Behavioral idiosyncrasy reveals genetic control of phenotypic variability

Towards powerful experimental and statistical approaches to study intraindividual variability in labile traits

There is a long-standing interest in behavioural ecology, exploring the causes and correlates of consistent individual differences in mean behavioural traits ('personality') and the response to the environment ('plasticity'). Recently, it has been observed that individuals also consistently differ in their residual intraindividual variability (rIIV). This variation will probably have broad biological and methodological implications to the study of trait variation in labile traits, such as behaviour and physiology, though we currently need studies to quantify variation in rIIV, using more standardized and powerful methodology. Focusing on activity rates in guppies (Poecilia reticulata), we provide a model example, from sampling design to data analysis, in how to quantify rIIV in labile traits. Building on the doubly hierarchical generalized linear model recently used to quantify individual differences in rIIV, we extend the model to evaluate the covariance between individual mean values and their rIIV. After accounting for time-related change in behaviour, our guppies substantially differed in rIIV, and it was the active individuals that tended to be more consistent (lower rIIV). We provide annotated data analysis code to implement these complex models, and discuss how to further generalize the model to evaluate covariances with other aspects of phenotypic variation.

Modularity: genes, development and evolution

Modularity has emerged as a central concept for evolutionary biology, providing the field with a theory of organismal structure and variation. This theory has reframed long standing questions and serves as a unified conceptual framework for genetics, developmental biology and multivariate evolution. Research programs in systems biology and quantitative genetics are bridging the gap between these fields. While this synthesis is ongoing, some major themes have emerged and empirical evidence for modularity has become abundant. In this review, we look at modularity from an historical perspective, highlighting its meaning at different levels of biological organization and the different methods that can be used to detect it. We then explore the relationship between quantitative genetic approaches to modularity and developmental genetic studies. We conclude by investigating the dynamic relationship between modularity and the adaptive landscape and how this potentially shapes evolution and can help bridge the gap between micro- and macroevolution.

Neuromodulatory Regulation of Behavioral Individuality in Zebrafish

Inter-individual behavioral variation is thought to increase fitness and aid adaptation to environmental change, but the underlying mechanisms are poorly understood. We find that variation between individuals in neuromodulatory input contributes to individuality in short-term habituation of the zebrafish (Danio Rerio) acoustic startle response (ASR). ASR habituation varies greatly between individuals, but differences are stable over days and are heritable. Acoustic stimuli that activate ASR-command Mauthner cells also activate dorsal raphe nucleus (DRN) serotonergic neurons, which project to the vicinity of the Mauthner cells and their inputs. DRN neuron activity decreases during habituation in proportion to habituation and a genetic manipulation that reduces serotonin content in DRN neurons increases habituation, whereas serotonergic agonism or DRN activation with ChR2 reduces habituation. Finally, level of rundown of DRN activity co-segregates with extent of behavioral habituation across generations. Thus, variation between individuals in neuromodulatory input contributes to individuality in a core adaptive behavior. VIDEO ABSTRACT.

Gene networks and developmental context: the importance of understanding complex gene expression patterns in evolution

Animal development is the product of distinct components and interactions-genes, regulatory networks, and cells-and it exhibits emergent properties that cannot be inferred from the components in isolation. Often the focus is on the genotype-to-phenotype map, overlooking the process of development that turns one into the other. We propose a move toward micro-evolutionary analysis of development, incorporating new tools that enable cell type resolution and single-cell microscopy. Using the sex determination pathway in Drosophila to illustrate potential avenues of research, we highlight some of the questions that these emerging technologies can address. For example, they provide an unprecedented opportunity to study heterogeneity within cell populations, and the potential to add the dimension of time to gene regulatory network analysis. Challenges still remain in developing methods to analyze this data and to increase the throughput. However this line of research has the potential to bridge the gaps between previously more disparate fields, such as population genetics and development, opening up new avenues of research.

