Proportionality between variances in gene expression induced by noise and mutation: consequence of evolutionary robustness

Background  

Characterization of robustness and plasticity of phenotypes is a basic issue in evolutionary and developmental biology. The robustness and plasticity are concerned with changeability of a biological system against external perturbations. The perturbations are either genetic, i.e., due to mutations in genes in the population, or epigenetic, i.e., due to noise during development or environmental variations. Thus, the variances of phenotypes due to genetic and epigenetic perturbations provide quantitative measures for such changeability during evolution and development, respectively.     

Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity

While reverse genetics and functional genomics have long affirmed the role of individual mutations in determining protein function, there have been fewer studies addressing how large‐scale changes in protein sequences, such as in entire modular segments, influence protein function and evolution. Given how recombination can reassort protein sequences, these types of changes may play an underappreciated role in how novel protein functions evolve in nature. Such studies could aid our understanding of whether certain organismal phenotypes related to protein function—such as growth in the presence or absence of an antibiotic—are robust with respect to the identity of certain modular segments. In this study, we combine molecular genetics with biochemical and biophysical methods to gain a better understanding of protein modularity in dihydrofolate reductase (DHFR), an enzyme target of antibiotics also widely used as a model for protein evolution. We replace an integral α‐helical segment of Escherichia coli DHFR with segments from a number of different organisms (many nonmicrobial) and examine how these chimeric enzymes affect organismal phenotypes (e.g., resistance to an antibiotic) as well as biophysical properties of the enzyme (e.g., thermostability). We find that organismal phenotypes and enzyme properties are highly sensitive to the identity of DHFR modules, and that this chimeric approach can create enzymes with diverse biophysical characteristics.     

Genetic robustness and selection at the protein level for synonymous codons

Synonymous codons are neutral at the protein level, therefore natural selection at the protein level should have no effect on their frequencies. Synonymous codons, however, differ in their capacity to reduce the effects of errors: after mutation, certain codons keep on coding for the same amino acid or for amino acids with similar properties, while other synonymous codons produce very different amino acids. Therefore, the impact of errors on a coding sequence (genetic robustness) can be measured by analysing its codon usage. I analyse the codon usage of sequenced nuclear and cytoplasmic genomes and I show that there is an extensive variation in genetic robustness at the DNA sequence level, both among genomes and among genes of the same genome. I also show theoretically that robustness can be adaptive, that is natural selection may lead to a preference for codons that reduce the impact of errors. If selection occurs only among the mutants of a codon (e.g. among the progeny before the adult phase), however, the codons that are more sensitive to the effects of mutations may increase in frequency because they manage to get rid more easily of deleterious mutations. I also suggest other possible explanations for the evolution of genetic robustness at the codon level.     

Prediction of complex phenotypes using the Drosophila melanogaster metabolome

Understanding the genotype–phenotype map and how variation at different levels of biological organization is associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins and metabolites. This can facilitate our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use the Drosophila melanogaster Genetic Reference Panel and nuclear magnetic resonance (NMR) metabolomics to investigate the ability of the metabolome to predict organismal phenotypes. We performed NMR metabolomics on four replicate pools of male flies from each of 170 different isogenic lines. Our results show that metabolite profiles are variable among the investigated lines and that this variation is highly heritable. Second, we identify genes associated with metabolome variation. Third, using the metabolome gave better prediction accuracies than genomic information for four of five quantitative traits analyzed. Our comprehensive characterization of population-scale diversity of metabolomes and its genetic basis illustrates that metabolites have large potential as predictors of organismal phenotypes. This finding is of great importance, e.g., in human medicine, evolutionary biology and animal and plant breeding.Subject terms: Quantitative trait, Genetic association study     

