Pleiotropic mutation, modularity and evolvability

The relationship between pleiotropy and the rate of evolution of a phenotypic character (evolvability) in a population is explored using computer simulations. I present results that suggest the rate of evolution of a phenotypic character may not decline when that character is pleiotropically associated to an increasing number of other characters, provided that the characters are under pure directional selection such that they are far from their optima relative to the average magnitude of a mutation. These conditions may be relevant during adaptive radiations. Adding pleiotropic associations to a set of characters in which one is under directional selection and the other is under stabilizing selection increases the rate of adaptation of the character under directional selection provided that the new characters that come to be pleiotropically associated are under directional selection. Thus, increasing the number of pleiotropic associations under these conditions increases the rate of adaptation of a character.     

Plasticity, evolvability, and modularity in RNA

RNA folding from sequences into secondary structures is a simple yet powerful, biophysically grounded model of a genotype-phenotype map in which concepts like plasticity, evolvability, epistasis, and modularity can not only be precisely defined and statistically measured but also reveal simultaneous and profoundly non-independent effects of natural selection. Molecular plasticity is viewed here as the capacity of an RNA sequence to assume a variety of energetically favorable shapes by equilibrating among them at constant temperature. Through simulations based on experimental designs, we study the dynamics of a population of RNA molecules that evolve toward a predefined target shape in a constant environment. Each shape in the plastic repertoire of a sequence contributes to the overall fitness of the sequence in proportion to the time the sequence spends in that shape. Plasticity is costly, since the more shapes a sequence can assume, the less time it spends in any one of them. Unsurprisingly, selection leads to a reduction of plasticity (environmental canalization). The most striking observation, however, is the simultaneous slow-down and eventual halting of the evolutionary process. The reduction of plasticity entails genetic canalization, that is, a dramatic loss of variability (and hence a loss of evolvability) to the point of lock-in. The causal bridge between environmental canalization and genetic canalization is provided by a correlation between the set of shapes in the plastic repertoire of a sequence and the set of dominant (minimum free energy) shapes in its genetic neighborhood. This statistical property of the RNA genotype-phenotype map, which we call plastogenetic congruence, traps populations in regions where most genetic variation is phenotypically neutral. We call this phenomenon neutral confinement. Analytical models of neutral confinement, made tractable by the assumption of perfect plastogenetic congruence, formally connect mutation rate, the topography of phenotype space, and evolvability. These models identify three mutational regimes: that corresponding to neutral confinement, an exploration threshold corresponding to a breakdown of neutral confinement with the simultaneous persistence of the dominant phenotype, and a classic error threshold corresponding to the loss of the dominant phenotype. In a final step, we analyze the structural properties of canalized phenotypes. The reduction of plasticity leads to extreme modularity, which we analyze from several perspectives: thermophysical (melting--the RNA version of a norm of reaction), kinetic (folding pathways--the RNA version of development), and genetic (transposability--the insensitivity to genetic context). The model thereby suggests a possible evolutionary origin of modularity as a side effect of environmental canalization.     

Quantifying protein modularity and evolvability: A comparison of different techniques

Modularity increases evolvability by reducing constraints on adaptation and by allowing preexisting parts to function in new contexts for novel uses. Protein evolution provides an excellent context to study the causes and consequences of biological modularity. In order to address such questions, however, an index for protein modularity is necessary. This paper proposes a simple index for protein modularity-"module density"-which is the number of evolutionarily independent modules that compose a protein divided by the number of amino acids in the protein. The decomposition of proteins into constituent modules can be accomplished by either of two classes of methods. The first class of methods relies on "suppositional" criteria to assign amino acids to modules, whereas the second class of methods relies on "coevolutionary" criteria for this task. One simple and practical method from the first class consists of approximating the number of modules in a protein as the number of regular secondary structure elements (i.e., helices and sheets). Methods based on coevolutionary criteria require more elaborate data, but they have the advantage of being able to specify modules without prior assumptions about why they exist. Given the increasing availability of datasets sampling protein mutational spectra (e.g., from comparative genomics, experimental evolution, and computational prediction), methods based on coevolutionary criteria will likely become more promising in the near future. The ability to meaningfully quantify protein modularity via simple indices has the potential to aid future efforts to understand protein evolutionary rate determinants, improve molecular evolution models and engineer novel proteins.     

Satb2, modularity,and the evolvability of the vertebrate jaw

Modularity is a key mechanism bridging development and evolution and is fundamental to evolvability. Herein, we investigate modularity of the Vertebrate jaw with the aim of understanding mechanisms of its morphological evolution. Conservation of the basic structural bauplan of Vertebrate jaws led to a Hinge and Caps model, in which polarity in the patterning system of developing jaws predicts modularity. We have tested the hypothesis that the Satb2+ cell population delineates a developmental module within the mandibular jaw. Satb2 is expressed in the mesenchyme of the jaw primordia that gives rise to distal elements of both the upper and lower jaws. Loss of Satb2 specifically affects structural elements of the distal (incisor) domain, reflecting the integration of these elements as well as their independence from other mandibular domains. Reducing Satb2 dosage leads to an increase in variation in mandibular length, providing insight into the developmental potential to generate variation. Inter‐taxa comparisons reveal that the Satb2 domain is conserved within gnathostomes. We complement previous loss of function studies in mice with gene knock‐down experiments in Xenopus, providing evidence for functional conservation of Satb2 in regulating size. Finally, we present evidence that the relative size of the amniote mandibular Satb2+ domain varies in relation to epithelial Fgf8 expression, suggesting a mechanism for evolutionary change in this domain. Taken together, our data support the Hinge and Caps model and provide evidence that Satb2 regulates coordinated distal jaw modules that are subject to evolutionary modification by signals emanating from the Hinge.     

