Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster

Leger RJ. Latitudinal Clines in Climate and Sleep Patterns Shape Disease Outcomes in Drosophila melanogaster Infected by Metarhizium anisopliae

Major latitudinal clines have been observed in Drosophila melanogaster, a human commensal that originated in tropical Africa and has subsequently dispersed globally to colonize temperate habitats. However, despite the crucial role pathogens play in species distribution, our understanding of how geographical factors influence disease susceptibility remains limited. This investigation explored the effects of latitudinal clines and biomes on disease resistance using the common fly pathogen Metarhizium anisopliae and 43 global Drosophila melanogaster populations. The findings revealed correlations between disease resistance and latitudinal gradients of sleep duration, temperature, and humidity. Although enhanced defenses may be driven by fungal diversity at tropical latitudes, the most disease-resistant tropical males also showed the highest susceptibility to desiccation. This suggests potential trade-offs between abiotic stress resistance, necessary for survival in temperate habitats, and disease resistance. Furthermore, the study uncovered interactions between sex, mating status, sleep, and abiotic stresses, affecting disease resistance. Notably, longer-sleeping males and virgin flies survived infections longer, with additional daytime sleep post-infection being protective, particularly in the most resistant fly lines. These observations support the hypothesis that sleep and disease defense are intertwined traits linked to organismal fitness and subject to joint clinal evolution.

A first characterization of the microbiota-resilience link in swine

BACKGROUND

The gut microbiome plays a crucial role in understanding complex biological mechanisms, including host resilience to stressors. Investigating the microbiota-resilience link in animals and plants holds relevance in addressing challenges like adaptation of agricultural species to a warming environment. This study aims to characterize the microbiota-resilience connection in swine. As resilience is not directly observable, we estimated it using four distinct indicators based on daily feed consumption variability, assuming animals with greater intake variation may face challenges in maintaining stable physiological status. These indicators were analyzed both as linear and categorical variables. In our first set of analyses, we explored the microbiota-resilience link using PERMANOVA, α-diversity analysis, and discriminant analysis. Additionally, we quantified the ratio of estimated microbiota variance to total phenotypic variance (microbiability). Finally, we conducted a Partial Least Squares-Discriminant Analysis (PLS-DA) to assess the classification performance of the microbiota with indicators expressed in classes.

RESULTS

This study offers four key insights. Firstly, among all indicators, two effectively captured resilience. Secondly, our analyses revealed robust relationship between microbial composition and resilience in terms of both composition and richness. We found decreased α-diversity in less-resilient animals, while specific amplicon sequence variants (ASVs) and KEGG pathways associated with inflammatory responses were negatively linked to resilience. Thirdly, considering resilience indicators in classes, we observed significant differences in microbial composition primarily in animals with lower resilience. Lastly, our study indicates that gut microbial composition can serve as a reliable biomarker for distinguishing individuals with lower resilience.

CONCLUSION

Our comprehensive analyses have highlighted the host-microbiota and resilience connection, contributing valuable insights to the existing scientific knowledge. The practical implications of PLS-DA and microbiability results are noteworthy. PLS-DA suggests that host-microbiota interactions could be utilized as biomarkers for monitoring resilience. Furthermore, the microbiability findings show that leveraging host-microbiota insights may improve the identification of resilient animals, supporting their adaptive capacity in response to changing environmental conditions. These practical implications offer promising avenues for enhancing animal well-being and adaptation strategies in the context of environmental challenges faced by livestock populations. Video Abstract.

Genetic basis and repeatability for desiccation resistance in Drosophila melanogaster (Diptera: Drosophilidae)

Dehydration is a stress factor for organisms inhabiting natural habitats where water is scarce. Thus, it may be expected that species facing arid environments will develop mechanisms that maximize resistance to desiccation. Insects are excellent models for studying the effects of dehydration as well as the mechanisms and processes that prevent water loss since the effect of desiccation is greater due to the higher area/volume ratio than larger animals. Even though physiological and behavioral mechanisms to cope with desiccation are being understood, the genetic basis underlying the mechanisms related to variation in desiccation resistance and the context-dependent effect remain unsolved. Here we analyze the genetic bases of desiccation resistance in Drosophila melanogaster and identify candidate genes that underlie trait variation. Our quantitative genetic analysis of desiccation resistance revealed sexual dimorphism and extensive genetic variation. The phenotype-genotype association analyses (GWAS) identified 71 candidate genes responsible for total phenotypic variation in desiccation resistance. Half of these candidate genes were sex-specific suggesting that the genetic architecture underlying this adaptive trait differs between males and females. Moreover, the public availability of desiccation data analyzed on the same lines but in a different lab allows us to investigate the reliability and repeatability of results obtained in independent screens. Our survey indicates a pervasive micro-environment lab-dependent effect since we did not detect overlap in the sets of genes affecting desiccation resistance identified between labs.

Feedback control of organ size precision is mediated by BMP2-regulated apoptosis in the Drosophila eye

Biological processes are intrinsically noisy, and yet, the result of development-like the species-specific size and shape of organs-is usually remarkably precise. This precision suggests the existence of mechanisms of feedback control that ensure that deviations from a target size are minimized. Still, we have very limited understanding of how these mechanisms operate. Here, we investigate the problem of organ size precision using the Drosophila eye. The size of the adult eye depends on the rates at which eye progenitor cells grow and differentiate. We first find that the progenitor net growth rate results from the balance between their proliferation and apoptosis, with this latter contributing to determining both final eye size and its variability. In turn, apoptosis of progenitor cells is hampered by Dpp, a BMP2/4 signaling molecule transiently produced by early differentiating retinal cells. Our genetic and computational experiments show how the status of retinal differentiation is communicated to progenitors through the differentiation-dependent production of Dpp, which, by adjusting the rate of apoptosis, exerts a feedback control over the net growth of progenitors to reduce final eye size variability.

