Dynamic Epistasis under Varying Environmental Perturbations

Epistasis describes the phenomenon that mutations at different loci do not have independent effects with regard to certain phenotypes. Understanding the global epistatic landscape is vital for many genetic and evolutionary theories. Current knowledge for epistatic dynamics under multiple conditions is limited by the technological difficulties in experimentally screening epistatic relations among genes. We explored this issue by applying flux balance analysis to simulate epistatic landscapes under various environmental perturbations. Specifically, we looked at gene-gene epistatic interactions, where the mutations were assumed to occur in different genes. We predicted that epistasis tends to become more positive from glucose-abundant to nutrient-limiting conditions, indicating that selection might be less effective in removing deleterious mutations in the latter. We also observed a stable core of epistatic interactions in all tested conditions, as well as many epistatic interactions unique to each condition. Interestingly, genes in the stable epistatic interaction network are directly linked to most other genes whereas genes with condition-specific epistasis form a scale-free network. Furthermore, genes with stable epistasis tend to have similar evolutionary rates, whereas this co-evolving relationship does not hold for genes with condition-specific epistasis. Our findings provide a novel genome-wide picture about epistatic dynamics under environmental perturbations.     

Environment Determines Epistatic Patterns for a ssDNA Virus

Despite the accumulation of substantial quantities of information about epistatic interactions among both deleterious and beneficial mutations in a wide array of experimental systems, neither consistent patterns nor causal explanations for these interactions have yet emerged. Furthermore, the effects of mutations depend on the environment in which they are characterized, implying that the environment may also influence epistatic interactions. Recent work with beneficial mutations for the single-stranded DNA bacteriophage ID11 demonstrated that interactions between pairs of mutations could be understood by means of a simple model that assumes that mutations have additive phenotypic effects and that epistasis arises through a nonlinear phenotype–fitness map with a single intermediate optimum. To determine whether such a model could also explain changes in epistatic patterns associated with changes in environment, we measured epistatic interactions for these same mutations under conditions for which we expected to find the wild-type ID11 at different distances from its phenotypic optimum by assaying fitnesses at three different temperatures: 33°, 37°, and 41°. Epistasis was present and negative under all conditions, but became more pronounced as temperature increased. We found that the additive-phenotypes model explained these patterns as changes in the parameters of the phenotype–fitness map, but that a model that additionally allows the phenotypes to vary across temperatures performed significantly better. Our results show that ostensibly complex patterns of fitness effects and epistasis across environments can be explained by assuming a simple structure for the genotype–phenotype relationship.     

Epistatic interactions of genes influence within-individual variation of physical activity traits in mice

A number of quantitative trait loci (QTLs) recently have been discovered that affect various activity traits in mice, but their collective impact does not appear to explain the consistently moderate to high heritabilities for these traits. We previously suggested interactions of genes, or epistasis, might account for additional genetic variability of activity, and tested this for the average distance, duration and speed run by mice during a 3 week period. We found abundant evidence for epistasis affecting these traits, although, recognized that epistatic effects may well vary within individuals over time. We therefore conducted a full genome scan for epistatic interactions affecting these traits in each of seven three-day intervals. Our intent was to assess the extent and trends in epistasis affecting these traits in each of the intervals. We discovered a number of epistatic interactions of QTLs that influenced the activity traits in the mice, the majority of which were not previously found and appeared to affect the activity traits (especially distance and speed) primarily in the early or in the late age intervals. The overall impact of epistasis was considerable, its contribution to the total phenotypic variance varying from an average of 22–35% in the three traits across all age intervals. It was concluded that epistasis is more important than single-locus effects of genes on activity traits at specific ages and it is therefore an essential component of the genetic architecture of physical activity.     