Evolution of phenotypic fluctuation under host-parasite interactions

Robustness and plasticity are essential features that allow biological systems to cope with complex and variable environments. In a constant environment, robustness, i.e., insensitivity of phenotypes, is expected to increase, whereas plasticity, i.e., the changeability of phenotypes, tends to diminish. Under a variable environment, existence of plasticity will be relevant. The robustness and plasticity, on the other hand, are related to phenotypic variances. As phenotypic variances decrease with the increase in robustness to perturbations, they are expected to decrease through the evolution. However, in nature, phenotypic fluctuation is preserved to a certain degree. One possible cause for this is environmental variation, where one of the most important “environmental” factors will be inter-species interactions. As a first step toward investigating phenotypic fluctuation in response to an inter-species interaction, we present the study of a simple two-species system that comprises hosts and parasites. Hosts are expected to evolve to achieve a phenotype that optimizes fitness. Then, the robustness of the corresponding phenotype will be increased by reducing phenotypic fluctuations. Conversely, plasticity tends to evolve to avoid certain phenotypes that are attacked by parasites. By using a dynamic model of gene expression for the host, we investigate the evolution of the genotype-phenotype map and of phenotypic variances. If the host–parasite interaction is weak, the fittest phenotype of the host evolves to reduce phenotypic variances. In contrast, if there exists a sufficient degree of interaction, the phenotypic variances of hosts increase to escape parasite attacks. For the latter case, we found two strategies: if the noise in the stochastic gene expression is below a certain threshold, the phenotypic variance increases via genetic diversification, whereas above this threshold, it is increased mediated by noise-induced phenotypic fluctuation. We examine how the increase in the phenotypic variances caused by parasite interactions influences the growth rate of a single host, and observed a trade-off between the two. Our results help elucidate the roles played by noise and genetic mutations in the evolution of phenotypic fluctuation and robustness in response to host–parasite interactions.     

Robustness and evolution: concepts, insights and challenges from a developmental model system

Robustness, the persistence of an organismal trait under perturbations, is a ubiquitous property of complex living systems. We here discuss key concepts related to robustness with examples from vulva development in the nematode Caenorhabditis elegans. We emphasize the need to be clear about the perturbations a trait is (or is not) robust to. We discuss two prominent mechanistic causes of robustness, namely redundancy and distributed robustness. We also discuss possible evolutionary causes of robustness, one of which does not involve natural selection. To better understand robustness is of paramount importance for understanding organismal evolution. Part of the reason is that highly robust systems can accumulate cryptic variation that can serve as a source of new adaptations and evolutionary innovations. We point to some key challenges in improving our understanding of robustness.     

Directional selection reduces developmental canalization against genetic and environmental perturbations in Drosophila wings

Natural selection may enhance or weaken the robustness of phenotypes against genetic or environmental perturbations. However, important aspects of the relationship between adaptive evolution and canalization remain unclear. Recent work showed that the evolution of larger wing size in a high altitude natural population of Drosophila melanogaster was accompanied by decanalized wing development–‐specifically a loss of robustness to genetic perturbation. But this study did not address environmental robustness, and it compared populations that may have numerous biological differences. Here, we perform artificial selection on this same trait in D. melanogaster (larger wing length) and directly test whether this directional selection resulted in decanalization. We find that in general, size‐selected replicates show greater frequencies of wing defects than control replicates both after mutagenesis (genetic perturbation) and when subjected to high temperature stress (environmental perturbation), although the increase in defect frequency varies importantly among replicates. These results support the hypothesis that directional selection may result in the loss of both genetic and environmental robustness–offering a rare window into the relationship between adaptation and canalization.     

Mitochondrial variation in small brown planthoppers linked to multiple traits and probably reflecting a complex evolutionary trajectory

While it has been proposed in several taxa that the mitochondrial genome is associated with adaptive evolution to different climatic conditions, making links between mitochondrial haplotypes and organismal phenotypes remains a challenge. Mitonuclear discordance occurs in the small brown planthopper (SBPH), Laodelphax striatellus, with one mitochondrial haplogroup (HGI) more common in the cold climate region of China relative to another form (HGII) despite strong nuclear gene flow, providing a promising model to investigate climatic adaptation of mitochondrial genomes. We hypothesized that cold adaptation through HGI may be involved, and considered mitogenome evolution, population genetic analyses, and bioassays to test this hypothesis. In contrast to our hypothesis, chill‐coma recovery tests and population genetic tests of selection both pointed to HGII being involved in cold adaptation. Phylogenetic analyses revealed that HGII is nested within HGI, and has three nonsynonymous changes in ND2, ND5 and CYTB in comparison to HGI. These molecular changes likely increased mtDNA copy number, cold tolerance and fecundity of SBPH, particularly through a function‐altering amino acid change involving M114T in ND2. Nuclear background also influenced fecundity and chill recovery (i.e., mitonuclear epistasis) and protein modelling indicates possible nuclear interactions for the two nonsynonymous changes in ND2 and CYTB. The high occurrence frequency of HGI in the cold climate region of China remains unexplained, but several possible reasons are discussed. Overall, our study points to a link between mtDNA variation and organismal‐level evolution and suggests a possible role of mitonuclear interactions in maintaining mtDNA diversity.     

