Using phenotypic plasticity to understand the structure and evolution of the genotype–phenotype map

Genetica - Deciphering the genotype–phenotype map necessitates relating variation at the genetic level to variation at the phenotypic level. This endeavour is inherently limited by the...     

Mechanisms for phenotypic variation in Lesch–Nyhan disease and its variants

Lesch–Nyhan disease is a neurogenetic disorder caused by mutation of the HPRT1 gene on the X chromosome. There is significant variation in the clinical phenotype, with more than 300 different known mutations. There are few studies that have addressed whether similar mutations result in similar phenotypes across different patients because hypoxanthine–guanine phosphoribosyltransferase (HGprt) deficiency is rare, and most mutations are unique or limited to individual families. However, recent studies have revealed multiple unrelated patients with similar mutations, providing an opportunity to examine genotype–phenotype correlations. We found significant variation among the clinical features of 10 patients from 8 unrelated families all carrying a mutation replacing guanine with adenine at base position 143 (c.143G>A) in the HPRT1 gene. This mutation results in replacement of arginine by histidine at amino acid position 48 (p.arg48his) in the HGprt enzyme. Biochemically, the enzyme exhibits reduced thermal integrity, a mechanism that may explain clinical variation. The literature reveals similar clinical variation among other patients with similar mutations, although the variation is relatively minor across the whole population of patients. Identifiable sources of clinical variation include known limitations of clinical ascertainment and mechanisms that affect residual enzyme activity and stability. These results are helpful for understanding genotype–phenotype correlations and discordance and likely are applicable to other neurogenetic disorders where similar variation occurs.     

The Developmental Basis of Variational Modularity: Insights from Quantitative Genetics,Morphometrics, and Developmental Biology

Groups of correlated characters (variational modules) often are considered to be the result of dissociated local developmental factors, i.e., of a modular genotype–phenotype map. But certain sets of pleiotropic factors can equally well induce modular phenotypic variation—no local developmental factors are necessary for a modular covariance structure. It is thus not possible to infer genetic or developmental modularity from standing variation alone. Yet, only for approximately linear genotype–phenotype maps is the induced covariance structure stable over changes of the phenotypic mean. For larger genetic and phenotypic variation, such as on a macroevolutionary level, developmental effects often are nonlinear and variational modularity remains stable only when it is realized by local dissociated developmental factors with no overlap of pleiotropic ranges. The evo-devo concept of modularity concurs only at this macroevolutionary level with the quantitative notion of variational modularity. Empirical evidence on the genetic and developmental architecture underlying phenotypic variation is inconclusive and partly subject to methodological problems. Many studies seem to indicate modularized phenotypic variation and local clusters of QTL effects, whereas other studies find support for several alternative models of modularity and report continuous distributions of QTL effects. This inconsistency partly results from the neglect of spatial relationships among the measured traits. Given the complex development of higher organisms, a combination of pleiotropic factors and more local developmental effects with a hierarchical, overlapping, and more or less continuous distribution appears most likely.     

Search for informative polymorphisms in candidate genes: clock genes and circadian behaviour in blue tits

The identification of functional polymorphisms in genes that underlie behavioural trait variation is a challenging but intriguing task in evolutionary biology. Given the wealth of genomic data and the increasing number of genotype–phenotype association studies in model organisms, one can ask whether and how this information can be used for non-model organisms. Here we describe two strategies to search for likely functional polymorphisms in candidate genes in a bird species that has been intensively studied by behavioural and population ecologists, the blue tit Cyanistes caeruleus. In the first approach we searched for repeating elements in coding regions of the genome using information about repeats in Gallus gallus genes. The rationale is that tandem-repeat elements have a high potential to be polymorphic and functional. The second strategy aimed to replicate reported genotype–phenotype association studies by extrapolating results from model organisms to our study species. Both strategies showed high success rates with respect to finding homologous gene regions and potentially informative genetic variants in the genes AANAT, ADCYAP1, CKIε, CLOCK, CREB1, NPAS2 and PERIOD2. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Quantitative Relationship Between Mutated Structure of Human Glucosylceramidase and Gaucher Disease Status

The mutations in human glucosylceramidase lead to Gaucher disease, which is the most prevalent lysosomal storage disease. So far 153 point mutations have been recorded in human glucosylceramidase, resulting in a wide variability in clinical presentations. In this study, we use the amino-acid distribution probability to quantify each mutation, and use the cross-impact analysis with Bayes’ law to build a quantitative relationship between mutated primary structure of human glucosylceramidase and status of Gaucher disease. The results demonstrate that we can build a quantitative relationship between changed structure and changed function of protein, which is useful for understanding the genotype–phenotype relationship of disease.     

