The conditional nature of genetic interactions: the consequences of wild-type backgrounds on mutational interactions in a genome-wide modifier screen

Genetic suppression interactions are highly conserved across genetically diverse yeast isolates

Genetic suppression occurs when the phenotypic defects caused by a deleterious mutation are rescued by another mutation. Suppression interactions are of particular interest for genetic diseases, as they identify ways to reduce disease severity, thereby potentially highlighting avenues for therapeutic intervention. To what extent suppression interactions are influenced by the genetic background in which they operate remains largely unknown. However, a high degree of suppression conservation would be crucial for developing therapeutic strategies that target suppressors. To gain an understanding of the effect of the genetic context on suppression, we isolated spontaneous suppressor mutations of temperature-sensitive alleles of SEC17, TAO3, and GLN1 in 3 genetically diverse natural isolates of the budding yeast Saccharomyces cerevisiae. After identifying and validating the genomic variants responsible for suppression, we introduced the suppressors in all 3 genetic backgrounds, as well as in a laboratory strain, to assess their specificity. Ten out of 11 tested suppression interactions were conserved in the 4 yeast strains, although the extent to which a suppressor could rescue the temperature-sensitive mutant varied across genetic backgrounds. These results suggest that suppression mechanisms are highly conserved across genetic contexts, a finding that is potentially reassuring for the development of therapeutics that mimic genetic suppressors.

Genome-scale analysis of interactions between genetic perturbations and natural variation

Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 8046 CRISPRi perturbations targeting 1721 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual's response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.

Genome-scale analysis of interactions between genetic perturbations and natural variation

Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 7,700 CRISPRi perturbations targeting 1,712 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual's response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.

Unveiling the vulnerabilities of synthetic lethality in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most invasive molecular subtype of breast cancer (BC), accounting for about nearly 15% of all BC cases reported annually. The absence of the three major BC hormone receptors, Estrogen (ER), Progesterone (PR), and Human Epidermal Growth Factor 2 (HER2) receptor, accounts for the characteristic "Triple negative" phraseology. The absence of these marked receptors makes this cancer insensitive to classical endocrine therapeutic approaches. Hence, the available treatment options remain solemnly limited to only conventional realms of chemotherapy and radiation therapy. Moreover, these therapeutic regimes are often accompanied by numerous treatment side-effects that account for early distant metastasis, relapse, and shorter overall survival in TNBC patients. The rigorous ongoing research in the field of clinical oncology has identified certain gene-based selective tumor-targeting susceptibilities, which are known to account for the molecular fallacies and mutation-based genetic alterations that develop the progression of TNBC. One such promising approach is synthetic lethality, which identifies novel drug targets of cancer, from undruggable oncogenes or tumor-suppressor genes, which cannot be otherwise clasped by the conventional approaches of mutational analysis. Herein, a holistic scientific review is presented, to undermine the mechanisms of synthetic lethal (SL) interactions in TNBC, the epigenetic crosstalks encountered, the role of Poly (ADP-ribose) polymerase inhibitors (PARPi) in inducing SL interactions, and the limitations faced by the lethal interactors. Thus, the future predicament of synthetic lethal interactions in the advancement of modern translational TNBC research is assessed with specific emphasis on patient-specific personalized medicine.

Model Organism Modifier (MOM): a user-friendly Galaxy workflow to detect modifiers from genome sequencing data using Caenorhabditis elegans

Genetic modifiers are variants modulating phenotypic outcomes of a primary detrimental variant. They contribute to rare diseases phenotypic variability, but their identification is challenging. Genetic screening with model organisms is a widely used method for demystifying genetic modifiers. Forward genetics screening followed by whole genome sequencing allows the detection of variants throughout the genome but typically produces thousands of candidate variants making the interpretation and prioritization process very time-consuming and tedious. Despite whole genome sequencing is more time and cost-efficient, usage of computational pipelines specific to modifier identification remains a challenge for biological-experiment-focused laboratories doing research with model organisms. To facilitate a broader implementation of whole genome sequencing in genetic screens, we have developed Model Organism Modifier or MOM, a pipeline as a user-friendly Galaxy workflow. Model Organism Modifier analyses raw short-read whole genome sequencing data and implements tailored filtering to provide a Candidate Variant List short enough to be further manually curated. We provide a detailed tutorial to run the Galaxy workflow Model Organism Modifier and guidelines to manually curate the Candidate Variant Lists. We have tested Model Organism Modifier on published and validated Caenorhabditis elegans modifiers screening datasets. As whole genome sequencing facilitates high-throughput identification of genetic modifiers in model organisms, Model Organism Modifier provides a user-friendly solution to implement the bioinformatics analysis of the short-read datasets in laboratories without expertise or support in Bioinformatics.

Leveraging the genetic correlation between traits improves the detection of epistasis in genome-wide association studies

Epistasis, commonly defined as the interaction between genetic loci, is known to play an important role in the phenotypic variation of complex traits. As a result, many statistical methods have been developed to identify genetic variants that are involved in epistasis, and nearly all of these approaches carry out this task by focusing on analyzing one trait at a time. Previous studies have shown that jointly modeling multiple phenotypes can often dramatically increase statistical power for association mapping. In this study, we present the "multivariate MArginal ePIstasis Test" (mvMAPIT)-a multioutcome generalization of a recently proposed epistatic detection method which seeks to detect marginal epistasis or the combined pairwise interaction effects between a given variant and all other variants. By searching for marginal epistatic effects, one can identify genetic variants that are involved in epistasis without the need to identify the exact partners with which the variants interact-thus, potentially alleviating much of the statistical and computational burden associated with conventional explicit search-based methods. Our proposed mvMAPIT builds upon this strategy by taking advantage of correlation structure between traits to improve the identification of variants involved in epistasis. We formulate mvMAPIT as a multivariate linear mixed model and develop a multitrait variance component estimation algorithm for efficient parameter inference and P-value computation. Together with reasonable model approximations, our proposed approach is scalable to moderately sized genome-wide association studies. With simulations, we illustrate the benefits of mvMAPIT over univariate (or single-trait) epistatic mapping strategies. We also apply mvMAPIT framework to protein sequence data from two broadly neutralizing anti-influenza antibodies and approximately 2,000 heterogeneous stock of mice from the Wellcome Trust Centre for Human Genetics. The mvMAPIT R package can be downloaded at https://github.com/lcrawlab/mvMAPIT.

