Functional overlap and regulatory links shape genetic interactions between signaling pathways

To understand relationships between phosphorylation-based signaling pathways, we analyzed 150 deletion mutants of protein kinases and phosphatases in S. cerevisiae using DNA microarrays. Downstream changes in gene expression were treated as a phenotypic readout. Double mutants with synthetic genetic interactions were included to investigate genetic buffering relationships such as redundancy. Three types of genetic buffering relationships are identified: mixed epistasis, complete redundancy, and quantitative redundancy. In mixed epistasis, the most common buffering relationship, different gene sets respond in different epistatic ways. Mixed epistasis arises from pairs of regulators that have only partial overlap in function and that are coupled by additional regulatory links such as repression of one by the other. Such regulatory modules confer the ability to control different combinations of processes depending on condition or context. These properties likely contribute to the evolutionary maintenance of paralogs and indicate a way in which signaling pathways connect for multiprocess control.     

Epistasis and Its Contribution to Genetic Variance Components

We present a new parameterization of physiological epistasis that allows the measurement of epistasis separate from its effects on the interaction (epistatic) genetic variance component. Epistasis is the deviation of two-locus genotypic values from the sum of the contributing single-locus genotypic values. This parameterization leads to statistical tests for epistasis given estimates of two-locus genotypic values such as can be obtained from quantitative trait locus studies. The contributions of epistasis to the additive, dominance and interaction genetic variances are specified. Epistasis can make substantial contributions to each of these variance components. This parameterization of epistasis allows general consideration of the role of epistasis in evolution by defining its contribution to the additive genetic variance.     

Epistasis in a model of molecular signal transduction

Biological functions typically involve complex interacting molecular networks, with numerous feedback and regulation loops. How the properties of the system are affected when one, or several of its parts are modified is a question of fundamental interest, with numerous implications for the way we study and understand biological processes and treat diseases. This question can be rephrased in terms of relating genotypes to phenotypes: to what extent does the effect of a genetic variation at one locus depend on genetic variation at all other loci? Systematic quantitative measurements of epistasis – the deviation from additivity in the effect of alleles at different loci – on a given quantitative trait remain a major challenge. Here, we take a complementary approach of studying theoretically the effect of varying multiple parameters in a validated model of molecular signal transduction. To connect with the genotype/phenotype mapping we interpret parameters of the model as different loci with discrete choices of these parameters as alleles, which allows us to systematically examine the dependence of the signaling output – a quantitative trait – on the set of possible allelic combinations. We show quite generally that quantitative traits behave approximately additively (weak epistasis) when alleles correspond to small changes of parameters; epistasis appears as a result of large differences between alleles. When epistasis is relatively strong, it is concentrated in a sparse subset of loci and in low order (e.g. pair-wise) interactions. We find that focusing on interaction between loci that exhibit strong additive effects is an efficient way of identifying most of the epistasis. Our model study defines a theoretical framework for interpretation of experimental data and provides statistical predictions for the structure of genetic interaction expected for moderately complex biological circuits.     

Epistasis,inbreeding depression,and the evolution of self-fertilization

Inbreeding depression resulting from partially recessive deleterious alleles is thought to be the main genetic factor preventing self-fertilizing mutants from spreading in outcrossing hermaphroditic populations. However, deleterious alleles may also generate an advantage to selfers in terms of more efficient purging, while the effects of epistasis among those alleles on inbreeding depression and mating system evolution remain little explored. In this article, we use a general model of selection to disentangle the effects of different forms of epistasis (additive-by-additive, additive-by-dominance, and dominance-by-dominance) on inbreeding depression and on the strength of selection for selfing. Models with fixed epistasis across loci, and models of stabilizing selection acting on quantitative traits (generating distributions of epistasis) are considered as special cases. Besides its effects on inbreeding depression, epistasis may increase the purging advantage associated with selfing (when it is negative on average), while the variance in epistasis favors selfing through the generation of linkage disequilibria that increase mean fitness. Approximations for the strengths of these effects are derived, and compared with individual-based simulation results.     

Re-evaluation of genetic formulae and epistasis

Experimental verification of some quantitative results, following from the new theory for investigation of non-allelic genes' interactions in the diallele analysis by Hayman was conducted. We postulated earlier a special kind of epistasis HC which is the new explication of epistasis j--the interaction between homozygote and heterozygote by Mather and Jinks. Genetic interpretation of the epistasis HC establishes some relations between epistasis and the model of ecological-genetical control of quantitative characters. We found the invariant characteristic of genetic control which is stable in a number of characters, environments, treatments, inspite of redetermination of genetic formulae under conditions of environmental variability.     

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.     

Improved power of sib-pair linkage analysis using measures of complex trait dynamics

The influence of epistasis on a quantitative trait can reduce the power of linkage analysis to identify the underlying loci. In the present study, we simulated a complex trait derived from a dynamic one-locus gene expression system with epistasis arising from feedback regulation and tested the power of sib-pair linkage analysis methods for detecting the underlying quantitative trait locus (QTL). Using this simple genetic architecture, we demonstrate that the power of sib-pair linkage analysis can be greatly improved if measures of complex trait dynamics are considered.     

