Despite the diversity of life, studies of variation across animals often remind us of our deep evolutionary past. Abundant genome sequencing over the last ∼25 years reveals remarkable conservation of genes and recent analyses of gene regulatory networks illustrate that not only genes but entire pathways are conserved, reused, and elaborated in the evolution of diversity. Predating these discoveries, 19th-century embryologists observed that though morphology at birth varies tremendously, certain stages of embryogenesis appear remarkably similar across vertebrates. Specifically, while early and late stages are variable across species, anatomy of mid-stages embryos (the phylotypic stage) is conserved. This model of vertebrate development and diversification has found mixed support in recent analyses comparing gene expression across species possibly owing to differences across studies in species, embryonic stages, and gene sets compared. Here we perform a meta-analysis of 186 microarray and RNA-seq expression data sets covering embryogenesis in six vertebrate species spanning ∼420 million years of evolution. We use an unbiased clustering approach to group stages of embryogenesis by transcriptomic similarity and ask whether gene expression similarity of clustered embryonic stages deviates from the null hypothesis of no relationship between timing and diversification. We use a phylogenetic comparative approach to characterize expression conservation pattern (i.e., early conservation, hourglass, inverse hourglass, late conservation, or no relationship) of each gene at each evolutionary node. We find an enrichment of early conservation and hourglass patterns and a large depletion of genes exhibiting no distinguishable pattern of conservation. Using this approach, we ask whether the proportions of genes following distinct evolutionary conservation patterns change through evolutionary time and whether genes consistently follow the same pattern across nodes of the vertebrate phylogeny. We find that genes exhibiting an hourglass pattern at one node of the phylogeny are more likely to show an hourglass pattern at other nodes with 89 hourglass genes shared in at least three of the four nodes compared to only six early conservation genes. Consistent with the hourglass hypothesis, this finding suggests that genes following an hourglass pattern are more conserved over evolutionary time.
In many species, cultures, and contexts, social dominance reflects the ability to exert influence over the behavior of others. Yet the behavioral attributes of those in dominant positions, and the behaviors of actually influential individuals may not be the same, and the behavioral attributes that generate influence in one social context may reduce influence in others. The question of what makes an effective leader is therefore not straightforward, and has many answers depending on the context in which leadership and influence is to be manifested. Most importantly, social dominance cannot always be assumed to be equivalent with social influence. Here we examine whether socially dominant males in the cichlid fish Astatotilapia burtoni are more effective in exerting social influence than socially subordinate males. Using machine-vision based automated tracking of behavior, we find that dominant males in this species display behavioral traits that typify leadership across taxonomic systems – they are aggressive, occupy central social network positions, and lead group movements, whereas subordinate males are passive, socially peripheral, and have little influence over typical group movement. However, in a more complex group-consensus task the influence of dominant males breaks down, and subordinate males become more effective agents of social change. In a more sophisticated group consensus task involving a visual association task, the behavioral attributes that define male dominance – aggression, rapid movement, and increased physical distance to others – interfere with the ability of dominant males to generate group to consensus. Dominant males occupy more spatially distant positions, and had lower signal-to-noise ratio of informative behavior in the association task, while subordinate males are typically is close physical association with their group members, have high signal-to-noise behaviors in the association task, and equal visual connectivity to other group members as dominant males. The attributes that define effective social influence are therefore highly context-specific in this species. These results demonstrate that in this and many other species including humans, behavioral traits that are typical of socially dominant individuals may be the same that reduce their social influence in other contexts.
Suicidal behaviors are strongly linked with mood disorders, but the specific neurobiological and functional gene-expression correlates for this linkage remain elusive. We therefore tested the hypothesis that a convergent neuroanatomical and gene-expression signature will underlie mood disorder associated psychiatric morbidity and related suicide mortality. To do so, first, we applied an anatomical likelihood estimation (ALE) MRI meta-analysis across 72 voxel-based morphometry (VBM) studies including 2387 (living) participants that identified a selectively reduced anterior insula cortex gray matter volume (GMV) as a potential neuroanatomical signature for mood disorder. This neuroanatomical signature was then specifically used to guide postmortem RNA-Sequencing studies of 100 independent donor brains with a life-time history of major depressive disorder (N=30), bipolar disorder (N=37) and non-affected controls (N=33) using a sample from the National Institute of Mental Health Brain collection core. In this latter study, factor analysis first identified a higher-order factor representing number of Axis-1 diagnoses (i.e. morbidity) and suicide-completion (i.e. suicide-mortality). Using this higher-order factor as a contrast variable, differential gene-expression changes were examined in high psychiatric morbidity and related suicide mortality versus low psychiatric morbidity and related suicide mortality in mood disorder cohorts and controls. We identified in immune, inflammasome, neurodevelopmental, and transcriptional pathways and a weighted gene co-activation network analysis identified co-activated gene modules for psychiatric morbidity and suicide-mortality outcomes. These results provide a functional gene-expression link between mood disorder associated psychiatric disease morbidity and suicide-mortality.