Phenotypic heterogeneity in human genetic diseases: ultrasensitivity-mediated threshold effects as a unifying molecular mechanism

Phenotypic heterogeneity is very common in genetic systems and in human diseases and has important consequences for disease diagnosis and treatment. In addition to the many genetic and non-genetic (e.g., epigenetic, environmental) factors reported to account for part of the heterogeneity, we stress the importance of stochastic fluctuation and regulatory network topology in contributing to phenotypic heterogeneity. We argue that a threshold effect is a unifying principle to explain the phenomenon; that ultrasensitivity is the molecular mechanism for this threshold effect; and discuss the three conditions for phenotypic heterogeneity to occur. We suggest that threshold effects occur not only at the cellular level, but also at the organ level. We stress the importance of context-dependence and its relationship to pleiotropy and edgetic mutations. Based on this model, we provide practical strategies to study human genetic diseases. By understanding the network mechanism for ultrasensitivity and identifying the critical factor, we may manipulate the weak spot to gently nudge the system from an ultrasensitive state to a stable non-disease state. Our analysis provides a new insight into the prevention and treatment of genetic diseases.

A deficiency screen of the 3rd chromosome for dominant modifiers of the Drosophila ER integral membrane protein, Jagunal

The mechanism surrounding chromosome inheritance during cell division has been well documented, however, organelle inheritance during mitosis is less understood. Recently, the endoplasmic reticulum (ER) has been shown to reorganize during mitosis, dividing asymmetrically in proneuronal cells prior to cell fate selection, indicating a programmed mechanism of inheritance. ER asymmetric partitioning in proneural cells relies on the highly conserved ER integral membrane protein, Jagunal (Jagn). Knockdown of Jagn in the compound Drosophila eye displays a pleotropic rough eye phenotype in 48% of the progeny. To identify genes involved in Jagn dependent ER partitioning pathway, we performed a dominant modifier screen of the 3rd chromosome for enhancers and suppressors of this Jagn-RNAi-induced rough eye phenotype. We screened through 181 deficiency lines covering the 3L and 3R chromosomes and identified 12 suppressors and 10 enhancers of the Jagn-RNAi phenotype. Based on the functions of the genes covered by the deficiencies, we identified genes that displayed a suppression or enhancement of the Jagn-RNAi phenotype. These include Division Abnormally Delayed (Dally), a heparan sulfate proteoglycan, the γ-secretase subunit Presenilin, and the ER resident protein Sec63. Based on our understanding of the function of these targets, there is a connection between Jagn and the Notch signaling pathway. Further studies will elucidate the role of Jagn and identified interactors within the mechanisms of ER partitioning during mitosis.

Genetic basis of a spontaneous mutation’s expressivity

Genetic background often influences the phenotypic consequences of mutations, resulting in variable expressivity. How standing genetic variants collectively cause this phenomenon is not fully understood. Here, we comprehensively identify loci in a budding yeast cross that impact the growth of individuals carrying a spontaneous missense mutation in the nuclear-encoded mitochondrial ribosomal gene MRP20. Initial results suggested that a single large effect locus influences the mutation’s expressivity, with one allele causing inviability in mutants. However, further experiments revealed this simplicity was an illusion. In fact, many additional loci shape the mutation’s expressivity, collectively leading to a wide spectrum of mutational responses. These results exemplify how complex combinations of alleles can produce a diversity of qualitative and quantitative responses to the same mutation.

The complex role of genetic background in shaping the effects of spontaneous and induced mutations

Spontaneous and induced mutations frequently show different phenotypic effects across genetically distinct individuals. It is generally appreciated that these background effects mainly result from genetic interactions between the mutations and segregating loci. However, the architectures and molecular bases of these genetic interactions are not well understood. Recent work in a number of model organisms has tried to advance knowledge of background effects both by using large‐scale screens to find mutations that exhibit this phenomenon and by identifying the specific loci that are involved. Here, we review this body of research, emphasizing in particular the insights it provides into both the prevalence of background effects across different mutations and the mechanisms that cause these background effects.

A large fraction of mutations show different effects in distinct individuals.

These background effects are mainly caused by epistasis with segregating loci.

Mapping studies show a diversity of genetic architectures can be involved.

Genetically complex changes in gene expression are often, but not always, causative.

Development of synthetic lethality in cancer: molecular and cellular classification

Recently, genetically targeted cancer therapies have been a topic of great interest. Synthetic lethality provides a new approach for the treatment of mutated genes that were previously considered unable to be targeted in traditional genotype-targeted treatments. The increasing researches and applications in the clinical setting made synthetic lethality a promising anticancer treatment option. However, the current understandings on different conditions of synthetic lethality have not been systematically assessed and the application of synthetic lethality in clinical practice still faces many challenges. Here, we propose a novel and systematic classification of synthetic lethality divided into gene level, pathway level, organelle level, and conditional synthetic lethality, according to the degree of specificity into its biological mechanism. Multiple preclinical findings of synthetic lethality in recent years will be reviewed and classified under these different categories. Moreover, synthetic lethality targeted drugs in clinical practice will be briefly discussed. Finally, we will explore the essential implications of this classification as well as its prospects in eliminating existing challenges and the future directions of synthetic lethality.

