Decanalizing thinking on genetic canalization

Selection for robust metabolism in domesticated yeasts is driven by adaptation to Hsp90 stress

Protein folding both promotes and constrains adaptive evolution. We uncover this surprising duality in the role of the protein-folding chaperone heat shock protein 90 (Hsp90) in maintaining the integrity of yeast metabolism amid proteotoxic stressors within industrial domestication niches. Ethanol disrupts critical Hsp90-dependent metabolic pathways and exerts strong selective pressure for redundant duplications of key genes within these pathways, yielding the classical genomic signatures of beer and bread domestication. This work demonstrates a mechanism of adaptive canalization in an ecology of major economic importance and highlights Hsp90-dependent variation as an important source of phantom heritability in complex traits.

Mutational robustness and the role of buffer genes in evolvability

Organisms rely on mutations to fuel adaptive evolution. However, many mutations impose a negative effect on fitness. Cells may have therefore evolved mechanisms that affect the phenotypic effects of mutations, thus conferring mutational robustness. Specifically, so-called buffer genes are hypothesized to interact directly or indirectly with genetic variation and reduce its effect on fitness. Environmental or genetic perturbations can change the interaction between buffer genes and genetic variation, thereby unmasking the genetic variation's phenotypic effects and thus providing a source of variation for natural selection to act on. This review provides an overview of our understanding of mutational robustness and buffer genes, with the chaperone gene HSP90 as a key example. It discusses whether buffer genes merely affect standing variation or also interact with de novo mutations, how mutational robustness could influence evolution, and whether mutational robustness might be an evolved trait or rather a mere side-effect of complex genetic interactions.

Tracing genetic diversity captures the molecular basis of misfolding disease

Genetic variation in human populations can result in the misfolding and aggregation of proteins, giving rise to systemic and neurodegenerative diseases that require management by proteostasis. Here, we define the role of GRP94, the endoplasmic reticulum Hsp90 chaperone paralog, in managing alpha-1-antitrypsin deficiency on a residue-by-residue basis using Gaussian process regression-based machine learning to profile the spatial covariance relationships that dictate protein folding arising from sequence variants in the population. Covariance analysis suggests a role for the ATPase activity of GRP94 in controlling the N- to C-terminal cooperative folding of alpha-1-antitrypsin responsible for the correction of liver aggregation and lung-disease phenotypes of alpha-1-antitrypsin deficiency. Gaussian process-based spatial covariance profiling provides a standard model built on covariant principles to evaluate the role of proteostasis components in guiding information flow from genome to proteome in response to genetic variation, potentially allowing us to intervene in the onset and progression of complex multi-system human diseases.

The Architecture of Metabolic Networks Constrains the Evolution of Microbial Resource Hierarchies

Microbial strategies for resource use are an essential determinant of their fitness in complex habitats. When facing environments with multiple nutrients, microbes often use them sequentially according to a preference hierarchy, resulting in well-known patterns of diauxic growth. In theory, the evolutionary diversification of metabolic hierarchies could represent a mechanism supporting coexistence and biodiversity by enabling temporal segregation of niches. Despite this ecologically critical role, the extent to which substrate preference hierarchies can evolve and diversify remains largely unexplored. Here, we used genome-scale metabolic modeling to systematically explore the evolution of metabolic hierarchies across a vast space of metabolic network genotypes. We find that only a limited number of metabolic hierarchies can readily evolve, corresponding to the most commonly observed hierarchies in genome-derived models. We further show how the evolution of novel hierarchies is constrained by the architecture of central metabolism, which determines both the propensity to change ranks between pairs of substrates and the effect of specific reactions on hierarchy evolution. Our analysis sheds light on the genetic and mechanistic determinants of microbial metabolic hierarchies, opening new research avenues to understand their evolution, evolvability, and ecology.

Role of genetic architecture in phenotypic plasticity

Phenotypic plasticity, the ability of an organism to display different phenotypes across environments, is widespread in nature. Plasticity aids survival in novel environments. Herein, we review studies from yeast that allow us to start uncovering the genetic architecture of phenotypic plasticity. Genetic variants and their interactions impact the phenotype in different environments, and distinct environments modulate the impact of genetic variants and their interactions on the phenotype. Because of this, certain hidden genetic variation is expressed in specific genetic and environmental backgrounds. A better understanding of the genetic mechanisms of phenotypic plasticity will help to determine short- and long-term responses to selection and how wide variation in disease manifestation occurs in human populations.