New phenotypes for new breeding goals in pigs

Pig breeders in the past have adopted their breeding goals according to the needs of the producers, processors and consumers and have made remarkable genetic improvements in the traits of interest. However, it is becoming more and more challenging to meet the market needs and expectations of consumers and in general of the citizens. In view of the current and future trends, the breeding goals have to include several additional traits and new phenotypes. These phenotypes include (a) vitality from birth to slaughter, (b) uniformity at different levels of production, (c) robustness, (d) welfare and health and (e) phenotypes to reduce carbon footprint. Advancements in management, genomics, statistical models and other technologies provide opportunities for recording these phenotypes. These new developments also provide opportunities for making effective use of the new phenotypes for faster genetic improvement to meet the newly adapted breeding goals.     

Toward a universal measure of robustness across model organs and systems

The development of an individual must be capable of resisting the harmful effects of internal and external perturbations. This capacity, called robustness, can make the difference between normal variation and disease. Some systems and organs are more resilient in their capacity to correct the effects of internal disturbances such as mutations. Similarly, organs and organisms differ in their capacity to be resilient against external disturbances, such as changes in temperature. Furthermore, all developmental systems must be somewhat flexible to permit evolutionary change, and understanding robustness requires a comparative framework. Over the last decades, most research on developmental robustness has been focusing on specific model systems and organs. Hence, we lack tools that would allow cross-species and cross-organ comparisons. Here, we emphasize the need for a uniform framework to experimentally test and quantify robustness across study systems and suggest that the analysis of fluctuating asymmetry might be a powerful proxy to do so. Such a comparative framework will ultimately help to resolve why and how organs of the same and different species differ in their sensitivity to internal (e.g., mutations) and external (e.g., temperature) perturbations and at what level of biological organization buffering capacities exist and therefore create robustness of the developmental system.     

Evolutionary framework for protein sequence evolution and gene pleiotropy

In this article, we develop an evolutionary model for protein sequence evolution. Gene pleiotropy is characterized by K distinct but correlated components (molecular phenotypes) that affect the organismal fitness. These K molecular phenotypes are under stabilizing selection with microadaptation (SM) due to random optima shifts, the SM model. Random coding mutations generate a correlated distribution of K molecular phenotypes. Under this SM model, we further develop a statistical method to estimate the "effective" number of molecular phenotypes (K(e)) of the gene. Therefore, for the first time we can empirically evaluate gene pleiotropy from the protein sequence analysis. Case studies of vertebrate proteins indicate that K(e) is typically approximately 6-9. We demonstrate that the newly developed SM model of protein evolution may provide a basis for exploring genomic evolution and correlations.     

The causes of epistasis in genetic networks

Epistasis refers to the nonadditive interactions between genes in determining phenotypes. Considerable efforts have shown that, even for a given organism, epistasis may vary both in intensity and sign. Recent comparative studies supported that the overall sign of epistasis switches from positive to negative as the complexity of an organism increases, and it has been hypothesized that this change shall be a consequence of the underlying gene network properties. Why should this be the case? What characteristics of genetic networks determine the sign of epistasis? Here we show, by evolving genetic networks that differ in their complexity and robustness against perturbations but that perform the same tasks, that robustness increased with complexity and that epistasis was positive for small nonrobust networks but negative for large robust ones. Our results indicate that robustness and negative epistasis emerge as a consequence of the existence of redundant elements in regulatory structures of genetic networks and that the correlation between complexity and epistasis is a byproduct of such redundancy, allowing for the decoupling of epistasis from the underlying network complexity.     

Sexually Antagonistic Zygotic Drive: A New Form of Genetic Conflict between the Sex Chromosomes