The perimenopausal transition at middle age is often associated with hot flashes and sleep disruptions, metabolic changes, and other symptoms. Whereas the mechanisms for these processes are incompletely understood, both aging and a loss of ovarian estrogens play contributing roles. Furthermore, the timing of when estradiol treatment should commence, and for how long, are key clinical questions in the management of symptoms. Using a rat model of surgical menopause, we determined the effects of regimens of estradiol treatment with differing time at onset and duration of treatment on diurnal rhythms of activity and core temperature, and on food intake and body weight. Reproductively mature (MAT, ∼4 mo.) or aging (AG, ∼11 mo.) female rats were ovariectomized, implanted intraperitoneally with a telemetry device, and given either a vehicle (V) or estradiol (E) subcutaneous capsule implantation. Rats were remotely recorded for 10 days per month for 3 (MAT) or 6 (AG) months. To ascertain whether delayed onset of treatment affected rhythms, a subset of AG-V rats had their capsules switched to E at the end of 3 months. Another set of AG-E rats had their capsules removed at 3 months to determine whether beneficial effects of E would persist. Overall, activity and temperature mesor, robustness, and amplitude declined with aging. Compared to V treatment, E treated rats showed: 1) better maintenance of body weight and food intake; 2) higher, more consolidated activity and temperature rhythms; and 3) higher activity and temperature robustness and amplitude. In the AG arm of the study, switching treatment from V to E or E to V quickly reversed these patterns. Thus, the presence of E was the dominant factor in determining stability and amplitude of locomotor activity and temperature rhythms. As a whole the results show benefits of E treatment, even with a delay, on biological rhythms and physiological functions.
Although social behavior can have a strong genetic component, it can also result in selection on genome structure and function, thereby influencing the evolution of the genome itself. Here we explore the bidirectional links between social behavior and genome architecture by considering variation in social and/or mating behavior among populations (social polymorphisms) and across closely related species. We propose that social behavior can influence genome architecture via associated demographic changes due to social living. We establish guidelines to exploit emerging whole-genome sequences using analytical approaches that examine genome structure and function at different levels (regulatory vs structural variation) from the perspective of both molecular biology and population genetics in an ecological context.
Unlike in terrestrial animals, the boundary between internal (e.g., hormones) and external (e.g., social) stimulation can be blurred for aquatic and amphibious species. When chemicals such as hormones and glandular secretions leach into the water, they can further interact with other signaling systems, creating multimodal stimuli. It is unclear, however, whether water-borne chemical secretions from courting male frogs affect the physiology and behavior of their rivals. In order to address this question we first established non-invasive, continuous sampling methods for simultaneously measuring both hormones and behavior in amphibious species. Then, we examined whether interactions between water-borne chemical secretions and conspecific calls affect reproductive behavior and physiology (testosterone and corticosterone) of courting male túngara frogs. Our results demonstrate that conspecific acoustic stimulation alone increases locomotor activity, decreases latency to call, and increases calling behavior but does not alter the amount of hormones excreted. In response to water containing chemical secretions from rivals, but in the absence of calls from other males, males excrete more testosterone. Interestingly, the combined acoustic and chemical stimulus causes a multiplicative increase in both calling behavior and hormonal excretion. Taken together, our results suggest that a multimodal chemical-acoustic stimulus physiologically primes males for aggressive behavior.
Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: if cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell type classification, we performed two forms of transcriptional profiling – RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from two small crustacean networks: the stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally-defined neuron types can be classified by expression profile alone. Our results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post-hoc grouping so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between two or more cell types. Therefore, our study supports the general utility of cell identification by transcriptional profiling, but adds a caution: it is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology or innervation target can neuronal identity be unambiguously determined.