Plasticity in growth is genetically variable and highly conserved across spatial scales in a Mediterranean pine

Phenotypic plasticity is a main mechanism for sessile organisms to cope with changing environments. Plasticity is genetically based and can evolve under natural selection so that populations within a species show distinct phenotypic responses to environment. An important question that remains elusive is whether the intraspecific variation in plasticity at different spatial scales is independent from each other. To test whether variation in plasticity to macro- and micro-environmental variation is related among each other, we used growth data of 25 Pinus pinaster populations established in seven field common gardens in NW Spain. Phenotypic plasticity to macro-environmental variation was estimated across test sites while plasticity to micro-environmental variation was estimated by using semivariography and kriging for modeling within-site heterogeneity. We provide empirical evidence of among-population variation in the magnitude of plastic responses to both micro- and macro-environmental variation. Importantly, we found that such responses were positively correlated across spatial scales. Selection for plasticity at one scale of environmental variation may impact the expression of plasticity at other scales, having important consequences on the ability of populations to buffer climate change. These results improve our understanding of the ecological drivers underlying the expression of phenotypic plasticity.

LTP2 hypomorphs show genotype-by-environment interaction in early seedling traits in Arabidopsis thaliana

Isogenic individuals can display seemingly stochastic phenotypic differences, limiting the accuracy of genotype-to-phenotype predictions. The extent of this phenotypic variation depends in part on genetic background, raising questions about the genes involved in controlling stochastic phenotypic variation. Focusing on early seedling traits in Arabidopsis thaliana, we found that hypomorphs of the cuticle-related gene LTP2 greatly increased variation in seedling phenotypes, including hypocotyl length, gravitropism and cuticle permeability. Many ltp2 hypocotyls were significantly shorter than wild-type hypocotyls while others resembled the wild type. Differences in epidermal properties and gene expression between ltp2 seedlings with long and short hypocotyls suggest a loss of cuticle integrity as the primary determinant of the observed phenotypic variation. We identified environmental conditions that reveal or mask the increased variation in ltp2 hypomorphs, and found that increased expression of its closest paralog LTP1 is necessary for ltp2 phenotypes. Our results illustrate how decreased expression of a single gene can generate starkly increased phenotypic variation in isogenic individuals in response to an environmental challenge.

Genomic prediction for grain yield and micro-environmental sensitivity in winter wheat

Individuals within a common environment experience variations due to unique and non-identifiable micro-environmental factors. Genetic sensitivity to micro-environmental variation (i.e. micro-environmental sensitivity) can be identified in residuals, and genotypes with lower micro-environmental sensitivity can show greater resilience towards environmental perturbations. Micro-environmental sensitivity has been studied in animals; however, research on this topic is limited in plants and lacking in wheat. In this article, we aimed to (i) quantify the influence of genetic variation on residual dispersion and the genetic correlation between genetic effects on (expressed) phenotypes and residual dispersion for wheat grain yield using a double hierarchical generalized linear model (DHGLM); and (ii) evaluate the predictive performance of the proposed DHGLM for prediction of additive genetic effects on (expressed) phenotypes and its residual dispersion. Analyses were based on 2,456 advanced breeding lines tested in replicated trials within and across different environments in Denmark and genotyped with a 15K SNP-Illumina-BeadChip. We found that micro-environmental sensitivity for grain yield is heritable, and there is potential for its reduction. The genetic correlation between additive effects on (expressed) phenotypes and dispersion was investigated, and we observed an intermediate correlation. From these results, we concluded that breeding for reduced micro-environmental sensitivity is possible and can be included within breeding objectives without compromising selection for increased yield. The predictive ability and variance inflation for predictions of the DHGLM and a linear mixed model allowing heteroscedasticity of residual variance in different environments (LMM-HET) were evaluated using leave-one-line-out cross-validation. The LMM-HET and DHGLM showed good and similar performance for predicting additive effects on (expressed) phenotypes. In addition, the accuracy of predicting genetic effects on residual dispersion was sufficient to allow genetic selection for resilience. Such findings suggests that DHGLM may be a good choice to increase grain yield and reduce its micro-environmental sensitivity.

Individual behavioral trajectories shape whole-brain connectivity in mice

It is widely assumed that our actions shape our brains and that the resulting connections determine who we are. To test this idea in a reductionist setting, in which genes and environment are controlled, we investigated differences in neuroanatomy and structural covariance by ex vivo structural magnetic resonance imaging in mice whose behavioral activity was continuously tracked for 3 months in a large, enriched environment. We confirmed that environmental enrichment increases mouse hippocampal volumes. Stratifying the enriched group according to individual longitudinal behavioral trajectories, however, revealed striking differences in mouse brain structural covariance in continuously highly active mice compared to those whose trajectories showed signs of habituating activity. Network-based statistics identified distinct subnetworks of murine structural covariance underlying these differences in behavioral activity. Together, these results reveal that differentiated behavioral trajectories of mice in an enriched environment are associated with differences in brain connectivity.

Genetic architecture of natural variation of cardiac performance from flies to humans

Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP). Genome-wide associations studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were used to gain insights as to the molecular and cellular processes affected. Non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict transcription factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart-specific knockdown. Additionally, we showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability was also associated with natural variation of gene regulatory networks. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans.

