A transcriptional network associated with natural variation in Drosophila aggressive behavior

Genetic correlation between aggressive signals and fighting

Theoretical analyses indicate that aggressive signals should positively correlate with the signallers' willingness and abilities to fight. Few experimental studies, however, have tested this prediction. In two experiments employing distinct, ecologically realistic protocols, we quantified the association between aggressive signals and fighting in fruit fly genotypes and found high positive genetic correlations between threat and fighting (rG = 0.80 and 0.74). Our results add to the growing body of experimental work indicating that aggressive signals have relatively high informational value.

Antibiotics increase aggression behavior and aggression-related pheromones and receptors in Drosophila melanogaster

Aggression is a behavior common in most species; it is controlled by internal and external drivers, including hormones, environmental cues, and social interactions, and underlying pathways are understood in a broad range of species. To date, though, effects of gut microbiota on aggression in the context of gut-brain communication and social behavior have not been completely elucidated. We examine how manipulation of Drosophila melanogaster microbiota affects aggression as well as the pathways that underlie the behavior in this species. Male flies treated with antibiotics exhibited significantly more aggressive behaviors. Furthermore, they had higher levels of cVA and (Z)-9 Tricosene, pheromones associated with aggression in flies, as well as higher expression of the relevant pheromone receptors and transporters OR67d, OR83b, GR32a, and LUSH. These findings suggest that aggressive behavior is, at least in part, mediated by bacterial species in flies.

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Aggression increases in flies that lack a microbiome

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Monocolonization with specific bacteria can mediate this effect

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We observed differences in aggression-related pheromone expression levels

The Divider Assay is a high-throughput pipeline for aggression analysis in Drosophila

Aggression is a complex social behavior that remains poorly understood. Drosophila has become a powerful model system to study the underlying biology of aggression but lack of high throughput screening and analysis continues to be a barrier for comprehensive mutant and circuit discovery. Here we developed the Divider Assay, a simplified experimental procedure to make aggression analysis in Drosophila fast and accurate. In contrast to existing methods, we can analyze aggression over long time intervals and in complete darkness. While aggression is reduced in the dark, flies are capable of intense fighting without seeing their opponent. Twenty-four-hour behavioral analysis showed a peak in fighting during the middle of the day, a drastic drop at night, followed by re-engagement with a further increase in aggression in anticipation of the next day. Our pipeline is easy to implement and will facilitate high throughput screening for mechanistic dissection of aggression.

Carry-over effects of resource competition and social environment on aggression

Aggressive behavior is common in many species and is often adaptive because it enables individuals to gain access to limited resources. However, aggression is also highly plastic and the degree of plasticity could be influenced by factors such as resource limitation and the social environment. In this study, we examined how the effects of social experience and resource limitation could persist to affect future aggressive interactions. Using naturally inbred strains of Drosophila melanogaster that differ in aggressiveness, we manipulated the level of available resources by varying fly density (two treatments: high and low per capita resources) and group composition by varying strain frequency (five treatments: homogeneous strains, or mixed at 1:3, 1:1 or 3:1 ratios of the more aggressive to less-aggressive strain). For each treatment group, we measured aggression before and after flies were placed through a 4-day period of fixed resources. There was no consistent effect of resource competition on aggression. Instead, changes in aggression depended on resource availability in combination with group composition. In homogeneous groups made up of only one strain, all males became more aggressive following the fixed-resource period, regardless of fly density. In mixed-strain treatments at high density, we observed plastic shifts in aggression of males from both strains, but the direction of plastic responses depended on social composition. Our results show that aggression may not only be influenced by the intensity of previous competitive experiences caused by resource limitation, but also through social effects caused by the composition of the group.

The peacefulness gene promotes aggression in Drosophila

Natural aggressiveness is commonly observed in all animal species, and is displayed frequently when animals compete for food, territory and mating. Aggression is an innate behaviour, and is influenced by both environmental and genetic factors. However, the genetics of aggression remains largely unclear. In this study, we identify the peacefulness (pfs) gene as a novel player in the control of male-male aggression in Drosophila. Mutations in pfs decreased intermale aggressiveness, but did not affect locomotor activity, olfactory avoidance response and sexual behaviours. pfs encodes for the evolutionarily conserved molybdenum cofactor (MoCo) synthesis 1 protein (Mocs1), which catalyzes the first step in the MoCo biosynthesis pathway. Neuronal-specific knockdown of pfs decreased aggressiveness. By contrast, overexpression of pfs greatly increased aggressiveness. Knocking down Cinnamon (Cin) catalyzing the final step in the MoCo synthesis pathway, caused a pfs-like aggression phenotype. In humans, inhibition of MoCo-dependent enzymes displays anti-aggressive effects. Thus, the control of aggression by Pfs-dependent MoCo pathways may be conserved throughout evolution.