Challenges and potential solutions for studying the genetic and phenotypic architecture of adaptation in microbes

All organisms are defined by the makeup of their DNA. Over billions of years, the structure and information contained in that DNA, often referred to as genetic architecture, have been honed by a multitude of evolutionary processes. Mutations that cause genetic elements to change in a way that results in beneficial phenotypic change are more likely to survive and propagate through the population in a process known as adaptation. Recent work reveals that the genetic targets of adaptation are varied and can change with genetic background. Further, seemingly similar adaptive mutations, even within the same gene, can have diverse and unpredictable effects on phenotype. These challenges represent major obstacles in predicting adaptation and evolution. In this review, we cover these concepts in detail and identify three emerging synergistic solutions: higher-throughput evolution experiments combined with updated genotype-phenotype mapping strategies and physiological models. Our review largely focuses on recent literature in yeast, and the field seems to be on the cusp of a new era with regard to studying the predictability of evolution.

Unexpected variation of human molar size patterns

A tenet of mammalian, including primate dental evolution, is the Inhibitory Cascade Model, where first molar (M1) size predicts in a linear cline the size and onset time of the second (M2) and third (M3) molars: a larger M1 portends a progressively smaller and later-developing M2 and M3. In contemporary modern Homo sapiens, later-developing M3s are less likely to erupt properly. The Inhibitory Cascade Model is also used to predict molar sizes of extinct taxa, including fossil Homo. The extent to which Inhibitory Cascade Model predictions hold in contemporary H. sapiens molars is unclear, including whether this tenet informs about molar initiation, development, and eruption. We tested these questions here. In our radiographic sample of 323 oral quadrants and molar rows from contemporary humans based on mesiodistal crown lengths, we observed the distribution of molar proportions with a central tendency around parity (M1 = M2 = M3) that parsed into 13 distinct molar size ratio patterns. These patterns presented at different frequencies (e.g., M1 > M2 > M3 in about one-third of cases) that reflected whether the molar row was located in the maxilla or mandible and included both linear (e.g., M1 < M2 < M3) and nonlinear molar size ratio progressions (e.g., M1 > M2 < M3). Up to four patterns were found in the same subject's mouth. Lastly, M1 size alone does not predict M3 size, developmental timing, or eruption; rather, M2 size is integral to predicting M3 size. Our study indicates that human molar size is genetically 'softwired' and sensitive to factors local to the human upper jaw vs. lower jaw. The lack of a single stereotypical molar size ratio for contemporary H. sapiens suggests that predictions of fossil H. sapiens molar sizes using the Inhibitory Cascade Model must be made with caution.

Growing points in attachment disorganization: looking back to advance forward

In this special issue paper we reflect on the next generation of attachment research with a focus on disorganization, a central but still poorly understood topic in this area. We suggest that progress will be facilitated by a return to attachment theory's evolutionary roots, and to the emphasis on biological function that inspired Bowlby's original thinking. Increased interdisciplinary cross-fertilization and collaborations would enable novel and generative research on some of the long-standing questions surrounding attachment disorganization. Accordingly, we present an agenda for future research that encompasses contributions of modern ethology and neurobiology, novel hypotheses based on the concept of adaptive decanalization, connections with neurodevelopmental vulnerability and risk for mental disorders such as schizophrenia, and the possibility of sex differences in the behavioral manifestations of attachment disorganization. We believe that these avenues of theory and research offer exciting potential for innovative work in attachment disorganization in the years ahead.

Exploring the Causality Between Hypothyroidism and Non-alcoholic Fatty Liver: A Mendelian Randomization Study

The etiology of non-alcoholic fatty liver disease (NAFLD) involves complex interaction of genetic and environmental factors. A large number of observational studies have shown that hypothyroidism contributes to a high risk of NAFLD. However, the exact causality is still unknown. Due to the progress of genome-wide association study (GWAS) and the discovery of Mendelian randomization (MR), it is possible to explore the causality between the two diseases. In this study, in order to research into the influence of intermediate phenotypes on outcome, nine independent genetic variants of hypothyroidism obtained from the GWAS were used as instrumental variables (IVs) to perform MR analysis on NAFLD. Since there was no heterogeneity between IVs (P = 0.70), a fixed-effects model was used. The correlation between hypothyroidism and NAFLD was evaluated by using inverse-variance weighted (IVW) method and weighted median method. Then the sensitivity test was analyzed. The results showed that there was a high OR (1.7578; 95%CI 1.1897–2.5970; P = 0.0046) and a low intercept (−0.095; P = 0.431). None of the genetic variants drove the overall result (P < 0.01). Simply, we proved for the first time that the risk of NAFLD increases significantly on patients with hypothyroidism. Furthermore, we explained possible causes of NAFLD caused by hypothyroidism.

