Flexibility in a gene network affecting a simple behavior in Drosophila melanogaster

A stochastic RNA editing process targets a limited number of sites in individual Drosophila glutamatergic motoneurons

RNA editing is a post-transcriptional source of protein diversity and occurs across the animal kingdom. Given the complete profile of mRNA targets and their editing rate in individual cells is unclear, we analyzed single cell RNA transcriptomes from Drosophila larval tonic and phasic glutamatergic motoneuron subtypes to determine the most highly edited targets and identify cell-type specific editing. From ∼15,000 genes encoded in the genome, 316 high confidence A-to-I canonical RNA edit sites were identified, with 102 causing missense amino acid changes in proteins regulating membrane excitability, synaptic transmission, and cellular function. Some sites showed 100% editing in single neurons as observed with mRNAs encoding mammalian AMPA receptors. However, most sites were edited at lower levels and generated variable expression of edited and unedited mRNAs within individual neurons. Together, these data provide insights into how the RNA editing landscape alters protein function to modulate the properties of two well-characterized neuronal populations in Drosophila .

The genetic architecture of behavioral canalization

Behaviors are components of fitness and contribute to adaptive evolution. Behaviors represent the interactions of an organism with its environment, yet innate behaviors display robustness in the face of environmental change, which we refer to as 'behavioral canalization'. We hypothesize that positive selection of hub genes of genetic networks stabilizes the genetic architecture for innate behaviors by reducing variation in the expression of interconnected network genes. Robustness of these stabilized networks would be protected from deleterious mutations by purifying selection or suppressing epistasis. We propose that, together with newly emerging favorable mutations, epistatically suppressed mutations can generate a reservoir of cryptic genetic variation that could give rise to decanalization when genetic backgrounds or environmental conditions change to allow behavioral adaptation.

Epistasis for head morphology in Drosophila melanogaster

Epistasis-gene-gene interaction-is common for mutations with large phenotypic effects in humans and model organisms. Epistasis impacts quantitative genetic models of speciation, response to natural and artificial selection, genetic mapping, and personalized medicine. However, the existence and magnitude of epistasis between alleles with small quantitative phenotypic effects are controversial and difficult to assess. Here, we use the Drosophila melanogaster Genetic Reference Panel of sequenced inbred lines to evaluate the magnitude of naturally occurring epistasis modifying the effects of mutations in jing and inv, two transcription factors that have subtle quantitative effects on head morphology as homozygotes. We find significant epistasis for both mutations and performed single marker genome-wide association analyses to map candidate modifier variants and loci affecting head morphology. A subset of these loci was significantly enriched for a known genetic interaction network, and mutations of the candidate epistatic modifier loci also affect head morphology.

Integration of evidence across human and model organism studies: A meeting report

The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration-particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs.

Evolution of Epistatic Networks and the Genetic Basis of Innate Behaviors

Instinctive behaviors are genetically programmed behaviors that occur independent of experience. How genetic programs that give rise to the manifestation of such behaviors evolve remains an unresolved question. I propose that evolution of species-specific innate behaviors is accomplished through progressive modifications of pre-existing genetic networks composed of allelic variants. I hypothesize that changes in frequencies of one or more constituent allelic variants within the network leads to changes in gene network connectivity and the emergence of a reorganized network that can support the emergence of a novel behavioral phenotype and becomes stabilized when key allelic variants are driven to fixation.

Mitonuclear gene X environment effects on lifespan and health: How common, how big?

Mitochondrial genetic variation can have profound effects on fitness, and the mitotype must interact with both the nuclear genes and the environment. We used Drosophila to investigate the extent to which mitotype effects on lifespan and activity are modulated by nucleotype and environmental variation. When nucleotype is varied, mitochondrial effects on lifespan persisted but were relatively small, and still male biased. Varying food as well, mitotype had substantial effects on male climbing speed, modifiable by nucleotype but less so by diet. Finally, mitotype affected fly lifespan much more in a cage environment compared with a vial, also modifiable by nucleotype and diet. The cage may represent a stressful environment. Mitochondrial genotype may affect fitness much more in conditions of stress, which may have implications for human health.

The complex underpinnings of genetic background effects

Genetic interactions between mutations and standing polymorphisms can cause mutations to show distinct phenotypic effects in different individuals. To characterize the genetic architecture of these so-called background effects, we genotype 1411 wild-type and mutant yeast cross progeny and measure their growth in 10 environments. Using these data, we map 1086 interactions between segregating loci and 7 different gene knockouts. Each knockout exhibits between 73 and 543 interactions, with 89% of all interactions involving higher-order epistasis between a knockout and multiple loci. Identified loci interact with as few as one knockout and as many as all seven knockouts. In mutants, loci interacting with fewer and more knockouts tend to show enhanced and reduced phenotypic effects, respectively. Cross–environment analysis reveals that most interactions between the knockouts and segregating loci also involve the environment. These results illustrate the complicated interactions between mutations, standing polymorphisms, and the environment that cause background effects.

Mutations often show distinct phenotypic effects across different genetic backgrounds. Here the authors describe the genetic basis of these so-called background effects using data on genotype and growth in 10 environments from 1411 segregants from a cross of two strains of budding yeast.

Why does the magnitude of genotype-by-environment interaction vary?

