Phenotypic Robustness Research Articles

Nonlinear gene expression-phenotype relationships contribute to variation and clefting in the A/WySn mouse.

Cleft lip and palate is one of the most common human birth defects, but the underlying etiology is poorly understood. The A/WySn mouse is a spontaneously occurring model of multigenic clefting in which 20% to 30% of individuals develop an orofacial cleft. Recent work has shown altered methylation at a specific retrotransposon insertion downstream of the Wnt9b locus in clefting animals, which results in decreased Wnt9b expression. Using a newly developed protocol that allows us to measure morphology, gene expression, and DNA methylation in the same embryo, we relate gene expression in an individual embryo directly to its three-dimensional morphology for the first time. We find that methylation at the retrotransposon relates to Wnt9b expression and morphology. IAP methylation relates to shape of the nasal process in a manner consistent with clefting. Embryos with low IAP methylation exhibit increased among-individual variance in facial shape. Methylation and gene expression relate nonlinearly to nasal process morphology. Individuals at one end of a continuum of phenotypic states display a clinical phenotype and increased phenotypic variation. Variable penetrance and expressivity in this model is likely determined both by among-individual variation in methylation and changes in phenotypic robustness along the underlying liability distribution for orofacial clefting.

Adaptation, fitness landscape learning and fast evolution.

We consider evolution of a large population, where fitness of each organism is defined by many phenotypical traits. These traits result from expression of many genes. Under some assumptions on fitness we prove that such model organisms are capable, to some extent, to recognize the fitness landscape.That fitness landscape learning sharply reduces the number of mutations needed for adaptation.Moreover, this learning increases phenotype robustness with respect to mutations, i.e., canalizes the phenotype. We show that learning and canalization work only when evolution is gradual. Organisms can be adapted to many constraints associated with a hard environment, if that environment becomes harder step by step.Our results explain why evolution can involve genetic changes of a relatively large effect and why the total number of changes are surprisingly small.

Commensal Gut Bacteria Buffer the Impact of Host Genetic Variants on Drosophila Developmental Traits under Nutritional Stress.

SummaryEukaryotic genomes encode several buffering mechanisms that robustly maintain invariant phenotypic outcome despite fluctuating environmental conditions. Here we show that the Drosophila gut-associated commensals, represented by a single facultative symbiont, Lactobacillus plantarum (LpWJL), constitutes a so far unexpected buffer that masks the contribution of the host's cryptic genetic variation (CGV) to developmental traits while the host is under nutritional stress. During chronic under-nutrition, LpWJL consistently reduces variation in different host phenotypic traits and ensures robust organ patterning during development; LpWJL also decreases genotype-dependent expression variation, particularly for development-associated genes. We further provide evidence that LpWJL buffers via reactive oxygen species (ROS) signaling whose inhibition impairs microbiota-mediated phenotypic robustness. We thus identified a hitherto unappreciated contribution of the gut facultative symbionts to host fitness that, beyond supporting growth rates and maturation timing, confers developmental robustness and phenotypic homogeneity in times of nutritional stress.

Multi-enhancer transcriptional hubs confer phenotypic robustness.

We previously showed in Drosophila melanogaster embryos that low-affinity Ultrabithorax (Ubx)-responsive shavenbaby (svb) enhancers drive expression using localized transcriptional environments and that active svb enhancers on different chromosomes tended to colocalize (Tsai et al., 2017). Here, we test the hypothesis that these multi-enhancer 'hubs' improve phenotypic resilience to stress by buffering against decreases in transcription factor concentrations and transcriptional output. Deleting a redundant enhancer from the svb locus led to reduced trichome numbers in embryos raised at elevated temperatures. Using high-resolution fluorescence microscopy, we observed lower Ubx concentration and transcriptional output in this deletion allele. Transcription sites of the full svb cis-regulatory region inserted into a different chromosome colocalized with the svb locus, increasing Ubx concentration, the transcriptional output of svb, and partially rescuing the phenotype. Thus, multiple enhancers could reinforce a local transcriptional hub to buffer against environmental stresses and genetic perturbations, providing a mechanism for phenotypical robustness.