Evolution of networks for body plan patterning; interplay of modularity, robustness and evolvability

A major goal of evolutionary developmental biology (evo-devo) is to understand how multicellular body plans of increasing complexity have evolved, and how the corresponding developmental programs are genetically encoded. It has been repeatedly argued that key to the evolution of increased body plan complexity is the modularity of the underlying developmental gene regulatory networks (GRNs). This modularity is considered essential for network robustness and evolvability. In our opinion, these ideas, appealing as they may sound, have not been sufficiently tested. Here we use computer simulations to study the evolution of GRNs' underlying body plan patterning. We select for body plan segmentation and differentiation, as these are considered to be major innovations in metazoan evolution. To allow modular networks to evolve, we independently select for segmentation and differentiation. We study both the occurrence and relation of robustness, evolvability and modularity of evolved networks. Interestingly, we observed two distinct evolutionary strategies to evolve a segmented, differentiated body plan. In the first strategy, first segments and then differentiation domains evolve (SF strategy). In the second scenario segments and domains evolve simultaneously (SS strategy). We demonstrate that under indirect selection for robustness the SF strategy becomes dominant. In addition, as a byproduct of this larger robustness, the SF strategy is also more evolvable. Finally, using a combined functional and architectural approach, we determine network modularity. We find that while SS networks generate segments and domains in an integrated manner, SF networks use largely independent modules to produce segments and domains. Surprisingly, we find that widely used, purely architectural methods for determining network modularity completely fail to establish this higher modularity of SF networks. Finally, we observe that, as a free side effect of evolving segmentation and differentiation in combination, we obtained in-silico developmental mechanisms resembling mechanisms used in vertebrate development.     

Potential of ants and beetles as indicators of rainforest restoration: characterising pasture and rainforest remnants as reference habitats

Assessment of habitat restoration requires baseline information on the communities present in both converted and intact forms of the focal ecosystem to enable comparisons with restored sites. Ants and beetles are commonly used in ecological monitoring programmes, as they display assemblage‐level responses to habitat change and can be a more direct measure of the recommencement of some ecosystem functions than the presence of more obvious biota such as plants. However, as these taxa differ substantially in ecological traits, their response patterns and utility as potential bioindicators may vary. Using pitfall traps, we compared assemblages of ant and beetle species between two reference habitats, pasture and remnant rainforest in subtropical eastern Australia. The assemblage composition of both groups differed significantly between rainforest and pasture but only beetles showed accompanying differences in species richness and abundance, which were both significantly lower in pasture. We identified ant and beetle species characteristic of either pasture or rainforest remnants, which may be used as bioindicators in future monitoring programmes. These species, however, displayed patchy distributions, suggesting that the use of individual species as bioindicators is likely to be unreliable. These findings support the use of ‘composite habitat indices’, which combine information from sets of indicator species. Given that patterns of change in species composition were similar between ants and beetles, either is an appropriate focal taxon for future monitoring programmes. Beetles, however, displayed some limitations as no species were indicative of the disturbed pasture habitat. Ants and beetles are likely to respond in different ways to different aspects of habitat change; thus, using both together could strengthen assessments of rainforest degradation or recovery.     

Evolution of novel mosaic castes in ants: modularity, phenotypic plasticity, and colonial buffering

Abstract Many ants have independently evolved castes with novel morphology as well as function, such as soldiers and permanently wingless (ergatoid) queens. We present a conceptual model, based on modularity in morphology and development, in which evolutionary innovation is facilitated by the ancestral ant polyphenism of winged queens and wingless workers. We suggest that novel castes evolved from rare intercastes, anomalous mosaics of winged queens and workers, erratically produced by colonies through environmental or genetic perturbations. The colonial environment is highly accommodating and buffers viable intercastes from individual selection. Their cost is limited because they are diluted by the large number of nestmates, yet some can bring disproportionate benefits to their colonies in the context of defense or reproduction (e.g., wingless intercastes able to mate). Useful intercastes will increase in frequency as their morphology is stabilized through genetic accommodation. We show that both soldiers and ergatoid queens are mosaics of winged queens and workers, and they are strikingly similar to some intercastes. Modularity and developmental plasticity together with winged/wingless polyphenism thus allow for the production of highly variable mosaic intercastes, and colonies incubate the advantageous mosaics.     