Genotype-by-environment interaction (G × E), that is, genetic variation in phenotypic plasticity, is a central concept in ecology and evolutionary biology. G×E has wide-ranging implications for trait development and for understanding how organisms will respond to environmental change. Although G × E has been extensively documented, its presence and magnitude vary dramatically across populations and traits. Despite this, we still know little about why G × E is so evident in some traits and populations, but minimal or absent in others. To encourage synthetic research in this area, we review diverse hypotheses for the underlying biological causes of variation in G × E. We extract common themes from these hypotheses to develop a more synthetic understanding of variation in G × E and suggest some important next steps.

Advancing behavioural genomics by considering timescale

Animal behavioural traits often covary with gene expression, pointing towards a genomic constraint on organismal responses to environmental cues. This pattern highlights a gap in our understanding of the time course of environmentally responsive gene expression, and moreover, how these dynamics are regulated. Advances in behavioural genomics explore how gene expression dynamics are correlated with behavioural traits that range from stable to highly labile. We consider the idea that certain genomic regulatory mechanisms may predict the timescale of an environmental effect on behaviour. This temporally minded approach could inform both organismal and evolutionary questions ranging from the remediation of early life social trauma to understanding the evolution of trait plasticity.

Cynefin as Reference Framework to Facilitate Insight and Decision-Making in Complex Contexts of Biomedical Research

The Cynefin scheme is a concept of knowledge management, originally devised to support decision making in management, but more generally applicable to situations, in which complexity challenges the quality of insight, prediction, and decision. Despite the fact that life itself, and especially the brain and its diseases, are complex to the extent that complexity could be considered their cardinal feature, complex problems in biomedicine are often treated as if they were actually not more than the complicated sum of solvable sub-problems. Because of the emergent properties of complex contexts this is not correct. With a set of clear criteria Cynefin helps to set apart complex problems from “simple/obvious,” “complicated,” “chaotic,” and “disordered” contexts in order to avoid misinterpreting the relevant causality structures. The distinction comes with the insight, which specific kind of knowledge is possible in each of these categories and what are the consequences for resulting decisions and actions. From student's theses over the publication and grant writing process to research politics, misinterpretation of complexity can have problematic or even dangerous consequences, especially in clinical contexts. Conceptualization of problems within a straightforward reference language like Cynefin improves clarity and stringency within projects and facilitates communication and decision-making about them.

Phenotypic Evolution With and Beyond Genome Evolution

DNA does not make phenotypes on its own. In this volume entitled "Genes and Phenotypic Evolution," the present review draws the attention on the process of phenotype construction-including development of multicellular organisms-and the multiple interactions and feedbacks between DNA, organism, and environment at various levels and timescales in the evolutionary process. First, during the construction of an individual's phenotype, DNA is recruited as a template for building blocks within the cellular context and may in addition be involved in dynamical feedback loops that depend on the environmental and organismal context. Second, in the production of phenotypic variation among individuals, stochastic, environmental, genetic, and parental sources of variation act jointly. While in controlled laboratory settings, various genetic and environmental factors can be tested one at a time or in various combinations, they cannot be separated in natural populations because the environment is not controlled and the genotype can rarely be replicated. Third, along generations, genotype and environment each have specific properties concerning the origin of their variation, the hereditary transmission of this variation, and the evolutionary feedbacks. Natural selection acts as a feedback from phenotype and environment to genotype. This review integrates recent results and concrete examples that illustrate these three points. Although some themes are shared with recent calls and claims to a new conceptual framework in evolutionary biology, the viewpoint presented here only means to add flesh to the standard evolutionary synthesis.

Armour GE, Mackay TFC, Anholt RRH. Epistatic partners of neurogenic genes modulate Drosophila olfactory behavior

The extent to which epistasis affects the genetic architecture of complex traits is difficult to quantify, and identifying variants in natural populations with epistatic interactions is challenging. Previous studies in Drosophila implicated extensive epistasis between variants in genes that affect neural connectivity and contribute to natural variation in olfactory response to benzaldehyde. In this study, we implemented a powerful screen to quantify the extent of epistasis as well as identify candidate interacting variants using 203 inbred wild-derived lines with sequenced genomes of the Drosophila melanogaster Genetic Reference Panel (DGRP). We crossed the DGRP lines to P[GT1]-element insertion mutants in Sema-5c and neuralized (neur), two neurodevelopmental loci which affect olfactory behavior, and to their coisogenic wild-type control. We observed significant variation in olfactory responses to benzaldehyde among F1 genotypes and for the DGRP line by mutant genotype interactions for both loci, showing extensive nonadditive genetic variation. We performed genome-wide association analyses to identify the candidate modifier loci. None of these polymorphisms were in or near the focal genes; therefore, epistasis is the cause of the nonadditive genetic variance. Candidate genes could be placed in interaction networks. Several candidate modifiers are associated with neural development. Analyses of mutants of candidate epistatic partners with neur (merry-go-round (mgr), prospero (pros), CG10098, Alhambra (Alh) and CG12535) and Sema-5c (CG42540 and bruchpilot (brp)) showed aberrant olfactory responses compared with coisogenic controls. Thus, integrating genome-wide analyses of natural variants with mutations at defined genomic locations in a common coisogenic background can unmask specific epistatic modifiers of behavioral phenotypes.