Experimental evidence that density mediates negative frequency-dependent selection on aggression

Aggression can be beneficial in competitive environments if aggressive individuals are more likely to access resources than non-aggressive individuals. However, variation in aggressive behaviour persists within populations, suggesting that high levels of aggression might not always be favoured. The goal of this study was to experimentally assess the effects of population density and phenotypic frequency on selection on aggression in a competitive environment. We compared survival of two strains of Drosophila melanogaster that differ in aggression across three density treatments and five frequency treatments (single strain groups, equal numbers of each strain and strains mixed at 3:1 and 1:3 ratios) during a period of limited resources. While there was no difference in survival across single-strain treatments, survival was strongly density dependent, with declining survival as density increased. Furthermore, at medium and high densities, there was evidence of negative frequency-dependent selection, where rare strains experienced greater survival than common strains. However, there was no evidence of negative frequency-dependent selection at low density. Our results indicate that the benefits of aggression during periods of limited resources can depend on the interaction between the phenotypic composition of populations and population density, both of which are mechanisms that could maintain variation in aggressive behaviours within natural populations.

SlgA, encoded by the homolog of the human schizophrenia-associated gene PRODH, acts in clock neurons to regulate Drosophila aggression

Mutations in the proline dehydrogenase gene PRODH are linked to behavioral alterations in schizophrenia and as part of DiGeorge and velo-cardio-facial syndromes, but the role of PRODH in their etiology remains unclear. Here, we establish a Drosophila model to study the role of PRODH in behavioral disorders. We determine the distribution of the Drosophila PRODH homolog slgA in the brain and show that knockdown and overexpression of human PRODH and slgA in the lateral neurons ventral (LNv) lead to altered aggressive behavior. SlgA acts in an isoform-specific manner and is regulated by casein kinase II (CkII). Our data suggest that these effects are, at least partially, due to effects on mitochondrial function. We thus show that precise regulation of proline metabolism is essential to drive normal behavior and we identify Drosophila aggression as a model behavior relevant for the study of the mechanisms that are impaired in neuropsychiatric disorders.

Editors' choice: A Drosophila model to study the role of PRODH, a schizophrenia-associated gene, in behavioral disorders.

Comparative analysis of the brain transcriptome in a hyper-aggressive fruit fly, Drosophila prolongata

Aggressive behavior is observed in many animals, but its intensity differs between species. In a model animal of genetics, Drosophila melanogaster, genetic basis of aggressive behavior has been studied intensively, including transcriptome analyses to identify genes whose expression level was associated with intra-species variation in aggressiveness. However, whether these genes are also involved in the evolution of aggressiveness among different species has not been examined. In this study, we performed de novo transcriptome analysis in the brain of Drosophila prolongata to identify genes associated with the evolution of aggressiveness. Males of D. prolongata were hyper-aggressive compared with closely related species. Comparison of the brain transcriptomes identified 21 differentially expressed genes in males of D. prolongata. They did not overlap with the list of aggression-related genes identified in D. melanogaster, suggesting that genes involved in the evolution of aggressiveness were independent of those associated with the intra-species variation in aggressiveness in Drosophila. Although females of D. prolongata were not aggressive as the males, expression levels of the 21 genes identified in this study were more similar between sexes than between species.

Divergence along the gonadal steroidogenic pathway: Implications for hormone-mediated phenotypic evolution

Across a range of taxa, hormones regulate suites of traits that influence survival and reproductive success; however, the mechanisms by which hormone-mediated traits evolve are still unclear. We hypothesized that phenotypic divergence might follow from differential regulation of genes encoding key steps in hormone biosynthesis and thus the rate of hormone production. We tested this hypothesis in relation to the steroid hormone testosterone by comparing two subspecies of junco (Junco hyemalis) in the wild and in captivity. These subspecies have diverged over the last 10-15kyears in multiple testosterone-mediated traits, including aggression, ornamentation, and body size. We show that variation in gonadal gene expression along the steroid biosynthetic pathway predicts phenotypic divergence within and among subspecies, and that the more androgenized subspecies exhibits a more prolonged time-course of elevated testosterone following exogenous stimulation. Our results point to specific genes that fulfill key conditions for phenotypic evolution because they vary functionally in their expression among individuals and between populations, and they map onto population variation in phenotype in a common garden. Our findings therefore build an important bridge between hormones, genes, and phenotypic evolution.