Sisters and brothers are completely unrelated with respect to the sex chromosomes they inherit from their heterogametic parent. This has the potential to result in a previously unappreciated form of genetic conflict between the sex chromosomes, called sexually antagonistic zygotic drive (SA-ZD). SA-ZD can arise whenever brothers and sisters compete over limited resources or there is brother–sister mating coupled with inbreeding depression. Although theory predicts that SA-ZD should be common and influence important evolutionary processes, there is little empirical evidence for its existence. Here we discuss the current understanding of SA-ZD, why it would be expected to elude empirical detection when present, and how it relates to other forms of genetic conflict.When a diploid individual reproduces sexually, the two alleles at heterozygous loci are necessarily in competition because reproduction by one allele must be at the expense of the other. Such competition is an inescapable component of the organismal level of evolution that was originally advanced by Darwin and later integrated with the field of genetics during the modern synthesis of the early 20th century (Huxley 1942). If the competition is mediated by Mendelian segregation followed by (1) differences in the Darwinian fitness (i.e., survival and fecundity) that each allele produces in offspring, (2) random sampling (genetic drift), and/or (3) differences in the alleles’ mutation or migration rates, then no genetic conflict exists and only canonical evolution at the organismal level occurs. But alleles can also compete outside the context of organismal evolution via diverse mechanisms of selection at the level of the gene that are collectively called genomic conflict (or selfish, ultraselfish, and parasitic DNA). These mechanisms can be divided into three general classes (Burt and Trivers 2006): (1) gonotaxis (in which the selfish elements bias Mendelian segregation by moving away from dead-end polar bodies and into the functional egg during oogenesis, i.e., meiotic or centromeric drive), (2) interference (in which the selfish element kills or debilitates noncarrier gametes or offspring, i.e., segregation distortion and zygotic drive), and (3) overreplication (in which the selfish element increases its copy number in the genome, e.g., biased gene conversion, transposable elements, and homing endonucleases). De novo mutations can also gain a transmission advantage by increasing the rate of stem cell division in the germ line (germline drive) (e.g., Yoon et al. 2013). All of these genomic conflict mechanisms have been described in detail in Burt and Trivers (2006).Genomic conflict frequently leads to reduced fitness at the organismal level. Meiotic drive can harm the organism as a whole because the attributes that provide a segregation advantage in oogenesis (e.g., the structure of the centromere and neighboring heterochromatin) can be maladaptive during spermatogenesis and contribute to male sterility (see, for review, Elde et al. 2011). Segregation distorters and zygotic drivers can substantially reduce a carrier male’s fitness because they kill up to half of his sperm (leading to reduced fertility) and offspring, respectively. Sex-linked, meiotic drivers in WZ females (like birds) and segregation distorters and zygotic drivers in XY males (like insects and mammals) cause biased sex ratios that reduce fitness with respect to Fisherian sex ratio selection and can also reduce population growth and potentially drive species to extinction. Biased gene conversion and germline drive (Yoon et al. 2013) reduce organismal fitness when harmful mutations accumulate to elevated levels (i.e., beyond the conventional values predicted by mutation-selection balance) because they have a molecular drive advantage over an allele that is more beneficial at the organismal level. Transposable elements insert at new places in the genome where they can disrupt gene function and thereby reduce their carrier’s fitness.Zygotic drive is an unusual form of genetic conflict because it directly reduces Darwinian fitness by killing or debilitating offspring. It is favored by gene-level selection when there is competition among siblings for limiting resources. By killing or weakening noncarrier competitor siblings, the gene(s) coding for zygotic drive gain a selective advantage because their survival is increased at the expense of siblings carrying alleles that are not identical by descent—despite any fitness loss to the parents, siblings, or other parts of the genome.Zygotic drive of the autosomes has been observed in a wide diversity of model organisms (e.g., worms, beetles, and mice) (reviewed in Burt and Trivers 2006) in which it can be efficiently detected because of the availability of numerous genetic markers. In general, an autosomal zygotic driver must have both a driver allele at one locus and a protective allele at a responder locus. In worms (Caenorhabditis elegans), a molecular mechanism leading to zygotic drive was recently discovered. Here a zygotic driver is coded by a pair of tightly linked genes, in which an allele at one gene (peel-1) produces a toxin, the driver locus, which is packaged in the sperm and transmitted to the zygote, whereas an allele at another gene (zeel-1) produces an antidote (the protective allele, which is expressed very early in development) that rescues only those embryos that inherit zeel-1 (and usually also the tightly linked driver, peel-1) (Seidel et al. 2011). Zygotic drive on the autosomes is expected to be difficult to evolve—and therefore to be relatively rare in genomes—because it requires an improbable phenotype (i.e., a functionally coupled driver gene product and a responder gene sequence or product) and genotype (i.e., very close linkage between the loci coding for the driver and responder).     

Assessing the repeatability,robustness to disturbance,and parent–offspring colony resemblance of collective behavior

Groups of animals possess phenotypes such as collective behaviour, which may determine the fitness of group members. However, the stability and robustness to perturbations of collective phenotypes in natural conditions is not established. Furthermore, whether group phenotypes are transmitted from parent to offspring groups with fidelity is required for understanding how selection on group phenotypes contributes to evolution, but parent–offspring resemblance at the group level is rarely estimated. We evaluated the repeatability, robustness to perturbation and parent–offspring resemblance of collective foraging aggressiveness in colonies of the social spider Anelosimus eximius. Among‐colony differences in foraging aggressiveness were consistent over time but changed if the colony was perturbed through the removal of individuals or via individuals’ removal and subsequent return. Offspring and parent colony behaviour were correlated at the phenotypic level, but only once the offspring colony had settled after being translocated, and the correlation overlapped with zero at the among‐colony level. The parent–offspring resemblance was not driven by a shared elevation but could be due to other environmental factors. The behaviour of offspring colonies in a common garden laboratory setting was not correlated with the behaviour of the parent colony nor with the same colony's behaviour once it was returned to the field. The phenotypes of groups represent a potentially important tier of biological organization, and assessing the stability and heritability of such phenotypes helps us better understand their role in evolution.     