Genetic and environmental canalization are not associated among altitudinally varying populations of Drosophila melanogaster

Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. There has been interest regarding the conditions enabling the evolution of canalization. Under some models, the circumstances under which genetic canalization evolves are limited despite apparent empirical evidence for it. It has been argued that genetic canalization evolves as a correlated response to environmental canalization (congruence model). Yet, empirical evidence has not consistently supported predictions of a correlation between genetic and environmental canalization. In a recent study, a population of Drosophila adapted to high altitude showed evidence of genetic decanalization relative to those from low altitudes. Using strains derived from these populations, we tested if they varied for multiple aspects of environmental canalization We observed the expected differences in wing size, shape, cell (trichome) density and mutational defects between high- and low-altitude populations. However, we observed little evidence for a relationship between measures of environmental canalization with population or with defect frequency. Our results do not support the predicted association between genetic and environmental canalization.

The impact of the genetic background on gene deletion phenotypes in Saccharomyces cerevisiae

Loss-of-function (LoF) mutations associated with disease do not manifest equally in different individuals. The impact of the genetic background on the consequences of LoF mutations remains poorly characterized. Here, we systematically assessed the changes in gene deletion phenotypes for 3,786 gene knockouts in four Saccharomyces cerevisiae strains and 38 conditions. We observed 18.5% of deletion phenotypes changing between pairs of strains on average with a small fraction conserved in all four strains. Conditions causing higher wild-type growth differences and the deletion of pleiotropic genes showed above-average changes in phenotypes. In addition, we performed a genome-wide association study (GWAS) for growth under the same conditions for a panel of 925 yeast isolates. Gene-condition associations derived from GWAS were not enriched for genes with deletion phenotypes under the same conditions. However, cases where the results were congruent indicate the most likely mechanism underlying the GWAS signal. Overall, these results show a high degree of genetic background dependencies for LoF phenotypes.

Unpredictable Effects of the Genetic Background of Transgenic Lines in Physiological Quantitative Traits

Physiology, fitness and disease phenotypes are complex traits exhibiting continuous variation in natural populations. To understand complex trait gene functions transgenic lines of undefined genetic background are often combined to assess quantitative phenotypes ignoring the impact of genetic polymorphisms. Here, we used inbred wild-type strains of the Drosophila Genetics Reference Panel to assess the phenotypic variation of six physiological and fitness traits, namely, female fecundity, survival and intestinal mitosis upon oral infection, defecation rate and fecal pH upon oral infection, and terminal tracheal cell branching in hypoxia. We found continuous variation in the approximately 150 strains tested for each trait, with extreme values differing by more than four standard deviations for all traits. In addition, we assessed the effects of commonly used Drosophila UAS-RNAi transgenic strains and their backcrossed isogenized counterparts, in the same traits plus baseline intestinal mitosis and tracheal branching in normoxia, in heterozygous conditions, when only half of the genetic background was different among strains. We tested 20 non-isogenic strains (10 KK and 10 GD) from the Vienna Drosophila Resource Center and their isogenized counterparts without Gal4 induction. Survival upon infection and female fecundity exhibited differences in 50% and 40% of the tested isogenic vs. non-isogenic pairs, respectively, whereas all other traits were affected in only 10–25% of the cases. When 11 isogenic and their corresponding non-isogenic UAS-RNAi lines were expressed ubiquitously with Gal4, 4 isogenic vs. non-isogenic pairs exhibited differences in survival to infection. Furthermore, when a single UAS-RNAi line was crossed with the same Gal4 transgene inserted in different genetic backgrounds, the quantitative variations observed were unpredictable on the basis of pure line performance. Thus, irrespective of the trait of interest, the genetic background of commonly used transgenic strains needs to be considered carefully during experimentation.

Genetic interaction networks mediate individual statin drug response in Saccharomyces cerevisiae

Eukaryotic genetic interaction networks (GINs) are extensively described in the Saccharomyces cerevisiae S288C model using deletion libraries, yet being limited to this one genetic background, not informative to individual drug response. Here we created deletion libraries in three additional genetic backgrounds. Statin response was probed with five queries against four genetic backgrounds. The 20 resultant GINs representing drug-gene and gene-gene interactions were not conserved by functional enrichment, hierarchical clustering, and topology-based community partitioning. An unfolded protein response (UPR) community exhibited genetic background variation including different betweenness genes that were network bottlenecks, and we experimentally validated this UPR community via measurements of the UPR that were differentially activated and regulated in statin-resistant strains relative to the statin-sensitive S288C background. These network analyses by topology and function provide insight into the complexity of drug response influenced by genetic background.

Synthetic Lethality and Cancer - Penetrance as the Major Barrier

Synthetic lethality has long been proposed as an approach for targeting genetic defects in tumours. Despite a decade of screening efforts, relatively few robust synthetic lethal targets have been identified. Improved genetic perturbation techniques, including CRISPR/Cas9 gene editing, have resulted in renewed enthusiasm for searching for synthetic lethal effects in cancer. An implicit assumption behind this enthusiasm is that the lack of reproducibly identified targets can be attributed to limitations of RNAi technologies. We argue here that a bigger hurdle is that most synthetic lethal interactions (SLIs) are not highly penetrant, in other words they are not robust to the extensive molecular heterogeneity seen in tumours. We outline strategies for identifying and prioritising SLIs that are most likely to be highly penetrant.