Pervasive,yet idiosyncratic,epistatic pleiotropy during adaptation in a behaviourally complex microbe

Understanding how multiple mutations interact to jointly impact multiple ecologically important traits is critical for creating a robust picture of organismal fitness and the process of adaptation. However, this is complicated by both environmental heterogeneity and the complexity of genotype‐to‐phenotype relationships generated by pleiotropy and epistasis. Moreover, little is known about how pleiotropic and epistatic relationships themselves change over evolutionary time. The soil bacterium Myxococcus xanthus employs several distinct social traits across a range of environments. Here, we use an experimental lineage of M. xanthus that evolved a novel form of social motility to address how interactions between epistasis and pleiotropy evolve. Specifically, we test how mutations accumulated during selection on soft agar pleiotropically affect several other social traits (hard agar motility, predation and spore production). Relationships between changes in swarming rate in the selective environment and the four other traits varied greatly over time in both direction and magnitude, both across timescales of the entire evolutionary lineage and individual evolutionary time steps. We also tested how a previously defined epistatic interaction is pleiotropically expressed across these traits. We found that phenotypic effects of this epistatic interaction were highly correlated between soft and hard agar motility, but were uncorrelated between soft agar motility and predation, and inversely correlated between soft agar motility and spore production. Our results show that ‘epistatic pleiotropy’ varied greatly in magnitude, and often even in sign, across traits and over time, highlighting the necessity of simultaneously considering the interacting complexities of pleiotropy and epistasis when studying the process of adaptation.     

Parallel emergence of negative epistasis across experimental lineages

Epistatic interactions can greatly impact evolutionary phenomena, particularly the process of adaptation. Here, we leverage four parallel experimentally evolved lineages to study the emergence and trajectories of epistatic interactions in the social bacterium Myxococcus xanthus. A social gene (pilA) necessary for effective group swarming on soft agar had been deleted from the common ancestor of these lineages. During selection for competitiveness at the leading edge of growing colonies, two lineages evolved qualitatively novel mechanisms for greatly increased swarming on soft agar, whereas the other two lineages evolved relatively small increases in swarming. By reintroducing pilA into different genetic backgrounds along the four lineages, we tested whether parallel lineages showed similar patterns of epistasis. In particular, we tested whether a pattern of negative epistasis between accumulating mutations and pilA previously found in the fastest lineage would be found only in the two evolved lineages with the fastest and most striking swarming phenotypes, or rather was due to common epistatic structure across all lineages arising from the generic fixation of adaptive mutations. Our analysis reveals the emergence of negative epistasis across all four independent lineages. Further, we present results showing that the observed negative epistasis is not due exclusively to evolving populations approaching a maximum phenotypic value that inherently limits positive effects of pilA reintroduction, but rather involves direct antagonistic interactions between accumulating mutations and the reintroduced social gene.     

The causes of epistasis

Since Bateson's discovery that genes can suppress the phenotypic effects of other genes, gene interactions-called epistasis-have been the topic of a vast research effort. Systems and developmental biologists study epistasis to understand the genotype-phenotype map, whereas evolutionary biologists recognize the fundamental importance of epistasis for evolution. Depending on its form, epistasis may lead to divergence and speciation, provide evolutionary benefits to sex and affect the robustness and evolvability of organisms. That epistasis can itself be shaped by evolution has only recently been realized. Here, we review the empirical pattern of epistasis, and some of the factors that may affect the form and extent of epistasis. Based on their divergent consequences, we distinguish between interactions with or without mean effect, and those affecting the magnitude of fitness effects or their sign. Empirical work has begun to quantify epistasis in multiple dimensions in the context of metabolic and fitness landscape models. We discuss possible proximate causes (such as protein function and metabolic networks) and ultimate factors (including mutation, recombination, and the importance of natural selection and genetic drift). We conclude that, in general, pleiotropy is an important prerequisite for epistasis, and that epistasis may evolve as an adaptive or intrinsic consequence of changes in genetic robustness and evolvability.     