Population genetic evidence for cold adaptation in European Drosophila melanogaster populations

We studied Drosophila melanogaster populations from Europe (the Netherlands and France) and Africa (Rwanda and Zambia) to uncover genetic evidence of adaptation to cold. We present here four lines of evidence for genes involved in cold adaptation from four perspectives: (i) the frequency of SNPs at genes previously known to be associated with chill-coma recovery time (CCRT), startle reflex (SR) and resistance to starvation stress (RSS) vary along environmental gradients and therefore among populations; (ii) SNPs of genes that correlate significantly with latitude and altitude in African and European populations overlap with SNPs that correlate with a latitudinal cline from North America; (iii) at the genomewide level, the top candidate genes are enriched in gene ontology (GO) terms that are related to cold tolerance; (iv) GO enriched terms from North American clinal genes overlap significantly with those from Africa and Europe. Each SNP was tested in 10 independent runs of Bayenv2, using the median Bayes factors to ascertain candidate genes. None of the candidate genes were found close to the breakpoints of cosmopolitan inversions, and only four candidate genes were linked to QTLs related to CCRT. To overcome the limitation that we used only four populations to test correlations with environmental gradients, we performed simulations to estimate the power of our approach for detecting selection. Based on our results, we propose a novel network of genes that is involved in cold adaptation.

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).

Laboratory evolution of adenylyl cyclase independent learning in Drosophila and missing heritability

Gene interactions are acknowledged to be a likely source of missing heritability in large-scale genetic studies of complex neurological phenotypes. However, involvement of rare variants, de novo mutations, genetic lesions that are not easily detected with commonly used methods and epigenetic factors also are possible explanations. We used a laboratory evolution study to investigate the modulatory effects of background genetic variation on the phenotypic effect size of a null mutation with known impact on olfactory learning. To accomplish this, we first established a population that contained variation at just 23 loci and used selection to evolve suppression of the learning defect seen with null mutations in the rutabaga adenylyl cyclase. We thus biased the system to favor relatively simplified outcomes by choosing a Mendelian trait and by restricting the genetic variation segregating in the population. This experimental design also assures that the causal effects are among the known 23 segregating loci. We observe a robust response to selection that requires the presence of the 23 variants. Analyses of the underlying genotypes showed that interactions between more than two loci are likely to be involved in explaining the selection response, with implications for the missing heritability problem.

Extensive epistasis for olfactory behaviour, sleep and waking activity in Drosophila melanogaster

Epistasis is an important feature of the genetic architecture of quantitative traits, but the dynamics of epistatic interactions in natural populations and the relationship between epistasis and pleiotropy remain poorly understood. Here, we studied the effects of epistatic modifiers that segregate in a wild-derived Drosophila melanogaster population on the mutational effects of P-element insertions in Semaphorin-5C (Sema-5c) and Calreticulin (Crc), pleiotropic genes that affect olfactory behaviour and startle behaviour and, in the case of Crc, sleep phenotypes. We introduced Canton-S B (CSB) third chromosomes with or without a P-element insertion at the Crc or Sema-5c locus in multiple wild-derived inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and assessed the effects of epistasis on the olfactory response to benzaldehyde and, for Crc, also on sleep. In each case, we found substantial epistasis and significant variation in the magnitude of epistasis. The predominant direction of epistatic effects was to suppress the mutant phenotype. These observations support a previous study on startle behaviour using the same D. melanogaster chromosome substitution lines, which concluded that suppressing epistasis may buffer the effects of new mutations. However, epistatic effects are not correlated among the different phenotypes. Thus, suppressing epistasis appears to be a pervasive general feature of natural populations to protect against the effects of new mutations, but different epistatic interactions modulate different phenotypes affected by mutations at the same pleiotropic gene.

Genes involved in sex pheromone discrimination in Drosophila melanogaster and their background-dependent effect

Mate choice is based on the comparison of the sensory quality of potential mating partners, and sex pheromones play an important role in this process. In Drosophila melanogaster, contact pheromones differ between male and female in their content and in their effects on male courtship, both inhibitory and stimulatory. To investigate the genetic basis of sex pheromone discrimination, we experimentally selected males showing either a higher or lower ability to discriminate sex pheromones over 20 generations. This experimental selection was carried out in parallel on two different genetic backgrounds: wild-type and desat1 mutant, in which parental males showed high and low sex pheromone discrimination ability respectively. Male perception of male and female pheromones was separately affected during the process of selection. A comparison of transcriptomic activity between high and low discrimination lines revealed genes not only that varied according to the starting genetic background, but varied reciprocally. Mutants in two of these genes, Shaker and quick-to-court, were capable of producing similar effects on discrimination on their own, in some instances mimicking the selected lines, in others not. This suggests that discrimination of sex pheromones depends on genes whose activity is sensitive to genetic context and provides a rare, genetically defined example of the phenomenon known as “allele flips,” in which interactions have reciprocal effects on different genetic backgrounds.

What is complex about complex disorders?

Rather than being polygenic, complex disorders probably represent umbrella terms for collections of conditions caused by rare, recent mutations in any of a large number of different genes.