Genetic Network Complexity Shapes Background-Dependent Phenotypic Expression

The phenotypic consequences of a given mutation can vary across individuals. This so-called background effect is widely observed, from mutant fitness of loss-of-function variants in model organisms to variable disease penetrance and expressivity in humans; however, the underlying genetic basis often remains unclear. Taking insights gained from recent large-scale surveys of genetic interaction and suppression analyses in yeast, we propose that the genetic network context for a given mutation may shape its propensity of exhibiting background-dependent phenotypes. We argue that further efforts in systematically mapping the genetic interaction networks beyond yeast will provide not only key insights into the functional properties of genes, but also a better understanding of the background effects and the (un)predictability of traits in a broader context.

How well do you know your mutation? Complex effects of genetic background on expressivity, complementation, and ordering of allelic effects

For a given gene, different mutations influence organismal phenotypes to varying degrees. However, the expressivity of these variants not only depends on the DNA lesion associated with the mutation, but also on factors including the genetic background and rearing environment. The degree to which these factors influence related alleles, genes, or pathways similarly, and whether similar developmental mechanisms underlie variation in the expressivity of a single allele across conditions and among alleles is poorly understood. Besides their fundamental biological significance, these questions have important implications for the interpretation of functional genetic analyses, for example, if these factors alter the ordering of allelic series or patterns of complementation. We examined the impact of genetic background and rearing environment for a series of mutations spanning the range of phenotypic effects for both the scalloped and vestigial genes, which influence wing development in Drosophila melanogaster. Genetic background and rearing environment influenced the phenotypic outcome of mutations, including intra-genic interactions, particularly for mutations of moderate expressivity. We examined whether cellular correlates (such as cell proliferation during development) of these phenotypic effects matched the observed phenotypic outcome. While cell proliferation decreased with mutations of increasingly severe effects, surprisingly it did not co-vary strongly with the degree of background dependence. We discuss these findings and propose a phenomenological model to aid in understanding the biology of genes, and how this influences our interpretation of allelic effects in genetic analysis.

Different mutations in a gene, or in genes with related functions, can have effects of varying severity. Studying sets of mutations and analyzing how they interact are essential components of a geneticist's toolkit. However, the effects caused by a mutation depend not only on the mutation itself, but on additional genetic variation throughout an organism's genome and on the environment that organism has experienced. Therefore, identifying how the genomic and environmental context alter the expression of mutations is critical for making reliable inferences about how genes function. Yet studies on this context dependence have largely been limited to single mutations in single genes. We examined how the genomic and environmental context influence the expression of multiple mutations in two related genes affecting the fruit fly wing. Our results show that the genetic and environmental context generally affect the expression of related mutations in similar ways. However, the interactions between two different mutations in a single gene sometimes depended strongly on context. In addition, cell proliferation in the developing wing and adult wing size were not affected by the genetic and environmental context in similar ways in mutant flies, suggesting that variation in cell growth cannot fully explain how mutations affect wings. Overall, our findings show that context can have a big impact on the interpretation of genetic experiments, including how we draw conclusions about gene function and cause-and-effect relationships.

Naturally Segregating Variation at Ugt86Dd Contributes to Nicotine Resistance in Drosophila melanogaster

Identifying the sequence polymorphisms underlying complex trait variation is a key goal of genetics research, since knowing the precise causative molecular events allows insight into the pathways governing trait variation. Genetic analysis of complex traits in model systems regularly starts by constructing QTL maps, but generally fails to identify causative sequence polymorphisms. Previously we mapped a series of QTL contributing to resistance to nicotine in a Drosophila melanogaster multiparental mapping resource and here use a battery of functional tests to resolve QTL to the molecular level. One large-effect QTL resided over a cluster of UDP-glucuronosyltransferases, and quantitative complementation tests using deficiencies eliminating subsets of these detoxification genes revealed allelic variation impacting resistance. RNAseq showed that Ugt86Dd had significantly higher expression in genotypes that are more resistant to nicotine, and anterior midgut-specific RNA interference (RNAi) of this gene reduced resistance. We discovered a segregating 22-bp frameshift deletion in Ugt86Dd, and accounting for the InDel during mapping largely eliminates the QTL, implying the event explains the bulk of the effect of the mapped locus. CRISPR/Cas9 editing of a relatively resistant genotype to generate lesions in Ugt86Dd that recapitulate the naturally occurring putative loss-of-function allele, leads to a large reduction in resistance. Despite this major effect of the deletion, the allele appears to be very rare in wild-caught populations and likely explains only a small fraction of the natural variation for the trait. Nonetheless, this putatively causative coding InDel can be a launchpad for future mechanistic exploration of xenobiotic detoxification.

Sex and Genetic Background Influence Superoxide Dismutase (cSOD)-Related Phenotypic Variation in Drosophila melanogaster

Mutations often have drastically different effects in different genetic backgrounds; understanding a gene’s biological function then requires an understanding of its interaction with genetic diversity. The antioxidant enzyme cytosolic copper/zinc superoxide dismutase (cSOD) catalyzes the dismutation of the superoxide radical, a molecule that can induce oxidative stress if its concentration exceeds cellular control. Accordingly, Drosophila melanogaster lacking functional cSOD exhibit a suite of phenotypes including decreased longevity, hypersensitivity to oxidative stress, impaired locomotion, and reduced NADP(H) enzyme activity in males. To date, cSOD-null phenotypes have primarily been characterized using males carrying one allele, cSodⁿ¹⁰⁸red, in a single genetic background. We used ANOVA, and the effect size partial eta squared, to partition the amount of variation attributable to cSOD activity, sex, and genetic background across a series of life history, locomotor, and biochemical phenotypes associated with the cSOD-null condition. Overall, the results demonstrate that the cSOD-null syndrome is largely consistent across sex and genetic background, but also significantly influenced by both. The sex-specific effects are particularly striking and our results support the idea that phenotypes cannot be considered to be fully defined if they are examined in limited genetic contexts.

Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits

Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects-the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the "MArginal ePIstasis Test", or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium.

The background puzzle: how identical mutations in the same gene lead to different disease symptoms

Identical disease-causing mutations can lead to different symptoms in different people. The reason for this has been a puzzling problem for geneticists. Differential penetrance and expressivity of mutations has been observed within individuals with different and similar genetic backgrounds. Attempts have been made to uncover the underlying mechanisms that determine differential phenotypic effects of identical mutations through studies of model organisms. From these studies evidence is accumulating that to understand disease mechanism or predict disease prevalence, an understanding of the influence of genetic background is as important as the putative disease-causing mutations of relatively large effect. This review highlights current insights into phenotypic variation due to gene interactions, epigenetics and stochasticity in model organisms, and discusses their importance for understanding the mutational effect on disease symptoms.

The Interaction of Genetic Background and Mutational Effects in Regulation of Mouse Craniofacial Shape

Inbred genetic background significantly influences the expression of phenotypes associated with known genetic perturbations and can underlie variation in disease severity between individuals with the same mutation. However, the effect of epistatic interactions on the development of complex traits, such as craniofacial morphology, is poorly understood. Here, we investigated the effect of three inbred backgrounds (129X1/SvJ, C57BL/6J, and FVB/NJ) on the expression of craniofacial dysmorphology in mice (Mus musculus) with loss of function in three members of the Sprouty family of growth factor negative regulators (Spry1, Spry2, or Spry4) in order to explore the impact of epistatic interactions on skull morphology. We found that the interaction of inbred background and the Sprouty genotype explains as much craniofacial shape variation as the Sprouty genotype alone. The most severely affected genotypes display a relatively short and wide skull, a rounded cranial vault, and a more highly angled inferior profile. Our results suggest that the FVB background is more resilient to Sprouty loss of function than either C57 or 129, and that Spry4 loss is generally less severe than loss of Spry1 or Spry2 While the specific modifier genes responsible for these significant background effects remain unknown, our results highlight the value of intercrossing mice of multiple inbred backgrounds to identify the genes and developmental interactions that modulate the severity of craniofacial dysmorphology. Our quantitative results represent an important first step toward elucidating genetic interactions underlying variation in robustness to known genetic perturbations in mice.

Genetic suppression: Extending our knowledge from lab experiments to natural populations

Many mutations have deleterious phenotypic effects that can be alleviated by suppressor mutations elsewhere in the genome. High-throughput approaches have facilitated the large-scale identification of these suppressors and have helped shed light on core functional mechanisms that give rise to suppression. Following reports that suppression occurs naturally within species, it is important to determine how our understanding of this phenomenon based on lab experiments extends to genetically diverse natural populations. Although suppression is typically mediated by individual genetic changes in lab experiments, recent studies have shown that suppression in natural populations can involve combinations of genetic variants. This difference in complexity suggests that sets of variants can exhibit similar functional effects to individual suppressors found in lab experiments. In this review, we discuss how characterizing the way in which these variants jointly lead to suppression could provide important insights into the genotype-phenotype map that are relevant to evolution and health.

Natural Variation of Molecular and Morphological Gibberellin Responses

Although phytohormones such as gibberellins are essential for many conserved aspects of plant physiology and development, plants vary greatly in their responses to these regulatory compounds. Here, we use genetic perturbation of endogenous gibberellin levels to probe the extent of intraspecific variation in gibberellin responses in natural accessions of Arabidopsis (Arabidopsis thaliana). We find that these accessions vary greatly in their ability to buffer the effects of overexpression of GA20ox1, encoding a rate-limiting enzyme for gibberellin biosynthesis, with substantial differences in bioactive gibberellin concentrations as well as transcriptomes and growth trajectories. These findings demonstrate a surprising level of flexibility in the wiring of regulatory networks underlying hormone metabolism and signaling.

Considerations when choosing a genetic model organism for metabolomics studies

Model organisms are important in many areas of chemical biology. In metabolomics, model organisms can provide excellent samples for methods development as well as the foundation of comparative phylometabolomics, which will become possible as metabolomics applications expand. Comparative studies of conserved and unique metabolic pathways will help in the annotation of metabolites as well as provide important new targets of investigation in biology and biomedicine. However, most chemical biologists are not familiar with genetics, which needs to be considered when choosing a model organism. In this review we summarize the strengths and weaknesses of several genetic systems, including natural isolates, recombinant inbred lines, and genetic mutations. We also discuss methods to detect targets of selection on the metabolome.

Disintegrating the fly: A mutational perspective on phenotypic integration and covariation

The structure of environmentally induced phenotypic covariation can influence the effective strength and magnitude of natural selection. Yet our understanding of the factors that contribute to and influence the evolutionary lability of such covariation is poor. Most studies have either examined environmental variation without accounting for covariation, or examined phenotypic and genetic covariation without distinguishing the environmental component. In this study, we examined the effect of mutational perturbations on different properties of environmental covariation, as well as mean shape. We use strains of Drosophila melanogaster bearing well-characterized mutations known to influence wing shape, as well as naturally derived strains, all reared under carefully controlled conditions and with the same genetic background. We find that mean shape changes more freely than the covariance structure, and that different properties of the covariance matrix change independently from each other. The perturbations affect matrix orientation more than they affect matrix eccentricity or total variance. Yet, mutational effects on matrix orientation do not cluster according to the developmental pathway that they target. These results suggest that it might be useful to consider a more general concept of "decanalization," involving all aspects of variation and covariation.