Major histocompatibility complex harbors widespread genotypic variability of non-additive risk of rheumatoid arthritis including epistasis

Genotypic variability based genome-wide association studies (vGWASs) can identify potentially interacting loci without prior knowledge of the interacting factors. We report a two-stage approach to make vGWAS applicable to diseases: firstly using a mixed model approach to partition dichotomous phenotypes into additive risk and non-additive environmental residuals on the liability scale and secondly using the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups per marker. We found widespread significant (P < 2.5e-05) vGWAS signals within the major histocompatibility complex (MHC) across all three study cohorts of rheumatoid arthritis. We further identified 10 epistatic interactions between the vGWAS signals independent of the MHC additive effects, each with a weak effect but jointly explained 1.9% of phenotypic variance. PTPN22 was also identified in the discovery cohort but replicated in only one independent cohort. Combining the three cohorts boosted power of vGWAS and additionally identified TYK2 and ANKRD55. Both PTPN22 and TYK2 had evidence of interactions reported elsewhere. We conclude that vGWAS can help discover interacting loci for complex diseases but require large samples to find additional signals.

Testing candidate genes for attention-deficit/hyperactivity disorder in fruit flies using a high throughput assay for complex behavior

Fruit flies are important model organisms for functional testing of candidate genes in multiple disciplines, including the study of human diseases. Here we use a high-throughput locomotor activity assay to test the response on activity behavior of gene disruption in Drosophila melanogaster. The aim was to investigate the impact of disruption of 14 candidate genes for human attention-deficit/hyperactivity disorder (ADHD) on fly behavior. By obtaining a range of correlated measures describing the space of variables for behavioral activity we show, that some mutants display similar phenotypic responses, and furthermore, that the genes disrupted in those mutants had common molecular functions; namely processes related to cGMP activity, cation channels and serotonin receptors. All but one of the candidate genes resulted in aberrant behavioral activity, suggesting involvement of these genes in behavioral activity in fruit flies. Results provide additional support for the investigated genes being risk candidate genes for ADHD in humans.

Bayesian Models of Development

Until recently, biology lacked a framework for studying how information from genes, parental effects, and different personal experiences is combined across the lifetime to affect phenotypic development. Over the past few years, researchers have begun to build such a framework, using models that incorporate Bayesian updating to study the evolution of developmental plasticity and developmental trajectories. Here, we describe the merits of a Bayesian approach to development, review the main findings and implications of the current set of models, and describe predictions that can be tested using protocols already used by empiricists. We suggest that a Bayesian perspective affords a simple and tractable way to conceptualize, explain, and predict how information combines across the lifetime to affect development.

Candidate genetic modifiers of retinitis pigmentosa identified by exploiting natural variation in Drosophila

Individuals carrying the same pathogenic mutation can present with a broad range of disease outcomes. While some of this variation arises from environmental factors, it is increasingly recognized that the background genetic variation of each individual can have a profound effect on the expressivity of a pathogenic mutation. In order to understand this background effect on disease-causing mutations, studies need to be performed across a wide range of backgrounds. Recent advancements in model organism biology allow us to test mutations across genetically diverse backgrounds and identify the genes that influence the expressivity of a mutation. In this study, we used the Drosophila Genetic Reference Panel, a collection of ∼200 wild-derived strains, to test the variability of the retinal phenotype of the Rh1(G69D) Drosophila model of retinitis pigmentosa (RP). We found that the Rh1(G69D) retinal phenotype is quite a variable quantitative phenotype. To identify the genes driving this extensive phenotypic variation, we performed a genome-wide association study. We identified 106 candidate genes, including 14 high-priority candidates. Functional testing by RNAi indicates that 10/13 top candidates tested influence the expressivity of Rh1(G69D). The human orthologs of the candidate genes have not previously been implicated as RP modifiers and their functions are diverse, including roles in endoplasmic reticulum stress, apoptosis and retinal degeneration and development. This study demonstrates the utility of studying a pathogenic mutation across a wide range of genetic backgrounds. These candidate modifiers provide new avenues of inquiry that may reveal new RP disease mechanisms and therapies.