Quantitative trait loci mapping and the genetic basis of heterosis in maize and rice

Despite its importance to agriculture, the genetic basis of heterosis is still not well understood. The main competing hypotheses include dominance, overdominance, and epistasis. NC design III is an experimental design that has been used for estimating the average degree of dominance of quantitative trait loci (QTL) and also for studying heterosis. In this study, we first develop a multiple-interval mapping (MIM) model for design III that provides a platform to estimate the number, genomic positions, augmented additive and dominance effects, and epistatic interactions of QTL. The model can be used for parents with any generation of selfing. We apply the method to two data sets, one for maize and one for rice. Our results show that heterosis in maize is mainly due to dominant gene action, although overdominance of individual QTL could not completely be ruled out due to the mapping resolution and limitations of NC design III. For rice, the estimated QTL dominant effects could not explain the observed heterosis. There is evidence that additive × additive epistatic effects of QTL could be the main cause for the heterosis in rice. The difference in the genetic basis of heterosis seems to be related to open or self pollination of the two species. The MIM model for NC design III is implemented in Windows QTL Cartographer, a freely distributed software.     

Metabolic Interrelations Underlying the Physiological and Evolutionary Advantages of Genetic Diversity

Past findings have established how the faster growth, greaterreproductive output and/or longer survival that are associatedwith heterosis and genomic diversity measured as multi-locusheterozygosity stem from slower intensities with which proteinsare renewed and replaced (=protein turnover). Slower turnoverresults in lower energy requirements and reduced metabolic sensitivityto environmental change, representing a mechanistic basis forevolutionary consequences of genetic polymorphism. To determinethe genetic and functional basis of differences in whole-bodyprotein turnover, we have begun to resolve different proteolyticpathways, searching for genetic polymorphisms with a directeffect upon proteolysis, and assessing the metabolic and physiologicalconsequences of those genetic influences in the mussel Mytilusedulis. Our recent work has established the physiological importanceof lysosomal enzymes under normal conditions of basal proteolysis,and shown that associated effects on energy flux may vary accordingto functional differences between separate enzymes. Data arepresented here which compare metabolic consequences of polymorphismin the lysosomal aminopeptidases Lap-1 and Lap-2. Findings establishthat metabolic and phenotypic effects of genetic polymorphismresult directly from genetic variation at the loci coding forthese peptidases, rather than from linked loci. They also illustratethe complexity of interrelations that ultimately influence theevolutionary consequences of genomic diversity, including associatedinfluences of both Lap-1 and Lap-2 on energy requirements andanimal condition. We impress that energy requirements for proteinturnover may represent a functional basis for epistasis, includingassociations whereby advantages of genetic polymorphism aregreatest at loci that code for enzymes acting in both proteincatabolism and energy provision.     

The genetical basis of hybrid vigour in a highly heterotic cross of Nicotiana tabacum

The genetical control of F₁ heterosis, observed in a cross of desirable Nicotiana tabacum varieties, was investigated by analysing the data of the basic generations, triple test cross-families and random samples of doubled haploids (DH) and single-seed descent (SSD) lines. Analyses of the first-degree statistics revealed a complex control underlying the genetic variation, including the presence of epistasis, linkage, maternal effects and their interactions, in addition to the additive and dominance effects of the genes segregating in the cross. These analyses identified gene dispersion, directional dominance, and duplicate epistasis, as the main causes of heterosis. The triple test-cross analysis also confirmed the presence of non-allelic interactions and indicated that the dominance ratio, although inflated by epistasis, is consistently partial for all the traits. The extent of transgression in the recombinant inbred lines finally established unequivocally that, as in numerous other crosses, gene dispersion and unidirectional, but partial, dominance are the true causes of heterosis in this cross too.     

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.     