Precise Quantification of Behavioral Individuality From 80 Million Decisions Across 183,000 Flies

Individual animals behave differently from each other. This variability is a component of personality and arises even when genetics and environment are held constant. Discovering the biological mechanisms underlying behavioral variability depends on efficiently measuring individual behavioral bias, a requirement that is facilitated by automated, high-throughput experiments. We compiled a large data set of individual locomotor behavior measures, acquired from over 183,000 fruit flies walking in Y-shaped mazes. With this data set we first conducted a "computational ethology natural history" study to quantify the distribution of individual behavioral biases with unprecedented precision and examine correlations between behavioral measures with high power. We discovered a slight, but highly significant, left-bias in spontaneous locomotor decision-making. We then used the data to evaluate standing hypotheses about biological mechanisms affecting behavioral variability, specifically: the neuromodulator serotonin and its precursor transporter, heterogametic sex, and temperature. We found a variety of significant effects associated with each of these mechanisms that were behavior-dependent. This indicates that the relationship between biological mechanisms and behavioral variability may be highly context dependent. Going forward, automation of behavioral experiments will likely be essential in teasing out the complex causality of individuality.

Do I build or do I move? Adaptation by habitat construction versus habitat choice

Trait adaptation to a heterogeneous environment can occur through six modes: genetic differentiation of those traits, a jack-of-all-trades phenotypic uniformity, diversified bet-hedging, phenotypic plasticity, habitat choice, and habitat construction. A key question is what circumstances favor one mode over another, and how they might interact if a system can express more than one mode at a time. We examined the joint evolution of habitat choice and habitat construction using individual-based simulations. We manipulated when during the life cycle construction occurred and the fitness value of construction. We found that for our model habitat construction was nearly always favored over habitat choice, especially if construction happened after dispersal. Because of the ways that the various modes of adaptation interact with each other, there is no simple answer as to which will be favored; it depends on details of the biology and ecology of a given system.

Selection for environmental variance of litter size in rabbits involves genes in pathways controlling animal resilience

Background

Environmental variance (V_E) is partially under genetic control, which means that the V_E of individuals that share the same environment can differ because they have different genotypes. Previously, a divergent selection experiment for V_E of litter size (LS) during 13 generations in rabbit yielded a successful response and revealed differences in resilience between the divergent lines. The aim of the current study was to identify signatures of selection in these divergent lines to better understand the molecular mechanisms and pathways that control V_E of LS and animal resilience. Three methods (F_ST, ROH and varLD) were used to identify signatures of selection in a set of 473 genotypes from these rabbit lines (377) and a base population (96). A whole-genome sequencing (WGS) analysis was performed on 54 animals to detect genes with functional mutations.

Results

By combining signatures of selection and WGS data, we detected 373 genes with functional mutations in their transcription units, among which 111 had functions related to the immune system, stress response, reproduction and embryo development, and/or carbohydrate and lipid metabolism. The genes TTC23L, FBXL20, GHDC, ENSOCUG00000031631, SLC18A1, CD300LG, MC2R, and ENSOCUG00000006264 were particularly relevant, since each one carried a functional mutation that was fixed in one of the rabbit lines and absent in the other line. In the 3ʹUTR region of the MC2R and ENSOCUG00000006264 genes, we detected a novel insertion/deletion (INDEL) variant.

Conclusions

Our findings provide further evidence in favour of V_E as a measure of animal resilience. Signatures of selection were identified for V_E of LS in genes that have a functional mutation in their transcription units and are mostly implicated in the immune response and stress response pathways. However, the real implications of these genes for V_E and animal resilience will need to be assessed through functional analyses.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00653-y.

Using single-plant-omics in the field to link maize genes to functions and phenotypes

Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

Flying Together: Drosophila as a Tool to Understand the Genetics of Human Alcoholism

Alcohol use disorder (AUD) exacts an immense toll on individuals, families, and society. Genetic factors determine up to 60% of an individual's risk of developing problematic alcohol habits. Effective AUD prevention and treatment requires knowledge of the genes that predispose people to alcoholism, play a role in alcohol responses, and/or contribute to the development of addiction. As a highly tractable and translatable genetic and behavioral model organism, Drosophila melanogaster has proven valuable to uncover important genes and mechanistic pathways that have obvious orthologs in humans and that help explain the complexities of addiction. Vinegar flies exhibit remarkably strong face and mechanistic validity as a model for AUDs, permitting many advancements in the quest to understand human genetic involvement in this disease. These advancements occur via approaches that essentially fall into one of two categories: (1) discovering candidate genes via human genome-wide association studies (GWAS), transcriptomics on post-mortem tissue from AUD patients, or relevant physiological connections, then using reverse genetics in flies to validate candidate genes' roles and investigate their molecular function in the context of alcohol. (2) Utilizing flies to discover candidate genes through unbiased screens, GWAS, quantitative trait locus analyses, transcriptomics, or single-gene studies, then validating their translational role in human genetic surveys. In this review, we highlight the utility of Drosophila as a model for alcoholism by surveying recent advances in our understanding of human AUDs that resulted from these various approaches. We summarize the genes that are conserved in alcohol-related function between humans and flies. We also provide insight into some advantages and limitations of these approaches. Overall, this review demonstrates how Drosophila have and can be used to answer important genetic questions about alcohol addiction.

Schizophrenia: Developmental Variability Interacts with Risk Factors to Cause the Disorder: Nonspecific Variability-Enhancing Factors Combine with Specific Risk Factors to Cause Schizophrenia

A new etiological model is proposed for schizophrenia that combines variability-enhancing nonspecific factors acting during development with more specific risk factors. This model is better suited than the current etiological models of schizophrenia, based on the risk factors paradigm, for predicting and/or explaining several important findings about schizophrenia: high co-morbidity rates, low specificity of many risk factors, and persistence in the population of the associated genetic polymorphisms. Compared with similar models, e.g., de-canalization, common psychopathology factor, sexual-selection, or differential sensitivity to the environment, this proposal is more general and integrative. Recently developed research methods have proven the existence of genetic and environmental factors that enhance developmental variability. Applying such methods to newly collected or already available data can allow for testing the hypotheses upon which this model is built. If validated, this model may change the understanding of the etiology of schizophrenia, the research models, and preventionbrk paradigms.

