Neural and Molecular Mechanisms of Biological Embedding of Social Interactions.

Animals operate in complex environments, and salient social information is encoded in the nervous system and then processed to initiate adaptive behavior. This encoding involves biological embedding, the process by which social experience affects the brain to influence future behavior. Biological embedding is an important conceptual framework for understanding social decision-making in the brain, as it encompasses multiple levels of organization that regulate how information is encoded and used to modify behavior. The framework we emphasize here is that social stimuli provoke short-term changes in neural activity that lead to changes in gene expression on longer timescales. This process, simplified-neurons are for today and genes are for tomorrow-enables the assessment of the valence of a social interaction, an appropriate and rapid response, and subsequent modification of neural circuitry to change future behavioral inclinations in anticipation of environmental changes. We review recent research on the neural and molecular basis of biological embedding in the context of social interactions, with a special focus on the honeybee.

The genomic case against genetic determinism.

Animal studies reveal that the molecular wiring of the brain can be altered by heredity, the environment, and their interaction. A deeper molecular understanding of these interactions could be a potent antidote to societal concerns of genetic determinism for human behavior, but this requires a paradigm that extends beyond traditional genome-wide association study (GWAS).

Behavioral genetics and genomics: Mendel's peas, mice, and bees.

The question of the heritability of behavior has been of long fascination to scientists and the broader public. It is now widely accepted that most behavioral variation has a genetic component, although the degree of genetic influence differs widely across behaviors. Starting with Mendel's remarkable discovery of "inheritance factors," it has become increasingly clear that specific genetic variants that influence behavior can be identified. This goal is not without its challenges: Unlike pea morphology, most natural behavioral variation has a complex genetic architecture. However, we can now apply powerful genome-wide approaches to connect variation in DNA to variation in behavior as well as analyses of behaviorally related variation in brain gene expression, which together have provided insights into both the genetic mechanisms underlying behavior and the dynamic relationship between genes and behavior, respectively, in a wide range of species and for a diversity of behaviors. Here, we focus on two systems to illustrate both of these approaches: the genetic basis of burrowing in deer mice and transcriptomic analyses of division of labor in honey bees. Finally, we discuss the troubled relationship between the field of behavioral genetics and eugenics, which reminds us that we must be cautious about how we discuss and contextualize the connections between genes and behavior, especially in humans.

Epigenetic MRI: Noninvasive imaging of DNA methylation in the brain.

Both neuronal and genetic mechanisms regulate brain function. While there are excellent methods to study neuronal activity in vivo, there are no nondestructive methods to measure global gene expression in living brains. Here, we present a method, epigenetic MRI (eMRI), that overcomes this limitation via direct imaging of DNA methylation, a major gene-expression regulator. eMRI exploits the methionine metabolic pathways for DNA methylation to label genomic DNA through 13C-enriched diets. A 13C magnetic resonance spectroscopic imaging method then maps the spatial distribution of labeled DNA. We validated eMRI using pigs, whose brains have stronger similarity to humans in volume and anatomy than rodents, and confirmed efficient 13C-labeling of brain DNA. We also discovered strong regional differences in global DNA methylation. Just as functional MRI measurements of regional neuronal activity have had a transformational effect on neuroscience, we expect that the eMRI signal, both as a measure of regional epigenetic activity and as a possible surrogate for regional gene expression, will enable many new investigations of human brain function, behavior, and disease.

Why sequence all eukaryotes?

Life on Earth has evolved from initial simplicity to the astounding complexity we experience today. Bacteria and archaea have largely excelled in metabolic diversification, but eukaryotes additionally display abundant morphological innovation. How have these innovations come about and what constraints are there on the origins of novelty and the continuing maintenance of biodiversity on Earth? The history of life and the code for the working parts of cells and systems are written in the genome. The Earth BioGenome Project has proposed that the genomes of all extant, named eukaryotes-about 2 million species-should be sequenced to high quality to produce a digital library of life on Earth, beginning with strategic phylogenetic, ecological, and high-impact priorities. Here we discuss why we should sequence all eukaryotic species, not just a representative few scattered across the many branches of the tree of life. We suggest that many questions of evolutionary and ecological significance will only be addressable when whole-genome data representing divergences at all of the branchings in the tree of life or all species in natural ecosystems are available. We envisage that a genomic tree of life will foster understanding of the ongoing processes of speciation, adaptation, and organismal dependencies within entire ecosystems. These explorations will resolve long-standing problems in phylogenetics, evolution, ecology, conservation, agriculture, bioindustry, and medicine.