Making scents of behavioural genetics: lessons from Drosophila

The expression of behaviours is influenced by many segregating genes. Behaviours are, therefore, complex traits. They have, however, unique characteristics that set them apart from physiological and morphological quantitative traits. First, behaviours are the ultimate expression of the nervous system. This means that understanding the genetic underpinnings of behaviours requires a neurobiological context, i.e. an understanding of the genes-brain-behaviour axis. In other words, how do ensembles of genes empower specific neural circuits to drive behaviours? Second, behaviours represent the interface between an organism and its environment. Thus, environmental effects are likely to make substantial contributions to determining behavioural outputs and genotype-by-environment interactions are expected to be prominent. It is important to differentiate between genes that contribute to the manifestation of the behavioural phenotype and genes that contribute to phenotypic variation in behaviour. The former are identified by classical mutagenesis experiments, whereas the latter can be detected through quantitative genetic approaches. Genes that contribute to phenotypic variation in behaviour harbour polymorphisms that provide the substrates for evolution. This review focuses on olfactory behaviour in Drosophila with the goal to illustrate how fundamental insights derived from studies on chemosensation can be applied to a wide range of behavioural phenotypes.

Molecular mechanisms of epistasis within and between genes

'Disease-causing' mutations do not cause disease in all individuals. One possible important reason for this is that the outcome of a mutation can depend upon other genetic variants in a genome. These epistatic interactions between mutations occur both within and between molecules, and studies in model organisms show that they are extremely prevalent. However, epistatic interactions are still poorly understood at the molecular level, and consequently difficult to predict de novo. Here I provide an overview of our current understanding of the molecular mechanisms that can cause epistasis, and areas where more research is needed. A more complete understanding of epistasis will be vital for making accurate predictions about the phenotypes of individuals.

Attributing functions to genes and gene products

A major focus of modern biochemical, biophysical and cell biological research is the attribution of function to elements of structure: gene products, genes and higher-order cellular structures. Misunderstandings and controversies can arise in connection with such assignments, in part because of the logical complexity inherent in the relating of structure to function and the failure to distinguish clearly among the different senses in which function can be imputed to elements of structure. I explore distinct ways in which functions are connected to structures and factors that contribute to the context-dependence of such associations so that the multiple senses of function can be made explicit.

Mutations and quantitative genetic variation: lessons from Drosophila

A central issue in evolutionary quantitative genetics is to understand how genetic variation for quantitative traits is maintained in natural populations. Estimates of genetic variation and of genetic correlations and pleiotropy among multiple traits, inbreeding depression, mutation rates for fitness and quantitative traits and of the strength and nature of selection are all required to evaluate theoretical models of the maintenance of genetic variation. Studies in Drosophila melanogaster have shown that a substantial fraction of segregating variation for fitness-related traits in Drosophila is due to rare deleterious alleles maintained by mutation-selection balance, with a smaller but significant fraction attributable to intermediate frequency alleles maintained by alleles with antagonistic pleiotropic effects, and late-age-specific effects. However, the nature of segregating variation for traits under stabilizing selection is less clear and requires more detailed knowledge of the loci, mutation rates, allelic effects and frequencies of molecular polymorphisms affecting variation in suites of pleiotropically connected traits. Recent studies in D. melanogaster have revealed unexpectedly complex genetic architectures of many quantitative traits, with large numbers of pleiotropic genes and alleles with sex-, environment- and genetic background-specific effects. Future genome wide association analyses of many quantitative traits on a common panel of fully sequenced Drosophila strains will provide much needed empirical data on the molecular genetic basis of quantitative traits.

Effect of laboratory acclimation on the variation of reproduction-related characters in Drosophila melanogaster

The natural variation of sex-specific characters between populations can favor their behavioral isolation, eventually leading to the formation of new species. Marked variations for male courtship, mating and the production of sex pheromones – three complex characters potentially inducing sexual isolation – were found between Drosophila melanogaster populations of various origins acclimated for many generations in research laboratories. However, the natural variation of these three characters between natural populations and their evolution after long-term acclimation in the laboratory remains unknown. We measured many traits involved in these characters in six stocks initiated with distinct populations sampled in a restricted geographic area. Several sex-specific traits varied between stocks freshly brought back to the laboratory. After 100 generations spent in the laboratory without any experimental selection, traits varied in a strain-dependent manner. This variation was not related to a reduction of their variance except for copulation duration. This indicates that reproduction-related characters can diverge between neighboring D. melanogaster populations, and differently adapt to stable laboratory conditions.

Enzyme promiscuity: a mechanistic and evolutionary perspective

Many, if not most, enzymes can promiscuously catalyze reactions, or act on substrates, other than those for which they evolved. Here, we discuss the structural, mechanistic, and evolutionary implications of this manifestation of infidelity of molecular recognition. We define promiscuity and related phenomena and also address their generality and physiological implications. We discuss the mechanistic enzymology of promiscuity--how enzymes, which generally exert exquisite specificity, catalyze other, and sometimes barely related, reactions. Finally, we address the hypothesis that promiscuous enzymatic activities serve as evolutionary starting points and highlight the unique evolutionary features of promiscuous enzyme functions.