Identification of functional mutations associated with environmental variance of litter size in rabbits

Background

Environmental variance (V_E) is partly under genetic control and has recently been proposed as a measure of resilience. Unravelling the genetic background of the V_E of complex traits could help to improve resilience of livestock and stabilize their production across farming systems. The objective of this study was to identify genes and functional mutations associated with variation in V_E of litter size (LS) in rabbits. To achieve this, we combined the results of a genome-wide association study (GWAS) and a whole-genome sequencing (WGS) analysis using data from two divergently selected rabbit lines for high and low V_E of LS. These lines differ in terms of biomarkers of immune response and mortality. Moreover, rabbits with a lower V_E of LS were found to be more resilient to infections than animals with a higher V_E of LS.

Results

By using two GWAS approaches (single-marker regression and Bayesian multiple-marker regression), we identified four genomic regions associated with V_E of LS, on chromosomes 3, 7, 10, and 14. We detected 38 genes in the associated genomic regions and, using WGS, we identified 129 variants in the splicing, UTR, and coding (missense and frameshift effects) regions of 16 of these 38 genes. These genes were related to the immune system, the development of sensory structures, and stress responses. All of these variants (except one) segregated in one of the rabbit lines and were absent (n = 91) or fixed in the other one (n = 37). The fixed variants were in the HDAC9, ITGB8, MIS18A, ENSOCUG00000021276 and URB1 genes. We also identified a 1-bp deletion in the 3′UTR region of the HUNK gene that was fixed in the low V_E line and absent in the high V_E line.

Conclusions

This is the first study that combines GWAS and WGS analyses to study the genetic basis of V_E. The new candidate genes and functional mutations identified in this study suggest that the V_E of LS is under the control of functions related to the immune system, stress response, and the nervous system. These findings could also explain differences in resilience between rabbits with homogeneous and heterogeneous V_E of litter size.

Patterns of environmental variance across environments and traits in domestic cattle

The variance in phenotypic trait values is a product of environmental and genetic variation. The sensitivity of traits to environmental variation has a genetic component and is likely to be under selection. However, there are few studies investigating the evolution of this sensitivity, in part due to the challenges of estimating the environmental variance. The livestock literature provides a wealth of studies that accurately partition components of phenotypic variance, including the environmental variance, in well-defined environments. These studies involve breeds that have been under strong selection on mean phenotype in optimal environments for many generations, and therefore represent an opportunity to study the potential evolution of trait sensitivity to environmental conditions. Here, we use literature on domestic cattle to examine the evolution of micro-environmental variance (CVR-the coefficient of residual variance) by testing for differences in expression of CVR in animals from the same breed reared in different environments. Traits that have been under strong selection did not follow a null expectation of an increase in CVR in heterogenous environments (e.g., grazing), a pattern that may reflect evolution of increased uniformity in heterogeneous environments. When comparing CVR across environments of different levels of optimality, here measured by trait mean, we found a reduction in CVR in the more optimal environments for both life history and growth traits. Selection aimed at increasing trait means in livestock breeds typically occurs in the more optimal environments, and we therefore suspect that the decreased CVR is a consequence of evolution of the expression of micro-environmental variance in this environment. Our results highlight the heterogeneity in micro-environmental variance across environments and point to possible connections to the intensity of selection on trait means.

Context-dependent genetic architecture of Drosophila life span

Understanding the genetic basis of variation in life span is a major challenge that is difficult to address in human populations. Evolutionary theory predicts that alleles affecting natural variation in life span will have properties that enable them to persist in populations at intermediate frequencies, such as late-life-specific deleterious effects, antagonistic pleiotropic effects on early and late-age fitness components, and/or sex- and environment-specific or antagonistic effects. Here, we quantified variation in life span in males and females reared in 3 thermal environments for the sequenced, inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and an advanced intercross outbred population derived from a subset of DGRP lines. Quantitative genetic analyses of life span and the micro-environmental variance of life span in the DGRP revealed significant genetic variance for both traits within each sex and environment, as well as significant genotype-by-sex interaction (GSI) and genotype-by-environment interaction (GEI). Genome-wide association (GWA) mapping in both populations implicates over 2,000 candidate genes with sex- and environment-specific or antagonistic pleiotropic allelic effects. Over 1,000 of these genes are associated with variation in life span in other D. melanogaster populations. We functionally assessed the effects of 15 candidate genes using RNA interference (RNAi): all affected life span and/or micro-environmental variance of life span in at least one sex and environment and exhibited sex-and environment-specific effects. Our results implicate novel candidate genes affecting life span and suggest that variation for life span may be maintained by variable allelic effects in heterogeneous environments.

The Evolution of Variance Control

Genetically identical individuals can be phenotypically variable, even in constant environmental conditions. The ubiquity of this phenomenon, known as 'intra-genotypic variability', is increasingly evident and the relevant mechanistic underpinnings are beginning to be understood. In parallel, theory has delineated a number of formal expectations for contexts in which such a feature would be adaptive. Here, we review empirical evidence across biological systems and theoretical expectations, including nonlinear averaging and bet hedging. We synthesize existing results to illustrate the dependence of selection outcomes both on trait characteristics, features of environmental variability, and species' demographic context. We conclude by discussing ways to bridge the gap between empirical evidence of intra-genotypic variability, studies demonstrating its genetic component, and evidence that it is adaptive.