Engineering and evolvability

Comparing engineering to evolution typically involves adaptationist thinking, where well-designed artifacts are likened to well-adapted organisms, and the process of evolution is likened to the process of design. A quite different comparison is made when biologists focus on evolvability instead of adaptationism. Here, the idea is that complex integrated systems, whether evolved or engineered, share universal principles that affect the way they change over time. This shift from adaptationism to evolvability is a significant move for, as I argue, we can make sense of these universal principles without making any adaptationism claims. Furthermore, evolvability highlights important aspects of engineering that are ignored in the adaptationist debates. I introduce some novel engineering examples that incorporate these key neglected aspects, and use these examples to challenge some commonly cited contrasts between engineering and evolution, and to highlight some novel resemblances that have gone unnoticed.     

Gynandromorphs of the pycnogonid Anoplodactylus portus

A large sample of the pycriogonid Anoplodactylus portus , collected from the Pacific side of the Panama Canal Zone, contains a high percentage of gynandromorphs. The literature on aquatic arthropod gynandromorphs is outlined. The nature and variations of the sexual mosaic population are described and discussed. The several morphological differences between normal and mosaic members of the population are illustrated, and the possible origin of these gynandromorphs is discussed.     

Bistability in feedback circuits as a byproduct of evolution of evolvability

Noisy bistable dynamics in gene regulation can underlie stochastic switching and is demonstrated to be beneficial under fluctuating environments. It is not known, however, if fluctuating selection alone can result in bistable dynamics. Using a stochastic model of simple feedback networks, we apply fluctuating selection on gene expression and run in silico evolutionary simulations. We find that independent of the specific nature of the environment–fitness relationship, the main outcome of fluctuating selection is the evolution of increased evolvability in the network; system parameters evolve toward a nonlinear regime where phenotypic diversity is increased and small changes in genotype cause large changes in expression level. In the presence of noise, the evolution of increased nonlinearity results in the emergence and maintenance of bistability. Our results provide the first direct evidence that bistability and stochastic switching in a gene regulatory network can emerge as a mechanism to cope with fluctuating environments. They strongly suggest that such emergence occurs as a byproduct of evolution of evolvability and exploitation of noise by evolution.     

Prokaryote and eukaryote evolvability

The concept of evolvability covers a broad spectrum of, often contradictory, ideas. At one end of the spectrum it is equivalent to the statement that evolution is possible, at the other end are untestable post hoc explanations, such as the suggestion that current evolutionary theory cannot explain the evolution of evolvability. We examine similarities and differences in eukaryote and prokaryote evolvability, and look for explanations that are compatible with a wide range of observations. Differences in genome organisation between eukaryotes and prokaryotes meets this criterion. The single origin of replication in prokaryote chromosomes (versus multiple origins in eukaryotes) accounts for many differences because the time to replicate a prokaryote genome limits its size (and the accumulation of junk DNA). Both prokaryotes and eukaryotes appear to switch from genetic stability to genetic change in response to stress. We examine a range of stress responses, and discuss how these impact on evolvability, particularly in unicellular organisms versus complex multicellular ones. Evolvability is also limited by environmental interactions (including competition) and we describe a model that places limits on potential evolvability. Examples are given of its application to predator competition and limits to lateral gene transfer. We suggest that unicellular organisms evolve largely through a process of metabolic change, resulting in biochemical diversity. Multicellular organisms evolve largely through morphological changes, not through extensive changes to cellular biochemistry.     

Robustness and evolvability in genetic regulatory networks

Living organisms are robust to a great variety of genetic changes. Gene regulation networks and metabolic pathways self-organize and reaccommodate to make the organism perform with stability and reliability under many point mutations, gene duplications and gene deletions. At the same time, living organisms are evolvable, which means that these kind of genetic perturbations can eventually make the organism acquire new functions and adapt to new environments. It is still an open problem to determine how robustness and evolvability blend together at the genetic level to produce stable organisms that yet can change and evolve. Here we address this problem by studying the robustness and evolvability of the attractor landscape of genetic regulatory network models under the process of gene duplication followed by divergence. We show that an intrinsic property of this kind of networks is that, after the divergence of the parent and duplicate genes, with a high probability the previous phenotypes, encoded in the attractor landscape of the network, are preserved and new ones might appear. The above is true in a variety of network topologies and even for the case of extreme divergence in which the duplicate gene bears almost no relation with its parent. Our results indicate that networks operating close to the so-called "critical regime" exhibit the maximum robustness and evolvability simultaneously.     

Early usage and meaning of evolvability

Evolvability has become an enormously popular concept in evolutionary biology and in machine learning software architecture. While it is claimed that the term was coined in 1988 by Richard Dawkins, it was used as early as 1931 as a characteristic of life by John A. Thomson. We quote and review the earliest uses and definitions of evolvability in biological frameworks up until 1989, which are remarkably few. The meaning changed from simply the “ability to evolve” as a characteristic of life to various versions of including necessary variation to predict whether or not something could evolve to the rate and quality of that evolution. Or, meaning changed from the ability to evolve to the “quality” of the ability to evolve. Since then, evolvability has taken on many definitions as it has exploded in usage.