Q&A: Evolutionary capacitance

The biology of grafting and its applications in studying information exchange between plants

Grafting techniques have been used for centuries for trait improvement in agriculture and horticulture. In recent years, technical progress with the grafting of species previously thought to be recalcitrant to the formation of a graft union, and the discovery of new types of information exchange between grafted plants, have stirred renewed interest in the use of grafting as a research tool. In this Review, we describe our current understanding of the molecular and cellular processes involved in the establishment of successful grafts between plants of the same genotype (homografts) or different genotypes (heterografts). We also highlight recent progress with the elucidation of the mechanisms underlying the exchange of macromolecules (small RNAs, messenger RNAs and proteins) across graft junctions as well as the transfer of cell organelles and its role in horizontal gene and genome transfer. Finally, we discuss novel applications of grafting, including new opportunities for transgene-free genetic engineering, and the relevance of grafting in plant evolution.

Plasticity-led and mutation-led evolutions are different modes of the same developmental gene regulatory network

The standard theory of evolution proposes that mutations cause heritable variations, which are naturally selected, leading to evolution. However, this mutation-led evolution (MLE) is being questioned by an alternative theory called plasticity-led evolution (PLE). PLE suggests that an environmental change induces adaptive phenotypes, which are later genetically accommodated. According to PLE, developmental systems should be able to respond to environmental changes adaptively. However, developmental systems are known to be robust against environmental and mutational perturbations. Thus, we expect a transition from a robust state to a plastic one. To test this hypothesis, we constructed a gene regulatory network (GRN) model that integrates developmental processes, hierarchical regulation, and environmental cues. We then simulated its evolution over different magnitudes of environmental changes. Our findings indicate that this GRN model exhibits PLE under large environmental changes and MLE under small environmental changes. Furthermore, we observed that the GRN model is susceptible to environmental or genetic fluctuations under large environmental changes but is robust under small environmental changes. This indicates a breakdown of robustness due to large environmental changes. Before the breakdown of robustness, the distribution of phenotypes is biased and aligned to the environmental changes, which would facilitate rapid adaptation should a large environmental change occur. These observations suggest that the evolutionary transition from mutation-led to plasticity-led evolution is due to a developmental transition from robust to susceptible regimes over increasing magnitudes of environmental change. Thus, the GRN model can reconcile these conflicting theories of evolution.

Eco-evolutionary trade-offs in the dynamics of prion strain competition

Prion and prion-like molecules are a type of self-replicating aggregate protein that have been implicated in a variety of neurodegenerative diseases. Over recent decades, the molecular dynamics of prions have been characterized both empirically and through mathematical models, providing insights into the epidemiology of prion diseases and the impact of prions on the evolution of cellular processes. At the same time, a variety of evidence indicates that prions are themselves capable of a form of evolution, in which changes to their structure that impact their rate of growth or fragmentation are replicated, making such changes subject to natural selection. Here we study the role of such selection in shaping the characteristics of prions under the nucleated polymerization model (NPM). We show that fragmentation rates evolve to an evolutionary stable value which balances rapid reproduction of PrPSc aggregates with the need to produce stable polymers. We further show that this evolved fragmentation rate differs in general from the rate that optimizes transmission between cells. We find that under the NPM, prions that are both evolutionary stable and optimized for transmission have a characteristic length of three times the critical length below which they become unstable. Finally, we study the dynamics of inter-cellular competition between strains, and show that the eco-evolutionary trade-off between intra- and inter-cellular competition favours coexistence.

Widespread epistasis among beneficial genetic variants revealed by high-throughput genome editing

The phenotypic effect of any genetic variant can be altered by variation at other genomic loci. Known as epistasis, these genetic interactions shape the genotype-phenotype map of every species, yet their origins remain poorly understood. To investigate this, we employed high-throughput genome editing to measure the fitness effects of 1,826 naturally polymorphic variants in four strains of Saccharomyces cerevisiae. About 31% of variants affect fitness, of which 24% have strain-specific fitness effects indicative of epistasis. We found that beneficial variants are more likely to exhibit genetic interactions and that these interactions can be mediated by specific traits such as flocculation ability. This work suggests that adaptive evolution will often involve trade-offs where a variant is only beneficial in some genetic backgrounds, potentially explaining why many beneficial variants remain polymorphic. In sum, we provide a framework to understand the factors influencing epistasis with single-nucleotide resolution, revealing widespread epistasis among beneficial variants.