Constructive Neutral Evolution 20 Years Later

Evolution has led to a great diversity that ranges from elegant simplicity to ornate complexity. Many complex features are often assumed to be more functional or adaptive than their simpler alternatives. However, in 1999, Arlin Stolzfus published a paper in the Journal of Molecular Evolution that outlined a framework in which complexity can arise through a series of non-adaptive steps. He called this framework Constructive Neutral Evolution (CNE). Despite its two-decade-old roots, many evolutionary biologists still appear to be unaware of this explanatory framework for the origins of complexity. In this perspective piece, we explain the theory of CNE and how it changes the order of events in narratives that describe the evolution of complexity. We also provide an extensive list of cellular features that may have become more complex through CNE. We end by discussing strategies to determine whether complexity arose through neutral or adaptive processes.

A model of developmental canalization, applied to human cranial form

Developmental mechanisms that canalize or compensate perturbations of organismal development (targeted or compensatory growth) are widely considered a prerequisite of individual health and the evolution of complex life, but little is known about the nature of these mechanisms. It is even unclear if and how a “target trajectory” of individual development is encoded in the organism’s genetic-developmental system or, instead, emerges as an epiphenomenon. Here we develop a statistical model of developmental canalization based on an extended autoregressive model. We show that under certain assumptions the strength of canalization and the amount of canalized variance in a population can be estimated, or at least approximated, from longitudinal phenotypic measurements, even if the target trajectories are unobserved. We extend this model to multivariate measures and discuss reifications of the ensuing parameter matrix. We apply these approaches to longitudinal geometric morphometric data on human postnatal craniofacial size and shape as well as to the size of the frontal sinuses. Craniofacial size showed strong developmental canalization during the first 5 years of life, leading to a 50% reduction of cross-sectional size variance, followed by a continual increase in variance during puberty. Frontal sinus size, by contrast, did not show any signs of canalization. Total variance of craniofacial shape decreased slightly until about 5 years of age and increased thereafter. However, different features of craniofacial shape showed very different developmental dynamics. Whereas the relative dimensions of the nasopharynx showed strong canalization and a reduction of variance throughout postnatal development, facial orientation continually increased in variance. Some of the signals of canalization may owe to independent variation in developmental timing of cranial components, but our results indicate evolved, partly mechanically induced mechanisms of canalization that ensure properly sized upper airways and facial dimensions.

Developmental mechanisms that canalize or compensate perturbations of organismal development are a prerequisite of individual health and the evolution of complex life. However, surprisingly little is known about these mechanisms, partly because the “target trajectories” of individual development cannot be directly observed. Here we develop a statistical model of developmental canalization that allows one to estimate the strength of canalization and the amount of canalized variance in a population even if the target trajectories are unobserved. We applied these approaches to data on human postnatal craniofacial growth. Whereas overall craniofacial size was strongly canalized during the first 5 years of age, frontal sinus size did not show any signs of canalization. The relative dimensions of the nasopharynx showed strong canalization and a reduction of variance throughout postnatal development, whereas other shape features, such as facial orientation, continually increased in variance. Our results indicate evolved, partly mechanically induced mechanisms of canalization that ensure properly sized upper airways and facial dimensions.