A multiscale model of epigenetic heterogeneity-driven cell fate decision-making

The inherent capacity of somatic cells to switch their phenotypic status in response to damage stimuli in vivo might have a pivotal role in ageing and cancer. However, how the entry-exit mechanisms of phenotype reprogramming are established remains poorly understood. In an attempt to elucidate such mechanisms, we herein introduce a stochastic model of combined epigenetic regulation (ER)-gene regulatory network (GRN) to study the plastic phenotypic behaviours driven by ER heterogeneity. To deal with such complex system, we additionally formulate a multiscale asymptotic method for stochastic model reduction, from which we derive an efficient hybrid simulation scheme. Our analysis of the coupled system reveals a regime of tristability in which pluripotent stem-like and differentiated steady-states coexist with a third indecisive state, with ER driving transitions between these states. Crucially, ER heterogeneity of differentiation genes is for the most part responsible for conferring abnormal robustness to pluripotent stem-like states. We formulate epigenetic heterogeneity-based strategies capable of unlocking and facilitating the transit from differentiation-refractory (stem-like) to differentiation-primed epistates. The application of the hybrid numerical method validates the likelihood of such switching involving solely kinetic changes in epigenetic factors. Our results suggest that epigenetic heterogeneity regulates the mechanisms and kinetics of phenotypic robustness of cell fate reprogramming. The occurrence of tunable switches capable of modifying the nature of cell fate reprogramming might pave the way for new therapeutic strategies to regulate reparative reprogramming in ageing and cancer.

Adaptation, fitness landscape learning and fast evolution

We consider evolution of a large population, where fitness of each organism is defined by many phenotypical traits. These traits result from expression of many genes. Under some assumptions on fitness we prove that such model organisms are capable, to some extent, to recognize the fitness landscape. That fitness landscape learning sharply reduces the number of mutations needed for adaptation. Moreover, this learning increases phenotype robustness with respect to mutations, i.e., canalizes the phenotype. We show that learning and canalization work only when evolution is gradual. Organisms can be adapted to many constraints associated with a hard environment, if that environment becomes harder step by step. Our results explain why evolution can involve genetic changes of a relatively large effect and why the total number of changes are surprisingly small.

Adaptation, fitness landscape learning and fast evolution

We consider evolution of a large population, where fitness of each organism is defined by many phenotypical traits. These traits result from expression of many genes. Under some assumptions on fitness we prove that such model organisms are capable, to some extent, to recognize the fitness landscape.That fitness landscape learning sharply reduces the number of mutations needed for adaptation.Moreover, this learning increases phenotype robustness with respect to mutations, i.e., canalizes the phenotype. We show that learning and canalization work only when evolution is gradual. Organisms can be adapted to many constraints associated with a hard environment, if that environment becomes harder step by step.Our results explain why evolution can involve genetic changes of a relatively large effect and why the total number of changes are surprisingly small.

Phenotypic Plasticity, Developmental Instability, and Robustness: The Concepts and How They Are Connected

Developmental systems integrate inputs of variation from different origins into the observable variation of the resulting phenotype. Different components of phenotypic variation can be distinguished that correspond to those inputs, but the response of the system to each input factor can be modulated by other factors, so that there are interactions among the factors. This study uses a simplified developmental model of a trait to illustrate these interactions for genetic variation, phenotypic plasticity in response to temperature variation, and random developmental noise. The simulations show extensive interactions among the input factors, which can be explained by the nonlinear nature of the developmental model. These results are broadly consistent with results from actual biological systems.

