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.     

Developmental objections to evolutionary modularity

Evolutionary psychologists argue that selective pressures in our ancestral environment yield a highly specialized set of modular cognitive capacities. However, recent papers in developmental psychology and neuroscience claim that evolutionary accounts of modularity are incompatible with the flexibility and plasticity of the developing brain. Instead, they propose cortical and neuronal brain structures are fixed through interactions with our developmental environment. Buller and Gray Hardcastle contend that evolutionary accounts of cognitive development are unacceptably rigid in light of evidence of cortical plasticity. The developing structure of the brain is both too random and too sensitive to external stimuli to be the product of a fixed genetic mechanism. They also claim that the complexity of the human brain cannot be explained in terms of our meager genetic endowment. There simply are not enough genes to program the intricate neuronal structures that are essential to cognition. I argue that neither of these arguments are persuasive. Small numbers of genes can function to determine diverse phenotypical outcomes through evolutionarily selected developmental systems. Similarly, theories of modularity do not rule out the possibility that innate cognitive systems exploit environmental regularities to guide the developing structure of the brain. Consequently, the anti-adaptionist consequences of these positions should be rejected.     

Modularity, comparative embryology and evo-devo: Developmental dissection of evolving body plans

Modules can be defined as quasi-autonomous units that are connected loosely with each other within a system. A need for the concept of modularity has emerged as we deal with evolving organisms in evolutionary developmental research, especially because it is unknown how genes are associated with anatomical patterns. One of the strategies to link genotypes with phenotypes could be to relate developmental modules with morphological ones. To do this, it is fundamental to grasp the context in which certain anatomical units and developmental processes are associated with each other specifically. By identifying morphological modularities as units recognized by some categories of general homology as established by comparative anatomy, it becomes possible to identify developmental modules whose genetic components exhibit coextensive expressions. This permits us to distinguish the evolutionary modification in which the identical morphological module simply alters its shape for adaptation, without being decoupled from the functioning gene network (‘coupled modularities’), from the evolution of novelty that involves a heterotopic shift between the anatomical and developmental modules. Using this formulation, it becomes possible, within the realm of Geoffroy's homologous networks, to reduce morphological homologies to developmental mechanistic terms by dissociating certain classes of modules that are often associated with actual shapes and functions.     

以发育模块重复征用和整合为基础的进化创新机制

进化新征的起源和分化是进化发育生物学研究的核心问题。通过对多细胞生物早期发育调控机制的比较分析,发现亲缘关系较远的生物所共有的一些形态特征受保守的发育调控程序调节（深同源性）。许多创新性状的发生是基于对预先存在的基因或发育调控模块的重复利用和整合。发育基因调控网络在结构和功能上高度模块化,因此不仅可以通过模块拆分和重复征用改变发育程式,而且也增强了调控网络自身的进化力。研究基因调控网络和发育系统的进化动态将有助于更深入地认识生物演化过程中创新性状发生和表型进化的分子机制。     

Evolutionary mechanisms: Modularity,morphogenetic fields of gene expression,genetic regulation

Modern concepts heterochrony mechanisms, taking into account the data on modularity of ontogenetic and evolutionary processes, morphogenetic fields of gene expression are considered. In the context of evolutionary changes, features of genetic regulation of heterochronies, and also suppression of gene activity by epigenetic regulation are analyzed. Features of the origin of evolutionary novelties due to heterochronies, macromutations, and divergence of duplicated genes, which result in the formation of new genes and gene families, are discussed.     

Origin of the fittest: link between emergent variation and evolutionary change as a critical question in evolutionary biology

In complex organisms, neutral evolution of genomic architecture, associated compensatory interactions in protein networks and emergent developmental processes can delineate the directions of evolutionary change, including the opportunity for natural selection. These effects are reflected in the evolution of developmental programmes that link genomic architecture with a corresponding functioning phenotype. Two recent findings call for closer examination of the rules by which these links are constructed. First is the realization that high dimensionality of genotypes and emergent properties of autonomous developmental processes (such as capacity for self-organization) result in the vast areas of fitness neutrality at both the phenotypic and genetic levels. Second is the ubiquity of context- and taxa-specific regulation of deeply conserved gene networks, such that exceptional phenotypic diversification coexists with remarkably conserved generative processes. Establishing the causal reciprocal links between ongoing neutral expansion of genomic architecture, emergent features of organisms' functionality, and often precisely adaptive phenotypic diversification therefore becomes an important goal of evolutionary biology and is the latest reincarnation of the search for a framework that links development, functioning and evolution of phenotypes. Here I examine, in the light of recent empirical advances, two evolutionary concepts that are central to this framework-natural selection and inheritance-the general rules by which they become associated with emergent developmental and homeostatic processes and the role that they play in descent with modification.     