Gene expression and variation in social aggression by queens of the harvester ant Pogonomyrmex californicus

A key requirement for social cooperation is the mitigation and/or social regulation of aggression towards other group members. Populations of the harvester ant Pogonomyrmex californicus show the alternate social phenotypes of queens founding nests alone (haplometrosis) or in groups of unrelated yet cooperative individuals (pleometrosis). Pleometrotic queens display an associated reduction in aggression. To understand the proximate drivers behind this variation, we placed foundresses of the two populations into social environments with queens from the same or the alternate population, and measured their behaviour and head gene expression profiles. A proportion of queens from both populations behaved aggressively, but haplometrotic queens were significantly more likely to perform aggressive acts, and conflict escalated more frequently in pairs of haplometrotic queens. Whole-head RNA sequencing revealed variation in gene expression patterns, with the two populations showing moderate differentiation in overall transcriptional profile, suggesting that genetic differences underlie the two founding strategies. The largest detected difference, however, was associated with aggression, regardless of queen founding type. Several modules of coregulated genes, involved in metabolism, immune system and neuronal function, were found to be upregulated in highly aggressive queens. Conversely, nonaggressive queens exhibited a striking pattern of upregulation in chemosensory genes. Our results highlight that the social phenotypes of cooperative vs. solitary nest founding tap into a set of gene regulatory networks that seem to govern aggression level. We also present a number of highly connected hub genes associated with aggression, providing opportunity to further study the genetic underpinnings of social conflict and tolerance.

Genetics of aggressive behavior: An overview

The Research Domain Criteria (RDoC) address three types of aggression: frustrative non-reward, defensive aggression and offensive/proactive aggression. This review sought to present the evidence for genetic underpinnings of aggression and to determine to what degree prior studies have examined phenotypes that fit into the RDoC framework. Although the constructs of defensive and offensive aggression have been widely used in the animal genetics literature, the human literature is mostly agnostic with regard to all the RDoC constructs. We know from twin studies that about half the variance in behavior may be explained by genetic risk factors. This is true for both dimensional, trait-like, measures of aggression and categorical definitions of psychopathology. The non-shared environment seems to have a moderate influence with the effects of shared environment being unclear. Human molecular genetic studies of aggression are in an early stage. The most promising candidates are in the dopaminergic and serotonergic systems along with hormonal regulators. Genome-wide association studies have not yet achieved genome-wide significance, but current samples are too small to detect variants having the small effects one would expect for a complex disorder. The strongest molecular evidence for a genetic basis for aggression comes from animal models comparing aggressive and non-aggressive strains or documenting the effects of gene knockouts. Although we have learned much from these prior studies, future studies should improve the measurement of aggression by using a systematic method of measurement such as that proposed by the RDoC initiative.

Natural variation in brain gene expression profiles of aggressive and nonaggressive individual sticklebacks

Within many species, some individuals are consistently more aggressive than others. We examine whether there are differences in brain gene expression between aggressive versus nonaggressive behavioural types of individuals within a natural population of male three-spined sticklebacks (Gasterosteus aculeatus). We compared gene expression profiles of aggressive male sticklebacks to nonaggressive males in four regions of the brain (brainstem, cerebellum, diencephalon and telencephalon). Relatively few genes were differentially expressed between behavioural types in telencephalon, cerebellum and diencephalon, but hundreds of genes were differentially expressed in brainstem, a brain area involved in detecting threats. Six genes that were differentially expressed in response to a territorial intrusion in a previous study were also differentially expressed between behavioural types in this study, implying primarily non-shared but some shared molecular mechanisms. Our findings offer new insights into the molecular causes and correlates of behavioural plasticity and individual variation in behaviour.

Genetic architecture of natural variation in Drosophila melanogaster aggressive behavior

Aggression is an evolutionarily conserved complex behavior essential for survival and the organization of social hierarchies. With the exception of genetic variants associated with bioamine signaling, which have been implicated in aggression in many species, the genetic basis of natural variation in aggression is largely unknown. Drosophila melanogaster is a favorable model system for exploring the genetic basis of natural variation in aggression. Here, we performed genome-wide association analyses using the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and replicate advanced intercross populations derived from the most and least aggressive DGRP lines. We identified genes that have been previously implicated in aggressive behavior as well as many novel loci, including gustatory receptor 63a (Gr63a), which encodes a subunit of the receptor for CO2, and genes associated with development and function of the nervous system. Although genes from the two association analyses were largely nonoverlapping, they mapped onto a genetic interaction network inferred from an analysis of pairwise epistasis in the DGRP. We used mutations and RNAi knock-down alleles to functionally validate 79% of the candidate genes and 75% of the candidate epistatic interactions tested. Epistasis for aggressive behavior causes cryptic genetic variation in the DGRP that is revealed by changing allele frequencies in the outbred populations derived from extreme DGRP lines. This phenomenon may pertain to other fitness traits and species, with implications for evolution, applied breeding, and human genetics.

Genomic basis of evolutionary change: evolving immunity

Complex traits are manifestations of intricate gene interaction networks. Evolution of complex traits revolves around the genetic variation in such networks. Genomics has increased our ability to investigate the complex gene interaction networks, and characterize the extent of genetic variation in these networks. Immunity is a complex trait, for which the ecological drivers and molecular networks are fairly well understood in Drosophila. By characterizing the natural variation in immunity, and mapping how the genome changes during the evolution of immunity in Drosophila, we can integrate our knowledge on the complex genetic architecture of traits and the molecular basis of evolutionary processes.