The ubiquitous nature of epistasis in determining susceptibility to common human diseases

There is increasing awareness that epistasis or gene-gene interaction plays a role in susceptibility to common human diseases. In this paper, we formulate a working hypothesis that epistasis is a ubiquitous component of the genetic architecture of common human diseases and that complex interactions are more important than the independent main effects of any one susceptibility gene. This working hypothesis is based on several bodies of evidence. First, the idea that epistasis is important is not new. In fact, the recognition that deviations from Mendelian ratios are due to interactions between genes has been around for nearly 100 years. Second, the ubiquity of biomolecular interactions in gene regulation and biochemical and metabolic systems suggest that relationship between DNA sequence variations and clinical endpoints is likely to involve gene-gene interactions. Third, positive results from studies of single polymorphisms typically do not replicate across independent samples. This is true for both linkage and association studies. Fourth, gene-gene interactions are commonly found when properly investigated. We review each of these points and then review an analytical strategy called multifactor dimensionality reduction for detecting epistasis. We end with ideas of how hypotheses about biological epistasis can be generated from statistical evidence using biochemical systems models. If this working hypothesis is true, it suggests that we need a research strategy for identifying common disease susceptibility genes that embraces, rather than ignores, the complexity of the genotype to phenotype relationship.     

Characterization of epistasis influencing complex spontaneous obesity in the BSB model

There is growing awareness that complex interactions among multiple genes and environmental factors play an important role in controlling obesity traits. The BSB mouse, which is produced by the backcross of (lean C57BL/6J x lean Mus spretus) x C57BL/6J, provides an excellent model of epistatic obesity. To evaluate potential epistatic interactions among six chromosomal regions previously determined to influence obesity phenotypes, we performed novel Bayesian analyses on the basis of both epistatic and nonepistatic models for four obesity traits: percentage of body fat, adiposity index, total fat mass, and body weight, and also for plasma total cholesterol. The epistatic analysis detected at least one more QTL than the nonepistatic analysis did for all obesity traits. These obesity traits were variously influenced by QTL on chromosomes 2, 7, 12, 15, and 16. Interaction between genes on chromosomes 2 and 12 was present for all obesity traits, accounting for 3-4.8% of the phenotypic variation. Chromosome 12 was found to have weak main effects on all obesity traits. Several different epistatic interactions were also detected for percentage of body fat, adiposity index, and total fat mass. Chromosomes 6 and 12 have not only main effects but also strong epistatic effects on plasma total cholesterol. Our results emphasize the importance of modeling epistasis for discovery of obesity genes.     

Epistasis between beneficial mutations and the phenotype-to-fitness Map for a ssDNA virus

Epistatic interactions between genes and individual mutations are major determinants of the evolutionary properties of genetic systems and have therefore been well documented, but few quantitative data exist on epistatic interactions between beneficial mutations, presumably because such mutations are so much rarer than deleterious ones. We explored epistasis for beneficial mutations by constructing genotypes with pairs of mutations that had been previously identified as beneficial to the ssDNA bacteriophage ID11 and by measuring the effects of these mutations alone and in combination. We constructed 18 of the 36 possible double mutants for the nine available beneficial mutations. We found that epistatic interactions between beneficial mutations were all antagonistic-the effects of the double mutations were less than the sums of the effects of their component single mutations. We found a number of cases of decompensatory interactions, an extreme form of antagonistic epistasis in which the second mutation is actually deleterious in the presence of the first. In the vast majority of cases, recombination uniting two beneficial mutations into the same genome would not be favored by selection, as the recombinant could not outcompete its constituent single mutations. In an attempt to understand these results, we developed a simple model in which the phenotypic effects of mutations are completely additive and epistatic interactions arise as a result of the form of the phenotype-to-fitness mapping. We found that a model with an intermediate phenotypic optimum and additive phenotypic effects provided a good explanation for our data and the observed patterns of epistatic interactions.     