Single-neuron gene expression studies may be especially important for understanding nervous system structure and function because of the neuron-specific functionality and plasticity that defines functional neural circuits. Cellular dissociation is a prerequi- site technical manipulation for single-cell and single cell-population studies, but the extent to which the cellular dissociation process affects neural gene expression has not been determined. This information is necessary for interpreting the results of experi- mental manipulations that affect neural function such as learning and memory. The goal of this research was to determine the impact of cellular dissociation on brain transcriptomes. We compared gene expression of microdissected samples from the dentate gyrus (DG), CA3, and CA1 subfields of the mouse hippocampus either prepared by a standard tissue homogenization protocol or subjected to enzymatic digestion used to dissociate cells within tissues. We report that compared to homoge- nization, enzymatic dissociation alters about 350 genes or 2% of the hippocampal transcriptome. While only a few genes canonically implicated in long-term potentiation and fear memory change expression levels in response to the dissociation procedure, these data indicate that sample preparation can affect gene expression profiles, which might confound interpretation of results depending on the research question. This study is important for the investigation of any complex tissues as research effort moves from subfield level analysis to single cell analysis of gene expression.
Early-life experiences can shape adult behavior, with consequences for fitness and health, yet fundamental questions remain unanswered about how early-life social experiences are translated into variation in brain and behavior. The African cichlid fish Astatotilapia burtoni, a model system in social neuroscience, is well known for its highly plastic social phenotypes in adulthood. Here, we rear juveniles in either social groups or pairs to investigate the effects of early-life social environments on behavior and neuroendocrine gene expression. We find that both juvenile behavior and neuroendocrine function are sensitive to early-life effects. Behavior robustly co-varies across multiple contexts (open field, social cue investigation, and dominance behavior assays) to form a behavioral syndrome, with pair-reared juveniles towards the end of syndrome that is less active and socially interactive. Pair-reared juveniles also submit more readily as subordinates. In a separate cohort, we measured whole brain expression of stress and sex hormone genes. Expression of glucocorticoid receptor 1a was elevated in group-reared juveniles, supporting a highly-conserved role for the stress axis mediating early-life effects. The effect of rearing environment on androgen receptor α and estrogen receptor α expression was mediated by treatment duration (1 vs. 5 weeks). Finally, expression of corticotropin-releasing factor and glucocorticoid receptor 2 decreased significantly over time. Rearing environment also caused striking differences in gene co-expression, such that expression was tightly integrated in pair-reared juveniles but not group-reared or isolates. Together, this research demonstrates the important developmental origins of behavioral phenotypes and identifies potential behavioral and neuroendocrine mechanisms.
Social monogamy, typically characterized by the formation of a pair bond, increased territorial defense, and often biparental care, has evolved numerous times in animals. Despite the independent evolutionary origins of monogamous mating systems, several homologous brain regions and neuroendocrine pathways play conserved roles in regulating social affiliation and parental care, but little is known about the evolution of the neuromolecular mechanisms underlying monogamy. Here, we show that shared transcriptomic profiles are associated with monogamy across vertebrates and discuss the importance of our discovery for understanding the origins of behavioral diversity. We compare neural transcriptomes of reproductive males in monogamous and nonmonogamous species pairs of mice, voles, parid songbirds, frogs, and cichlid fishes. Our results provide evidence of a universal transcriptomic code underlying monogamy in vertebrates.
While extensive research has focused on how social interactions evolve, the fitness consequences of the neuroendocrine mechanisms underlying these interactions have rarely been documented, especially in the wild. Here, we measure how the neuroendocrine mechanisms underlying male behavior affecting mating success and sperm competition in the ocellated wrasse (Symphodus ocellatus). In this species, males exhibit three alternative reproductive types. ‘Nesting males’ provide parental care, defend territories, and form cooperative associations with unrelated ‘satellites’, who cheat by sneaking fertilizations but help by reducing sperm competition from ‘sneakers’ who do not cooperate or provide care. To measure the fitness consequences of the mechanisms underlying these social interactions, we used “phenotypic engineering” that involved administering an androgen receptor antagonist (flutamide) to wild, free-living fish. Nesting males treated with flutamide shifted their aggression from sneakers to satellite males and experienced decreased submissiveness by sneaker males (which correlated with decreased nesting male mating success). The preoptic area (POA), a region controlling male reproductive behaviors, exhibited dramatic down-regulation of androgen receptor (AR) and vasotocin 1a receptor (V1aR) mRNA following experimental manipulation of androgen signaling. We did not find a direct effect of the manipulation on male mating success, paternity or larval production. However, variation in neuroendocrine mechanisms generated by the experimental manipulation was significantly correlated with changes in behavior and mating success: V1aR expression was negatively correlated with satellite-directed aggression and expression of its ligand arginine vasotocin (AVT) was positively correlated with courtship and mating success, thus revealing the potential for sexual selection on these mechanisms.
