Biology subjects

Robinson, G. E.

Publications and source records attributed to Robinson, G. E..

14 recordsLinked to original sources

bioRxiv2025

Host genetic background and social environment have different effects on the establishment and structure of the adult worker honey bee gut microbiota

Many studies have highlighted the importance of gut microbiomes to many aspects of host physiology. Therefore, understanding how factors, such host genetics and social environment, impact the establishment and composition of the gut microbiota can provide insight into host biological functioning. Here, we controlled the microbial inoculation of honey bees across distinct social groups, each composed of a mixture of bees from three distinct genetic backgrounds, to determine the relative effects of host genetic background and social environment on the establishment and composition of the gut microbiota. Using 16S rRNA gene sequencing, we found that host genetic background and social environment had effects on gut microbiota structure, with each influencing gut microbiota beta diversity. In addition, host genetic background and social environment each affected the abundance of different individual gut microbes. Together, these results suggest that host genetic background and social environment may play distinct roles in shaping the establishment and structure of host gut microbiota.

ecology↗

bioRxiv2025

RESCUE: recovery of idiosyncratic expression patterns in spatial transcriptomics

Spatial transcriptomics (ST) enables gene expression profiling while preserving the spatial architecture of intact tissue. Analyzing ST data often proceeds by first extracting cell-level information, typically through cell segmentation or cell-type deconvolution. However, a critical oversight has been that a substantial portion of molecular expression is systematically lost or unannotated by these methods. This lost expression can arise from diverse and biologically important sources like fragile or underrepresented cell types, subcellular structures like neurites, and extracellular expression. These omissions can result in biased analyses and incorrect or incomplete biological interpretations. We describe a new computational method, RESCUE, that can recover the unattributed spatial expression patterns missed by existing ST analysis methods and enable robust inference even when reference is incomplete. We validate RESCUE using MERFISH data from the honey bee brain and apply it to multiple ST datasets to demonstrate how it can reveal novel insights into complex tissue biology.

bioinformatics↗

bioRxiv2025

Social evolution and absence of olfactory function in larval honey bees

Social evolution made larval honey bees dependent on adult colony members for feeding. We therefore predicted they have diminished olfactory capabilities, and based on organismal resource conservation theory, also have downregulated olfactory receptor (OR) gene expression. Behavioral assays demonstrated that larvae cannot find food via olfaction and expressed very low levels of Orco, an essential gene for OR function. By contrast, larvae showed higher expression of Ir25a, an essential gene for multiple forms of sensory perception including gustation. These results suggest larvae rely on taste for feeding. In addition, considering that adult bees use OR-based olfaction extensively, they demonstrate strong developmental regulation of the OR system. Comparative transcriptomics of social and non-social insects further highlight the role of social evolution in shaping this sensory trait.

evolutionary biology↗

bioRxiv2024

Molecular analyses of individual variation in honey bee sociability

Individual variation in sociability is a central feature of every society. This includes honey bees, with some individuals well-connected and sociable, and others at the periphery of their colonys social network. However, the genetic and molecular bases of sociability are poorly understood. Trophallaxis - a behavior involving sharing liquid with nutritional and signaling properties - comprises a social interaction and a proxy for sociability in honey bee colonies: more sociable bees engage in more trophallaxis. Here we identify genetic and molecular mechanisms of trophallaxis-based sociability by combining genome sequencing, brain transcriptomics, and automated behavioral tracking. A genome-wide association study (GWAS) identified 18 single-nucleotide polymorphisms (SNPs) associated with variation in sociability. Several SNPs were localized to genes previously associated with sociability in other species, including in the context of human autism, suggesting shared molecular mechanisms of sociability. Variation in sociability also was linked to differential brain gene expression, particularly genes associated with neural signaling and development. Using comparative genomic and transcriptomic approaches, we also detected evidence for divergent mechanisms underpinning sociability across species, including those related to reward sensitivity and encounter probability. These results highlight both potential evolutionary conservation of the molecular roots of sociability and points of divergence.

genomics↗

bioRxiv2024

SpaceExpress: a method for comparative spatial transcriptomics based on intrinsic coordinate systems of tissues

Spatial transcriptomics (ST) technologies have enabled new explorations into the spatial organization of tissues and their functional implications. However, one of the most fundamental analyses - comparative analysis of spatial gene expression across phenotypes - remains a formidable challenge. We introduce SpaceExpress, a novel statistical tool for detecting phenotype-associated changes in spatial expression patterns. SpaceExpress employs a neural network to embed multiple ST samples in a common latent space, enabling robust cross-sample comparisons despite structural and technical variations. It then uses spline regression to test differential spatial expression of genes between conditions, identifying specific regions of the tissue where expression patterns diverge and quantifying the magnitude of those differences, with rigorous false discovery control and handling of multiple replicates per condition. It includes visualization tools to help interpret spatial pattern differences. We demonstrate the tools effectiveness on synthetic and real ST datasets, revealing mechanistic insights into behavior- and development-related neurogenomic changes in honey bees and mice. Our work extends the highly influential paradigm of differential gene expression analysis to spatial omics.

bioinformatics↗

bioRxiv2023

Gut microbes contribute to variation in foraging intensity in the honey bee, Apis mellifera.