Genome-Wide Association Analyses Point to Candidate Genes for Electric Shock Avoidance in Drosophila melanogaster

Electric shock is a common stimulus for nociception-research and the most widely used reinforcement in aversive associative learning experiments. Yet, nothing is known about the mechanisms it recruits at the periphery. To help fill this gap, we undertook a genome-wide association analysis using 38 inbred Drosophila melanogaster strains, which avoided shock to varying extents. We identified 514 genes whose expression levels and/ or sequences co-varied with shock avoidance scores. We independently scrutinized 14 of these genes using mutants, validating the effect of 7 of them on shock avoidance. This emphasizes the value of our candidate gene list as a guide for follow-up research. In addition, by integrating our association results with external protein-protein interaction data we obtained a shock avoidance-associated network of 38 genes. Both this network and the original candidate list contained a substantial number of genes that affect mechanosensory bristles, which are hair-like organs distributed across the fly’s body. These results may point to a potential role for mechanosensory bristles in shock sensation. Thus, we not only provide a first list of candidate genes for shock avoidance, but also point to an interesting new hypothesis on nociceptive mechanisms.

Epistasis for quantitative traits in Drosophila

The role of gene-gene interactions in the genetic architecture of quantitative traits is controversial, despite the biological plausibility of nonlinear molecular interactions underpinning variation in quantitative traits. In strictly outbreeding populations, genetic architecture is inferred indirectly by estimating variance components; however, failure to detect epistatic variance does not mean lack of epistatic gene action and is even consistent with pervasive epistasis. In Drosophila, more focused approaches to detecting epistatic gene action are possible, based on the ability to create de novo mutations and perform crosses among them; to construct inbred lines, artificial selection lines, and chromosome substitution lines; to map quantitative trait loci affecting complex traits by linkage and association; and to evaluate effects of induced mutations on multiple wild-derived backgrounds. Here, I review evidence for epistasis in Drosophila from the application of these methods, and conclude that additivity is an emergent property of underlying epistatic gene action for Drosophila quantitative traits. Such studies can be used to infer novel, highly interconnected genetic networks that are enriched for gene ontology categories and metabolic and cellular pathways. The consequence of epistasis is that the main effects of each of the interacting loci depend on allele frequency, which negatively impacts the predictive ability of additive models. Finally, epistasis results in hidden quantitative genetic variation in natural populations (genetic canalization) and the potential for rapid evolution of Dobzhansky-Muller incompatibilities (speciation).

Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis

Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing <2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic “fingerprint”. Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness.

Epistasis and quantitative traits: using model organisms to study gene-gene interactions

The role of epistasis in the genetic architecture of quantitative traits is controversial, despite the biological plausibility that nonlinear molecular interactions underpin the genotype-phenotype map. This controversy arises because most genetic variation for quantitative traits is additive. However, additive variance is consistent with pervasive epistasis. In this Review, I discuss experimental designs to detect the contribution of epistasis to quantitative trait phenotypes in model organisms. These studies indicate that epistasis is common, and that additivity can be an emergent property of underlying genetic interaction networks. Epistasis causes hidden quantitative genetic variation in natural populations and could be responsible for the small additive effects, missing heritability and the lack of replication that are typically observed for human complex traits.

Proximate perspectives on the evolution of female aggression: good for the gander, good for the goose?

Female-female aggression often functions in competition over reproductive or social benefits, but the proximate mechanisms of this apparently adaptive behaviour are not well understood. The sex steroid hormone testosterone (T) and its metabolites are well-established mediators of male-male aggression, and several lines of evidence suggest that T-mediated mechanisms may apply to females as well. However, a key question is whether mechanisms of female aggression primarily reflect correlated evolutionary responses to selection acting on males, or whether direct selection acting on females has made modifications to these mechanisms that are adaptive in light of female life history. Here, I examine the degree to which female aggression is mediated at the level of T production, target tissue sensitivity to T, or downstream genomic responses in order to test the hypothesis that selection favours mechanisms that facilitate female aggression while minimizing the costs of systemically elevated T. I draw heavily from avian systems, including the dark-eyed junco (Junco hyemalis), as well as other organisms in which these mechanisms have been well studied from an evolutionary/ecological perspective in both sexes. Findings reveal that the sexes share many behavioural and hormonal mechanisms, though several patterns also suggest sex-specific adaptation. I argue that greater attention to multiple levels of analysis-from hormone to receptor to gene network, including analyses of individual variation that represents the raw material of evolutionary change-will be a fruitful path for understanding mechanisms of behavioural regulation and intersexual coevolution.