Motivation: We set out to develop an algorithm that can mine differential gene expression data to identify candidate cell type-specific DNA regulatory sequences. Differential expression is usually quantified as a continuous score—fold-change, test-statistic, P-value—comparing biological classes. Unlike existing approaches, our de novo strategy, termed SArKS, applies non-parametric kernel smoothing to uncover promoter motif sites that correlate with elevated differential expression scores. SArKS detects motif k-mers by smoothing sequence scores over sequence similarity. A second round of smoothing over spatial proximity reveals multi-motif domains (MMDs). Discovered motif sites can then be merged or extended based on adjacency within MMDs. False positive rates are estimated and controlled by permutation testing. Results: We applied SArKS to published gene expression data representing distinct neocortical neuron classes in Mus musculus and interneuron developmental states in Homo sapiens. When benchmarked against several existing algorithms using a cross-validation procedure, SArKS identified larger motif sets that formed the basis for regression models with higher correlative power. Availability and implementation: https://github.com/denniscwylie/sarks. Contact: email@example.com or firstname.lastname@example.org Supplementary information: Supplementary data are available at Bioinformatics online.
The ability to reliably identify individuals over time and across contexts is essential in numerous areas of science. There are a variety of well-established methods for uniquely marking individuals, such as using paint or dye, visible implant elastomer tags, numbers or barcodes glued to the animal, passive integrated transponders, and more. For some species, life history stages, and/or experiments, however, these existing tagging methods are not sufficient. Here, we describe the method we developed for tagging juveniles of the African cichlid fish, Astatotilapia burtoni, which are too small for the methods used to tag adults. We used fishing line threaded through the needle of an insulin syringe to tie a loop of line through the dorsal muscle of juveniles as small as 10 mm standard length. Unique color patterns on the line can be used to distinguish among individuals. The tag is compatible with normal locomotion and social behavior, discernible to the eye and on camera, durable enough to last at least months, and the juvenile can grow with the tag. For A. burtoni, which is a model system in social neuroscience, the lack of an appropriate tagging method for very small juveniles likely contributes to the relative lack of early-life studies, and the same may be true for other small species. We expect this method to be useful in a variety of species and will facilitate the integration of organismal and behavioral development into more research programs.
A central challenge to evolutionary computation is enabling techniques to evolve increasingly complex target end products. Frequently direct approaches that reward only the target end product itself are not successful because the path between the starting conditions and the target end product traverses through a complex fitness landscape, where the directly accessible intermediary states may be require deleterious or even simply neutral mutations. As such, a host of techniques have sprung up to support evolutionary computation techniques taking these paths. One technique is scaffolding where intermediary targets are used to provide a path from the starting state to the end state. While scaffolding can be successful within well-understood domains it also poses the challenge of identifying useful intermediaries. Within this paper we first identify some shortcomings of scaffolding approaches --- namely, that poorly selected intermediaries may in fact hurt the evolutionary computation's chance of producing the desired target end product. We then describe a light-weight approach to selecting intermediate scaffolding states that improve the efficacy of the evolutionary computation.
Understanding how the brain processes social information and generates adaptive behavioural responses is a major goal in neuroscience. We examined behaviour and neural activity patterns in socially relevant brain nuclei of hermaphroditic mangrove rivulus fish (Kryptolebias marmoratus) provided with different types of social stimuli: stationary model opponent, regular mirror, non-reversing mirror and live opponent. We found that: (i) individuals faced with a regular mirror were less willing to interact with, delivered fewer attacks towards and switched their orientation relative to the opponent more frequently than fish exposed to a non-reversing mirror image or live opponent; (ii) fighting with a regular mirror image caused higher expression of immediate-early genes (IEGs: egr-1 and c-Fos) in the teleost homologues of the basolateral amygdala and hippocampus, but lower IEG expression in the preoptic area, than fighting with a non-reversing mirror image or live opponent; (iii) stationary models elicited the least behavioural and IEG responses among the four stimuli; and (iv) the nonreversing mirror image and live opponent drove similar behavioural and neurobiological responses. These results suggest that the various stimuli provide different types of information related to conspecific recognition in the context of aggressive contests, which ultimately drive different neurobiological responses.