Simultaneous mapping of epistatic QTL in DU6i × DBA/2 mice

We have mapped epistatic quantitative trait loci (QTL) in an F₂ cross between DU6i × DBA/2 mice. By including these epistatic QTL and their interaction parameters in the genetic model, we were able to increase the genetic variance explained substantially (8.8%–128.3%) for several growth and body composition traits. We used an analysis method based on a simultaneous search for epistatic QTL pairs without assuming that the QTL had any effect individually. We were able to detect several QTL that could not be detected in a search for marginal QTL effects because the epistasis cancelled out the individual effects of the QTL. In total, 23 genomic regions were found to contain QTL affecting one or several of the traits and eight of these QTL did not have significant individual effects. We identified 44 QTL pairs with significant effects on the traits, and, for 28 of the pairs, an epistatic QTL model fit the data significantly better than a model without interactions. The epistatic pairs were classified by the significance of the epistatic parameters in the genetic model, and visual inspection of the two-locus genotype means identified six types of related genotype–phenotype patterns among the pairs. Five of these patterns resembled previously published patterns of QTL interactions.     

Epistatic interaction maps relative to multiple metabolic phenotypes

An epistatic interaction between two genes occurs when the phenotypic impact of one gene depends on another gene, often exposing a functional association between them. Due to experimental scalability and to evolutionary significance, abundant work has been focused on studying how epistasis affects cellular growth rate, most notably in yeast. However, epistasis likely influences many different phenotypes, affecting our capacity to understand cellular functions, biochemical networks adaptation, and genetic diseases. Despite its broad significance, the extent and nature of epistasis relative to different phenotypes remain fundamentally unexplored. Here we use genome-scale metabolic network modeling to investigate the extent and properties of epistatic interactions relative to multiple phenotypes. Specifically, using an experimentally refined stoichiometric model for Saccharomyces cerevisiae, we computed a three-dimensional matrix of epistatic interactions between any two enzyme gene deletions, with respect to all metabolic flux phenotypes. We found that the total number of epistatic interactions between enzymes increases rapidly as phenotypes are added, plateauing at approximately 80 phenotypes, to an overall connectivity that is roughly 8-fold larger than the one observed relative to growth alone. Looking at interactions across all phenotypes, we found that gene pairs interact incoherently relative to different phenotypes, i.e. antagonistically relative to some phenotypes and synergistically relative to others. Specific deletion-deletion-phenotype triplets can be explained metabolically, suggesting a highly informative role of multi-phenotype epistasis in mapping cellular functions. Finally, we found that genes involved in many interactions across multiple phenotypes are more highly expressed, evolve slower, and tend to be associated with diseases, indicating that the importance of genes is hidden in their total phenotypic impact. Our predictions indicate a pervasiveness of nonlinear effects in how genetic perturbations affect multiple metabolic phenotypes. The approaches and results reported could influence future efforts in understanding metabolic diseases and the role of biochemical regulation in the cell.     

Effects of epistasis on phenotypic robustness in metabolic pathways

It is an open question whether phenomena such as phenotypic robustness to mutation evolve as adaptations or are simply an inherent property of genetic systems. As a case study, we examine this question with regard to dominance in metabolic physiology. Traditionally the conclusion that has been derived from Metabolic Control Analysis has been that dominance is an inevitable property of multi-enzyme systems and hence does not require an evolutionary explanation. This view is based on a mathematical result commonly referred to as the flux summation theorem. However it is shown here that for mutations involving finite changes (of any magnitude) in enzyme concentration, the flux summation theorem can only hold in a very restricted set of conditions. Using both analytical and simulation results we show that for finite changes, the summation theorem is only valid in cases where the relationship between genotype and phenotype is linear and devoid of non-linearities in the form of epistasis. Such an absence of epistasis is unlikely in metabolic systems. As an example, we show that epistasis can arise in scenarios where we assume generic non-linearities such as those caused by enzyme saturation. In such cases dominance levels can be modified by mutations that affect saturation levels. The implication is that dominance is not a necessary property of metabolic systems and that it can be subject to evolutionary modification.     

Genetic basis of grain yield heterosis in an “immortalized F2” maize population

Key message

Genetic basis of grain yield heterosis relies on the cumulative effects of dominance, overdominance, and epistasis in maize hybrid Yuyu22.