Functional genomics of adaptation to hypoxic cold-stress in high-altitude deer mice: transcriptomic plasticity and thermogenic performance

In species that are distributed across steep environmental gradients, adaptive variation in physiological performance may be attributable to transcriptional plasticity in underlying regulatory networks. Here we report the results of common-garden experiments that were designed to elucidate the role of regulatory plasticity in evolutionary adaptation to hypoxic cold-stress in deer mice (Peromyscus maniculatus). We integrated genomic transcriptional profiles with measures of metabolic enzyme activities and whole-animal thermogenic performance under hypoxia in highland (4350 m) and lowland (430 m) mice from three experimental groups: (1) wild-caught mice that were sampled at their native elevations; (2) wild-caught/lab-reared mice that were deacclimated to low-elevation conditions in a common-garden lab environment; and (3) the F(1) progeny of deacclimated mice that were maintained under the same low-elevation common-garden conditions. In each experimental group, highland mice exhibited greater thermogenic capacities than lowland mice, and this enhanced performance was associated with upregulation of transcriptional modules that influence several hierarchical steps in the O(2) cascade, including tissue O(2) diffusion (angiogenesis) and tissue O(2) utilization (metabolic fuel use and cellular oxidative capacity). Most of these performance-related transcriptomic changes occurred over physiological and developmental timescales, suggesting that regulatory plasticity makes important contributions to fitness-related physiological performance in highland deer mice.

Mapping Wolbachia distributions in the adult Drosophila brain

The maternally inherited bacterium Wolbachia infects the germline of most arthropod species. Using Drosophila simulans and D. melanogaster, we demonstrate that localization of Wolbachia to the fat bodies and adult brain is likely also a conserved feature of Wolbachia infection. Examination of three Wolbachia strains (WMel , WRiv , WPop ) revealed that the bacteria preferentially concentrate in the central brain with low titres in the optic lobes. Distribution within regions of the central brain is largely determined by the Wolbachia strain, while the titre is influenced by both, the host species and the bacteria strain. In neurons of the central brain and ventral nerve cord, Wolbachia preferentially localizes to the neuronal cell bodies but not to axons. All examined Wolbachia strains are present intracellularly or in extracellular clusters, with the pathogenic WPop strain exhibiting the largest and most abundant clusters. We also discovered that 16 of 40 lines from the Drosophila Genetic Reference Panel are Wolbachia infected. Direct comparison of Wolbachia infected and cured lines from this panel reveals that differences in physiological traits (chill coma recovery, starvation, longevity) are partially due to host line influences. In addition, a tetracycline-induced increase in Drosophila longevity was detected many generations after treatment.

Behavior genetics and postgenomics

The science of genetics is undergoing a paradigm shift. Recent discoveries, including the activity of retrotransposons, the extent of copy number variations, somatic and chromosomal mosaicism, and the nature of the epigenome as a regulator of DNA expressivity, are challenging a series of dogmas concerning the nature of the genome and the relationship between genotype and phenotype. According to three widely held dogmas, DNA is the unchanging template of heredity, is identical in all the cells and tissues of the body, and is the sole agent of inheritance. Rather than being an unchanging template, DNA appears subject to a good deal of environmentally induced change. Instead of identical DNA in all the cells of the body, somatic mosaicism appears to be the normal human condition. And DNA can no longer be considered the sole agent of inheritance. We now know that the epigenome, which regulates gene expressivity, can be inherited via the germline. These developments are particularly significant for behavior genetics for at least three reasons: First, epigenetic regulation, DNA variability, and somatic mosaicism appear to be particularly prevalent in the human brain and probably are involved in much of human behavior; second, they have important implications for the validity of heritability and gene association studies, the methodologies that largely define the discipline of behavior genetics; and third, they appear to play a critical role in development during the perinatal period and, in particular, in enabling phenotypic plasticity in offspring. I examine one of the central claims to emerge from the use of heritability studies in the behavioral sciences, the principle of minimal shared maternal effects, in light of the growing awareness that the maternal perinatal environment is a critical venue for the exercise of adaptive phenotypic plasticity. This consideration has important implications for both developmental and evolutionary biology.

Neural sensitivity to sex steroids predicts individual differences in aggression: implications for behavioural evolution

Testosterone (T) regulates many traits related to fitness, including aggression. However, individual variation in aggressiveness does not always relate to circulating T, suggesting that behavioural variation may be more closely related to neural sensitivity to steroids, though this issue remains unresolved. To assess the relative importance of circulating T and neural steroid sensitivity in predicting behaviour, we measured aggressiveness during staged intrusions in free-living male and female dark-eyed juncos (Junco hyemalis). We compared aggressiveness to plasma T levels and to the abundance of androgen receptor (AR), aromatase (AROM) and oestrogen receptor alpha (ORα) mRNA in behaviourally relevant brain areas (avian medial amygdala, hypothalamus and song control regions). We also asked whether patterns of covariation among behaviour and endocrine parameters differed in males and females, anticipating that circulating T may be a better predictor of behaviour in males than in females. We found that circulating T related to aggressiveness only in males, but that gene expression for ORα, AR and AROM covaried with individual differences in aggressiveness in both sexes. These findings are among the first to show that individual variation in neural gene expression for three major sex steroid-processing molecules predicts individual variation in aggressiveness in both sexes in nature. The results have broad implications for our understanding of the mechanisms by which aggressive behaviour may evolve.