The effect of environmental enrichment on behavioral variability depends on genotype, behavior, and type of enrichment

Non-genetic individuality in behavior, also termed intragenotypic variability, has been observed across many different organisms. A potential cause of intragenotypic variability is sensitivity to minute environmental differences during development, which are present even when major environmental parameters are kept constant. Animal enrichment paradigms often include the addition of environmental diversity, whether in the form of social interaction, novel objects or exploratory opportunities. Enrichment could plausibly affect intragenotypic variability in opposing ways: it could cause an increase in variability due to the increase in microenvironmental variation, or a decrease in variability due to elimination of aberrant behavior as animals are taken out of impoverished laboratory conditions. In order to test these hypothesis, we assayed five isogenic Drosophila melanogaster lines raised in control and mild enrichment conditions, and one isogenic line under both mild and intense enrichment conditions. We compared the mean and variability of six behavioral metrics between our enriched fly populations and the laboratory housing control. We found that enrichment often caused a small increase in variability across most of our behaviors, but that the ultimate effect of enrichment on both behavioral means and variabilities was highly dependent on genotype and its interaction with the particular enrichment treatment. Our results support previous work on enrichment that presents a highly variable picture of its effects on both behavior and physiology.

Stage- and thermal-specific genetic architecture for preadult viability in natural populations of Drosophila melanogaster

Studying the processes affecting variation for preadult viability is essential to understand the evolutionary trajectories followed by natural populations. This task requires focusing on the complex nature of the phenotype-genotype relationship by taking into account usually neglected aspects of the phenotype and recognizing the modularity between different ontogenetic stages. Here, we describe phenotypic variability for viability during the larval and pupal stages in lines derived from three natural populations of Drosophila melanogaster, as well as the variability for phenotypic plasticity and canalization at two different rearing temperatures. The results indicate that the three populations present significant phenotypic differences for preadult viability. Furthermore, distinct aspects of the phenotype (means, plasticity, canalization, plasticity of canalization) are affected by different genetic bases underlying changes in viability in a stage- and environment-specific manner. These findings explain the generalized maintenance of genetic variability for this fitness trait.

What can genetic association panels tell us about evolutionary processes in insects?

If we are to fully comprehend the evolution of insect diversity at a genomic level we need to understand how natural selection can alter genetically encoded characters within populations. Genetic association panels have the potential to be standard bearers in this endeavour. They enable the mapping of phenotypes to genotypes at unprecedented resolution while simultaneously providing population genomic samples that can be interrogated for the tell-tale signs of selection. Analyses of these panels promise to elucidate the entanglement of gene ontologies, pathways, developmental processes and evolutionary constraints, and inform how these are shaped by adaptation.

Genome-Wide Association Study of Circadian Behavior in Drosophila melanogaster

Circadian rhythms influence physiological processes from sleep–wake cycles to body temperature and are controlled by highly conserved cycling molecules. Although the mechanistic basis of the circadian clock has been known for decades, the extent to which circadian rhythms vary in nature and the underlying genetic basis for that variation is not well understood. We measured circadian period (Ʈ) and rhythmicity index in the Drosophila Genetic Reference Panel (DGRP) and observed extensive genetic variation in both. Seven DGRP lines had sexually dimorphic arrhythmicity and one line had an exceptionally long Ʈ. Genome-wide analyses identified 584 polymorphisms in 268 genes. We observed differences among transcripts for nine genes predicted to interact among themselves and canonical clock genes in the long period line and a control. Mutations/RNAi knockdown targeting these genes also affected circadian behavior. Our observations reveal that complex genetic interactions influence high levels of variation in circadian phenotypes.

Genetic basis of thermal plasticity variation in Drosophila melanogaster body size

Body size is a quantitative trait that is closely associated to fitness and under the control of both genetic and environmental factors. While developmental plasticity for this and other traits is heritable and under selection, little is known about the genetic basis for variation in plasticity that can provide the raw material for its evolution. We quantified genetic variation for body size plasticity in Drosophila melanogaster by measuring thorax and abdomen length of females reared at two temperatures from a panel representing naturally segregating alleles, the Drosophila Genetic Reference Panel (DGRP). We found variation between genotypes for the levels and direction of thermal plasticity in size of both body parts. We then used a Genome-Wide Association Study (GWAS) approach to unravel the genetic basis of inter-genotype variation in body size plasticity, and used different approaches to validate selected QTLs and to explore potential pleiotropic effects. We found mostly “private QTLs”, with little overlap between the candidate loci underlying variation in plasticity for thorax versus abdomen size, for different properties of the plastic response, and for size versus size plasticity. We also found that the putative functions of plasticity QTLs were diverse and that alleles for higher plasticity were found at lower frequencies in the target population. Importantly, a number of our plasticity QTLs have been targets of selection in other populations. Our data sheds light onto the genetic basis of inter-genotype variation in size plasticity that is necessary for its evolution.

Environmental conditions can influence development and lead to the production of phenotypes adjusted to the conditions adults will live in. This developmental plasticity, which can help organisms cope with environmental heterogeneity, is heritable and under selection. Its evolution will depend on available genetic variation. Using a panel of D. melanogaster flies representing naturally segregating alleles, we identified DNA sequence variants associated to variation in thermal plasticity for body size. We found that these variants correspond to a diverse set of functions and that their effects differ between body parts and properties of the thermal response. Our results shed new light onto the long discussed genes for plasticity.