Computational modelling of plasticity-led evolution

Plasticity-led evolution is a form of evolution where a change in the environment induces novel traits via phenotypic plasticity, after which the novel traits are genetically accommodated over generations under the novel environment. This mode of evolution is expected to resolve the problem of gradualism (i.e., evolution by the slow accumulation of mutations that induce phenotypic variation) implied by the Modern Evolutionary Synthesis, in the face of a large environmental change. While experimental works are essential for validating that plasticity-led evolution indeed happened, we need computational models to gain insight into its underlying mechanisms and make qualitative predictions. Such computational models should include the developmental process and gene-environment interactions in addition to genetics and natural selection. We point out that gene regulatory network models can incorporate all the above notions. In this review, we highlight results from computational modelling of gene regulatory networks that consolidate the criteria of plasticity-led evolution. Since gene regulatory networks are mathematically equivalent to artificial recurrent neural networks, we also discuss their analogies and discrepancies, which may help further understand the mechanisms underlying plasticity-led evolution.

Universal Constraints on Protein Evolution in the Long-Term Evolution Experiment with Escherichia coli

Although it is well known that abundant proteins evolve slowly across the tree of life, there is little consensus for why this is true. Here, I report that abundant proteins evolve slowly in the hypermutator populations of Lenski's long-term evolution experiment with Escherichia coli (LTEE). Specifically, the density of all observed mutations per gene, as measured in metagenomic time series covering 60,000 generations of the LTEE, significantly anticorrelates with mRNA abundance, protein abundance, and degree of protein-protein interaction. The same pattern holds for nonsynonymous mutation density. However, synonymous mutation density, measured across the LTEE hypermutator populations, positively correlates with protein abundance. These results show that universal constraints on protein evolution are visible in data spanning three decades of experimental evolution. Therefore, it should be possible to design experiments to answer why abundant proteins evolve slowly.

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

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

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

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

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

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

Structural instability and divergence from conserved residues underlie intracellular retention of mammalian odorant receptors

Mammalian odorant receptors are a diverse and rapidly evolving set of G protein-coupled receptors expressed in olfactory cilia membranes. Most odorant receptors show little to no cell surface expression in nonolfactory cells due to endoplasmic reticulum retention, which has slowed down biochemical studies. Here we provide evidence that structural instability and divergence from conserved residues of individual odorant receptors underlie intracellular retention using a combination of large-scale screening of odorant receptors cell surface expression in heterologous cells, point mutations, structural modeling, and machine learning techniques. We demonstrate the importance of conserved residues by synthesizing consensus odorant receptors that show high levels of cell surface expression similar to conventional G protein-coupled receptors. Furthermore, we associate in silico structural instability with poor cell surface expression using molecular dynamics simulations. We propose an enhanced evolutionary capacitance of olfactory sensory neurons that enable the functional expression of odorant receptors with cryptic mutations.

Complex chromosomal neighborhood effects determine the adaptive potential of a gene under selection

How the organization of genes on a chromosome shapes adaptation is essential for understanding evolutionary paths. Here, we investigate how adaptation to rapidly increasing levels of antibiotic depends on the chromosomal neighborhood of a drug-resistance gene inserted at different positions of the Escherichia coli chromosome. Using a dual-fluorescence reporter that allows us to distinguish gene amplifications from other up-mutations, we track in real-time adaptive changes in expression of the drug-resistance gene. We find that the relative contribution of several mutation types differs systematically between loci due to properties of neighboring genes: essentiality, expression, orientation, termination, and presence of duplicates. These properties determine rate and fitness effects of gene amplification, deletions, and mutations compromising transcriptional termination. Thus, the adaptive potential of a gene under selection is a system-property with a complex genetic basis that is specific for each chromosomal locus, and it can be inferred from detailed functional and genomic data.