Genomic Variation, Evolvability, and the Paradox of Mental Illness

Twentieth-century genetics was hard put to explain the irregular behavior of neuropsychiatric disorders. Autism and schizophrenia defy a principle of natural selection; they are highly heritable but associated with low reproductive success. Nevertheless, they persist. The genetic origins of such conditions are confounded by the problem of variable expression, that is, when a given genetic aberration can lead to any one of several distinct disorders. Also, autism and schizophrenia occur on a spectrum of severity, from mild and subclinical cases to the overt and disabling. Such irregularities reflect the problem of missing heritability; although hundreds of genes may be associated with autism or schizophrenia, together they account for only a small proportion of cases. Techniques for higher resolution, genomewide analysis have begun to illuminate the irregular and unpredictable behavior of the human genome. Thus, the origins of neuropsychiatric disorders in particular and complex disease in general have been illuminated. The human genome is characterized by a high degree of structural and behavioral variability: DNA content variation, epistasis, stochasticity in gene expression, and epigenetic changes. These elements have grown more complex as evolution scaled the phylogenetic tree. They are especially pertinent to brain development and function. Genomic variability is a window on the origins of complex disease, neuropsychiatric disorders, and neurodevelopmental disorders in particular. Genomic variability, as it happens, is also the fuel of evolvability. The genomic events that presided over the evolution of the primate and hominid lineages are over-represented in patients with autism and schizophrenia, as well as intellectual disability and epilepsy. That the special qualities of the human genome that drove evolution might, in some way, contribute to neuropsychiatric disorders is a matter of no little interest.

Genotype by environment interaction for gene expression in Drosophila melanogaster

The genetics of phenotypic responses to changing environments remains elusive. Using whole-genome quantitative gene expression as a model, here we study how the genetic architecture of regulatory variation in gene expression changed in a population of fully sequenced inbred Drosophila melanogaster strains when flies developed in different environments (25 °C and 18 °C). We find a substantial fraction of the transcriptome exhibited genotype by environment interaction, implicating environmentally plastic genetic architecture of gene expression. Genetic variance in expression increases at 18 °C relative to 25 °C for most genes that have a change in genetic variance. Although the majority of expression quantitative trait loci (eQTLs) for the gene expression traits in the two environments are shared and have similar effects, analysis of the environment-specific eQTLs reveals enrichment of binding sites for two transcription factors. Finally, although genotype by environment interaction in gene expression could potentially disrupt genetic networks, the co-expression networks are highly conserved across environments. Genes with higher network connectivity are under stronger stabilizing selection, suggesting that stabilizing selection on expression plays an important role in promoting network robustness.

Genetic buffering and potentiation in metabolism

Cells adjust their metabolism in response to mutations, but how this reprogramming depends on the genetic context is not well known. Specifically, the absence of individual enzymes can affect reprogramming, and thus the impact of mutations in cell growth. Here, we examine this issue with an in silico model of Saccharomyces cerevisiae's metabolism. By quantifying the variability in the growth rate of 10000 different mutant metabolisms that accumulated changes in their reaction fluxes, in the presence, or absence, of a specific enzyme, we distinguish a subset of modifier genes serving as buffers or potentiators of variability. We notice that the most potent modifiers refer to the glycolysis pathway and that, more broadly, they show strong pleiotropy and epistasis. Moreover, the evidence that this subset depends on the specific growing condition strengthens its systemic underpinning, a feature only observed before in a toy model of a gene-regulatory network. Some of these enzymes also modulate the effect that biochemical noise and environmental fluctuations produce in growth. Thus, the reorganization of metabolism induced by mutations has not only direct physiological implications but also transforms the influence that other mutations have on growth. This is a general result with implications in the development of cancer therapies based on metabolic inhibitors.

What Has a Century of Quantitative Genetics Taught Us About Nature's Genetic Tool Kit?

The complexity of heredity has been appreciated for decades: Many traits are controlled not by a single genetic locus but instead by polymorphisms throughout the genome. The importance of complex traits in biology and medicine has motivated diverse approaches to understanding their detailed genetic bases. Here, we focus on recent systematic studies, many in budding yeast, which have revealed that large numbers of all kinds of molecular variation, from noncoding to synonymous variants, can make significant contributions to phenotype. Variants can affect different traits in opposing directions, and their contributions can be modified by both the environment and the epigenetic state of the cell. The integration of prospective (synthesizing and analyzing variants) and retrospective (examining standing variation) approaches promises to reveal how natural selection shapes quantitative traits. Only by comprehensively understanding nature's genetic tool kit can we predict how phenotypes arise from the complex ensembles of genetic variants in living organisms.