Plasticity and epistasis strongly affect bacterial fitness after losing multiple metabolic genes

Many bacterial lineages lack seemingly essential metabolic genes. Previous work suggested selective benefits could drive the loss of biosynthetic functions from bacterial genomes when the corresponding metabolites are sufficiently available in the environment. However, the factors that govern this “genome streamlining” remain poorly understood. Here we determine the effect of plasticity and epistasis on the fitness of Escherichia coli genotypes from whose genome biosynthetic genes for one, two, or three different amino acids have been deleted. Competitive fitness experiments between auxotrophic mutants and prototrophic wild‐type cells in one of two carbon environments revealed that plasticity and epistasis strongly affected the mutants’ fitness individually and interactively. Positive and negative epistatic interactions were prevalent, yet on average cancelled each other out. Moreover, epistasis correlated negatively with the expected effects of combined auxotrophy‐causing mutations, thus producing a pattern of diminishing returns. Moreover, computationally analyzing 1,432 eubacterial metabolic networks revealed that most pairs of auxotrophies co‐occurred significantly more often than expected by chance, suggesting epistatic interactions and/or environmental factors favored these combinations. Our results demonstrate that both the genetic background and environmental conditions determine the adaptive value of a loss‐of‐biochemical‐function mutation and that fitness gains decelerate, as more biochemical functions are lost.     

Quantitative trait loci for maternal performance for offspring survival in mice

Maternal performance refers to the effect that the environment provided by mothers has on their offspring's phenotypes, such as offspring survival and growth. Variations in maternal behavior and physiology are responsible for variations in maternal performance, which in turn affects offspring survival. In our study we found females that failed to nurture their offspring and showed abnormal maternal behaviors. The genetic architecture of maternal performance for offspring survival was investigated in 241 females of an F(2) intercross of the SM/J and LG/J inbred mouse strains. Using interval-mapping methods we found two quantitative trait loci (QTL) affecting maternal performance at D2Mit17 + 6 cM and D7Mit21 + 2 cM on chromosomes 2 and 7, respectively. In a two-way genome-wide epistasis scan we found 15 epistatic interactions involving 23 QTL distributed across all chromosomes except 12, 16, and 17. These loci form several small sets of interacting QTL, suggesting a complex set of mechanisms operating to determine maternal performance for offspring survival. Taken all together and correcting for the large number of significant factors, QTL and their interactions explain almost 35% of the phenotypic variation for maternal performance for offspring survival in this cross. This study allowed the identification of many possible candidate genes, as well as the relative size of gene effects and patterns of gene action affecting maternal performance in mice. Detailed behavior observation of mothers from later generations suggests that offspring survival in the first week is related to maternal success in building nests, grooming their pups, providing milk, and/or manifesting aggressive behavior against intruders.     

Predicting epistasis: an experimental test of metabolic control theory with bacterial transcription and translation

Epistatic interactions between mutations are thought to play a crucial role in a number of evolutionary processes, including adaptation and sex. Evidence for epistasis is abundant, but tests of general theoretical models that can predict epistasis are lacking. In this study, I test the ability of metabolic control theory to predict epistasis using a novel experimental approach that combines phenotypic and genetic perturbations of enzymes involved in gene expression and protein synthesis in the bacterium Pseudomonas aeruginosa. These experiments provide experimental support for two key predictions of metabolic control theory: (i) epistasis between genes involved in the same pathway is antagonistic; (ii) epistasis becomes increasingly antagonistic as mutational severity increases. Metabolic control theory is a general theory that applies to any set of genes that are involved in the same linear processing chain, not just metabolic pathways, and I argue that this theory is likely to have important implications for predicting epistasis between functionally coupled genes, such as those involved in antibiotic resistance. Finally, this study highlights the fact that phenotypic manipulations of gene activity provide a powerful method for studying epistasis that complements existing genetic methods.     

Nonadditive genetic components in resistance of the red flour beetle Tribolium castanaeum against parasite infection

Genetically coupled antagonistic coevolution between host and parasites can select for the maintenance of recombination in the host. Mechanistically, maintenance of recombination relies on epistatic interactions between resistance genes creating linkage disequilibria (LD). The role of epistasis in host resistance traits is however only partly understood. Therefore, we applied the joint scaling principle to assess epistasis and other nonadditive genetic components of two resistance traits, survival, and parasite spore load, in population crosses of the red flour beetle Tribolium castanaeum under infections with the microsporidian Nosema whitei. We found nonadditive components only in infected populations but not in control populations. The genetic architecture underlying survival under parasite infection was more complex than that of spore load. Accordingly, the observed negative correlation between survival and spore load was mainly based on a correlation between shared additive components. Breakdown of resistance was especially strong in F2 crosses between resistant lines indicating that multiple epistatic routes can lead to the same adaptation. In general, the wide range of nonoverlapping genetic components between crosses indicated that parasite resistance in T. castanaeum can be understood as a multi peaked fitness landscape with epistasis contributing substantially to phenotypic differentiation in resistance.     