Estimation of maternal,sex-linked and additive x additive epistatic gene effects for body size of Tribolium

Summary The genetic structure of two quantitative traits, 13-day larval weight and pupal weight, in two unselected populations of Tribolium castaneum was investigated by the genetic model of Carbonell et al. (1983). The variability among two and three-way crosses was analyzed into components due to: general and specific combining abilities, maternal, sex-linkage, specific reciprocal and additive-by-additive epistasis. Also, indirect evidence of higher order epistasis was studied. It is concluded that the heterotic trait larval weight is highly affected by sex-linked genes and by non-additive gene action with additive-by-additive as well as higher order epistasis playing major roles. Pupal weight, on the other hand, is determined mostly by additive gene action although epistasis is also a significant source for genetic variability. Both traits are significantly influenced by maternal effects.Journal Paper No. 9033 from Purdue University Agricultural Experiment Station. Based in part on PhD Theses submitted by the first two authors at Purdue University     

Interaction of mutations affecting tip growth and branching in Neurospora

There are at least 100 loci encoding products that influence tip growth and branching in Neurospora crassa. The functional relationships between 38 of these loci were examined by an analysis of gene interaction in double mutants. A complex range of interactions was revealed. These have been grouped into full and partial epistasis, costasis, novel phenotypes, and synthetic lethality and sublethality. Epistasis was used to construct the simplest "pathway" that accommodated the results; this pathway was Y-shaped. If synthetic sublethality is interpreted to reflect mutations in the same pathway, the sublethal connections are compatible with the chart of epistasis. The gene interactions discovered represent candidates for future cell and molecular studies on the interaction of gene products in the control of tip growth and branching.     

Genotypic Variation for a Quantitative Character Maintained under Stabilizing Selection without Mutations: Epistasis

A model of the gene action on a quantitative character is suggested. The model takes into account epistasis by combining multiplicative with the traditional additive approximation of the action of loci. It is demonstrated on the basis of this model that a high level of genotypic variation can be maintained in a population for a quantitative character under stabilizing selection in the absence of mutations, if there is epistasis. It is also shown that a large amount of additive variation as well as high heritability can be "hidden" in such a population and "released" if stabilizing selection is relaxed.     

eSGA: E. coli synthetic genetic array analysis

Physical and functional interactions define the molecular organization of the cell. Genetic interactions, or epistasis, tend to occur between gene products involved in parallel pathways or interlinked biological processes. High-throughput experimental systems to examine genetic interactions on a genome-wide scale have been devised for Saccharomyces cerevisiae, Schizosaccharomyces pombe, Caenorhabditis elegans and Drosophila melanogaster, but have not been reported previously for prokaryotes. Here we describe the development of a quantitative screening procedure for monitoring bacterial genetic interactions based on conjugation of Escherichia coli deletion or hypomorphic strains to create double mutants on a genome-wide scale. The patterns of synthetic sickness and synthetic lethality (aggravating genetic interactions) we observed for certain double mutant combinations provided information about functional relationships and redundancy between pathways and enabled us to group bacterial gene products into functional modules.     

WHY EPISTASIS IS IMPORTANT FOR SELECTION AND ADAPTATION

Organisms are built from thousands of genes that interact in complex ways. Still, the mathematical theory of evolution is dominated by a gene‐by‐gene perspective in which genes are assumed to have the same effects regardless of genetic background. Gene interaction, or epistasis, plays a role in some theoretical developments such as the evolution of recombination, reproductive isolation, and canalization, but is strikingly missing from our standard accounts of phenotypic adaptation. This absence is most puzzling within the field of quantitative genetics, which, despite its polygenic perspective and elaborate statistical representation of epistasis, has not found a single important role for gene interaction in evolution. To the contrary, there is a widespread consensus that epistasis is evolutionary inert, and that all we need to know to predict evolutionary dynamics is the additive component of the genetic variance. This view may have roots in convenience, but also in theoretical results showing that the response to selection derived from epistatic variance components is not permanent and will decay when selection is relaxed. I show that these results are tied to a conceptual confusion, and are misleading as general statements about the significance of epistasis for the selection response and adaptation.     

上位性及其在遗传育种研究中的应用

上位性引入遗传学已有一个多世纪,直到近些年才受到广泛关注,成为复杂性状遗传研究体系的一个重要组成部分。上位性可分为统计上位性和功能上位性两类,前者具有群体特性,后者属于基因型现象。分子标记技术是研究上位性的一个有力工具,理论与实验研究证实上位性在动植物数量性状的表现中具有重要作用。上位性在作物育种中的应用因作物的繁殖方式,育种方法等不同而异,上位性是杂种优势形成的重要遗传基础。     

The RAD52 recombinational repair pathway is essential in pol30 (PCNA) mutants that accumulate small single-stranded DNA fragments during DNA synthesis.