Epistatic interactions attenuate mutations affecting startle behaviour in Drosophila melanogaster

Epistasis is an important feature of the genetic architecture of quantitative traits. Previously, we showed that startle-induced locomotor behaviour of Drosophila melanogaster, a critical survival trait, is highly polygenic and exhibits epistasis. Here, we characterize epistatic interactions among homozygous P-element mutations affecting startle-induced locomotion in the Canton-S isogenic background and in 21 wild-derived inbred genetic backgrounds. We find pervasive epistasis for pairwise combinations of homozygous P-element insertional mutations as well as for mutations in wild-derived backgrounds. In all cases, the direction of the epistatic effects is to suppress the mutant phenotypes. The magnitude of the epistatic interactions in wild-derived backgrounds is highly correlated with the magnitude of the main effects of mutations, leading to phenotypic robustness of the startle response in the face of deleterious mutations. There is variation in the magnitude of epistasis among the wild-derived genetic backgrounds, indicating evolutionary potential for enhancing or suppressing effects of single mutations. These results provide a partial glimpse of the complex genetic network underlying the genetic architecture of startle behaviour and provide empirical support for the hypothesis that suppressing epistasis is the mechanism underlying genetic canalization of traits under strong stabilizing selection. Widespread suppressing epistasis will lead to underestimates of the main effects of quantitative trait loci (QTLs) in mapping experiments when not explicitly accounted for. In addition, suppressing epistasis could lead to underestimates of mutational variation for quantitative traits and overestimates of the strength of stabilizing selection, which has implications for maintenance of variation of complex traits by mutation-selection balance.

The role of genetic variation in the causation of mental illness: an evolution-informed framework

The apparently large genetic contribution to the aetiology of mental illness presents a formidable puzzle. Unlike common physical disorders, mental illness usually has an onset early in the reproductive age and is associated with substantial reproductive disadvantage. Therefore, genetic variants associated with vulnerability to mental illness should be under strong negative selection pressure and be eliminated from the genetic pool through natural selection. Still, mental disorders are common and twin studies indicate a strong genetic contribution to their aetiology. Several theories have been advanced to explain the paradox of high heritability and reproductive disadvantage associated with the same common phenotype, but none provides a satisfactory explanation for all types of mental illness. At the same time, identification of the molecular substrate underlying the large genetic contribution to the aetiology of mental illness is proving more difficult than expected. The quest for genetic variants associated with vulnerability to mental illness is predicated upon the common disease/common variant (CDCV) hypothesis. On the basis of a summary of evidence, it is concluded that the CDCV hypothesis is untenable for most types of mental illness. An alternative evolution-informed framework is proposed, which suggests that gene-environment interactions and rare genetic variants constitute most of the genetic contribution to mental illness. Common mental illness with mild reproductive disadvantage is likely to have a large contribution from interactions between common genetic variants and environmental exposures. Severe mental illness that confers strong reproductive disadvantage is likely to have a large and pleiotropic contribution from rare variants of recent origin. This framework points to a need for a paradigm change in genetic research to enable major progress in elucidating the aetiology of mental illness.

Ion channels to inactivate neurons in Drosophila

Ion channels are the determinants of excitability; therefore, manipulation of their levels and properties provides an opportunity for the investigator to modulate neuronal and circuit function. There are a number of ways to suppress electrical activity in Drosophila neurons, for instance, over-expression of potassium channels (i.e. Shaker Kv1, Shaw Kv3, Kir2.1 and DORK) that are open at resting membrane potential. This will result in increased potassium efflux and membrane hyperpolarisation setting resting membrane potential below the threshold required to fire action potentials. Alternatively over-expression of other channels, pumps or co-transporters that result in a hyperpolarised membrane potential will also prevent firing. Lastly, neurons can be inactivated by, disrupting or reducing the level of functional voltage-gated sodium (Nav1 paralytic) or calcium (Cav2 cacophony) channels that mediate the depolarisation phase of action potentials. Similarly, strategies involving the opposite channel manipulation should allow net depolarisation and hyperexcitation in a given neuron. These changes in ion channel expression can be brought about by the versatile transgenic (i.e. Gal4/UAS based) systems available in Drosophila allowing fine temporal and spatial control of (channel) transgene expression. These systems are making it possible to electrically inactivate (or hyperexcite) any neuron or neural circuit in the fly brain, and much like an exquisite lesion experiment, potentially elucidate whatever interesting behaviour or phenotype each network mediates. These techniques are now being used in Drosophila to reprogram electrical activity of well-defined circuits and bring about robust and easily quantifiable changes in behaviour, allowing different models and hypotheses to be rapidly tested.

The Drosophila foraging gene mediates adult plasticity and gene-environment interactions in behaviour, metabolites, and gene expression in response to food deprivation

Nutrition is known to interact with genotype in human metabolic syndromes, obesity, and diabetes, and also in Drosophila metabolism. Plasticity in metabolic responses, such as changes in body fat or blood sugar in response to changes in dietary alterations, may also be affected by genotype. Here we show that variants of the foraging (for) gene in Drosophila melanogaster affect the response to food deprivation in a large suite of adult phenotypes by measuring gene by environment interactions (GEI) in a suite of food-related traits. for affects body fat, carbohydrates, food-leaving behavior, metabolite, and gene expression levels in response to food deprivation. This results in broad patterns of metabolic, genomic, and behavioral gene by environment interactions (GEI), in part by interaction with the insulin signaling pathway. Our results show that a single gene that varies in nature can have far reaching effects on behavior and metabolism by acting through multiple other genes and pathways.