Reproductive activity triggers accelerated male mortality and decreases lifespan: genetic and gene expression determinants in Drosophila

Reproduction and aging evolved to be intimately associated. Experimental selection for early-life reproduction drives the evolution of decreased longevity in Drosophila whereas experimental selection for increased longevity leads to changes in reproduction. Although life history theory offers hypotheses to explain these relationships, the genetic architecture and molecular mechanisms underlying reproduction-longevity associations remain a matter of debate. Here we show that mating triggers accelerated mortality in males and identify hundreds of genes that are modulated upon mating in the fruit fly Drosophila melanogaster. Interrogation of genome-wide gene expression in virgin and recently mated males revealed coherent responses, with biological processes that are upregulated (testis-specific gene expression) or downregulated (metabolism and mitochondria-related functions) upon mating. Furthermore, using a panel of genotypes from the Drosophila Synthetic Population Resource (DSPR) as a source of naturally occurring genetic perturbation, we uncover abundant variation in longevity and reproduction-induced mortality among genotypes. Genotypes displayed more than fourfold variation in longevity and reproduction-induced mortality that can be traced to variation in specific segments of the genome. The data reveal individual variation in sensitivity to reproduction and physiological processes that are enhanced and suppressed upon mating. These results raise the prospect that variation in longevity and age-related traits could be traced to processes that coordinate germline and somatic function.

The Phenotypic Effects of Royal Jelly on Wild-Type D. melanogaster Are Strain-Specific

The role for royal jelly (RJ) in promoting caste differentiation of honeybee larvae into queens rather than workers is well characterized. A recent study demonstrated that this poorly understood complex nutrition drives strikingly similar phenotypic effects in Drosophila melanogaster, such as increased body size and reduced developmental time, making possible the use of D. melanogaster as a model system for the genetic analysis of the cellular mechanisms underlying RJ and caste differentiation. We demonstrate here that RJ increases the body size of some wild-type strains of D. melanogaster but not others, and report significant delays in developmental time in all flies reared on RJ. These findings suggest that cryptic genetic variation may be a factor in the D. melanogaster response to RJ, and should be considered when attempting to elucidate response mechanisms to environmental changes in non-honeybee species.

Cryptic Genetic Variation in Evolutionary Developmental Genetics

Evolutionary developmental genetics has traditionally been conducted by two groups: Molecular evolutionists who emphasize divergence between species or higher taxa, and quantitative geneticists who study variation within species. Neither approach really comes to grips with the complexities of evolutionary transitions, particularly in light of the realization from genome-wide association studies that most complex traits fit an infinitesimal architecture, being influenced by thousands of loci. This paper discusses robustness, plasticity and lability, phenomena that we argue potentiate major evolutionary changes and provide a bridge between the conceptual treatments of macro- and micro-evolution. We offer cryptic genetic variation and conditional neutrality as mechanisms by which standing genetic variation can lead to developmental system drift and, sheltered within canalized processes, may facilitate developmental transitions and the evolution of novelty. Synthesis of the two dominant perspectives will require recognition that adaptation, divergence, drift and stability all depend on similar underlying quantitative genetic processes-processes that cannot be fully observed in continuously varying visible traits.

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.

Decanalization of wing development accompanied the evolution of large wings in high-altitude Drosophila

In higher organisms, the phenotypic impacts of potentially harmful or beneficial mutations are often modulated by complex developmental networks. Stabilizing selection may favor the evolution of developmental canalization--that is, robustness despite perturbation--to insulate development against environmental and genetic variability. In contrast, directional selection acts to alter the developmental process, possibly undermining the molecular mechanisms that buffer a trait's development, but this scenario has not been shown in nature. Here, we examined the developmental consequences of size increase in highland Ethiopian Drosophila melanogaster. Ethiopian inbred strains exhibited much higher frequencies of wing abnormalities than lowland populations, consistent with an elevated susceptibility to the genetic perturbation of inbreeding. We then used mutagenesis to test whether Ethiopian wing development is, indeed, decanalized. Ethiopian strains were far more susceptible to this genetic disruption of development, yielding 26 times more novel wing abnormalities than lowland strains in F2 males. Wing size and developmental perturbability cosegregated in the offspring of between-population crosses, suggesting that genes conferring size differences had undermined developmental buffering mechanisms. Our findings represent the first observation, to our knowledge, of morphological evolution associated with decanalization in the same tissue, underscoring the sensitivity of development to adaptive change.

The role of functional data in interpreting the effects of genetic variation

Progress in DNA-sequencing technologies has provided a catalogue of millions of DNA variants in the human population, but characterization of the functional effects of these variants has lagged far behind. For example, sequencing of tumor samples is driving an urgent need to classify whether or not mutations seen in cancers affect disease progression or treatment effectiveness or instead are benign. Furthermore, mutations can interact with genetic background and with environmental effects. A new approach, termed deep mutational scanning, has enabled the quantitative assessment of the effects of thousands of mutations in a protein. However, this type of experiment is carried out in model organisms, tissue culture, or in vitro; typically addresses only a single biochemical function of a protein; and is generally performed under a single condition. The current challenge lies in using these functional data to generate useful models for the phenotypic consequences of genetic variation in humans.

Prediction of Genetic Interactions Using Machine Learning and Network Properties

A genetic interaction (GI) is a type of interaction where the effect of one gene is modified by the effect of one or several other genes. These interactions are important for delineating functional relationships among genes and their corresponding proteins, as well as elucidating complex biological processes and diseases. An important type of GI - synthetic sickness or synthetic lethality - involves two or more genes, where the loss of either gene alone has little impact on cell viability, but the combined loss of all genes leads to a severe decrease in fitness (sickness) or cell death (lethality). The identification of GIs is an important problem for it can help delineate pathways, protein complexes, and regulatory dependencies. Synthetic lethal interactions have important clinical and biological significance, such as providing therapeutically exploitable weaknesses in tumors. While near systematic high-content screening for GIs is possible in single cell organisms such as yeast, the systematic discovery of GIs is extremely difficult in mammalian cells. Therefore, there is a great need for computational approaches to reliably predict GIs, including synthetic lethal interactions, in these organisms. Here, we review the state-of-the-art approaches, strategies, and rigorous evaluation methods for learning and predicting GIs, both under general (healthy/standard laboratory) conditions and under specific contexts, such as diseases.