Schizophrenia: Developmental Variability Interacts with Risk Factors to Cause the Disorder: Nonspecific Variability-Enhancing Factors Combine with Specific Risk Factors to Cause Schizophrenia

A new etiological model is proposed for schizophrenia that combines variability-enhancing nonspecific factors acting during development with more specific risk factors. This model is better suited than the current etiological models of schizophrenia, based on the risk factors paradigm, for predicting and/or explaining several important findings about schizophrenia: high co-morbidity rates, low specificity of many risk factors, and persistence in the population of the associated genetic polymorphisms. Compared with similar models, e.g., de-canalization, common psychopathology factor, sexual-selection, or differential sensitivity to the environment, this proposal is more general and integrative. Recently developed research methods have proven the existence of genetic and environmental factors that enhance developmental variability. Applying such methods to newly collected or already available data can allow for testing the hypotheses upon which this model is built. If validated, this model may change the understanding of the etiology of schizophrenia, the research models, and preventionbrk paradigms.

Resurrection from lethal knockouts: Bypass of gene essentiality

Understanding genotype-phenotype relationships is a central pursuit in biology. Gene knockout generates a complete loss-of-function genotype and is a commonly used approach for probing gene functions. The most severe phenotypic consequence of gene knockout is lethality. Genes with a lethal knockout phenotype are called essential genes. Based on genome-wide knockout analyses in yeasts, up to approximately a quarter of genes in a genome can be essential. Like other genotype-phenotype relationships, gene essentiality is subject to background effects and can vary due to gene-gene interactions. In particular, for some essential genes, lethality caused by knockout can be rescued by extragenic suppressors. Such "bypass of essentiality" (BOE) gene-gene interactions have been an understudied type of genetic suppression. A recent systematic analysis revealed that, remarkably, the essentiality of nearly 30% of essential genes in the fission yeast Schizosaccharomyces pombe can be bypassed by BOE interactions. Here, I review the history and recent progress on uncovering and understanding the bypass of gene essentiality.

Genetic and environmental canalization are not associated among altitudinally varying populations of Drosophila melanogaster

Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. There has been interest regarding the conditions enabling the evolution of canalization. Under some models, the circumstances under which genetic canalization evolves are limited despite apparent empirical evidence for it. It has been argued that genetic canalization evolves as a correlated response to environmental canalization (congruence model). Yet, empirical evidence has not consistently supported predictions of a correlation between genetic and environmental canalization. In a recent study, a population of Drosophila adapted to high altitude showed evidence of genetic decanalization relative to those from low altitudes. Using strains derived from these populations, we tested if they varied for multiple aspects of environmental canalization We observed the expected differences in wing size, shape, cell (trichome) density and mutational defects between high- and low-altitude populations. However, we observed little evidence for a relationship between measures of environmental canalization with population or with defect frequency. Our results do not support the predicted association between genetic and environmental canalization.

Distinct metabolic states of a cell guide alternate fates of mutational buffering through altered proteostasis

Metabolic changes alter the cellular milieu; can this also change intracellular protein folding? Since proteostasis can modulate mutational buffering, if change in metabolism has the ability to change protein folding, arguably, it should also alter mutational buffering. Here we find that altered cellular metabolic states in E. coli buffer distinct mutations on model proteins. Buffered-mutants have folding problems in vivo and are differently chaperoned in different metabolic states. Notably, this assistance is dependent upon the metabolites and not on the increase in canonical chaperone machineries. Being able to reconstitute the folding assistance afforded by metabolites in vitro, we propose that changes in metabolite concentrations have the potential to alter protein folding capacity. Collectively, we unravel that the metabolite pools are bona fide members of proteostasis and aid in mutational buffering. Given the plasticity in cellular metabolism, we posit that metabolic alterations may play an important role in cellular proteostasis.

Changes in osmotic homeostasis alter metabolites and therefore chemical milieu of the cells. Here, the authors show that altering metabolites in E. coli also change the cellular capacity for buffering mutations that impair protein folding and influences proteostasis irrespective of molecular chaperones

Embryonic canalization and its limits-A view from temperature

Many animals are able to produce similar offspring over a range of environmental conditions. This property of the developmental process has been termed canalization-the channeling of developmental pathways to generate a stable outcome despite varying conditions. Temperature is one environmental parameter that has fundamental effects on cell physiology and biochemistry, yet developmental programs generally result in a stable phenotype under a range of temperatures. On the other hand, there are typically upper and lower temperature limits beyond which the developmental program is unable to produce normal offspring. This review summarizes data on how development is affected by temperature, particularly high temperature, in various animal species. It also brings together information on potential cell biological and developmental genetic factors that may be responsible for developmental stability in varying temperatures, and likely critical mechanisms that break down at high temperature. Also reviewed are possible means for studying temperature effects on embryogenesis and how to determine which factors are most critical at the high-temperature limits for normal development. Increased knowledge of these critical factors will point to the targets of selection under climate change, and more generally, how developmental robustness in varying environments is maintained.