The genomic basis of evolutionary differentiation among honey bees.

In contrast to the western honey bee, Apis mellifera, other honey bee species have been largely neglected despite their importance and diversity. The genetic basis of the evolutionary diversification of honey bees remains largely unknown. Here, we provide a genome-wide comparison of three honey bee species, each representing one of the three subgenera of honey bees, namely the dwarf (Apis florea), giant (A. dorsata), and cavity-nesting (A. mellifera) honey bees with bumblebees as an outgroup. Our analyses resolve the phylogeny of honey bees with the dwarf honey bees diverging first. We find that evolution of increased eusocial complexity in Apis proceeds via increases in the complexity of gene regulation, which is in agreement with previous studies. However, this process seems to be related to pathways other than transcriptional control. Positive selection patterns across Apis reveal a trade-off between maintaining genome stability and generating genetic diversity, with a rapidly evolving piRNA pathway leading to genomes depleted of transposable elements, and a rapidly evolving DNA repair pathway associated with high recombination rates in all Apis species. Diversification within Apis is accompanied by positive selection in several genes whose putative functions present candidate mechanisms for lineage-specific adaptations, such as migration, immunity, and nesting behavior.

Effects of microRNA-305 knockdown on brain gene expression associated with division of labor in honey bee colonies (Apis mellifera).

Division of labor in honey bee colonies is based on the behavioral maturation of adult workers that involves a transition from working in the hive to foraging. This behavioral maturation is associated with distinct task-related transcriptomic profiles in the brain and abdominal fat body that are related to multiple regulatory factors including juvenile hormone (JH) and queen mandibular pheromone (QMP). A prominent physiological feature associated with behavioral maturation is a loss of abdominal lipid mass as bees transition to foraging. We used transcriptomic and physiological analyses to study whether microRNAs (miRNAs) are involved in the regulation of division of labor. We first identified two miRNAs that showed patterns of expression associated with behavioral maturation, ame-miR-305-5p and ame-miR-375-3p. We then downregulated the expression of these two miRNAs with sequence-specific antagomirs. Neither ame-miR-305-5p nor ame-miR-375-3p knockdown in the abdomen affected abdominal lipid mass on their own. Similarly, knockdown of ame-miR-305-5p in combination with JH or QMP also did not affect lipid mass. By contrast, ame-miR-305-5p knockdown in the abdomen caused substantial changes in gene expression in the brain. Brain gene expression changes included genes encoding transcription factors previously implicated in behavioral maturation. The results of these functional genomic experiments extend previous correlative associations of microRNAs with honey bee division of labor and point to specific roles for ame-miR-305-5p.

Genes and environments, development and time.

A now substantial body of science implicates a dynamic interplay between genetic and environmental variation in the development of individual differences in behavior and health. Such outcomes are affected by molecular, often epigenetic, processes involving gene-environment (G-E) interplay that can influence gene expression. Early environments with exposures to poverty, chronic adversities, and acutely stressful events have been linked to maladaptive development and compromised health and behavior. Genetic differences can impart either enhanced or blunted susceptibility to the effects of such pathogenic environments. However, largely missing from present discourse regarding G-E interplay is the role of time, a "third factor" guiding the emergence of complex developmental endpoints across different scales of time. Trajectories of development increasingly appear best accounted for by a complex, dynamic interchange among the highly linked elements of genes, contexts, and time at multiple scales, including neurobiological (minutes to milliseconds), genomic (hours to minutes), developmental (years and months), and evolutionary (centuries and millennia) time. This special issue of PNAS thus explores time and timing among G-E transactions: The importance of timing and timescales in plasticity and critical periods of brain development; epigenetics and the molecular underpinnings of biologically embedded experience; the encoding of experience across time and biological levels of organization; and gene-regulatory networks in behavior and development and their linkages to neuronal networks. Taken together, the collection of papers offers perspectives on how G-E interplay operates contingently within and against a backdrop of time and timescales.

Individual variations lead to universal and cross-species patterns of social behavior.

The duration of interaction events in a society is a fundamental measure of its collective nature and potentially reflects variability in individual behavior. Here we performed a high-throughput measurement of trophallaxis and face-to-face event durations experienced by a colony of honeybees over their entire lifetimes. The interaction time distribution is heavy-tailed, as previously reported for human face-to-face interactions. We developed a theory of pair interactions that takes into account individual variability and predicts the scaling behavior for both bee and extant human datasets. The individual variability of worker honeybees was nonzero but less than that of humans, possibly reflecting their greater genetic relatedness. Our work shows how individual differences can lead to universal patterns of behavior that transcend species and specific mechanisms for social interactions.