DOI:http://dx.doi.org/10.7554/eLife.25100.001

Diverse genetic architectures lead to the same cryptic phenotype in a yeast cross

Cryptic genetic variants that do not typically influence traits can interact epistatically with each other and mutations to cause unexpected phenotypes. To improve understanding of the genetic architectures and molecular mechanisms that underlie these interactions, we comprehensively dissected the genetic bases of 17 independent instances of the same cryptic colony phenotype in a yeast cross. In eight cases, the phenotype resulted from a genetic interaction between a de novo mutation and one or more cryptic variants. The number and identities of detected cryptic variants depended on the mutated gene. In the nine remaining cases, the phenotype arose without a de novo mutation due to two different classes of higher-order genetic interactions that only involve cryptic variants. Our results may be relevant to other species and disease, as most of the mutations and cryptic variants identified in our study reside in components of a partially conserved and oncogenic signalling pathway.

Cryptic genetic variants may not individually show discernible phenotypic effects, but collectively, these polymorphisms can lead to unexpected, genetically complex traits that might be relevant to evolution and disease. Here, the authors use large yeast populations to comprehensively dissect the genetic bases of 17 independent occurrences of a phenotype that arises due to combinations of epistatically interacting cryptic variants.

Genetic assimilation: a review of its potential proximate causes and evolutionary consequences

BACKGROUND

Most, if not all, organisms possess the ability to alter their phenotype in direct response to changes in their environment, a phenomenon known as phenotypic plasticity. Selection can break this environmental sensitivity, however, and cause a formerly environmentally induced trait to evolve to become fixed through a process called genetic assimilation. Essentially, genetic assimilation can be viewed as the evolution of environmental robustness in what was formerly an environmentally sensitive trait. Because genetic assimilation has long been suggested to play a key role in the origins of phenotypic novelty and possibly even new species, identifying and characterizing the proximate mechanisms that underlie genetic assimilation may advance our basic understanding of how novel traits and species evolve.

SCOPE

This review begins by discussing how the evolution of phenotypic plasticity, followed by genetic assimilation, might promote the origins of new traits and possibly fuel speciation and adaptive radiation. The evidence implicating genetic assimilation in evolutionary innovation and diversification is then briefly considered. Next, the potential causes of phenotypic plasticity generally and genetic assimilation specifically are examined at the genetic, molecular and physiological levels and approaches that can improve our understanding of these mechanisms are described. The review concludes by outlining major challenges for future work.

CONCLUSIONS

Identifying and characterizing the proximate mechanisms involved in phenotypic plasticity and genetic assimilation promises to help advance our basic understanding of evolutionary innovation and diversification.

Evidence for a sexual dimorphism in gene expression noise in metazoan species

Many biological processes depend on very few copies of intervening elements, which makes such processes particularly susceptible to the stochastic fluctuations of these elements. The intrinsic stochasticity of certain processes is propagated across biological levels, causing genotype- and environment-independent biological variation which might permit populations to better cope with variable environments. Biological variations of stochastic nature might also allow the accumulation of variations at the genetic level that are hidden from natural selection, which might have a great potential for population diversification. The study of any mechanism that resulted in the modulation of stochastic variation is, therefore, of potentially wide interest. I propose that sex might be an important modulator of the stochastic variation in gene expression, i.e., gene expression noise. Based on known associations between different patterns of gene expression variation, I hypothesize that in metazoans the gene expression noise might be generally larger in heterogametic than in homogametic individuals. I directly tested this hypothesis by comparing putative genotype- and environment-independent variations in gene expression between females and males of Drosophila melanogaster strains. Also, considering the potential effect of the propagation of gene expression noise across biological levels, I indirectly tested the existence of a metazoan sexual dimorphism in gene expression noise by analyzing putative genotype- and environment-independent variation in phenotypes related to interaction with the environment in D. melanogaster strains and metazoan species. The results of these analyses are consistent with the hypothesis that gene expression is generally noisier in heterogametic than in homogametic individuals. Further analyses and discussion of existing literature permits the speculation that the sexual dimorphism in gene expression noise is ultimately based on the nuclear dynamics in gametogenesis and very early embryogenesis of sex-specific chromosomes, i.e., Y and W chromosomes.