The genetics of quantitative traits: challenges and prospects

A major challenge in current biology is to understand the genetic basis of variation for quantitative traits. We review the principles of quantitative trait locus mapping and summarize insights about the genetic architecture of quantitative traits that have been obtained over the past decades. We are currently in the midst of a genomic revolution, which enables us to incorporate genetic variation in transcript abundance and other intermediate molecular phenotypes into a quantitative trait locus mapping framework. This systems genetics approach enables us to understand the biology inside the 'black box' that lies between genotype and phenotype in terms of causal networks of interacting genes.

Reliable neuromodulation from circuits with variable underlying structure

Recent work argues that similar network performance can result from highly variable sets of network parameters, raising the question of whether neuromodulation can be reliable across individuals with networks with different sets of synaptic strengths and intrinsic membrane conductances. To address this question, we used the dynamic clamp to construct 2-cell reciprocally inhibitory networks from gastric mill (GM) neurons of the crab stomatogastric ganglion. When the strength of the artificial inhibitory synapses (g(syn)) and the conductance of an artificial I(h) (g(h)) were varied with the dynamic clamp, a variety of network behaviors resulted, including regions of stable alternating bursting. Maps of network output as a function of g(syn) and g(h) were constructed in normal saline and again in the presence of serotonin or oxotremorine. Both serotonin and oxotremorine depolarize and excite isolated individual GM neurons, but by different cellular mechanisms. Serotonin and oxotremorine each increased the size of the parameter regions that supported alternating bursting, and, on average, increased burst frequency. Nonetheless, in both cases some parameter sets within the sample space deviated from the mean population response and decreased in frequency. These data provide insight into why pharmacological treatments that work in most individuals can generate anomalous actions in a few individuals, and they have implications for understanding the evolution of nervous systems.

Genetic architecture of quantitative traits in mice, flies, and humans

We compare and contrast the genetic architecture of quantitative phenotypes in two genetically well-characterized model organisms, the laboratory mouse, Mus musculus, and the fruit fly, Drosophila melanogaster, with that found in our own species from recent successes in genome-wide association studies. We show that the current model of large numbers of loci, each of small effect, is true for all species examined, and that discrepancies can be largely explained by differences in the experimental designs used. We argue that the distribution of effect size of common variants is the same for all phenotypes regardless of species, and we discuss the importance of epistasis, pleiotropy, and gene by environment interactions. Despite substantial advances in mapping quantitative trait loci, the identification of the quantitative trait genes and ultimately the sequence variants has proved more difficult, so that our information on the molecular basis of quantitative variation remains limited. Nevertheless, available data indicate that many variants lie outside genes, presumably in regulatory regions of the genome, where they act by altering gene expression. As yet there are very few instances where homologous quantitative trait loci, or quantitative trait genes, have been identified in multiple species, but the availability of high-resolution mapping data will soon make it possible to test the degree of overlap between species.

Shadows of complexity: what biological networks reveal about epistasis and pleiotropy

Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene-gene interaction, has also been treated as an exception to the Mendelian one gene-one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. These phenomena should not be treated as exceptions, but rather as fundamental components of genetic analyses. A systems level understanding of epistasis and pleiotropy is, therefore, critical to furthering our understanding of human genetics and its contribution to common human disease. Finally, graph theory offers an intuitive and powerful set of tools with which to study the network bases of these important genetic phenomena.

Network features of the mammalian circadian clock

The mammalian circadian clock is a cell-autonomous system that drives oscillations in behavior and physiology in anticipation of daily environmental change. To assess the robustness of a human molecular clock, we systematically depleted known clock components and observed that circadian oscillations are maintained over a wide range of disruptions. We developed a novel strategy termed Gene Dosage Network Analysis (GDNA) in which small interfering RNA (siRNA)-induced dose-dependent changes in gene expression were used to build gene association networks consistent with known biochemical constraints. The use of multiple doses powered the analysis to uncover several novel network features of the circadian clock, including proportional responses and signal propagation through interacting genetic modules. We also observed several examples where a gene is up-regulated following knockdown of its paralog, suggesting the clock network utilizes active compensatory mechanisms rather than simple redundancy to confer robustness and maintain function. We propose that these network features act in concert as a genetic buffering system to maintain clock function in the face of genetic and environmental perturbation.

Strain-dependent differences in several reproductive traits are not accompanied by early postmating transcriptome changes in female Drosophila melanogaster

Upon mating, Drosophila melanogaster females undergo numerous alterations in their behavior and reproductive physiology that are accompanied by small-magnitude transcript-level changes in up to 1700 genes. Many of these postmating transcriptome changes are the direct result of the sperm and seminal fluid proteins (Acps) that females receive from their mates. To begin to determine if the genetic background of the female's mate contributes to the previously described gene expression changes, we assessed whether interactions between the genotypes of two commonly used laboratory strains of D. melanogaster (Canton-S and Oregon R) influence the female's postmating transcriptome as well as several pre- and postcopulatory phenotypes. We find negligible differences in the female's transcriptome at 1-3 hr postmating regardless of the strain of the male with whom she mated. However, a male x female genotype interaction significantly influenced mate selection, and, in some cases, fecundity, fertility, and hatchability. Our data support previous work suggesting that many of the early postmating changes observed in D. melanogaster females are not caused by large modifications of transcript levels. Instead, early postmating phenotypes result from preexisting receptors or pathways that are already in place upon sexual maturity.