Honey bee virus causes context-dependent changes in host social behavior.

Anthropogenic changes create evolutionarily novel environments that present opportunities for emerging diseases, potentially changing the balance between host and pathogen. Honey bees provide essential pollination services, but intensification and globalization of honey bee management has coincided with increased pathogen pressure, primarily due to a parasitic mite/virus complex. Here, we investigated how honey bee individual and group phenotypes are altered by a virus of concern, Israeli acute paralysis virus (IAPV). Using automated and manual behavioral monitoring of IAPV-inoculated individuals, we find evidence for pathogen manipulation of worker behavior by IAPV, and reveal that this effect depends on social context; that is, within versus between colony interactions. Experimental inoculation reduced social contacts between honey bee colony members, suggesting an adaptive host social immune response to diminish transmission. Parallel analyses with double-stranded RNA (dsRNA)-immunostimulated bees revealed these behaviors are part of a generalized social immune defensive response. Conversely, inoculated bees presented to groups of bees from other colonies experienced reduced aggression compared with dsRNA-immunostimulated bees, facilitating entry into susceptible colonies. This reduction was associated with a shift in cuticular hydrocarbons, the chemical signatures used by bees to discriminate colony members from intruders. These responses were specific to IAPV infection, suggestive of pathogen manipulation of the host. Emerging bee pathogens may thus shape host phenotypes to increase transmission, a strategy especially well-suited to the unnaturally high colony densities of modern apiculture. These findings demonstrate how anthropogenic changes could affect arms races between human-managed hosts and their pathogens to potentially affect global food security.

Genomic regions influencing aggressive behavior in honey bees are defined by colony allele frequencies.

For social animals, the genotypes of group members affect the social environment, and thus individual behavior, often indirectly. We used genome-wide association studies (GWAS) to determine the influence of individual vs. group genotypes on aggression in honey bees. Aggression in honey bees arises from the coordinated actions of colony members, primarily nonreproductive "soldier" bees, and thus, experiences evolutionary selection at the colony level. Here, we show that individual behavior is influenced by colony environment, which in turn, is shaped by allele frequency within colonies. Using a population with a range of aggression, we sequenced individual whole genomes and looked for genotype-behavior associations within colonies in a common environment. There were no significant correlations between individual aggression and specific alleles. By contrast, we found strong correlations between colony aggression and the frequencies of specific alleles within colonies, despite a small number of colonies. Associations at the colony level were highly significant and were very similar among both soldiers and foragers, but they covaried with one another. One strongly significant association peak, containing an ortholog of the Drosophila sensory gene dpr4 on linkage group (chromosome) 7, showed strong signals of both selection and admixture during the evolution of gentleness in a honey bee population. We thus found links between colony genetics and group behavior and also, molecular evidence for group-level selection, acting at the colony level. We conclude that group genetics dominates individual genetics in determining the fatal decision of honey bees to sting.

Behavior-related gene regulatory networks: A new level of organization in the brain.

Neuronal networks are the standard heuristic model today for describing brain activity associated with animal behavior. Recent studies have revealed an extensive role for a completely distinct layer of networked activities in the brain-the gene regulatory network (GRN)-that orchestrates expression levels of hundreds to thousands of genes in a behavior-related manner. We examine emerging insights into the relationships between these two types of networks and discuss their interplay in spatial as well as temporal dimensions, across multiple scales of organization. We discuss properties expected of behavior-related GRNs by drawing inspiration from the rich literature on GRNs related to animal development, comparing and contrasting these two broad classes of GRNs as they relate to their respective phenotypic manifestations. Developmental GRNs also represent a third layer of network biology, playing out over a third timescale, which is believed to play a crucial mediatory role between neuronal networks and behavioral GRNs. We end with a special emphasis on social behavior, discuss whether unique GRN organization and cis-regulatory architecture underlies this special class of behavior, and review literature that suggests an affirmative answer.

Context-dependent influence of threat on honey bee social network dynamics and brain gene expression.