Abstract

Heterosis, i.e., when F₁ hybrid phenotypes are superior to those of the parents, continues to play a critical role in boosting global grain yield. Notwithstanding our limited insight into the genetic and molecular basis of heterosis, it has been exploited extensively using different breeding approaches. In this study, we investigated the genetic underpinnings of grain yield and its components using “immortalized F₂” and recombinant inbred line populations derived from the elite hybrid Yuyu22. A high-density linkage map consisting of 3,184 bins was used to assess (1) the additive and additive-by-additive effects determined using recombinant inbred lines; (2) the dominance and dominance-by-dominance effects from a mid-parent heterosis dataset; and (3) the various genetic effects in the “immortalized F₂” population. Compared with a low-density simple sequence repeat map, the bin map identified more quantitative trait loci, with higher LOD scores and better accuracy of detecting quantitative trait loci. The bin map showed that, among all traits, dominance was more important to heterosis than other genetic effects. The importance of overdominance/pseudo-overdominance was proportional to the amount of heterosis. In addition, epistasis contributed to heterosis as well. Phenotypic variances explained by the QTLs detected were close to the broad-sense heritabilities of the observed traits. Comparison of the analyzed results obtained for the “immortalized F₂” population with those for the mid-parent heterosis dataset indicated identical genetic modes of action for mid-parent heterosis and grain yield performance of the hybrid.     

Epistasis can accelerate adaptive diversification in haploid asexual populations

A fundamental goal of the biological sciences is to determine processes that facilitate the evolution of diversity. These processes can be separated into ecological, physiological, developmental and genetic. An ecological process that facilitates diversification is frequency-dependent selection caused by competition. Models of frequency-dependent adaptive diversification have generally assumed a genetic basis of phenotype that is non-epistatic. Here, we present a model that indicates diversification is accelerated by an epistatic basis of phenotype in combination with a competition model that invokes frequency-dependent selection. Our model makes use of a genealogical model of epistasis and insights into the effects of balancing selection on the genealogical structure of a population to understand how epistasis can facilitate diversification. The finding that epistasis facilitates diversification may be informative with respect to empirical results that indicate an epistatic basis of phenotype in experimental bacterial populations that experienced adaptive diversification.     

A novel survival multifactor dimensionality reduction method for detecting gene–gene interactions with application to bladder cancer prognosis

The widespread use of high-throughput methods of single nucleotide polymorphism (SNP) genotyping has created a number of computational and statistical challenges. The problem of identifying SNP–SNP interactions in case–control studies has been studied extensively, and a number of new techniques have been developed. Little progress has been made, however, in the analysis of SNP–SNP interactions in relation to time-to-event data, such as patient survival time or time to cancer relapse. We present an extension of the two class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP–SNP interactions in the context of survival analysis. The proposed Survival MDR (Surv-MDR) method handles survival data by modifying MDR’s constructive induction algorithm to use the log-rank test. Surv-MDR replaces balanced accuracy with log-rank test statistics as the score to determine the best models. We simulated datasets with a survival outcome related to two loci in the absence of any marginal effects. We compared Surv-MDR with Cox-regression for their ability to identify the true predictive loci in these simulated data. We also used this simulation to construct the empirical distribution of Surv-MDR’s testing score. We then applied Surv-MDR to genetic data from a population-based epidemiologic study to find prognostic markers of survival time following a bladder cancer diagnosis. We identified several two-loci SNP combinations that have strong associations with patients’ survival outcome. Surv-MDR is capable of detecting interaction models with weak main effects. These epistatic models tend to be dropped by traditional Cox regression approaches to evaluating interactions. With improved efficiency to handle genome wide datasets, Surv-MDR will play an important role in a research strategy that embraces the complexity of the genotype–phenotype mapping relationship since epistatic interactions are an important component of the genetic basis of disease.     

A dynamic and complex network regulates the heterosis of yield-correlated traits in rapeseed (Brassica napus L.)