Genomic consequences of background effects on scalloped mutant expressivity in the wing of Drosophila melanogaster

Genetic background effects contribute to the phenotypic consequences of mutations and are pervasive across all domains of life that have been examined, yet little is known about how they modify genetic systems. In part this is due to the lack of tractable model systems that have been explicitly developed to study the genetic and evolutionary consequences of background effects. In this study we demonstrate that phenotypic expressivity of the scalloped(E3) (sd(E3)) mutation of Drosophila melanogaster is background dependent and is the result of at least one major modifier segregating between two standard lab wild-type strains. We provide evidence that at least one of the modifiers is linked to the vestigial region and demonstrate that the background effects modify the spatial distribution of known sd target genes in a genotype-dependent manner. In addition, microarrays were used to examine the consequences of genetic background effects on the global transcriptome. Expression differences between wild-type strains were found to be as large as or larger than the effects of mutations with substantial phenotypic effects, and expression differences between wild type and mutant varied significantly between genetic backgrounds. Significantly, we demonstrate that the epistatic interaction between sd(E3) and an optomotor blind mutation is background dependent. The results are discussed within the context of developing a complex but more realistic view of the consequences of genetic background effects with respect to mutational analysis and studies of epistasis and cryptic genetic variation segregating in natural populations.

The implications of gene-environment interactions in depression: will cause inform cure?

In a number of human diseases, including depression, interactions between genetic and environmental factors have been identified in the absence of direct genotype-disorder associations. The lack of genes with major direct pathogenic effect suggests that genotype-specific vulnerabilities are balanced by adaptive advantages and implies aetiological heterogeneity. A model of depression is proposed that incorporates the interacting genetic and environmental factors over the life course and provides an explanatory framework for the heterogeneous aetiology of depression. Early environmental influences act on the genome to shape the adaptability to environmental changes in later life. The possibility is explored that genotype- and epigenotype-related traits can be harnessed to develop personalized therapeutic interventions. As diagnosis of depression alone is a weak predictor of response to specific treatments, aetiological subtypes can be used to inform the choice between treatments. As a specific application of this notion, a hypothesis is proposed regarding relative responsiveness of aetiological subtypes of depression to psychological treatment and antidepressant medication. Other testable predictions are likely to emerge from the general framework of interacting genetic, epigenetic and environmental mechanisms in depression.

Developmental systems biology flourishing on new technologies

Organism development is a systems level process. It has benefited greatly from the recent technological advances in the field of systems biology. DNA microarray, phenome, interactome and transcriptome mapping, the new generation of deep sequencing technologies, and faster and better computational and modeling approaches have opened new frontiers for both systems biologists and developmental biologists to reexamine the old developmental biology questions, such as pattern formation, and to tackle new problems, such as stem cell reprogramming. As showcased in the International Developmental Systems Biology Symposium organized by Chinese Academy of Sciences, developmental systems biology is flourishing in many perspectives, from the evolution of developmental systems, to the underlying genetic and molecular pathways and networks, to the genomic, epigenomic and noncoding levels, to the computational analysis and modeling. We believe that the field will continue to reap rewards into the future with these new approaches.

Neurogenetic networks for startle-induced locomotion in Drosophila melanogaster

Understanding how the genome empowers the nervous system to express behaviors remains a critical challenge in behavioral genetics. The startle response is an attractive behavioral model for studies on the relationship between genes, brain, and behavior, as the ability to respond rapidly to harmful changes in the environment is a universal survival trait. Drosophila melanogaster provides a powerful system in which genetic studies on individuals with controlled genetic backgrounds and reared under controlled environmental conditions can be combined with neuroanatomical studies to analyze behaviors. In a screen of 720 lines of D. melanogaster, carrying single P[GT1] transposon insertions, we found 267 lines that showed significant changes in startle-induced locomotor behavior. Excision of the transposon reversed this effect in five lines out of six tested. We infer that most of the 267 lines show mutant effects on startle-induced locomotion that are caused by the transposon insertions. We selected a subset of 15 insertions in the same genetic background in autosomal genes with strong mutant effects and crossed them to generate all 105 possible nonreciprocal double heterozygotes. These hybrids revealed an extensive network of epistatic interactions on the behavioral trait. In addition, we observed changes in neuroanatomy that were caused by these 15 mutations, individually and in their double heterozygotes. We find that behavioral and neuroanatomical phenotypes are determined by a common set of genes that are organized as partially overlapping genetic networks.

Revealing the architecture of gene regulation: the promise of eQTL studies

Expression quantitative trait loci (eQTL) mapping studies have become a widely used tool for identifying genetic variants that affect gene regulation. In these studies, expression levels are viewed as quantitative traits, and gene expression phenotypes are mapped to particular genomic loci by combining studies of variation in gene expression patterns with genome-wide genotyping. Results from recent eQTL mapping studies have revealed substantial heritable variation in gene expression within and between populations. In many cases, genetic factors that influence gene expression levels can be mapped to proximal (putatively cis) eQTLs and, less often, to distal (putatively trans) eQTLs. Beyond providing great insight into the biology of gene regulation, a combination of eQTL studies with results from traditional linkage or association studies of human disease may help predict a specific regulatory role for polymorphic sites previously associated with disease.

