in corbiculate bees; these loci could represent gene regulatory elements associated with division of labour within this group. Thus, our findings are consistent with the hypothesis that gene regulatory innovations are associated with the evolution of eusociality and illustrate how a thorough examination of both coding and non-coding sequence can provide a more complete understanding of the molecular mechanisms underlying behavioural evolution. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.

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The emergence of eusociality represents a major evolutionary transition from solitary to group reproduction. The most commonly studied eusocial species, honey bees and ants, represent the behavioral extremes of social evolution but lack close relatives that are non-social. Unlike these species, the halictid bee Lasioglossum albipes produces both solitary and eusocial nests and this intraspecific variation has a genetic basis. Here, we identify genetic variants associated with this polymorphism, including one located in the intron of syntaxin 1a (syx1a), a gene that mediates synaptic vesicle release. We show that this variant can alter gene expression in a pattern consistent with differences between social and solitary bees. Surprisingly, syx1a and several other genes associated with sociality in L. albipes have also been implicated in autism spectrum disorder in humans. Thus, genes underlying behavioral variation in L. albipes may also shape social behaviors across a wide range of taxa, including humans.

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Social interactions can facilitate transmission of microbes between individuals, reducing variation in gut communities within social groups. Thus, the evolution of social behaviours and symbiont community composition have the potential to be tightly linked. We explored this connection by characterizing the diversity of bacteria associated with both eusocial and solitary bee species within the behaviourally variable family Halictidae using 16S amplicon sequencing. Contrary to expectations, we found few differences in bacterial abundance or variation between social forms; most halictid species appear to share similar gut bacterial communities. However, several strains of Sodalis, a genus described as a symbiont in a variety of insects but yet to be characterized in bees, differ in abundance between eusocial and solitary bees. Phylogenetic reconstructions based on whole-genome alignments indicate that Sodalis has independently colonized halictids at least three times. These strains appear to be mutually exclusive within individual bees, although they are not host-species-specific and no signatures of vertical transmission were observed, suggesting that Sodalis strains compete for access to hosts. The symbiosis between halictids and Sodalis therefore appears to be in its early stages.

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Bee viral ecology is a fascinating emerging area of research: viruses exert a range of effects on their hosts, exacerbate impacts of other environmental stressors, and, importantly, are readily shared across multiple bee species in a community. However, our understanding of bee viral communities is limited, as it is primarily derived from studies of North American and European Apis mellifera populations. Here, we examined viruses in populations of A. mellifera and 11 other bee species from 9 countries, across 4 continents and Oceania. We developed a novel pipeline to rapidly and inexpensively screen for bee viruses. This pipeline includes purification of encapsulated RNA/DNA viruses, sequence-independent amplification, high throughput sequencing, integrated assembly of contigs, and filtering to identify contigs specifically corresponding to viral sequences. We identified sequences for (+)ssRNA, (-)ssRNA, dsRNA, and ssDNA viruses. Overall, we found 127 contigs corresponding to novel viruses (i.e. previously not observed in bees), with 27 represented by >0.1% of the reads in a given sample, and 7 contained an RdRp or replicase sequence which could be used for robust phylogenetic analysis. This study provides a sequence-independent pipeline for viral metagenomics analysis, and greatly expands our understanding of the diversity of viruses found in bee communities.

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The original version of the Article contained incorrect citation information in reference 67. The reference should read "Russell, A. L., Morrison, S. J., Moschonas, E. H. & Papaj, D. R. Patterns of pollen and nectar foraging specialization by bumblebees over multiple timescales using RFID. Sci. Rep. 7, 1-13 (2017)." This error has now been corrected in the PDF and HTML versions of the Article.

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Individuals in social insect colonies cooperate to perform collective work. While colonies often respond to changing environmental conditions by flexibly reallocating workers to different tasks, the factors determining which workers switch and why are not well understood. Here, we use an automated tracking system to continuously monitor nest behavior and foraging activity of uniquely identified workers from entire bumble bee (Bombus impatiens) colonies foraging in a natural outdoor environment. We show that most foraging is performed by a small number of workers and that the intensity and distribution of foraging is actively regulated at the colony level in response to forager removal. By analyzing worker nest behavior before and after forager removal, we show that spatial fidelity of workers within the nest generates uneven interaction with relevant localized information sources, and predicts which workers initiate foraging after disturbance. Our results highlight the importance of spatial fidelity for structuring information flow and regulating collective behavior in social insect colonies.

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Changes in gene regulation that underlie phenotypic evolution can be encoded directly in the DNA sequence or mediated by chromatin modifications such as DNA methylation. It has been hypothesized that the evolution of eusocial division of labor is associated with enhanced gene regulatory potential, which may include expansions in DNA methylation in the genomes of Hymenoptera (bees, ants, wasps, and sawflies). Recently, this hypothesis garnered support from analyses of a commonly used metric to estimate DNA methylation in silico, CpG content. Here, we test this hypothesis using direct, nucleotide-level measures of DNA methylation across nine species of Hymenoptera. In doing so, we generated new DNA methylomes for three species of interest, including one solitary and one facultatively eusocial halictid bee and a sawfly. We demonstrate that the strength of correlation between CpG content and DNA methylation varies widely among hymenopteran taxa, highlighting shortcomings in the utility of CpG content as a proxy for DNA methylation in comparative studies of taxa with sparse DNA methylomes. We observed strikingly high levels of DNA methylation in the sawfly relative to other investigated hymenopterans. Analyses of molecular evolution suggest the relatively distinct sawfly DNA methylome may be associated with positive selection on functional DNMT3 domains. Sawflies are an outgroup to all ants, bees, and wasps, and no sawfly species are eusocial. We find no evidence that either global expansions or variation within individual ortholog groups in DNA methylation are consistently associated with the evolution of social behavior.

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