Why and how to study genetic changes with context-dependent effects

The phenotypic impacts of a genetic change can depend on genetic background (e.g. epistasis), as well as other contexts including environment, developmental stage, cell type, disease state, and higher-order combinations thereof. Recent advances in high-throughput phenotyping are uncovering examples of context dependence faster than genotype-phenotype maps and other core concepts are changing to reflect the dynamic nature of biological systems. Here, we review several approaches to study context dependence and their findings. In our opinion, these findings encourage more studies that examine the spectrum of effects a genetic change may have, as opposed to studies that exclusively measure the impact of a genetic change in a particular context. Studies that elucidate the mechanisms that cause the effects of genetic change to vary with context are of special interest. Previous studies of the mechanisms underlying context dependence have improved predictions of phenotype from genotype and have provided insight about how biological systems function and evolve.

Genetic and environmental perturbations lead to regulatory decoherence

Correlation among traits is a fundamental feature of biological systems that remains difficult to study. To address this problem, we developed a flexible approach that allows us to identify factors associated with inter-individual variation in correlation. We use data from three human cohorts to study the effects of genetic and environmental variation on correlations among mRNA transcripts and among NMR metabolites. We first show that environmental exposures (infection and disease) lead to a systematic loss of correlation, which we define as 'decoherence'. Using longitudinal data, we show that decoherent metabolites are better predictors of whether someone will develop metabolic syndrome than metabolites commonly used as biomarkers of this disease. Finally, we demonstrate that correlation itself is under genetic control by mapping hundreds of 'correlation quantitative trait loci (QTLs)'. Together, this work furthers our understanding of how and why coordinated biological processes break down, and points to a potential role for decoherence in disease.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

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.

Chaperones, Canalization, and Evolution of Animal Forms

Over half a century ago, British developmental biologist Conrad Hal Waddington proposed the idea of canalization, that is, homeostasis in development. Since the breakthrough that was made by Rutherford and Lindquist (1998), who proposed a role of Hsp90 in developmental buffering, chaperones have gained much attention in the study of canalization. However, recent studies have revealed that a number of other molecules are also potentially involved in canalization. Here, I introduce the emerging role of DnaJ chaperones in canalization. I also discuss how the expression levels of such buffering molecules can be altered, thereby altering organismal development. Since developmental robustness is maternally inherited in various organisms, I propose that dynamic bet hedging, an increase in within-clutch variation in offspring phenotypes that is caused by unpredictable environmental challenges to the mothers, plays a key role in altering the expression levels of buffering molecules. Investigating dynamic bet hedging at the molecular level and how it impacts upon morphological phenotypes will help our understanding of the molecular mechanisms of canalization and evolutionary processes.

The developmental-genetics of canalization

Canalization, or robustness to genetic or environmental perturbations, is fundamental to complex organisms. While there is strong evidence for canalization as an evolved property that varies among genotypes, the developmental and genetic mechanisms that produce this phenomenon are very poorly understood. For evolutionary biology, understanding how canalization arises is important because, by modulating the phenotypic variation that arises in response to genetic differences, canalization is a determinant of evolvability. For genetics of disease in humans and for economically important traits in agriculture, this subject is important because canalization is a potentially significant cause of missing heritability that confounds genomic prediction of phenotypes. We review the major lines of thought on the developmental-genetic basis for canalization. These fall into two groups. One proposes specific evolved molecular mechanisms while the other deals with robustness or canalization as a more general feature of development. These explanations for canalization are not mutually exclusive and they overlap in several ways. General explanations for canalization are more likely to involve emergent features of development than specific molecular mechanisms. Disentangling these explanations is also complicated by differences in perspectives between genetics and developmental biology. Understanding canalization at a mechanistic level will require conceptual and methodological approaches that integrate quantitative genetics and developmental biology.