Expression profiles reveal parallel evolution of epistatic interactions involving the CRP regulon in Escherichia coli

The extent and nature of epistatic interactions between mutations are issues of fundamental importance in evolutionary biology. However, they are difficult to study and their influence on adaptation remains poorly understood. Here, we use a systems-level approach to examine epistatic interactions that arose during the evolution of Escherichia coli in a defined environment. We used expression arrays to compare the effect on global patterns of gene expression of deleting a central regulatory gene, crp. Effects were measured in two lineages that had independently evolved for 20,000 generations and in their common ancestor. We found that deleting crp had a much more dramatic effect on the expression profile of the two evolved lines than on the ancestor. Because the sequence of the crp gene was unchanged during evolution, these differences indicate epistatic interactions between crp and mutations at other loci that accumulated during evolution. Moreover, a striking degree of parallelism was observed between the two independently evolved lines; 115 genes that were not crp-dependent in the ancestor became dependent on crp in both evolved lines. An analysis of changes in crp dependence of well-characterized regulons identified a number of regulatory genes as candidates for harboring beneficial mutations that could account for these parallel expression changes. Mutations within three of these genes have previously been found and shown to contribute to fitness. Overall, these findings indicate that epistasis has been important in the adaptive evolution of these lines, and they provide new insight into the types of genetic changes through which epistasis can evolve. More generally, we demonstrate that expression profiles can be profitably used to investigate epistatic interactions.     

Long-term adaptation of epistatic genetic networks

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

Both additivity and epistasis control the genetic variation for fruit quality traits in tomato

The effect of a gene involved in the variation of a quantitative trait may change due to epistatic interactions with the overall genetic background or with other genes through digenic interactions. The classical populations used to map quantitative trait loci (QTL) are poorly efficient to detect epistasis. To assess the importance of epistasis in the genetic control of fruit quality traits, we compared 13 tomato lines having the same genetic background except for one to five chromosome fragments introgressed from a distant line. Six traits were assessed: fruit soluble solid content, sugar content and titratable acidity, fruit weight, locule number and fruit firmness. Except for firmness, a large part of the variation of the six traits was under additive control, but interactions between QTL leading to epistasis effects were common. In the lines cumulating several QTL regions, all the significant epistatic interactions had a sign opposite to the additive effects, suggesting less than additive epistasis. Finally the re-examination of the segregating population initially used to map the QTL confirmed the extent of epistasis, which frequently involved a region where main effect QTL have been detected in this progeny or in other studies.     

CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis

Contemporary genetic studies are revealing the genetic complexity of many traits in humans and model organisms. Two hallmarks of this complexity are epistasis, meaning gene-gene interaction, and pleiotropy, in which one gene affects multiple phenotypes. Understanding the genetic architecture of complex traits requires addressing these phenomena, but interpreting the biological significance of epistasis and pleiotropy is often difficult. While epistasis reveals dependencies between genetic variants, it is often unclear how the activity of one variant is specifically modifying the other. Epistasis found in one phenotypic context may disappear in another context, rendering the genetic interaction ambiguous. Pleiotropy can suggest either redundant phenotype measures or gene variants that affect multiple biological processes. Here we present an R package, R/cape, which addresses these interpretation ambiguities by implementing a novel method to generate predictive and interpretable genetic networks that influence quantitative phenotypes. R/cape integrates information from multiple related phenotypes to constrain models of epistasis, thereby enhancing the detection of interactions that simultaneously describe all phenotypes. The networks inferred by R/cape are readily interpretable in terms of directed influences that indicate suppressive and enhancing effects of individual genetic variants on other variants, which in turn account for the variance in quantitative traits. We demonstrate the utility of R/cape by analyzing a mouse backcross, thereby discovering novel epistatic interactions influencing phenotypes related to obesity and diabetes. R/cape is an easy-to-use, platform-independent R package and can be applied to data from both genetic screens and a variety of segregating populations including backcrosses, intercrosses, and natural populations. The package is freely available under the GPL-3 license at http://cran.r-project.org/web/packages/cape.