Molecular mechanisms of canalization: Hsp90 and beyond

The Hsp90 chaperone machine facilitates the maturation of a diverse set of ‘client’ proteins. Many of these Hsp90 clients are essential nodes in signal transduction pathways and regulatory circuits, accounting for the important role Hsp90 plays in organismal development and responses to the environment. Recent findings suggest a broader impact of the chaperone on phenotype: fully functional Hsp90 canalizes wild-type phenotypes by suppressing underlying genetic and epigenetic variation. This variation can be expressed upon challenging the Hsp90 machinery by environmental stress, genetic or pharmaceutical targeting of Hsp90. The existence of Hsp90-buffered genetic and epigenetic variation together with plausible release mechanisms has wide-ranging implication for phenotype and possibly evolutionary processes. Here, we discuss the role of Hsp90 in canalization and organismal plasticity, and highlight important questions for future experimental inquiry.     

Quantifying the propagation of parametric uncertainty on flux balance analysis

Flux balance analysis (FBA) and associated techniques operating on stoichiometric genome-scale metabolic models play a central role in quantifying metabolic flows and constraining feasible phenotypes. At the heart of these methods lie two important assumptions: (i) the biomass precursors and energy requirements neither change in response to growth conditions nor environmental/genetic perturbations, and (ii) metabolite production and consumption rates are equal at all times (i.e., steady-state). Despite the stringency of these two assumptions, FBA has been shown to be surprisingly robust at predicting cellular phenotypes. In this paper, we formally assess the impact of these two assumptions on FBA results by quantifying how uncertainty in biomass reaction coefficients, and departures from steady-state due to temporal fluctuations could propagate to FBA results. In the first case, conditional sampling of parameter space is required to re-weigh the biomass reaction so as the molecular weight remains equal to 1 g mmol⁻¹, and in the second case, metabolite (and elemental) pool conservation must be imposed under temporally varying conditions. Results confirm the importance of enforcing the aforementioned constraints and explain the robustness of FBA biomass yield predictions.     

Rate of adaptive peak shifts with partial genetic robustness

How adaptive evolution occurs with individually deleterious but jointly beneficial mutations has been one of the major problems in population genetics theory. Adaptation in this case is commonly described as a population's escape from a local peak to a higher peak on Sewall Wright's fitness landscape. Recent molecular genetic and computational studies have suggested that genetic robustness can facilitate such peak shifts. If phenotypic expressions of new mutations are suppressed under genetic robustness, mutations that are otherwise deleterious can accumulate in the population as neutral variants. When the robustness is perturbed by an environmental change or a major mutation, these variants become exposed to natural selection. It is argued that this process promotes adaptation because allelic combinations enriched under genetic robustness can then be positively selected. Here, I propose simple two- and three-locus models of adaptation with partial genetic robustness as suggested by recent studies. The waiting time until the fixation of an adaptive haplotype was observed in stochastic simulations and compared to the expectation without robustness. It is shown that peak shifts can be delayed or accelerated depending on the conditions of genetic robustness. The evolutionary significance of these processes is discussed.     

Integrating life history traits into predictive phylogeography

Predictive phylogeography seeks to aggregate genetic, environmental and taxonomic data from multiple species in order to make predictions about unsampled taxa using machine‐learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive frameworks due to difficulties inherent to the scoring of trait data across a taxonomically broad set of taxa. We refine predictive frameworks from two North American systems, the inland temperate rainforests of the Pacific Northwest and the Southwestern Arid Lands (SWAL), by incorporating a number of organismal trait variables. Our results indicate that incorporating life history traits as predictor variables improves the performance of the supervised machine‐learning approach to predictive phylogeography, especially for the SWAL system, in which predictions made from only taxonomic and climate variables meets only moderate success. In particular, traits related to reproduction (e.g., reproductive mode; clutch size) and trophic level appear to be particularly informative to the predictive framework. Predictive frameworks offer an important mechanism for integration of organismal trait, environmental data, and genetic data in phylogeographic studies.