Gut microbiomes are increasingly recognized for mediating diverse biological aspects of their hosts, including complex behavioral phenotypes. While many studies have reported that experimental disruptions to the gut microbiome result in atypical host behavior, studies that address how gut microbes contribute to adaptive behavioral trait variation are rare. Eusocial insects represent a powerful model to test this, due to their simple microbiomes and complex division of labor characterized by colony-level variation in behavioral phenotypes. While previous studies report correlational differences in gut microbiome associated with division of labor, here, we provide evidence that gut microbes play a causal role in defining differences in foraging behavior between honey bees. Gut microbial community structure consistently differed between hive-based nurse bees and bees that leave the hive to forage for floral resources. These differences were associated with variation in the abundance of individual microbes, including Bifidobacterium asteroides, Bombilactobacillus mellis, and Lactobacillus melliventris. Manipulations of colony demography and individual foraging experience suggested that differences in microbiome composition were associated with task experience. Moreover, single microbe inoculations with B. asteroides, B. mellis, and L. melliventris caused changes in foraging intensity. These results demonstrate that gut microbes contribute to division of labor in a social insect, and support a role of gut microbes in modulating host behavioral phenotypic variation.

animal behavior and cognition↗

bioRxiv2022

Evolution of decreased aggression in honey bees targeted brain cell gene regulatory networks

Understanding how genotypic variation results in phenotypic variation, a major challenge in biology, is especially difficult for collective behaviour because collective group phenotypes arise from complex interactions between group members1. Honeybees aggressively defend their colony from attacks with highly integrated collective behaviour in which different groups of bees play specific roles, giving rise to distinct colony-level differences in aggression. A previous genome-wide association study of a population of Africanized honeybees (Apis mellifera scutellata) from Puerto Rico that recently evolved decreased aggression identified hundreds of genes with single nucleotide polymorphisms (SNPs) that associated with colony-level variation in aggression2. Many of these SNPs also showed strong signals of selection for decreased aggression2,3, but their influence on brain function was unknown. Using brain single-cell (sc) transcriptomics and sc gene regulatory network analysis, we show here that variants of these genes give rise to genetic differences in transcription factor-target gene relationships. These differences involved the activity of several TFs, some that have been previously associated with aggression, like single stranded-binding protein c31A, and some that have been associated with tissue morphogenesis but not behaviour, like apontic. The activity of these and other TFs was located in specific brain cell populations related to olfaction and vision, the two sensory modalities that bees use in colony defence. They also implicate metabolism of serotonin, a neurochemical already known to influence honeybee aggression, but not from a genetic perspective. Surprisingly, genetic differences were more pronounced in the brains of forager bees than in similarly aged but more aggressive soldier bees, pointing to an evolutionary change in division of labour for colony defence. Our results demonstrate how group genetics can shape a collective phenotype by modulating individual brain gene regulatory network architecture.

genomics↗

bioRxiv2021

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 magnetic resonance imaging (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 novel 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 MRI measurements of regional neuronal activity have had a transformational effect on neuroscience, we expect that the eMRI signal as a surrogate for regional gene expression will enable many new investigations into the roles of gene expression in human brain function, behavior, and disease.

bioengineering↗

bioRxiv2020

Automated monitoring of animal behaviour with barcodes and convolutional neural networks

Barcode-based tracking of individuals revolutionizes the study of animal behaviour, but further progress hinges on whether specific behaviours can be monitored. We achieve this goal by combining information obtained from the barcodes with image analysis through convolutional neural networks. Applying this novel approach to a challenging test case, the honeybee hive, we reveal that food exchange among bees generates two distinct social networks with qualitatively different transmission capabilities.

systems biology↗

bioRxiv2020

Individual differences in honey bee (Apis mellifera) behavior enabled by plasticity in brain gene regulatory networks

Understanding the regulatory architecture of phenotypic variation is a fundamental goal in biology, but connections between gene regulatory network (GRN) activity and individual differences in behavior are poorly understood. We characterized the molecular basis of behavioral plasticity in queenless honey bee (Apis mellifera) colonies, where individuals engage in both reproductive and non-reproductive behaviors. Using high-throughput behavioral tracking, we discovered these colonies contain a continuum of phenotypes, with some individuals specialized for either egg-laying or foraging and "generalists" that perform both. Brain gene expression and chromatin accessibility profiles were correlated with behavioral variation, with generalists intermediate in behavior and molecular profiles. Models of brain GRNs constructed for individuals revealed that transcription factor (TF) activity was highly predictive of behavior, and behavior-associated regulatory regions had more TF motifs. These results provide new insights into the important role played by brain GRN plasticity in the regulation of behavior, with implications for social evolution.