Evolution of resilience in protein interactomes across the tree of life

Phenotype robustness to environmental fluctuations is a common biological phenomenon. Although most phenotypes involve multiple proteins that interact with each other, the basic principles of how such interactome networks respond to environmental unpredictability and change during evolution are largely unknown. Here we study interactomes of 1,840 species across the tree of life involving a total of 8,762,166 protein-protein interactions. Our study focuses on the resilience of interactomes to network failures and finds that interactomes become more resilient during evolution, meaning that interactomes become more robust to network failures over time. In bacteria, we find that a more resilient interactome is in turn associated with the greater ability of the organism to survive in a more complex, variable, and competitive environment. We find that at the protein family level proteins exhibit a coordinated rewiring of interactions over time and that a resilient interactome arises through gradual change of the network topology. Our findings have implications for understanding molecular network structure in the context of both evolution and environment.

Mouse Skull Mean Shape and Shape Robustness Rely on Different Genetic Architectures and Different Loci.

The genetic architecture of skull shape has been extensively studied in mice and the results suggest a highly polygenic and additive basis. In contrast few studies have explored the genetic basis of the skull variability. Canalization and developmental stability are the two components of phenotypic robustness. They have been proposed to be emergent properties of the genetic networks underlying the development of the trait itself, but this hypothesis has been rarely tested empirically. Here we use outbred mice to investigate the genetic architecture of canalization of the skull shape by implementing a genome-wide marginal epistatic test on 3D geometric morphometric data. The same data set had been used previously to explore the genetic architecture of the skull mean shape and its developmental stability. Here, we address two questions: (1) Are changes in mean shape and changes in shape variance associated with the same genomic regions? and (2) Do canalization and developmental stability rely on the same loci and genetic architecture and do they involve the same patterns of shape variation? We found that unlike skull mean shape, among-individual shape variance and fluctuating asymmetry (FA) show a total lack of additive effects. They are both associated with complex networks of epistatic interactions involving many genes (protein-coding and regulatory elements). Remarkably, none of the genomic loci affecting mean shape contribute these networks despite their enrichment for genes involved in craniofacial variation and diseases. We also found that the patterns of shape FA and individual variation are largely similar and rely on similar multilocus epistatic genetic networks, suggesting that the processes channeling variation within and among individuals are largely common. However, the loci involved in these two networks are completely different. This in turn underlines the difference in the origin of the variation at these two levels, and points at buffering processes that may be specific to each level.

Dichotomy in redundant enhancers points to presence of initiators of gene regulation

BackgroundThe regulatory landscape of a gene locus often consists of several functionally redundant enhancers establishing phenotypic robustness and evolutionary stability of its regulatory program. However, it is unclear what mechanisms are employed by redundant enhancers to cooperatively orchestrate gene expression.ResultsBy comparing redundant enhancers to single enhancers (enhancers present in a single copy in a gene locus), we observed that the DNA sequence encryption differs between these two classes of enhancers, suggesting a difference in their regulatory mechanisms. Initiator enhancers, which are a subset of redundant enhancers and show similar sequence encryption to single enhancers, differ from the rest of redundant enhancers in their sequence encryption, evolutionary conservation and proximity to target genes. Genes hosting initiator enhancers in their loci feature elevated levels of expression. Initiator enhancers show a high level of 3D chromatin contacts with both transcription start sites and regular enhancers, suggesting their roles as primary activators and intermediate catalysts of gene expression, through which the regulatory signals of redundant enhancers are propagated to the target genes. In addition, GWAS and eQTLs variants are significantly enriched in initiator enhancers compared to redundant enhancers, suggesting a key functional role these sequences play in gene regulation.ConclusionsThe specific characteristics and widespread abundance of initiator enhancers advocate for a possible universal hierarchical mechanism of tissue-specific gene regulation involving multiple redundant enhancers acting through initiator enhancers.