To identify in vivo pathways that compensate for impaired proliferating cell nuclear antigen (PCNA or Pol30p in yeast) activity, we performed a synthetic lethal screen with the yeast pol30-104 mutation. We identified nine mutations that display synthetic lethality with pol30-104; three mutations affected the structural gene for the large subunit of replication factor C (rfc1), which loads PCNA onto DNA, and six mutations affected three members of the RAD52 epistasis group for DNA recombinational repair (rad50, rad52 and rad57). We also found that pol30-104 displayed synthetic lethality with mutations in other members of the RAD52 epistasis group (rad51 and rad54), but not with mutations in members of the RAD3 nor the RAD6 epistasis group. Analysis of nine different pol30 mutations shows that the requirement for the RAD52 pathway is correlated with a DNA replication defect but not with the relative DNA repair defect caused by pol30 mutations. In addition, mutants that require RAD52 for viability (pol30-100, pol30-104, rfc1-1 and rth1delta) accumulate small single-stranded DNA fragments during DNA replication in vivo. Taken together, these data suggest that the RAD52 pathway is required when there are defects in the maturation of Okazaki fragments.     

Modeling epistasis of quantitative trait loci using Cockerham's model

We use the orthogonal contrast scales proposed by Cockerham to construct a genetic model, called Cockerham's model, for studying epistasis between genes. The properties of Cockerham's model in modeling and mapping epistatic genes under linkage equilibrium and disequilibrium are investigated and discussed. Because of its orthogonal property, Cockerham's model has several advantages in partitioning genetic variance into components, interpreting and estimating gene effects, and application to quantitative trait loci (QTL) mapping when compared to other models, and thus it can facilitate the study of epistasis between genes and be readily used in QTL mapping. The issues of QTL mapping with epistasis are also addressed. Real and simulated examples are used to illustrate Cockerham's model, compare different models, and map for epistatic QTL. Finally, we extend Cockerham's model to multiple loci and discuss its applications to QTL mapping.     

Influence of Gene Interaction on Complex Trait Variation with Multilocus Models

Although research effort is being expended into determining the importance of epistasis and epistatic variance for complex traits, there is considerable controversy about their importance. Here we undertake an analysis for quantitative traits utilizing a range of multilocus quantitative genetic models and gene frequency distributions, focusing on the potential magnitude of the epistatic variance. All the epistatic terms involving a particular locus appear in its average effect, with the number of two-locus interaction terms increasing in proportion to the square of the number of loci and that of third order as the cube and so on. Hence multilocus epistasis makes substantial contributions to the additive variance and does not, per se, lead to large increases in the nonadditive part of the genotypic variance. Even though this proportion can be high where epistasis is antagonistic to direct effects, it reduces with multiple loci. As the magnitude of the epistatic variance depends critically on the heterozygosity, for models where frequencies are widely dispersed, such as for selectively neutral mutations, contributions of epistatic variance are always small. Epistasis may be important in understanding the genetic architecture, for example, of function or human disease, but that does not imply that loci exhibiting it will contribute much genetic variance. Overall we conclude that theoretical predictions and experimental observations of low amounts of epistatic variance in outbred populations are concordant. It is not a likely source of missing heritability, for example, or major influence on predictions of rates of evolution.     

Accounting for epistasis in linkage analysis of general pedigrees

Complex traits are generally believed to be influenced by multiple loci. Identification of loci involved in complex traits is more difficult for interacting than for additive loci. Here we describe an extension of the program lm_twoqtl in the package MORGAN to handle two quantitative trait loci (QTLs) with gene-gene interaction. We investigate whether parametric linkage analysis that accounts for such epistasis improves prospects for linkage detection and accuracy of localization of QTLs. Through use of simulated data we show that analysis that accounts for epistasis provides higher lod scores and better localization than does analysis without epistasis. In addition, we demonstrate that the difference between lod scores in the presence vs. absence of use of an interaction model in analysis is greater in extended than in nuclear pedigrees.     

Efficiency of triple test cross for detecting epistasis with marker information

The triple test cross (TTC) is an experimental design for detecting epistasis and estimating the components of genetic variance for quantitative traits. In this paper, we extend the analysis to include molecular information. The statistical power of the mating design was assessed under a model assuming that a finite number of loci affect the trait in question. Formulae are developed for the analysis with or without marker information relating to the recombination fraction between loci, the genetical properties of quantitative trait controlled by the quantitative trait loci (QTL), the linkage phases of the parents and population size. Application of these formulae showed that the recombination fraction between genes and the magnitude and the types of epistasis have important interactions in their effects on power. The results demonstrate that the TTC may have increased power to detect epistasis when marker information is present. However, the simulation experiments show that the standard deviation of the estimated expected mean square was higher with one marker than that with two, whereas the corresponding value without marker information was the lowest. In addition, we demonstrate that the relative position of QTL and markers and the number of markers can both affect the power of epistatic detection.