Varieties of modules: kinds, levels, origins, and behaviors

This article began as a review of a conference, organized by Gerhard Schlosser, entitled "Modularity in Development and Evolution." The conference was held at, and sponsored by, the Hanse Wissenschaftskolleg in Delmenhorst, Germany in May, 2000. The article subsequently metamorphosed into a literature and concept review as well as an analysis of the differences in current perspectives on modularity. Consequently, I refer to general aspects of the conference but do not review particular presentations. I divide modules into three kinds: structural, developmental, and physiological. Every module fulfills none, one, or multiple functional roles. Two further orthogonal distinctions are important in this context: module-kinds versus module-variants-of-a-kind and reproducer versus nonreproducer modules. I review criteria for individuation of modules and mechanisms for the phylogenetic origin of modularity. I discuss conceptual and methodological differences between developmental and evolutionary biologists, in particular the difference between integration and competition perspectives on individualization and modular behavior. The variety in views regarding modularity presents challenges that require resolution in order to attain a comprehensive, rather than a piecemeal and fragmentary, evolutionary developmental biology. J. Exp. Zool. (Mol. Dev. Evol.) 291:116-129, 2001.     

Developmental constraints vs. variational properties: How pattern formation can help to understand evolution and development

This article suggests that apparent disagreements between the concept of developmental constraints and neo-Darwinian views on morphological evolution can disappear by using a different conceptualization of the interplay between development and selection. A theoretical framework based on current evolutionary and developmental biology and the concepts of variational properties, developmental patterns and developmental mechanisms is presented. In contrast with existing paradigms, the approach in this article is specifically developed to compare developmental mechanisms by the morphological variation they produce and the way in which their functioning can change due to genetic variation. A developmental mechanism is a gene network, which is able to produce patterns in space though the regulation of some cell behaviour (like signalling, mitosis, apoptosis, adhesion, etc.). The variational properties of a developmental mechanism are all the pattern transformations produced under different initial and environmental conditions or IS-mutations. IS-mutations are DNA changes that affect how two genes in a network interact, while T-mutations are mutations that affect the topology of the network itself. This article explains how this new framework allows predictions not only about how pattern formation affects variation, and thus phenotypic evolution, but also about how development evolves by replacement between pattern formation mechanisms. This article presents testable inferences about the evolution of the structure of development and the phenotype under different selective pressures. That is what kind of pattern formation mechanisms, in which relative temporal order, and which kind of phenotypic changes, are expected to be found in development.     

From Caenorhabditis elegans to the human connectome: a specific modular organization increases metabolic,functional and developmental efficiency

The connectome, or the entire connectivity of a neural system represented by a network, ranges across various scales from synaptic connections between individual neurons to fibre tract connections between brain regions. Although the modularity they commonly show has been extensively studied, it is unclear whether the connection specificity of such networks can already be fully explained by the modularity alone. To answer this question, we study two networks, the neuronal network of Caenorhabditis elegans and the fibre tract network of human brains obtained through diffusion spectrum imaging. We compare them to their respective benchmark networks with varying modularities, which are generated by link swapping to have desired modularity values. We find several network properties that are specific to the neural networks and cannot be fully explained by the modularity alone. First, the clustering coefficient and the characteristic path length of both C. elegans and human connectomes are higher than those of the benchmark networks with similar modularity. High clustering coefficient indicates efficient local information distribution, and high characteristic path length suggests reduced global integration. Second, the total wiring length is smaller than for the alternative configurations with similar modularity. This is due to lower dispersion of connections, which means each neuron in the C. elegans connectome or each region of interest in the human connectome reaches fewer ganglia or cortical areas, respectively. Third, both neural networks show lower algorithmic entropy compared with the alternative arrangements. This implies that fewer genes are needed to encode for the organization of neural systems. While the first two findings show that the neural topologies are efficient in information processing, this suggests that they are also efficient from a developmental point of view. Together, these results show that neural systems are organized in such a way as to yield efficient features beyond those given by their modularity alone.     