Differential expression of the aryl hydrocarbon receptor pathway associates with craniofacial polymorphism in sympatric Arctic charr

Background

The developmental basis of craniofacial morphology hinges on interactions of numerous signalling systems. Extensive craniofacial variation in the polymorphic Arctic charr, a member of the salmonid family, from Lake Thingvallavatn (Iceland), offers opportunities to find and study such signalling pathways and their key regulators, thereby shedding light on the developmental pathways, and the genetics of trophic divergence.

Results

To identify genes involved in the craniofacial differences between benthic and limnetic Arctic charr, we used transcriptome data from different morphs, spanning early development, together with data on craniofacial expression patterns and skeletogenesis in model vertebrate species. Out of 20 genes identified, 7 showed lower gene expression in benthic than in limnetic charr morphs. We had previously identified a conserved gene network involved in extracellular matrix (ECM) organization and skeletogenesis, showing higher expression in developing craniofacial elements of benthic than in limnetic Arctic charr morphs. The present study adds a second set of genes constituting an expanded gene network with strong, benthic–limnetic differential expression. To identify putative upstream regulators, we performed knowledge-based motif enrichment analyses on the regulatory sequences of the identified genes which yielded potential binding sites for a set of known transcription factors (TFs). Of the 8 TFs that we examined using qPCR, two (Ahr2b and Ap2) were found to be differentially expressed between benthic and limnetic charr. Expression analysis of several known AhR targets indicated higher activity of the AhR pathway during craniofacial development in benthic charr morphotypes.

Conclusion

These results suggest a key role of the aryl hydrocarbon receptor (AhR) pathway in the observed craniofacial differences between distinct charr morphotypes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13227-015-0022-6) contains supplementary material, which is available to authorized users.

Wild worm embryogenesis harbors ubiquitous polygenic modifier variation

Embryogenesis is an essential and stereotypic process that nevertheless evolves among species. Its essentiality may favor the accumulation of cryptic genetic variation (CGV) that has no effect in the wild-type but that enhances or suppresses the effects of rare disruptions to gene function. Here, we adapted a classical modifier screen to interrogate the alleles segregating in natural populations of Caenorhabditis elegans: we induced gene knockdowns and used quantitative genetic methodology to examine how segregating variants modify the penetrance of embryonic lethality. Each perturbation revealed CGV, indicating that wild-type genomes harbor myriad genetic modifiers that may have little effect individually but which in aggregate can dramatically influence penetrance. Phenotypes were mediated by many modifiers, indicating high polygenicity, but the alleles tend to act very specifically, indicating low pleiotropy. Our findings demonstrate the extent of conditional functionality in complex trait architecture.

DOI:http://dx.doi.org/10.7554/eLife.09178.001

Individuals of the same species have similar, but generally not identical, DNA sequences. This ‘genetic variation’ is due to random changes in the DNA—known as mutations—that occur among individuals. These mutations may be passed on to these individuals' offspring, who in turn pass them on to their descendants. Some of these mutations may have a positive or negative effect on the ability of the organisms to survive and reproduce, but others may have no effect at all.

The process by which an embryo forms (which is called embryogenesis) follows a precisely controlled series of events. Within the same species, there is genetic variation in the DNA that programs embryogenesis, but it is not clear what effect this variation has on how the embryo develops. Here, Paaby et al. adapted a genetics technique called a ‘modifier screen’ to study how genetic variation affects the development of a roundworm known as Caenorhabditis elegans.

The experiments show that populations of worms harbor a lot of genetic variation that affects how they tolerate the loss of an important gene. One by one, Paaby et al. interrupted the activity of specific genes that embryos need in order to develop. How this affected the embryo, and whether or not it was able to survive, was due in large part to the naturally-occurring genetic variation in other genes in these worms.

Paaby et al.'s findings serve as a reminder that the effect of a mutation depends on other DNA sequences in the organism. In humans, for example, a gene that causes a genetic disease may produce severe symptoms in one patient but mild symptoms in another. Future experiments will reveal the details of how genetic variation affects embryogenesis, which may also provide new insights into how complex processes in animals evolve over time.

DOI:http://dx.doi.org/10.7554/eLife.09178.002

A recurrent deletion on chromosome 2q13 is associated with developmental delay and mild facial dysmorphisms

We report two unrelated patients with overlapping chromosome 2q13 deletions (patient 1 in chr2:111415137-113194067 bp and patient 2 in chr2:110980342-113007823 bp, hg 19). Patient 1 presents with developmental delay, microcephaly and mild dysmorphic facial features, and patient 2 with autism spectrum disorder, borderline cognitive abilities, deficits in attention and executive functions and mild dysmorphic facial features. The mother and maternal grandmother of patient 1 were healthy carriers of the deletion. Previously, 2q13 deletions were reported in 27 patients, and the interpretation of its clinical significance varied. Our findings support that the 2q13 deletion is associated with a developmental delay syndrome manifesting with variable expressivity and reduced penetrance which poses a challenge for genetic counselling as well as the clinical recognition of 2q13 deletion patients.