Animals have evolved flexible strategies that allow them to evaluate and respond to their social environment by integrating the salience of external stimuli with internal physiological cues into adaptive behavioral responses. A highly conserved social decision-makingnetwork (SDMN), consisting of interconnected social behavior and mesolimbic reward networks, has been proposed to underlie such adaptive behaviors across all vertebrates, although our understanding of this system in reptiles is very limited. Here we measure neural activation across the SDMN and associated regions in the male brown anole (Anolis sagrei), within both reproductive and agonistic contexts, by quantifying the expression density of the immediate early gene product Fos. We then relate this neural activity measure to social context, behavioral expression, and activation (as measured by colocalization with Fos) of different phenotypes of ‘source’ node neurons that produce neurotransmittersand neuropeptides known to modulate SDMN ‘target’ node activity. Our results demonstrate that measures of neural activation across the SDMN network are generally independent of specific behavioral output, although Fos induction in a few select nodes of the social behavior network component of the SDMN does vary with social environment and behavioral output. Under control conditions, the mesolimbic reward nodes of the SDMN actually correlate little with the social behavior nodes, but the interconnectivity of these SDMN components increases dramatically within a reproductive context. When relating behavioral output to specific source node activation profiles, we found that catecholaminergic activation is associated with the frequency and intensity of reproductive behavior output, as well as with aggression intensity. Finally, in terms of the effects of source node activation on SDMN activity, we found that Ile8-oxytocin (mesotocin) populations correlate positively, while Ile3-vasopressin (vasotocin), catecholamine, and serotonin populations correlate negatively with SDMN activity. Taken together, our findings present evidence for a highly dynamic SDMN in reptiles that is responsive to salient cues in a social context-dependent manner.
The diversity of mating systems among animals is astounding. Importantly, similar mating systems have evolved even across distantly related taxa. However, our understanding of the mechanisms underlying these convergently evolved phenotypes is limited. Here, we examine on a genomic scale the neuromolecular basis of social organization in Ectodini cichlids from Lake Tanganyika. Using field collected males and females of four closely related species representing two independent evolutionary transitions from polygyny to monogamy, we take a comparative transcriptomic approach to test the hypothesis that these independent transitions have recruited similar gene sets. Our results demonstrate that while lineage and species exert a strong influence on neural gene expression profiles, social phenotype can also drive gene expression evolution. Specifically, 331 genes (~6% of those assayed) were associated with monogamous mating systems independent of species or sex. Among these genes, we find a strong bias (4:1 ratio) toward genes with increased expression in monogamous individuals. A highly conserved nonapeptide system known to be involved in the regulation of social behavior across animals was not associated with mating system in our analysis. Overall, our findings suggest deep molecular homologies underlying the convergent or parallel evolution of monogamy in different lineages of Ectodini cichlids.
Evolutionary computation and neuroevolution seek to create systems of ever increasing sophistication, such that the digitally evolved forms reflect the variety, diversity, and complexity seen within nature in living organisms. In general, most evolutionary computation and neuroevolution techniques do so by encoding the final form without any type of development. This is in contrast to nature, where most complex organisms go through a developmental period. Here we focus on an evolving digital tissues that develop from a single cell and unfold into a complex body plan. It quickly became evident that evolving developing forms is quite challenging. We compare four different techniques that have successfully been employed within evolutionary computation to evolve complex forms and behavior: scaffolding (i.e., gradually increasing the difficulty of the task rewarded by the environment over evolutionary time), stepping stones (i.e., rewarding easier tasks within an environment that can co-opted for the performance of more complex tasks), and island models (i.e., rewarding different fitness functions within different subpopulations with migration). We show the effect of these methods on the evolution of complex forms that develop from a single cell, the rate of adaptation, and different dimensions of robustness and variation among solutions.