Assessing the utility of conserving evolutionary history

It is often claimed that conserving evolutionary history is more efficient than species‐based approaches for capturing the attributes of biodiversity that benefit people. This claim underpins academic analyses and recommendations about the distribution and prioritization of species and areas for conservation, but evolutionary history is rarely considered in practical conservation activities. One impediment to implementation is that arguments related to the human‐centric benefits of evolutionary history are often vague and the underlying mechanisms poorly explored. Herein we identify the arguments linking the prioritization of evolutionary history with benefits to people, and for each we explicate the purported mechanism, and evaluate its theoretical and empirical support. We find that, even after 25 years of academic research, the strength of evidence linking evolutionary history to human benefits is still fragile. Most – but not all – arguments rely on the assumption that evolutionary history is a useful surrogate for phenotypic diversity. This surrogacy relationship in turn underlies additional arguments, particularly that, by capturing more phenotypic diversity, evolutionary history will preserve greater ecosystem functioning, capture more of the natural variety that humans prefer, and allow the maintenance of future benefits to humans. A surrogate relationship between evolutionary history and phenotypic diversity appears reasonable given theoretical and empirical results, but the strength of this relationship varies greatly. To the extent that evolutionary history captures unmeasured phenotypic diversity, maximizing the representation of evolutionary history should capture variation in species characteristics that are otherwise unknown, supporting some of the existing arguments. However, there is great variation in the strength and availability of evidence for benefits associated with protecting phenotypic diversity. There are many studies finding positive biodiversity–ecosystem functioning relationships, but little work exists on the maintenance of future benefits or the degree to which humans prefer sets of species with high phenotypic diversity or evolutionary history. Although several arguments link the protection of evolutionary history directly with the reduction of extinction rates, and with the production of relatively greater future biodiversity via increased adaptation or diversification, there are few direct tests. Several of these putative benefits have mismatches between the relevant spatial scales for conservation actions and the spatial scales at which benefits to humans are realized. It will be important for future work to fill in some of these gaps through direct tests of the arguments we define here.     

Mosaic heterochrony and evolutionary modularity: the trilobite genus Zacanthopsis as a case study

Logical connections exist between evolutionary modularity and heterochrony, two unifying and structuring themes in the expanding field of evolutionary developmental biology. The former sees complex phenotypes as being made up of semi-independent units of evolutionary transformation; the latter requires such a modular organization of phenotypes to occur in a localized or mosaic fashion. This conceptual relationship is illustrated here by analyzing the evolutionary changes in the cranidial ontogeny of two related species of Cambrian trilobites. With arguments from comparative developmental genetics and functional morphology, we delineate putative evolutionary modules within the cranidium and examine patterns of evolutionary changes in ontogeny at both global and local scales. Results support a case of mosaic heterochrony, that is, a combination of local heterochronies affecting the different parts individuated in the cranidium, leading to the complex pattern of allometric repatterning observed at the global scale. Through this example, we show that recasting morphological analyses of complex phenotypes with a priori knowledge or hypotheses about their organizational and variational properties can significantly improve our interpretation and understanding of evolutionary changes among related taxa, fossil and extant. Such considerations open avenues to investigate the large-scale dynamics of modularity and its role in phenotypic evolution.     

Modularity in the evolution of yeast protein interaction network

Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction networks became to exhibit modularity in their evolution? Here, we propose a hypothesis of modularity in the evolution of yeast protein interaction network based on molecular evolutionary evidence. We assigned yeast proteins into six evolutionary ages by constructing a phylogenetic profile. We found that all the almost half of hub proteins are evolutionarily new. Examining the evolutionary processes of protein complexes, functional modules and topological modules, we also found that member proteins of these modules tend to appear in one or two evolutionary ages. Moreover, proteins in protein complexes and topological modules show significantly low evolutionary rates than those not in these modules. Our results suggest a hypothesis of modularity in the evolution of yeast protein interaction network as systems evolution.     