genomics↗

bioRxiv2020

The evolution of extreme fertility defied ancestral gonadotropin mediated brain-reproduction tradeoff

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 ants. To probe the evolutionary basis of this change, we combined endocrine manipulations, transcriptomics, and behavioral analyses to study JH regulated processes in a bumble bee showing an intermediate level of sociliality. We found that in the fat body, more JH-regulated genes were upregulated and enriched for metabolic and biosynthetic pathways. This transcriptomic pattern is consistent with earlier evidence that JH is the major gonadotropin in the bumble bee. In the brain, most JH-regulated genes were downregulated and enriched for protein turnover pathways. Brain ribosomal protein gene expression was similarly downregulated 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, and is associated with compromised long-term memory and health. These findings suggest a previously unknown gonadotropin-mediated tradeoff. We did not find a similar downregulation of protein turnover pathways in the brain of honey bees in which JH is not a gonadotropin but rather regulates division of labor. These differences between JH effets in the bumble bee and in the advanced eusocial honey bee suggest that the evolution of advanced eusociality was associated with modifications in hormonal signaling supporting extended and extremely high fertility while reducing the ancient costs of high gonadotropin titers to the brain.

evolutionary biology↗

bioRxiv2018

Oculomotor nerve requires an early interaction with muscle precursors for nerve guidance and branch patterning

Muscle function is dependent on innervation by the correct motor nerves. Motor nerves are composed of motor axons that extend through peripheral tissues as a compact bundle, but then diverge to create nerve branches to specific muscle targets. A transition point typically occurs as motor nerves grow near their targets, where the fasciculated nerve halts further growth, then later initiates branching to muscles. The motor nerve transition point is potentially an intermediate target acting as a guidepost to present specific cellular and molecular signals for navigation. Here we describe the navigation of the oculomotor nerve with respect to eye muscle precursor cells in mouse embryos. We found that the oculomotor nerve initially grew to the eye three days prior to the appearance of any eye muscles. The oculomotor axons spread to form a plexus within a mass of eye muscle precursors, then the nerve growth paused for more than two days. This plexus persisted during primary extraocular myogenesis, with a subsequent phase in which the nerve branched out to specific muscles. To test the functional significance of the nerve-precursor contact in the plexus, we genetically ablated muscle precursors early in nerve development, prior to nerve contact. Ablation of muscle precursors resulted in oculomotor nerve fibers failing to stop to form the plexus, but instead growing past the eye. In contrast, ablating the precursor pool at later stages, after the nerve has contacted the precursor cells, results in ectopic branching restricted near the eye. These results demonstrate that muscle precursors act as an intermediate target for nerve guidance, and are required for the oculomotor nerve to transition between nerve growth and distinct stages of terminal axon branching.

neuroscience↗

bioRxiv2018

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

BackgroundThe 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.\n\nResultsEach 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.\n\nConclusionsThe improved assembly will be of utility for refining gene models, studying genome function, mapping functional genetic variation, identification of structural variants, and comparative genomics.

genomics↗

bioRxiv2017

Cross-species systems analyses reveal a conserved brain transcriptional response to social challenge

Social challenges like territorial intrusions evoke behavioral responses in widely diverging species. Recent work has revealed that evolutionary \"toolkits\" - genes and modules with lineage-specific variations but deep conservation of function - participate in the behavioral response to social challenge. Here, we develop a multi-species computational-experimental approach to characterize such a toolkit at a systems level. Brain transcriptomic responses to social challenge was probed via RNA-seq profiling in three diverged species - honey bees, mice, and three-spined stickleback fish - following a common methodology, allowing fair comparisons across species. Data were collected from multiple brain regions and multiple time points after social challenge exposure, achieving anatomical and temporal resolution substantially greater than previous work. We developed statistically rigorous analyses equipped to find homologous functional groups among these species at the levels of individual genes, functional and coexpressed gene modules, and transcription factor sub-networks. We identified six orthogroups involved in response to social challenge, including groups represented by mouse genes Npas4 and Nr4a1, as well as common modulation of systems such as transcriptional regulators, ion channels, G-protein coupled receptors, and synaptic proteins. We also identified conserved coexpression modules enriched for mitochondrial fatty acid metabolism and heat shock that constitute the shared neurogenomic response. Our analysis suggests a toolkit wherein nuclear receptors, interacting with chaperones, induce transcriptional changes in mitochondrial activity, neural cytoarchitecture, and synaptic transmission after social challenge. It reveals systems-level mechanisms that have been repeatedly co-opted during evolution of analogous behaviors, thus advancing the genetic toolkit concept beyond individual genes.

genomics↗