Sexual selection contributes to partial restoration of phenotypic robustness in a butterfly

Phenotypic variation is the raw material for selection that is ubiquitous for most traits in natural populations, yet the processes underlying phenotypic evolution or stasis often remain unclear. Here, we report phenotypic evolution in a mutant line of the butterfly Bicyclus anynana after outcrossing with the genetically polymorphic wild type population. The comet mutation modifies two phenotypic traits known to be under sexual selection in this butterfly: the dorsal forewing eyespots and the pheromone-producing structures. The original comet mutant line was inbred and remained phenotypically stable for at least seven years, but when outcrossed to the wild type population the outcrossed comet line surprisingly recovered the wild type phenotype within 8 generations at high (27 °C), but not at low (20 °C), developmental temperatures. Male mating success experiments then revealed that outcrossed comet males with the typical comet phenotype suffered from lower mating success, while mating success of outcrossed comet males resembling wild types was partially restored. We document a fortuitous case where the addition of genetic polymorphism around a spontaneous mutation could have allowed partial restoration of phenotypic robustness. We further argue that sexual selection through mate choice is likely the driving force leading to phenotypic robustness in our system.

Non-deterministic genotype-phenotype maps of biological self-assembly(a)(a)Contribution to the Focus Issue Evolutionary Modeling and Experimental Evolution edited by José Cuesta, Joachim Krug and Susanna Manrubia.

In recent years large-scale studies of different genotype-phenotype (GP) maps, including those of RNA secondary structure, lattice proteins, and self-assembling Polyominoes, have revealed that these maps share structural properties. Such properties include skewed distributions of genotypes per phenotype, negative correlations between genotypic evolvability and robustness, positive correlations between phenotypic evolvability and robustness, and the fact that a majority of phenotypes can be reached from any genotype in just a few mutations. Traditionally this research has focused on deterministic GP maps, meaning that a single sequence maps to a single outcome. Here, by contrast, we consider non-deterministic GP maps, in which a single sequence can map to multiple outcomes. Most GP maps already contain such sequences, but these are typically classified as a single, undesirable phenotype for the reason that biological processes typically rely on robust transformation of sequences into biological structures and functions. For the same reason, however, non-deterministic phenotypes play an important role in diseases, and a deeper understanding of non-deterministic GP maps may therefore inform the study of their evolution. By redefining deterministic and non-deterministic Polyomino self-assembly phenotypes in terms of the pattern of possible interactions rather than the final structure we are able to calculate GP map properties for the non-deterministic part of the map, and find that they match those found in deterministic maps.

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.

More than Fitness. A Robustness-based Proposal of a Logical Space to Classify Processes Behind Evolutionary Phenomena

Abstract The assumption that natural selection alone is sufficient to explain not only which traits get fixed in a population/species, but also how they develop, has been questioned since Darwin’s times, and increasingly in the last decades. Alternative theories, linked to genetic and phenotypic processes, or to the theory of complex systems, have been proposed to explain the rise of the phenotypic variety upon which natural selection acts. In this article, we illustrate the current state of the issue and we propose a logical space based on phenotypic robustness that allows a classification of evolutionary phenomena and can provide a framework for unifying all these accounts.

Enhancer redundancy provides phenotypic robustness in mammalian development.

SummaryDistant-acting tissue-specific enhancers vastly outnumber protein-coding genes in mammalian genomes, but the functional significance of this regulatory complexity remains insufficiently understood1,2. Here we show that the pervasive presence of multiple enhancers with similar activities near the same gene confers phenotypic robustness to loss-of-function mutations in individual enhancers. We used genome editing to create 23 mouse deletion lines and inter-crosses, including both single and combinatorial enhancer deletions at seven distinct loci required for limb development. Surprisingly, none of ten deletions of individual enhancers caused noticeable changes in limb morphology. In contrast, removal of pairs of limb enhancers near the same gene resulted in discernible phenotypes, indicating that enhancers function redundantly in establishing normal morphology. In a genetic background sensitized by reduced baseline expression of the target gene, even single enhancer deletions caused limb abnormalities, suggesting that functional redundancy is conferred by additive effects of enhancers on gene expression levels. A genome-wide analysis integrating epigenomic and transcriptomic data from 29 developmental mouse tissues revealed that mammalian genes are very commonly associated with multiple enhancers that have similar spatiotemporal activity. Systematic exploration of three representative developmental structures (limb, brain, heart) uncovered more than a thousand cases in which five or more enhancers with redundant activity patterns were found near the same gene. Taken together, our data indicate that enhancer redundancy is a remarkably widespread feature of mammalian genomes and provides an effective regulatory buffer preventing deleterious phenotypic consequences upon loss of individual enhancers.