Specialization Can Drive the Evolution of Modularity

Organismal development and many cell biological processes are organized in a modular fashion, where regulatory molecules form groups with many interactions within a group and few interactions between groups. Thus, the activity of elements within a module depends little on elements outside of it. Modularity facilitates the production of heritable variation and of evolutionary innovations. There is no consensus on how modularity might evolve, especially for modules in development. We show that modularity can increase in gene regulatory networks as a byproduct of specialization in gene activity. Such specialization occurs after gene regulatory networks are selected to produce new gene activity patterns that appear in a specific body structure or under a specific environmental condition. Modules that arise after specialization in gene activity comprise genes that show concerted changes in gene activities. This and other observations suggest that modularity evolves because it decreases interference between different groups of genes. Our work can explain the appearance and maintenance of modularity through a mechanism that is not contingent on environmental change. We also show how modularity can facilitate co-option, the utilization of existing gene activity to build new gene activity patterns, a frequent feature of evolutionary innovations.     

Evo-Devo: evolutionary developmental mechanisms

Evolutionary developmental biology (Evo-Devo) as a discipline is concerned, among other things, with discovering and understanding the role of changes in developmental mechanisms in the evolutionary origin of aspects of the phenotype. In a very real sense, Evo-Devo opens the black box between genotype and phenotype, or more properly, phenotypes as multiple life history stages arise in many organisms from a single genotype. Changes in the timing or positioning of an aspect of development in a descendant relative to an ancestor (heterochrony and heterotopy) were two evolutionary developmental mechanisms identified by Ernst Haeckel in the 1870s. Many more have since been identified, in large part because of our enhanced understanding of development and because new mechanisms emerge as development proceeds: the transfer from maternal to zygotic genomic control; cell-to-cell interactions; cell differentiation and cell migration; embryonic inductions; functional interactions at the tissue and organ levels; growth. Within these emergent processes, gene networks and gene cascades (genetic modules) link the genotype with morphogenetic units (cellular modules, namely germ layers, embryonic fields or cellular condensations), while epigenetic processes such as embryonic inductions, tissue interactions and functional integration, link morphogenetic units to the phenotype. Evolutionary developmental mechanisms also include interactions between individuals of the same species, individuals of different species, and species and their biotic and/or abiotic environment. Such interactions link ecological communities. Importantly, there is little to distinguish the causality that underlies these interactions from that which underlies inductive interactions within embryos.     

Evolutionary crossroads in developmental biology: sea urchins

Embryos of the echinoderms, especially those of sea urchins and sea stars, have been studied as model organisms for over 100 years. The simplicity of their early development, and the ease of experimentally perturbing this development, provides an excellent platform for mechanistic studies of cell specification and morphogenesis. As a result, echinoderms have contributed significantly to our understanding of many developmental mechanisms, including those that govern the structure and design of gene regulatory networks, those that direct cell lineage specification, and those that regulate the dynamic morphogenetic events that shape the early embryo.     

A potential role for differential contractility in early brain development and evolution

Differences in brain structure between species have long fascinated evolutionary biologists. Understanding how these differences arise requires knowing how they are generated in the embryo. Growing evidence in the field of evolutionary developmental biology (evo-devo) suggests that morphological differences between species result largely from changes in the spatiotemporal regulation of gene expression during development. Corresponding changes in functional cellular behaviors (morphogenetic mechanisms) are only beginning to be explored, however. Here we show that spatiotemporal patterns of tissue contractility are sufficient to explain differences in morphology of the early embryonic brain between disparate species. We found that enhancing cytoskeletal contraction in the embryonic chick brain with calyculin A alters the distribution of contractile proteins on the apical side of the neuroepithelium and changes relatively round cross-sections of the tubular brain into shapes resembling triangles, diamonds, and narrow slits. These perturbed shapes, as well as overall brain morphology, are remarkably similar to those of corresponding sections normally found in species such as zebrafish and Xenopus laevis (frog). Tissue staining revealed relatively strong concentration of F-actin at vertices of hyper-contracted cross-sections, and a finite element model shows that local contraction in these regions can convert circular sections into the observed shapes. Another model suggests that these variations in contractility depend on the initial geometry of the brain tube, as localized contraction may be needed to open the initially closed lumen in normal zebrafish and Xenopus brains, whereas this contractile machinery is not necessary in chick brains, which are already open when first created. We conclude that interspecies differences in cytoskeletal contraction may play a larger role in generating differences in morphology, and at much earlier developmental stages, in the brain than previously appreciated. This study is a step toward uncovering the underlying morphomechanical mechanisms that regulate how neural phenotypic differences arise between species.