Genetics of aggression

Aggression mediates competition for food, mating partners, and habitats and, among social animals, establishes stable dominance hierarchies. In humans, abnormal aggression is a hallmark of neuropsychiatric disorders and can be elicited by environmental factors acting on an underlying genetic susceptibility. Identifying the genetic architecture that predisposes to aggressive behavior in people is challenging because of difficulties in quantifying the phenotype, genetic heterogeneity, and uncontrolled environmental conditions. Studies on mice have identified single-gene mutations that result in hyperaggression, contingent on genetic background. These studies can be complemented by systems genetics approaches in Drosophila melanogaster, in which mutational analyses together with genome-wide transcript analyses, artificial selection studies, and genome-wide analysis of epistasis have revealed that a large segment of the genome contributes to the manifestation of aggressive behavior with widespread epistatic interactions. Comparative genomic analyses based on the principle of evolutionary conservation are needed to enable a complete dissection of the neurogenetic underpinnings of this universal fitness trait.

On the prospects of whole-genome association mapping in Saccharomyces cerevisiae

Advances in sequencing technology have enabled whole-genome sequences to be obtained from multiple individuals within species, particularly in model organisms with compact genomes. For example, 36 genome sequences of Saccharomyces cerevisiae are now publicly available, and SNP data are available for even larger collections of strains. One potential use of these resources is mapping the genetic basis of phenotypic variation through genome-wide association (GWA) studies, with the benefit that associated variants can be studied experimentally with greater ease than in outbred populations such as humans. Here, we evaluate the prospects of GWA studies in S. cerevisiae strains through extensive simulations and a GWA study of mitochondrial copy number. We demonstrate that the complex and heterogeneous patterns of population structure present in yeast populations can lead to a high type I error rate in GWA studies of quantitative traits, and that methods typically used to control for population stratification do not provide adequate control of the type I error rate. Moreover, we show that while GWA studies of quantitative traits in S. cerevisiae may be difficult depending on the particular set of strains studied, association studies to map cis-acting quantitative trait loci (QTL) and Mendelian phenotypes are more feasible. We also discuss sampling strategies that could enable GWA studies in yeast and illustrate the utility of this approach in Saccharomyces paradoxus. Thus, our results provide important practical insights into the design and interpretation of GWA studies in yeast, and other model organisms that possess complex patterns of population structure.

Genetics and neurobiology of aggression in Drosophila

Aggressive behavior is widely present throughout the animal kingdom and is crucial to ensure survival and reproduction. Aggressive actions serve to acquire territory, food, or mates and in defense against predators or rivals; while in some species these behaviors are involved in establishing a social hierarchy. Aggression is a complex behavior, influenced by a broad range of genetic and environmental factors. Recent studies in Drosophila provide insight into the genetic basis and control of aggression. The state of the art on aggression in Drosophila and the many opportunities provided by this model organism to unravel the genetic and neurobiological basis of aggression are reviewed.

Genetic contributions to behavioural diversity at the gene-environment interface

Recent work on behavioural variation within and between species has furthered our understanding of the genetic architecture of behavioural traits, the identities of relevant genes and the ways in which genetic variants affect neuronal circuits to modify behaviour. Here we review our understanding of the genetics of natural behavioural variation in non-human animals and highlight the implications of these findings for human genetics. We suggest that gene-environment interactions are central to natural genetic variation in behaviour and that genes affecting neuromodulatory pathways and sensory processing are preferred sites of naturally occurring mutations.

The effects of weak genetic perturbations on the transcriptome of the wing imaginal disc and its association with wing shape in Drosophila melanogaster

A major objective of genomics is to elucidate the mapping between genotypic and phenotypic space as a step toward understanding how small changes in gene function can lead to elaborate phenotypic changes. One approach that has been utilized is to examine overall patterns of covariation between phenotypic variables of interest, such as morphology, physiology, and behavior, and underlying aspects of gene activity, in particular transcript abundance on a genome-wide scale. Numerous studies have demonstrated that such patterns of covariation occur, although these are often between samples with large numbers of unknown genetic differences (different strains or even species) or perturbations of large effect (sexual dimorphism or strong loss-of-function mutations) that may represent physiological changes outside of the normal experiences of the organism. We used weak mutational perturbations in genes affecting wing development in Drosophila melanogaster that influence wing shape relative to a co-isogenic wild type. We profiled transcription of 1150 genes expressed during wing development in 27 heterozygous mutants, as well as their co-isogenic wild type and one additional wild-type strain. Despite finding clear evidence of expression differences between mutants and wild type, transcriptional profiles did not covary strongly with shape, suggesting that information from transcriptional profiling may not generally be predictive of final phenotype. We discuss these results in the light of possible attractor states of gene expression and how this would affect interpretation of covariation between transcriptional profiles and other phenotypes.