Control of primary metabolism by a virulence regulatory network promotes robustness in a plant pathogen

Robustness is a key system-level property of living organisms to maintain their functions while tolerating perturbations. We investigate here how a regulatory network controlling multiple virulence factors impacts phenotypic robustness of a bacterial plant pathogen. We reconstruct a cell-scale model of Ralstonia solanacearum connecting a genome-scale metabolic network, a virulence macromolecule network, and a virulence regulatory network, which includes 63 regulatory components. We develop in silico methods to quantify phenotypic robustness under a broad set of conditions in high-throughput simulation analyses. This approach reveals that the virulence regulatory network exerts a control of the primary metabolism to promote robustness upon infection. The virulence regulatory network plugs into the primary metabolism mainly through the control of genes likely acquired via horizontal gene transfer, which results in a functional overlay with ancestral genes. These results support the view that robustness may be a selected trait that promotes pathogenic fitness upon infection.

Phenotypes can be robust and evolvable if mutations have non-local effects on sequence constraints.

The mapping between biological genotypes and phenotypes plays an important role in evolution, and understanding the properties of this mapping is crucial to determine the outcome of evolutionary processes. One of the most striking properties observed in several genotype-phenotype (GP) maps is the positive correlation between the robustness and evolvability of phenotypes. This implies that a phenotype can be strongly robust against mutations and at the same time evolvable to a diverse range of alternative phenotypes. Here, we examine the causes for this positive correlation by introducing two analytically tractable GP map models that follow the principles of real biological GP maps. The first model is based on gene-like GP maps, reflecting the way in which genetic sequences are organized into protein-coding genes, and the second one is based on the GP map of RNA secondary structure. For both models, we find that a positive correlation between phenotype robustness and evolvability only emerges if mutations at one sequence position can have non-local effects on the sequence constraints at another position. This highlights that non-local effects of mutations are closely related to the coexistence of robustness and evolvability in phenotypes, and are likely to be an important feature of many biological GP maps.

Why Phenotype Robustness Promotes Phenotype Evolvability.

Robustness and evolvability are fundamental characteristics of life whose relationship has intrigued generations of biologists. Studies of several genotype–phenotype maps (GPMs) such as the map between short DNA sequences and their bindings to transcription factors showed that phenotype robustness (PR) promotes phenotype evolvability (PE), but the underlying reason is unclear. Here, we show mathematically that the expected PE is a monotonically increasing function of the expected PR in random GPMs. Population genetic simulations confirm that increasing PR raises the probability that a target phenotype appears in a population within a given time, under empirical as well as randomly rewired GPMs. These and other results demonstrate that the positive correlation between PR and PE is mathematical rather than biological. Hence, it is unsurprising to observe this correlation in every empirical GPM investigated, although the magnitude of the correlation may vary due to influences of various biological factors.

Developmental nonlinearity drives phenotypic robustness

Robustness to perturbation is a fundamental feature of complex organisms. Mutations are the raw material for evolution, yet robustness to their effects is required for species survival. The mechanisms that produce robustness are poorly understood. Nonlinearities are a ubiquitous feature of development that may link variation in development to phenotypic robustness. Here, we manipulate the gene dosage of a signaling molecule, Fgf8, a critical regulator of vertebrate development. We demonstrate that variation in Fgf8 expression has a nonlinear relationship to phenotypic variation, predicting levels of robustness among genotypes. Differences in robustness are not due to gene expression variance or dysregulation, but emerge from the nonlinearity of the genotype–phenotype curve. In this instance, embedded features of development explain robustness differences. How such features vary in natural populations and relate to genetic variation are key questions for unraveling the origin and evolvability of this feature of organismal development.