This is a PLOS Computational Biology Software Article

     

Little epistasis for anxiety-related measures in the DeFries strains of laboratory mice

Recent advances in methodologies for testing epistatic interactions, combined with several successes in demonstrating genetic interaction effects in animal and human genetics, have rekindled interest in the role of epistatic influences on complex traits. It has even been suggested that the unacknowledged presence of epistasis vitiates the genetic dissection of human and animal behavior. Here we report a genome-wide interaction analysis of 1636 F₂ mice to show that epistasis is of minimal importance in an animal model of anxiety. By using a sufficiently large sample of F₂ animals, we provide evidence that interaction effects between any two loci contribute less than 5% to the total phenotypic variance in multiple tests of anxiety. We conclude that interactions between loci do not necessarily vitiate the genetic analysis of behavior in at least one animal model of anxiety.     

A test for Y‐linked additive and epistatic effects on surviving bacterial infections in Drosophila melanogaster

Y‐ and W‐chromosomes offer a theoretically powerful way for sexual dimorphism to evolve. Consistent with this possibility, Drosophila melanogaster Y‐chromosomes can influence gene regulation throughout the genome; particularly immune‐related genes. In order for Y‐linked regulatory variation (YRV) to contribute to adaptive evolution it must be comprised of additive genetic variance, such that variable Ys induce consistent phenotypic effects within the local gene pool. We assessed the potential for Y‐chromosomes to adaptively shape gram‐negative and gram‐positive bacterial defence by introgressing Ys across multiple genetic haplotypes from the same population. We found no Y‐linked additive effects on immune phenotypes, suggesting a restricted role for the Y to facilitate dimorphic evolution. We did find, however, a large magnitude Y by background interaction that induced rank order reversals of Y‐effects across the backgrounds (i.e. sign epistasis). Thus, Y‐chromosome effects appeared consistent within backgrounds, but highly variable among backgrounds. This large sign epistatic effect could constrain monomorphic selection in both sexes, considering that autosomal alleles under selection must spend half of their time in a male background where relative fitness values are altered. If the pattern described here is consistent for other traits or within other XY (or ZW) systems, then YRV may represent a universal constraint to autosomal trait evolution.     

Weak Epistasis Generally Stabilizes Phenotypes in a Mouse Intercross

The extent and strength of epistasis is commonly unresolved in genetic studies, and observed epistasis is often difficult to interpret in terms of biological consequences or overall genetic architecture. We investigated the prevalence and consequences of epistasis by analyzing four body composition phenotypes—body weight, body fat percentage, femoral density, and femoral circumference—in a large F2 intercross of B6-lit/lit and C3.B6-lit/lit mice. We used Combined Analysis of Pleiotropy and Epistasis (CAPE) to examine interactions for the four phenotypes simultaneously, which revealed an extensive directed network of genetic loci interacting with each other, circulating IGF1, and sex to influence these phenotypes. The majority of epistatic interactions had small effects relative to additive effects of individual loci, and tended to stabilize phenotypes towards the mean of the population rather than extremes. Interactive effects of two alleles inherited from one parental strain commonly resulted in phenotypes closer to the population mean than the additive effects from the two loci, and often much closer to the mean than either single-locus model. Alternatively, combinations of alleles inherited from different parent strains contribute to more extreme phenotypes not observed in either parental strain. This class of phenotype-stabilizing interactions has effects that are close to additive and are thus difficult to detect except in very large intercrosses. Nevertheless, we found these interactions to be useful in generating hypotheses for functional relationships between genetic loci. Our findings suggest that while epistasis is often weak and unlikely to account for a large proportion of heritable variance, even small-effect genetic interactions can facilitate hypotheses of underlying biology in well-powered studies.