The Sleep Inbred Panel, a Collection of Inbred Drosophila melanogaster with Extreme Long and Short Sleep Duration

Understanding how genomic variation causes differences in observable phenotypes remains a major challenge in biology. It is difficult to trace the sequence of events originating from genomic variants to changes in transcriptional responses or protein modifications. Ideally, one would conduct experiments with individuals that are at either extreme of the trait of interest, but such resources are often not available. Further, advances in genome editing will enable testing of candidate polymorphisms individually and in combination. Here we have created a resource for the study of sleep with 39 inbred lines of Drosophila-the Sleep Inbred Panel (SIP). SIP lines have stable long- and short-sleeping phenotypes developed from naturally occurring polymorphisms. These lines are fully sequenced, enabling more accurate targeting for genome editing and transgenic constructs. This panel facilitates the study of intermediate transcriptional and proteomic correlates of sleep, and supports genome editing studies to verify polymorphisms associated with sleep duration.

Genome-wide regulatory deterioration impedes adaptive responses to stress in inbred populations of Drosophila melanogaster

Inbreeding depression is often intensified under environmental stress (i.e., inbreeding-stress interaction). Although the fitness consequences of this phenomenon are well-described, underlying mechanisms such as an increased expression of deleterious alleles under stress, or a lower capacity for adaptive responses to stress with inbreeding, have rarely been investigated. We investigated a fitness component (egg-to-adult viability) and gene-expression patterns using RNA-seq analyses in noninbred control lines and in inbred lines of Drosophila melanogaster exposed to benign temperature or heat stress. We find little support for an increase in the cumulative expression of deleterious alleles under stress. Instead, inbred individuals had a reduced ability to induce an adaptive gene regulatory stress response compared to controls. The decrease in egg-to-adult viability due to stress was most pronounced in the lines with the largest deviation in the adaptive stress response (R2 = 0.48). Thus, we find strong evidence for a lower capacity of inbred individuals to respond by gene regulation to stress and that this is the main driver of inbreeding-stress interactions. In comparison, the altered gene expression due to inbreeding at benign temperature showed no correlation with fitness and was pronounced in genomic regions experiencing the highest increase in homozygosity.

Genotype Influences Day-to-Day Variability in Sleep in Drosophila melanogaster

Patterns of sleep often vary among individuals. But sleep and activity may also vary within an individual, fluctuating in pattern across time. One possibility is that these daily fluctuations in sleep are caused by the underlying genotype of the individual. However, differences attributable to genetic causes are difficult to distinguish from environmental factors in outbred populations such as humans. We therefore employed Drosophila as a model of intra-individual variability in sleep using previously collected sleep and activity data from the Drosophila Genetic Reference Panel, a collection of wild-derived inbred lines. Individual flies had significant daily fluctuations in their sleep patterns, and these fluctuations were heritable. Using the standard deviation of sleep parameters as a metric, we conducted a genome-wide association study. We found 663 polymorphisms in 104 genes associated with daily fluctuations in sleep. We confirmed the effects of 12 candidate genes on the standard deviation of sleep parameters. Our results suggest that daily fluctuations in sleep patterns are due in part to gene activity.

Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel

Understanding the genetic architecture (causal molecular variants, their effects, and frequencies) of quantitative traits is important for precision agriculture and medicine and predicting adaptive evolution, but is challenging in most species. The Drosophila melanogaster Genetic Reference Panel (DGRP) is a collection of 205 inbred strains with whole genome sequences derived from a single wild population in Raleigh, NC, USA. The large amount of quantitative genetic variation, lack of population structure, and rapid local decay of linkage disequilibrium in the DGRP and outbred populations derived from DGRP lines present a favorable scenario for performing genome-wide association (GWA) mapping analyses to identify candidate causal genes, polymorphisms, and pathways affecting quantitative traits. The many GWA studies utilizing the DGRP have revealed substantial natural genetic variation for all reported traits, little evidence for variants with large effects but enrichment for variants with low P-values, and a tendency for lower frequency variants to have larger effects than more common variants. The variants detected in the GWA analyses rarely overlap those discovered using mutagenesis, and often are the first functional annotations of computationally predicted genes. Variants implicated in GWA analyses typically have sex-specific and genetic background-specific (epistatic) effects, as well as pleiotropic effects on other quantitative traits. Studies in the DGRP reveal substantial genetic control of environmental variation. Taking account of genetic architecture can greatly improve genomic prediction in the DGRP. These features of the genetic architecture of quantitative traits are likely to apply to other species, including humans. WIREs Dev Biol 2018, 7:e289. doi: 10.1002/wdev.289 This article is categorized under: Invertebrate Organogenesis > Flies.

An attempt to select non-genetic variation in resistance to starvation and reduced chill coma recovery time in Drosophila melanogaster

Phenotypic variance is attributed to genetic and non-genetic factors, and only the former are supposed to be inherited and thus suitable for the action of selection. Although increasing amounts of data suggest that non-genetic variability may be inherited, we have limited empirical data in animals. Here, we performed an artificial selection experiment using Drosophila melanogaster inbred lines. We quantified the response to selection for a decrease in chill coma recovery time and an increase in starvation resistance. We observed a weak response to selection in the inbred and outbred lines, with variability across lines. At the end of the selection process, differential expression was detected for some genes associated with epigenetics, the piRNA pathway and canalization functions. As the selection process can disturb the canalization process and increase the phenotypic variance of developmental traits, we also investigated possible effects of the selection process on the number of scutellar bristles, fluctuating asymmetry levels, and fitness estimates. These results suggest that, contrary to what was shown in plants, selection of non-genetic variability is not straightforward in Drosophila and appears to be strongly genotype-dependent.

Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel

Understanding the genetic architecture (causal molecular variants, their effects, and frequencies) of quantitative traits is important for precision agriculture and medicine and predicting adaptive evolution, but is challenging in most species. The Drosophila melanogaster Genetic Reference Panel (DGRP) is a collection of 205 inbred strains with whole genome sequences derived from a single wild population in Raleigh, NC, USA. The large amount of quantitative genetic variation, lack of population structure, and rapid local decay of linkage disequilibrium in the DGRP and outbred populations derived from DGRP lines present a favorable scenario for performing genome-wide association (GWA) mapping analyses to identify candidate causal genes, polymorphisms, and pathways affecting quantitative traits. The many GWA studies utilizing the DGRP have revealed substantial natural genetic variation for all reported traits, little evidence for variants with large effects but enrichment for variants with low P-values, and a tendency for lower frequency variants to have larger effects than more common variants. The variants detected in the GWA analyses rarely overlap those discovered using mutagenesis, and often are the first functional annotations of computationally predicted genes. Variants implicated in GWA analyses typically have sex-specific and genetic background-specific (epistatic) effects, as well as pleiotropic effects on other quantitative traits. Studies in the DGRP reveal substantial genetic control of environmental variation. Taking account of genetic architecture can greatly improve genomic prediction in the DGRP. These features of the genetic architecture of quantitative traits are likely to apply to other species, including humans. WIREs Dev Biol 2018, 7:e289. doi: 10.1002/wdev.289 This article is categorized under: Invertebrate Organogenesis > Flies.

Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel

Understanding the genetic architecture (causal molecular variants, their effects, and frequencies) of quantitative traits is important for precision agriculture and medicine and predicting adaptive evolution, but is challenging in most species. The Drosophila melanogaster Genetic Reference Panel (DGRP) is a collection of 205 inbred strains with whole genome sequences derived from a single wild population in Raleigh, NC, USA. The large amount of quantitative genetic variation, lack of population structure, and rapid local decay of linkage disequilibrium in the DGRP and outbred populations derived from DGRP lines present a favorable scenario for performing genome-wide association (GWA) mapping analyses to identify candidate causal genes, polymorphisms, and pathways affecting quantitative traits. The many GWA studies utilizing the DGRP have revealed substantial natural genetic variation for all reported traits, little evidence for variants with large effects but enrichment for variants with low P-values, and a tendency for lower frequency variants to have larger effects than more common variants. The variants detected in the GWA analyses rarely overlap those discovered using mutagenesis, and often are the first functional annotations of computationally predicted genes. Variants implicated in GWA analyses typically have sex-specific and genetic background-specific (epistatic) effects, as well as pleiotropic effects on other quantitative traits. Studies in the DGRP reveal substantial genetic control of environmental variation. Taking account of genetic architecture can greatly improve genomic prediction in the DGRP. These features of the genetic architecture of quantitative traits are likely to apply to other species, including humans. WIREs Dev Biol 2018, 7:e289. doi: 10.1002/wdev.289 This article is categorized under: Invertebrate Organogenesis > Flies.

Genetics of alcohol consumption in Drosophila melanogaster

Individual variation in alcohol consumption in human populations is determined by genetic, environmental, social and cultural factors. In contrast to humans, genetic contributions to complex behavioral phenotypes can be readily dissected in Drosophila, where both the genetic background and environment can be controlled and behaviors quantified through simple high-throughput assays. Here, we measured voluntary consumption of ethanol in ∼3000 individuals of each sex from an advanced intercross population derived from 37 lines of the Drosophila melanogaster Genetic Reference Panel. Extreme quantitative trait loci mapping identified 385 differentially segregating allelic variants located in or near 291 genes at P < 10-8 . The effects of single nucleotide polymorphisms associated with voluntary ethanol consumption are sex-specific, as found for other alcohol-related phenotypes. To assess causality, we used RNA interference knockdown or P{MiET1} mutants and their corresponding controls and functionally validated 86% of candidate genes in at least one sex. We constructed a genetic network comprised of 23 genes along with a separate trio and a pair of connected genes. Gene ontology analyses showed enrichment of developmental genes, including development of the nervous system. Furthermore, a network of human orthologs showed enrichment for signal transduction processes, protein metabolism and developmental processes, including nervous system development. Our results show that the genetic architecture that underlies variation in voluntary ethanol consumption is sexually dimorphic and partially overlaps with genetic factors that control variation in feeding behavior and alcohol sensitivity. This integrative genetic architecture is rooted in evolutionarily conserved features that can be extrapolated to human genetic interaction networks.

Heritable Micro-environmental Variance Covaries with Fitness in an Outbred Population of Drosophila serrata

The genetic basis of stochastic variation within a defined environment, and the consequences of such micro-environmental variance for fitness are poorly understood . Using a multigenerational breeding design in Drosophila serrata, we demonstrated that the micro-environmental variance in a set of morphological wing traits in a randomly mating population had significant additive genetic variance in most single wing traits. Although heritability was generally low (<1%), coefficients of additive genetic variance were of a magnitude typical of other morphological traits, indicating that the micro-environmental variance is an evolvable trait. Multivariate analyses demonstrated that the micro-environmental variance in wings was genetically correlated among single traits, indicating that common mechanisms of environmental buffering exist for this functionally related set of traits. In addition, through the dominance genetic covariance between the major axes of micro-environmental variance and fitness, we demonstrated that micro-environmental variance shares a genetic basis with fitness, and that the pattern of selection is suggestive of variance-reducing selection acting on micro-environmental variance.

Selection for environmental variance of litter size in rabbits

Background

In recent years, there has been an increasing interest in the genetic determination of environmental variance. In the case of litter size, environmental variance can be related to the capacity of animals to adapt to new environmental conditions, which can improve animal welfare.

Results

We developed a ten-generation divergent selection experiment on environmental variance. We selected one line of rabbits for litter size homogeneity and one line for litter size heterogeneity by measuring intra-doe phenotypic variance. We proved that environmental variance of litter size is genetically determined and can be modified by selection. Response to selection was 4.5% of the original environmental variance per generation. Litter size was consistently higher in the Low line than in the High line during the entire experiment.