Variability in thermal and phototactic preferences in Drosophila may reflect an adaptive bet-hedging strategy

Organisms use various strategies to cope with fluctuating environmental conditions. In diversified bet‐hedging, a single genotype exhibits phenotypic heterogeneity with the expectation that some individuals will survive transient selective pressures. To date, empirical evidence for bet‐hedging is scarce. Here, we observe that individual Drosophila melanogaster flies exhibit striking variation in light‐ and temperature‐preference behaviors. With a modeling approach that combines real world weather and climate data to simulate temperature preference‐dependent survival and reproduction, we find that a bet‐hedging strategy may underlie the observed interindividual behavioral diversity. Specifically, bet‐hedging outcompetes strategies in which individual thermal preferences are heritable. Animals employing bet‐hedging refrain from adapting to the coolness of spring with increased warm‐seeking that inevitably becomes counterproductive in the hot summer. This strategy is particularly valuable when mean seasonal temperatures are typical, or when there is considerable fluctuation in temperature within the season. The model predicts, and we experimentally verify, that the behaviors of individual flies are not heritable. Finally, we model the effects of historical weather data, climate change, and geographic seasonal variation on the optimal strategies underlying behavioral variation between individuals, characterizing the regimes in which bet‐hedging is advantageous.

The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance

Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.

Most biological traits vary in natural populations, and understanding the genetic basis of this variation remains an important challenge. Genome-wide association (GWA) studies have emerged as a powerful tool to address this challenge by dissecting the genetic architecture of trait variation into the contribution of individual genes. This contribution has traditionally been measured as the difference in the phenotypic means between groups of individuals with alternative genotypes at one, or multiple loci. However, instead of altering the trait mean, certain loci alter the variability of the trait. Here, we describe the genetic dissection of one such variance-controlling locus that drives variation in leaf molybdenum concentrations amongst natural accessions of Arabidopsis thaliana. The variance-controlling locus was found to result from the contributions of multiple alleles at multiple loci that are closely linked on the chromosome and is a major contributor to the “missing heritability” for this trait identified in previous studies. This illustrates that multi-allelic genetic architectures can hide large amounts of additive genetic variation, and that it is possible to uncover this hidden variation using the appropriate experimental designs and statistical methods described here.

Quantitative Genetics of Food Intake in Drosophila melanogaster

Food intake is an essential animal activity, regulated by neural circuits that motivate food localization, evaluate nutritional content and acceptance or rejection responses through the gustatory system, and regulate neuroendocrine feedback loops that maintain energy homeostasis. Excess food consumption in people is associated with obesity and metabolic and cardiovascular disorders. However, little is known about the genetic basis of natural variation in food consumption. To gain insights in evolutionarily conserved genetic principles that regulate food intake, we took advantage of a model system, Drosophila melanogaster, in which food intake, environmental conditions and genetic background can be controlled precisely. We quantified variation in food intake among 182 inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel (DGRP). We found significant genetic variation in the mean and within-line environmental variance of food consumption and observed sexual dimorphism and genetic variation in sexual dimorphism for both food intake traits (mean and variance). We performed genome wide association (GWA) analyses for mean food intake and environmental variance of food intake (using the coefficient of environmental variation, CV_E, as the metric for environmental variance) and identified molecular polymorphisms associated with both traits. Validation experiments using RNAi-knockdown confirmed 24 of 31 (77%) candidate genes affecting food intake and/or variance of food intake, and a test cross between selected DGRP lines confirmed a SNP affecting mean food intake identified in the GWA analysis. The majority of the validated candidate genes were novel with respect to feeding behavior, and many had mammalian orthologs implicated in metabolic diseases.

Neuronal control of locomotor handedness in Drosophila

Genetically identical individuals display variability in their physiology, morphology, and behaviors, even when reared in essentially identical environments, but there is little mechanistic understanding of the basis of such variation. Here, we investigated whether Drosophila melanogaster displays individual-to-individual variation in locomotor behaviors. We developed a new high-throughout platform capable of measuring the exploratory behavior of hundreds of individual flies simultaneously. With this approach, we find that, during exploratory walking, individual flies exhibit significant bias in their left vs. right locomotor choices, with some flies being strongly left biased or right biased. This idiosyncrasy was present in all genotypes examined, including wild-derived populations and inbred isogenic laboratory strains. The biases of individual flies persist for their lifetime and are nonheritable: i.e., mating two left-biased individuals does not yield left-biased progeny. This locomotor handedness is uncorrelated with other asymmetries, such as the handedness of gut twisting, leg-length asymmetry, and wing-folding preference. Using transgenics and mutants, we find that the magnitude of locomotor handedness is under the control of columnar neurons within the central complex, a brain region implicated in motor planning and execution. When these neurons are silenced, exploratory laterality increases, with more extreme leftiness and rightiness. This observation intriguingly implies that the brain may be able to dynamically regulate behavioral individuality.