Although much research has been conducted, the genetic architecture of heterosis remains ambiguous. To unravel the genetic architecture of heterosis, a reconstructed F(2) population was produced by random intercross among 202 lines of a double haploid population in rapeseed (Brassica napus L.). Both populations were planted in three environments and 15 yield-correlated traits were measured, and only seed yield and eight yield-correlated traits showed significant mid-parent heterosis, with the mean ranging from 8.7% (branch number) to 31.4% (seed yield). Hundreds of QTL and epistatic interactions were identified for the 15 yield-correlated traits, involving numerous variable loci with moderate effect, genome-wide distribution and obvious hotspots. All kinds of mode-of-inheritance of QTL (additive, A; partial-dominant, PD; full-dominant, D; over-dominant, OD) and epistatic interactions (additive × additive, AA; additive × dominant/dominant × additive, AD/DA; dominant × dominant, DD) were observed and epistasis, especially AA epistasis, seemed to be the major genetic basis of heterosis in rapeseed. Consistent with the low correlation between marker heterozygosity and mid-parent heterosis/hybrid performance, a considerable proportion of dominant and DD epistatic effects were negative, indicating heterozygosity was not always advantageous for heterosis/hybrid performance. The implications of our results on evolution and crop breeding are discussed.     

Coming to Grips with Evolvability

To explain the evolution of complex organisms by random mutation, drift, and selection is not a trivial task. This becomes obvious if we imagine an organism in which most genes affect most traits and all mutations are immediately expressed in the phenotype. Most of the mutations will be deleterious. Computer programmers experienced a similar problem when trying to evolve computer programs by introducing random changes to a conventional computer code, realizing that almost all random changes are “lethal.” Everyone who has done any programming knows that conventional computer languages are very brittle! Real organisms are not organized in this way but rather involve mediation between the genes and the phenotypic traits, namely development, also sometimes called the genotype–phenotype map. This map of genetic effects is structured in a way that enables evolvability, that is, enhances the probability that mutations will improve the performance of the organism. Here we outline two properties of organismal development, namely modularity and robustness. Modularity refers to the situation in which genes affect a restricted number of functionally related phenotypic characters. Robustness describes a situation in which cryptic mutations can accumulate without effect on fitness but can become visible to selection in a new environment or genetic background. We discuss recent empirical evidence in support of both phenomena and their effect on evolvability and also briefly address their evolution.     

Metabolic flux analysis of<Emphasis Type="Italic"> pykF</Emphasis> gene knockout<Emphasis Type="Italic"> Escherichia coli</Emphasis> based on <Superscript>13</Superscript>C-labeling experiments together with measurements of enzyme activities and intracellular metabolite concentrations

Metabolic flux analysis based on ¹³C-labeling experiments followed by the measurement of intracellular isotope distribution using both 2D NMR and GC-MS was carried out to investigate the effect of pyruvate kinase (pyk) gene knockout on the metabolism of Escherichia coli in continuous culture. In addition, the activities of 16 enzymes, and the concentrations of 5 intracellular metabolites, were measured as a function of time in batch culture as well as continuous culture. It was found that flux through phosphoenol pyruvate carboxylase and malic enzyme were up-regulated in the pykF^– mutant as compared with the wild type, and acetate formation was significantly reduced in the mutant. In addition, flux through the phosphofructose kinase pathway was reduced and that through the oxidative pentose phosphate (PP) pathway increased in the mutant. This was evidenced by the corresponding enzyme activities, and the increase in the concentrations of phosphoenol pyruvate, glucose-6-phosphate and 6-phosphogluconate, etc. It was also found for continuous cultivation that the enzyme activities of the oxidative PP and Entner-Doudoroff pathways increased as the dilution rate increased for the pykF^– mutant. To clarify the metabolism quantitatively, it was found to be quite important to integrate the information on intracellular metabolic flux distribution, enzyme activities and intracellular metabolite concentrations.     

Analysis of heterosis by a direct method using the concept of heritability

The presence of heterosis has been observed in many species at both phenotypic and gene levels. Strangely, the genetic basis of heterosis was and still is largely unknown. In this study, we extended and simplified some formulas that we reported previously. The foundation of our model was based on partitioning the F ₁ phenotypic variance of the cross between two pure lines into additive, dominance and epistasis components, which lead to the estimation of effective factors, crossheritability in the broad and narrow sense and heterotic power. In the model, we assume that all polygenes controlling a quantitative trait have an equal genetic effect and are independent of each other. By extension of the heritability to a cross population, new features appear. The word crossheritability acquires the status of a new genetic parameter that suffices to deal with the problem of crossbreeding and clarifies the picture of heterosis. Lastly, an example of employing the proposed method in analyzing the crossing data from Drosophila melanogaster is given to illustrate its application.