Conclusions

We conclude that environmental variance of litter size is genetically determined based on the results of our divergent selection experiment. This has implications for animal welfare, since animals that cope better with their environment have better welfare than more sensitive animals. We also conclude that selection for reduced environmental variance of litter size does not depress litter size.

Leger RJ. The genetic basis for variation in resistance to infection in the Drosophila melanogaster genetic reference panel

Individuals vary extensively in the way they respond to disease but the genetic basis of this variation is not fully understood. We found substantial individual variation in resistance and tolerance to the fungal pathogen Metarhizium anisopliae Ma549 using the Drosophila melanogaster Genetic Reference Panel (DGRP). In addition, we found that host defense to Ma549 was correlated with defense to the bacterium Pseudomonas aeruginosa Pa14, and several previously published DGRP phenotypes including oxidative stress sensitivity, starvation stress resistance, hemolymph glucose levels, and sleep indices. We identified polymorphisms associated with differences between lines in both their mean survival times and microenvironmental plasticity, suggesting that lines differ in their ability to adapt to variable pathogen exposures. The majority of polymorphisms increasing resistance to Ma549 were sex biased, located in non-coding regions, had moderately large effect and were rare, suggesting that there is a general cost to defense. Nevertheless, host defense was not negatively correlated with overall longevity and fecundity. In contrast to Ma549, minor alleles were concentrated in the most Pa14-susceptible as well as the most Pa14-resistant lines. A pathway based analysis revealed a network of Pa14 and Ma549-resistance genes that are functionally connected through processes that encompass phagocytosis and engulfment, cell mobility, intermediary metabolism, protein phosphorylation, axon guidance, response to DNA damage, and drug metabolism. Functional testing with insertional mutagenesis lines indicates that 12/13 candidate genes tested influence susceptibility to Ma549. Many candidate genes have homologs identified in studies of human disease, suggesting that genes affecting variation in susceptibility are conserved across species.

Microenvironmental Gene Expression Plasticity Among Individual Drosophila melanogaster

Differences in phenotype among genetically identical individuals exposed to the same environmental condition are often noted in genetic studies. Despite this commonplace observation, little is known about the causes of this variability, which has been termed microenvironmental plasticity. One possibility is that stochastic or technical sources of variance produce these differences. A second possibility is that this variation has a genetic component. We have explored gene expression robustness in the transcriptomes of 730 individual Drosophila melanogaster of 16 fixed genotypes, nine of which are infected with Wolbachia. Three replicates of flies were grown, controlling for food, day/night cycles, humidity, temperature, sex, mating status, social exposure, and circadian timing of RNA extraction. Despite the use of inbred genotypes, and carefully controlled experimental conditions, thousands of genes were differentially expressed, revealing a unique and dynamic transcriptional signature for each individual fly. We found that 23% of the transcriptome was differentially expressed among individuals, and that the variability in gene expression among individuals is influenced by genotype. This transcriptional variation originated from specific gene pathways, suggesting a plastic response to the microenvironment; but there was also evidence of gene expression differences due to stochastic fluctuations. These observations reveal previously unappreciated genetic sources of variability in gene expression among individuals, which has implications for complex trait genetics and precision medicine.

Genetic basis of transcriptome diversity in Drosophila melanogaster

Understanding how DNA sequence variation is translated into variation for complex phenotypes has remained elusive but is essential for predicting adaptive evolution, for selecting agriculturally important animals and crops, and for personalized medicine. Gene expression may provide a link between variation in DNA sequence and organismal phenotypes, and its abundance can be measured efficiently and accurately. Here we quantified genome-wide variation in gene expression in the sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP), increasing the annotated Drosophila transcriptome by 11%, including thousands of novel transcribed regions (NTRs). We found that 42% of the Drosophila transcriptome is genetically variable in males and females, including the NTRs, and is organized into modules of genetically correlated transcripts. We found that NTRs often were negatively correlated with the expression of protein-coding genes, which we exploited to annotate NTRs functionally. We identified regulatory variants for the mean and variance of gene expression, which have largely independent genetic control. Expression quantitative trait loci (eQTLs) for the mean, but not for the variance, of gene expression were concentrated near genes. Notably, the variance eQTLs often interacted epistatically with local variants in these genes to regulate gene expression. This comprehensive characterization of population-scale diversity of transcriptomes and its genetic basis in the DGRP is critically important for a systems understanding of quantitative trait variation.

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.

Genetic Control of Environmental Variation of Two Quantitative Traits of Drosophila melanogaster Revealed by Whole-Genome Sequencing

Genetic studies usually focus on quantifying and understanding the existence of genetic control on expected phenotypic outcomes. However, there is compelling evidence suggesting the existence of genetic control at the level of environmental variability, with some genotypes exhibiting more stable and others more volatile performance. Understanding the mechanisms responsible for environmental variability not only informs medical questions but is relevant in evolution and in agricultural science. In this work fully sequenced inbred lines of Drosophila melanogaster were analyzed to study the nature of genetic control of environmental variance for two quantitative traits: starvation resistance (SR) and startle response (SL). The evidence for genetic control of environmental variance is compelling for both traits. Sequence information is incorporated in random regression models to study the underlying genetic signals, which are shown to be different in the two traits. Genomic variance in sexual dimorphism was found for SR but not for SL. Indeed, the proportion of variance captured by sequence information and the contribution to this variance from four chromosome segments differ between sexes in SR but not in SL. The number of studies of environmental variation, particularly in humans, is limited. The availability of full sequence information and modern computationally intensive statistical methods provides opportunities for rigorous analyses of environmental variability.