Transcriptional networks for alcohol sensitivity in Drosophila melanogaster

Understanding the genetic architecture of polygenic traits requires investigating how complex networks of interacting molecules mediate the effect of genetic variation on organismal phenotypes. We used a combination of P-element mutagenesis and analysis of natural variation in gene expression to predict transcriptional networks that underlie alcohol sensitivity in Drosophila melanogaster. We identified 139 unique P-element mutations (124 in genes) that affect sensitivity or resistance to alcohol exposure. Further analyses of nine of the lines showed that the P-elements affected expression levels of the tagged genes, and P-element excision resulted in phenotypic reversion. The majority of the mutations were in computationally predicted genes or genes with unexpected effects on alcohol phenotypes. Therefore we sought to understand the biological relationships among 21 of these genes by leveraging genetic correlations among genetically variable transcripts in wild-derived inbred lines to predict coregulated transcriptional networks. A total of 32 "hub" genes were common to two or more networks associated with the focal genes. We used RNAi-mediated inhibition of expression of focal genes and of hub genes connected to them in the network to confirm their effects on alcohol-related phenotypes. We then expanded the computational networks using the hub genes as foci and again validated network predictions. Iteration of this approach allows a stepwise expansion of the network with simultaneous functional validation. Although coregulated transcriptional networks do not provide information about causal relationships among their constituent transcripts, they provide a framework for subsequent functional studies on the genetic basis of alcohol sensitivity.

Candidate genes detected in transcriptome studies are strongly dependent on genetic background

Whole genome transcriptomic studies can point to potential candidate genes for organismal traits. However, the importance of potential candidates is rarely followed up through functional studies and/or by comparing results across independent studies. We have analysed the overlap of candidate genes identified from studies of gene expression in Drosophila melanogaster using similar technical platforms. We found little overlap across studies between putative candidate genes for the same traits in the same sex. Instead there was a high degree of overlap between different traits and sexes within the same genetic backgrounds. Putative candidates found using transcriptomics therefore appear very sensitive to genetic background and this can mask or override effects of treatments. The functional importance of putative candidate genes emerging from transcriptome studies needs to be validated through additional experiments and in future studies we suggest a focus on the genes, networks and pathways affecting traits in a consistent manner across backgrounds.

A genetical genomics approach to genome scans increases power for QTL mapping

We describe a method for integrating gene expression information into genome scans and show that this can substantially increase the statistical power of QTL mapping. The method has three stages. First, standard clustering methods identify small (size 5-20) groups of genes with similar expression patterns. Second, each gene group is tested for a causative genetic locus shared with the clinical trait of interest. This is done using an EM algorithm approach that treats genotype at the putative causative locus as an unobserved variable and combines expression information from all of the genes in the group to infer genotype information at the locus. Finally, expression QTL (eQTL) are mapped for each gene group that shares a causative locus with the clinical trait. Such eQTL are candidates for the causative locus. Simulation results show that this method has far superior power to standard QTL mapping techniques in many circumstances. We applied this method to existing data on mouse obesity. Our method identified 27 putative body weight QTL, whereas standard QTL mapping produced only one. Furthermore, most gene groups with body weight QTL included cis genes, so candidate genes could be immediately identified. Eleven body weight QTL produced 16 candidate genes that have been previously associated with body weight or body weight-related traits, thus validating our method. In addition, 15 of the 16 other loci produced 32 candidate genes that have not been associated with body weight. Thus, this method shows great promise for finding new causative loci for complex traits.

Unravelling the neurophysiological basis of aggression in a fish model

Background

Aggression is a near-universal behaviour with substantial influence on and implications for human and animal social systems. The neurophysiological basis of aggression is, however, poorly understood in all species and approaches adopted to study this complex behaviour have often been oversimplified. We applied targeted expression profiling on 40 genes, spanning eight neurological pathways and in four distinct regions of the brain, in combination with behavioural observations and pharmacological manipulations, to screen for regulatory pathways of aggression in the zebrafish (Danio rerio), an animal model in which social rank and aggressiveness tightly correlate.