Adverse social experience affects social structure by modifying the behavior of individuals, but the relationship between an individual's behavioral state and its response to adversity is poorly understood. We leveraged naturally occurring division of labor in honey bees and studied the biological embedding of environmental threat using laboratory assays and automated behavioral tracking of whole colonies. Guard bees showed low intrinsic levels of sociability compared with foragers and nurse bees, but large increases in sociability following exposure to a threat. Threat experience also modified the expression of caregiving-related genes in a brain region called the mushroom bodies. These results demonstrate that the biological embedding of environmental experience depends on an individual's societal role and, in turn, affects its future sociability.

Neurodevelopmental and transcriptomic effects of CRISPR/Cas9-induced somatic orco mutation in honey bees.

In insects, odorant receptors facilitate olfactory communication and require the functionality of the highly conserved co-receptor gene orco. Genome editing studies in a few species of ants and moths have revealed that orco can also have a neurodevelopmental function, in addition to its canonical role in adult olfaction, discovered first in Drosophila melanogaster. To extend this analysis, we determined whether orco mutations also affect the development of the adult brain of the honey bee Apis mellifera, an important model system for social behavior and chemical communication. We used CRISPR/Cas9 to knock out orco and examined anatomical and molecular consequences. To increase efficiency, we coupled embryo microinjection with a laboratory egg collection and in vitro rearing system. This new workflow advances genomic engineering technologies in honey bees by overcoming restrictions associated with field studies. We used Sanger sequencing to quickly select individuals with complete orco knockout for neuroanatomical analyses and later validated and described the mutations with amplicon sequencing. Mutant bees had significantly fewer glomeruli, smaller total volume of all the glomeruli, and higher mean individual glomerulus volume in the antennal lobe compared to wild-type controls. RNA-Sequencing revealed that orco knockout also caused differential expression of hundreds of genes in the antenna, including genes related to neural development and genes encoding odorant receptors. The expression of other types of chemoreceptor genes was generally unaffected, reflecting specificity of CRISPR activity in this study. These results suggest that neurodevelopmental effects of orco are related to specific insect life histories.

Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks.

Social networks mediate the spread of information and disease. The dynamics of spreading depends, among other factors, on the distribution of times between successive contacts in the network. Heavy-tailed (bursty) time distributions are characteristic of human communication networks, including face-to-face contacts and electronic communication via mobile phone calls, email, and internet communities. Burstiness has been cited as a possible cause for slow spreading in these networks relative to a randomized reference network. However, it is not known whether burstiness is an epiphenomenon of human-specific patterns of communication. Moreover, theory predicts that fast, bursty communication networks should also exist. Here, we present a high-throughput technology for automated monitoring of social interactions of individual honeybees and the analysis of a rich and detailed dataset consisting of more than 1.2 million interactions in five honeybee colonies. We find that bees, like humans, also interact in bursts but that spreading is significantly faster than in a randomized reference network and remains so even after an experimental demographic perturbation. Thus, while burstiness may be an intrinsic property of social interactions, it does not always inhibit spreading in real-world communication networks. We anticipate that these results will inform future models of large-scale social organization and information and disease transmission, and may impact health management of threatened honeybee populations.

Earth BioGenome Project: Sequencing life for the future of life.

Increasing our understanding of Earth's biodiversity and responsibly stewarding its resources are among the most crucial scientific and social challenges of the new millennium. These challenges require fundamental new knowledge of the organization, evolution, functions, and interactions among millions of the planet's organisms. Herein, we present a perspective on the Earth BioGenome Project (EBP), a moonshot for biology that aims to sequence, catalog, and characterize the genomes of all of Earth's eukaryotic biodiversity over a period of 10 years. The outcomes of the EBP will inform a broad range of major issues facing humanity, such as the impact of climate change on biodiversity, the conservation of endangered species and ecosystems, and the preservation and enhancement of ecosystem services. We describe hurdles that the project faces, including data-sharing policies that ensure a permanent, freely available resource for future scientific discovery while respecting access and benefit sharing guidelines of the Nagoya Protocol. We also describe scientific and organizational challenges in executing such an ambitious project, and the structure proposed to achieve the project's goals. The far-reaching potential benefits of creating an open digital repository of genomic information for life on Earth can be realized only by a coordinated international effort.

Understanding the relationship between brain gene expression and social behavior: lessons from the honey bee.