Using genomics to characterize evolutionary potential for conservation of wild populations

Genomics promises exciting advances towards the important conservation goal of maximizing evolutionary potential, notwithstanding associated challenges. Here, we explore some of the complexity of adaptation genetics and discuss the strengths and limitations of genomics as a tool for characterizing evolutionary potential in the context of conservation management. Many traits are polygenic and can be strongly influenced by minor differences in regulatory networks and by epigenetic variation not visible in DNA sequence. Much of this critical complexity is difficult to detect using methods commonly used to identify adaptive variation, and this needs appropriate consideration when planning genomic screens, and when basing management decisions on genomic data. When the genomic basis of adaptation and future threats are well understood, it may be appropriate to focus management on particular adaptive traits. For more typical conservations scenarios, we argue that screening genome-wide variation should be a sensible approach that may provide a generalized measure of evolutionary potential that accounts for the contributions of small-effect loci and cryptic variation and is robust to uncertainty about future change and required adaptive response(s). The best conservation outcomes should be achieved when genomic estimates of evolutionary potential are used within an adaptive management framework.

On the Nature and Evolutionary Impact of Phenotypic Robustness Mechanisms

Biologists have long observed that physiological and developmental processes are insensitive, or robust, to many genetic and environmental perturbations. A complete understanding of the evolutionary causes and consequences of this robustness is lacking. Recent progress has been made in uncovering the regulatory mechanisms that underlie environmental robustness in particular. Less is known about robustness to the effects of mutations, and indeed the evolution of mutational robustness remains a controversial topic. The controversy has spread to related topics, in particular the evolutionary relevance of cryptic genetic variation. This review aims to synthesize current understanding of robustness mechanisms and to cut through the controversy by shedding light on what is and is not known about mutational robustness. Some studies have confused mutational robustness with non-additive interactions between mutations (epistasis). We conclude that a profitable way forward is to focus investigations (and rhetoric) less on mutational robustness and more on epistasis.

Cryptic genetic variation can make "irreducible complexity" a common mode of adaptation in sexual populations

The existence of complex (multiple-step) genetic adaptations that are "irreducible" (i.e., all partial combinations are less fit than the original genotype) is one of the longest standing problems in evolutionary biology. In standard genetics parlance, these adaptations require the crossing of a wide adaptive valley of deleterious intermediate stages. Here, we demonstrate, using a simple model, that evolution can cross wide valleys to produce "irreducibly complex" adaptations by making use of previously cryptic mutations. When revealed by an evolutionary capacitor, previously cryptic mutants have higher initial frequencies than do new mutations, bringing them closer to a valley-crossing saddle in allele frequency space. Moreover, simple combinatorics implies an enormous number of candidate combinations exist within available cryptic genetic variation. We model the dynamics of crossing of a wide adaptive valley after a capacitance event using both numerical simulations and analytical approximations. Although individual valley crossing events become less likely as valleys widen, by taking the combinatorics of genotype space into account, we see that revealing cryptic variation can cause the frequent evolution of complex adaptations.

Extracellular environment modulates the formation and propagation of particular amyloid structures

Amyloidogenic proteins, including prions, assemble into multiple forms of structurally distinct fibres. The [PSI(+)] prion, endogenous to the yeast Saccharomyces cerevisiae, is a dominantly inherited, epigenetic modifier of phenotypes. [PSI(+)] formation relies on the coexistence of another prion, [RNQ(+)]. Here, in order to better define the role of amyloid diversity on cellular phenotypes, we investigated how physiological and environmental changes impact the generation and propagation of diverse protein conformations from a single polypeptide. Utilizing the yeast model system, we defined extracellular factors that influence the formation of a spectrum of alternative self-propagating amyloid structures of the Sup35 protein, called [PSI(+)] variants. Strikingly, exposure to specific stressful environments dramatically altered the variants of [PSI(+)] that formed de novo. Additionally, we found that stress also influenced the association between the [PSI(+)] and [RNQ(+)] prions in a way that it superceded their typical relationship. Furthermore, changing the growth environment modified both the biochemical properties and [PSI(+)]-inducing capabilities of the [RNQ(+)] template. These data suggest that the cellular environment contributes to both the generation and the selective propagation of specific amyloid structures, providing insight into a key feature that impacts phenotypic diversity in yeast and the cross-species transmission barriers characteristic of prion diseases.