Results

Substantial differences occurred in gene expression profiles between dominant and subordinate males associated with phenotypic differences in aggressiveness and, for the chosen gene set, they occurred mainly in the hypothalamus and telencephalon. The patterns of differentially-expressed genes implied multifactorial control of aggression in zebrafish, including the hypothalamo-neurohypophysial-system, serotonin, somatostatin, dopamine, hypothalamo-pituitary-interrenal, hypothalamo-pituitary-gonadal and histamine pathways, and the latter is a novel finding outside mammals. Pharmacological manipulations of various nodes within the hypothalamo-neurohypophysial-system and serotonin pathways supported their functional involvement. We also observed differences in expression profiles in the brains of dominant versus subordinate females that suggested sex-conserved control of aggression. For example, in the HNS pathway, the gene encoding arginine vasotocin (AVT), previously believed specific to male behaviours, was amongst those genes most associated with aggression, and AVT inhibited dominant female aggression, as in males. However, sex-specific differences in the expression profiles also occurred, including differences in aggression-associated tryptophan hydroxylases and estrogen receptors.

Conclusions

Thus, through an integrated approach, combining gene expression profiling, behavioural analyses, and pharmacological manipulations, we identified candidate genes and pathways that appear to play significant roles in regulating aggression in fish. Many of these are novel for non-mammalian systems. We further present a validated system for advancing our understanding of the mechanistic underpinnings of complex behaviours using a fish model.

Systems genetics analysis of body weight and energy metabolism traits in Drosophila melanogaster

Background

Obesity and phenotypic traits associated with this condition exhibit significant heritability in natural populations of most organisms. While a number of genes and genetic pathways have been implicated to play a role in obesity associated traits, the genetic architecture that underlies the natural variation in these traits is largely unknown. Here, we used 40 wild-derived inbred lines of Drosophila melanogaster to quantify genetic variation in body weight, the content of three major metabolites (glycogen, triacylglycerol, and glycerol) associated with obesity, and metabolic rate in young flies. We chose these lines because they were previously screened for variation in whole-genome transcript abundance and in several adult life-history traits, including longevity, resistance to starvation stress, chill-coma recovery, mating behavior, and competitive fitness. This enabled us not only to identify candidate genes and transcriptional networks that might explain variation for energy metabolism traits, but also to investigate the genetic interrelationships among energy metabolism, behavioral, and life-history traits that have evolved in natural populations.

Results

We found significant genetically based variation in all traits. Using a genome-wide association screen for single feature polymorphisms and quantitative trait transcripts, we identified 337, 211, 237, 553, and 152 novel candidate genes associated with body weight, glycogen content, triacylglycerol storage, glycerol levels, and metabolic rate, respectively. Weighted gene co-expression analyses grouped transcripts associated with each trait in significant modules of co-expressed genes and we interpreted these modules in terms of their gene enrichment based on Gene Ontology analysis. Comparison of gene co-expression modules for traits in this study with previously determined modules for life-history traits identified significant modular pleiotropy between glycogen content, body weight, competitive fitness, and starvation resistance.

Conclusions

Combining a large phenotypic dataset with information on variation in genome wide transcriptional profiles has provided insight into the complex genetic architecture underlying natural variation in traits that have been associated with obesity. Our findings suggest that understanding the maintenance of genetic variation in metabolic traits in natural populations may require that we understand more fully the degree to which these traits are genetically correlated with other traits, especially those directly affecting fitness.

Social interactions in "simple" model systems

Deciphering the genetic and neurobiological underpinnings of social behavior is a difficult task. Simple model organisms such as C. elegans, Drosophila, and social insects display a wealth of social behaviors similar to those in more complex animals, including social dominance, group decision making, learning from experienced individuals, and foraging in groups. Although the study of social interactions is still in its infancy, the ability to assess the contributions of gene expression, neural circuitry, and the environment in response to social context in these simple model organisms is unsurpassed. Here, I take a comparative approach, discussing selected examples of social behavior across species and highlighting the common themes that emerge.

Expression quantitative trait loci analysis in plants

An expression Quantitative Trait Locus or eQTL is a chromosomal region that accounts for a proportion of the variation in abundance of a mRNA transcript observed between individuals in a genetic mapping population. A single gene can have one or multiple eQTLs. Large scale mRNA profiling technologies advanced genome-wide eQTL mapping in a diverse range of organisms allowing thousands of eQTLs to be detected in a single experiment. When combined with classical or trait QTLs, correlation analyses can directly suggest candidates for genes underlying these traits. Furthermore, eQTL mapping data enables genetic regulatory networks to be modelled and potentially provide a better understanding of the underlying phenotypic variation. The mRNA profiling data sets can also be used to infer the chromosomal positions of thousands of genes, an outcome that is particularly valuable for species with unsequenced genomes where the chromosomal location of the majority of genes remains unknown. In this review we focus on eQTL studies in plants, addressing conceptual and technical aspects that include experimental design, genetic polymorphism prediction and candidate gene identification.