Long-term adaptation of epistatic genetic networks

Gene networks are likely to govern most traits in nature. Mutations at these genes often show functional epistatic interactions that lead to complex genetic architectures and variable fitness effects in different genetic backgrounds. Understanding how epistatic genetic systems evolve in nature remains one of the great challenges in evolutionary biology. Here we combine an analytical framework with individual-based simulations to generate novel predictions about long-term adaptation of epistatic networks. We find that relative to traits governed by independently evolving genes, adaptation with epistatic gene networks is often characterized by longer waiting times to selective sweeps, lower standing genetic variation, and larger fitness effects of adaptive mutations. This may cause epistatic networks to either adapt more slowly or more quickly relative to a nonepistatic system. Interestingly, epistatic networks may adapt faster even when epistatic effects of mutations are on average deleterious. Further, we study the evolution of epistatic properties of adaptive mutations in gene networks. Our results show that adaptive mutations with small fitness effects typically evolve positive synergistic interactions, whereas adaptive mutations with large fitness effects evolve positive synergistic and negative antagonistic interactions at approximately equal frequencies. These results provide testable predictions for adaptation of traits governed by epistatic networks and the evolution of epistasis within networks.

Pleiotropic effects of Drosophila neuralized on complex behaviors and brain structure

Understanding how genotypic variation influences variation in brain structures and behavioral phenotypes represents a central challenge in behavioral genetics. In Drosophila melanogaster, the neuralized (neur) gene plays a key role in development of the nervous system. Different P-element insertional mutations of neur allow the development of viable and fertile adults with profoundly altered behavioral phenotypes that depend on the exact location of the inserted P element. The neur mutants exhibit reduced responsiveness to noxious olfactory and mechanosensory stimulation and increased aggression when limited food is presented after a period of food deprivation. These behavioral phenotypes are correlated with distinct structural changes in integrative centers in the brain, the mushroom bodies, and the ellipsoid body of the central complex. Transcriptional profiling of neur mutants revealed considerable overlap among ensembles of coregulated genes in the different mutants, but also distinct allele-specific differences. The diverse phenotypic effects arising from nearby P-element insertions in neur provide a new appreciation of the concept of allelic effects on phenotype, in which the wild type and null mutant are at the extreme ends of a continuum of pleiotropic allelic effects.

Microarray analysis of replicate populations selected against a wing-shape correlation in Drosophila melanogaster

We selected bidirectionally to change the phenotypic correlation between two wing dimensions in Drosophila melanogaster and measured gene expression differences in late third instar wing disks, using microarrays. We tested an array of 12 selected lines, including 10 from a Massachusetts population (5 divergently selected pairs) and 2 from a California population (1 divergently selected pair). In the Massachusetts replicates, 29 loci showed consistent, significant expression differences in all 5 line-pair comparisons. However, the significant loci in the California lines were almost completely different from these. The disparity between responding genes in different gene pools confirms recent evidence that surprisingly large numbers of loci can affect wing shape. Our results also show that with well-replicated selection lines, of large effective size, the numbers of candidate genes in microarray-based searches can be reduced to realistic levels.

Phenotypic evolution from genetic polymorphisms in a radial network architecture

Background

The genetic architecture of a quantitative trait influences the phenotypic response to natural or artificial selection. One of the main objectives of genetic mapping studies is to identify the genetic factors underlying complex traits and understand how they contribute to phenotypic expression. Presently, we are good at identifying and locating individual loci with large effects, but there is a void in describing more complex genetic architectures. Although large networks of connected genes have been reported, there is an almost complete lack of information on how polymorphisms in these networks contribute to phenotypic variation and change. To date, most of our understanding comes from theoretical, model-based studies, and it remains difficult to assess how realistic their conclusions are as they lack empirical support.

Results

A previous study provided evidence that nearly half of the difference in eight-week body weight between two divergently selected lines of chickens was a result of four loci organized in a 'radial' network (one central locus interacting with three 'radial' loci that, in turn, only interacted with the central locus). Here, we study the relationship between phenotypic change and genetic polymorphism in this empirically detected network. We use a model-free approach to study, through individual-based simulations, the dynamic properties of this polymorphic and epistatic genetic architecture. The study provides new insights to how epistasis can modify the selection response, buffer and reveal effects of major loci leading to a progressive release of genetic variation. We also illustrate the difficulty of predicting genetic architecture from observed selection response, and discuss mechanisms that might lead to misleading conclusions on underlying genetic architectures from quantitative trait locus (QTL) experiments in selected populations.

Conclusion

Considering both molecular (QTL) and phenotypic (selection response) data, as suggested in this work, provides additional insights into the genetic mechanisms involved in the response to selection. Such dissection of genetic architectures and in-depth studies of their ability to contribute to short- or long-term selection response represents an important step towards a better understanding of the genetic bases of complex traits and, consequently, of the evolutionary properties of populations.