Behavior is a complex phenotype that is plastic and evolutionarily labile. The advent of genomics has revolutionized the field of behavioral genetics by providing tools to quantify the dynamic nature of brain gene expression in relation to behavioral output. The honey bee Apis mellifera provides an excellent platform for investigating the relationship between brain gene expression and behavior given both the remarkable behavioral repertoire expressed by members of its intricate society and the degree to which behavior is influenced by heredity and the social environment. Here, we review a linked series of studies that assayed changes in honey bee brain transcriptomes associated with natural and experimentally induced changes in behavioral state. These experiments demonstrate that brain gene expression is closely linked with behavior, that changes in brain gene expression mediate changes in behavior, and that the association between specific genes and behavior exists over multiple timescales, from physiological to evolutionary.

Juvenile hormone regulates brain-reproduction tradeoff in bumble bees but not in honey bees.

Gonadotropic hormones coordinate processes in diverse tissues regulating animal reproductive physiology and behavior. Juvenile hormone (JH) is the ancient and most common gonadotropin in insects, but not in advanced eusocial honey bees and some ants. To start probing the evolutionary basis of this change, we combined endocrine manipulations, transcriptomics, and behavioral analyses to study JH regulated processes in a bumble bee showing a relatively simple level of eusociality. We found that in worker fat body, more JH-regulated genes were up- rather than down-regulated, and enriched for metabolic and biosynthetic pathways. This transcriptomic pattern is consistent with earlier evidence that JH is the major gonadotropin in bumble bees. In the brain, more JH-regulated genes were down- rather than up-regulated and enriched for protein turnover pathways. Brain ribosomal protein gene expression shows a similar trend of downregulation in dominant workers, which naturally have high JH titers. In other species, similar downregulation of protein turnover is found in aging brains or under stress, associated with compromised long-term memory and health. These findings suggest a previously unknown gonadotropin-mediated tradeoff. Analysis of published data reveals no such downregulation of protein turnover pathways in the brain of honey bee workers, which exhibit more complex eusociality and in which JH is not a gonadotropin but rather regulates division of labor. These results suggest that the evolution of complex eusociality in honey bees was associated with modifications in hormonal signalling supporting extended and extremely high fertility while reducing the ancient costs of high gonadotropin titers to the brain.

Deep evolutionary conservation of autism-related genes.

E. O. Wilson proposed in Sociobiology that similarities between human and animal societies reflect common mechanistic and evolutionary roots. When introduced in 1975, this controversial hypothesis was beyond science's ability to test. We used genomic analyses to determine whether superficial behavioral similarities in humans and the highly social honey bee reflect common molecular mechanisms. Here, we report that gene expression signatures for individual bees unresponsive to various salient social stimuli are significantly enriched for autism spectrum disorder-related genes. These signatures occur in the mushroom bodies, a high-level integration center of the insect brain. Furthermore, our finding of enrichment was unique to autism spectrum disorders; brain gene expression signatures from other honey bee behaviors do not show this enrichment, nor do datasets from other human behavioral and health conditions. These results demonstrate deep conservation for genes associated with a human social pathology and individual differences in insect social behavior, thus providing an example of how comparative genomics can be used to test sociobiological theory.

A hybrid de novo genome assembly of the honeybee, Apis mellifera, with chromosome-length scaffolds.

BACKGROUND: The ability to generate long sequencing reads and access long-range linkage information is revolutionizing the quality and completeness of genome assemblies. Here we use a hybrid approach that combines data from four genome sequencing and mapping technologies to generate a new genome assembly of the honeybee Apis mellifera. We first generated contigs based on PacBio sequencing libraries, which were then merged with linked-read 10x Chromium data followed by scaffolding using a BioNano optical genome map and a Hi-C chromatin interaction map, complemented by a genetic linkage map. RESULTS: Each of the assembly steps reduced the number of gaps and incorporated a substantial amount of additional sequence into scaffolds. The new assembly (Amel_HAv3) is significantly more contiguous and complete than the previous one (Amel_4.5), based mainly on Sanger sequencing reads. N50 of contigs is 120-fold higher (5.381 Mbp compared to 0.053 Mbp) and we anchor > 98% of the sequence to chromosomes. All of the 16 chromosomes are represented as single scaffolds with an average of three sequence gaps per chromosome. The improvements are largely due to the inclusion of repetitive sequence that was unplaced in previous assemblies. In particular, our assembly is highly contiguous across centromeres and telomeres and includes hundreds of AvaI and AluI repeats associated with these features. CONCLUSIONS: The improved assembly will be of utility for refining gene models, studying genome function, mapping functional genetic variation, identification of structural variants, and comparative genomics.