The genetics and neurobiology of ESSENCE: The third Birgit Olsson lecture

ESSENCE refers to early symptomatic syndromes eliciting neurodevelopmental clinical examinations. It includes a broad range of early onset neurodevelopmental disorders affecting more than 10% of children before 5 years of age. ESSENCE includes among others attention deficit hyperactivity disorder (ADHD), intellectual disability (ID) and autism spectrum disorders (ASD). Some degree of disability is the rule rather than the exception. The causes are heterogeneous ranging from extreme social deprivation, pre- and perinatal risk factors, genetic and metabolic diseases, immune and infectious disorders, nutritional factors, physical trauma, and postnatal toxic and environmental factors (and combinations/interactions of some or several of these). Treatments often involve a combination of psychoeducational interventions, home- and school-based programmes, and medication. Here, I will first briefly review our main knowledge on the biological pathways associated with early onset neurodevelopmental disorders and will provide useful links to be informed of the progress in the field. Five main pathways are associated with ASD and ID: chromatin remodelling, cytoskeleton dynamics, mRNA translation, metabolism and synapse formation/function. I will then detail three propositions coming from institutions, researchers and/or communities of patients and families to foster research: 1) to use more dimensional and quantitative data than diagnostic categories; 2) to increase data sharing and research on genetic and brain diversity in human populations; 3) to involve patients and relatives as participants for research. Finally, I will provide examples of very stimulating initiatives towards a more inclusive world for individuals with ESSENCE.

Dissecting the Genetic Architecture of Behavior in Drosophila melanogaster

Variation in behaviors in natural populations arises from complex networks of multiple segregating polymorphic alleles whose expression can be modulated by the environment. Since behaviors reflect dynamic interactions between organisms and their environments, they are central targets for adaptive evolution. Drosophila melanogaster presents a powerful system for dissecting the genetic basis of behavioral phenotypes, since both the genetic background and environmental conditions can be controlled and behaviors accurately quantified. Single gene mutational analyses can identify the roles of individual genes within cellular pathways, whereas systems genetic approaches that exploit natural variation can construct genetic networks that underlie phenotypic variation. Combining these approaches with emerging technologies, such as genome editing, is likely to yield a comprehensive understanding of the neurogenetic underpinnings that orchestrate the manifestation of behaviors.

Heredity and self-organization: partners in the generation and evolution of phenotypes

In this review we examine the role of self-organization in the context of the evolution of morphogenesis. We provide examples to show that self-organized behavior is ubiquitous, and suggest it is a mechanism that can permit high levels of biodiversity without the invention of ever-increasing numbers of genes. We also examine the implications of self-organization for understanding the "internal descriptions" of organisms and the concept of a genotype-phenotype map.

Rewiring of genetic networks in response to modification of genetic background

Genome-scale genetic interaction networks are progressively contributing to map the molecular circuitry that determines cellular behavior. To what extent this mapping changes in response to different environmental or genetic conditions is, however, largely unknown. Here, we assembled a genetic network using an in silico model of metabolism in yeast to explicitly ask how separate genetic backgrounds alter network structure. Backgrounds defined by single deletions of metabolically active enzymes induce strong rewiring when the deletion corresponds to a catabolic gene, evidencing a broad redistribution of fluxes to alternative pathways. We also show how change is more pronounced in interactions linking genes in distinct functional modules and in those connections that present weak epistasis. These patterns reflect overall the distributed robustness of catabolism. In a second class of genetic backgrounds, in which a number of neutral mutations accumulate, we dominantly observe modifications in the negative interactions that together with an increase in the number of essential genes indicate a global reduction in buffering. Notably, neutral trajectories that originate considerable changes in the wild-type network comprise mutations that diminished the environmental plasticity of the corresponding metabolism, what emphasizes a mechanistic integration of genetic and environmental buffering. More generally, our work demonstrates how the specific mechanistic causes of robustness influence the architecture of multiconditional genetic interaction maps.

Regulation of synaptic development and function by the Drosophila PDZ protein Dyschronic

Synaptic scaffold proteins control the localization of ion channels and receptors, and facilitate molecular associations between signaling components that modulate synaptic transmission and plasticity. Here, we define novel roles for a recently described scaffold protein, Dsychronic (DYSC), at the Drosophila larval neuromuscular junction. DYSC is the Drosophila homolog of whirlin/DFNB31, a PDZ domain protein linked to Usher syndrome, the most common form of human deaf-blindness. We show that DYSC is expressed presynaptically and is often localized adjacent to the active zone, the site of neurotransmitter release. Loss of DYSC results in marked alterations in synaptic morphology and cytoskeletal organization. Moreover, active zones are frequently enlarged and misshapen in dysc mutants. Electrophysiological analyses further demonstrate that dysc mutants exhibit substantial increases in both evoked and spontaneous synaptic transmission. We have previously shown that DYSC binds to and regulates the expression of the Slowpoke (SLO) BK potassium channel. Consistent with this, slo mutant larvae exhibit similar alterations in synapse morphology, active zone size and neurotransmission, and simultaneous loss of dysc and slo does not enhance these phenotypes, suggesting that dysc and slo act in a common genetic pathway to modulate synaptic development and output. Our data expand our understanding of the neuronal functions of DYSC and uncover non-canonical roles for the SLO potassium channel at Drosophila synapses.

Higher-order genetic interactions and their contribution to complex traits

The contribution of genetic interactions involving three or more loci to complex traits is poorly understood. These higher-order genetic interactions (HGIs) are difficult to detect in genetic mapping studies, therefore, few examples of them have been described. However, the lack of data on HGIs should not be misconstrued as proof that this class of genetic effect is unimportant. To the contrary, evidence from model organisms suggests that HGIs frequently influence genetic studies and contribute to many complex traits. Here, we review the growing literature on HGIs and discuss the future of research on this topic.