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This paper examines how the evolution of architectural generative design processes aim to apply similar physical and geometrical principles of biological processes taking place during development and to translate them to fabrication processes. In analogy to the reaction-diffusion mechanism for biological pattern prediction, the logic of stripe is used as construction system and examined for its structural behaviour. Both, mesh relaxation processes and weighted mesh graphs representations are employed as design tools for the construction of a minimal thin shell structural skin with branching topologies. Eventually the design workflow is extended to engage also collaborative fabrication processes and to steer the design based on intuition, knowledge of the fabrication tools, properties of the materials, manufacturing simulations and logic of assemble. This approach could lead to the optimization of material usage and machine time and facilitate the assembly process of a physical object which integrates the whole process into its form. The outcomes have been used to fabricate a prototype, using three different materials and digital fabrication methods, to examine the stability and the mechanical connectivity by taking in count the tolerances. The paper argues that biological skin patterns and segmentation in fabrication open a new field of interdisciplinary investigation and architectural applications.

The position of cells during development is constantly subject to noise, i.e. cell-level noise. We do not yet fully understand how cell-level noise coming from processes such as cell division or movement leads to morphological noise, i.e. morphological differences between genetically identical individuals developing in the same environment. To address this question we constructed a large ensemble of random genetic networks regulating cell behaviors (contraction, adhesion, etc.) and cell signaling. We simulated them with a general computational model of development, EmbryoMaker. We identified and studied the dynamics, under cell-level noise, of those networks that lead to the development of animal-like morphologies from simple blastula-like initial conditions. We found that growth by cell division is a major contributor to morphological noise. Self-activating gene network loops also amplified cell-level noise into morphological noise while long-range signaling and epithelial stiffness tended to reduce morphological noise., Competing Interests: Declaration of competing interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

What morphologies are more likely to appear during evolution is a central question in zoology. Here we offer a novel approach to this question based on first developmental principles. We assumed that morphogenesis results from the genetic regulation of cell properties and behaviors (adhesion, contraction, etc.). We used EmbryoMaker, a general model of development that can simulate any gene network regulating cell properties and behaviors, the mechanical interactions and signaling between cells and the morphologies arising from those. We created spherical initial conditions with anterior and dorsal territories. We performed simulations changing the cell properties and behaviors regulated in these territories to explore which morphologies may have been possible. Thus, we obtained a set of the most basic animal morphologies that can be developmentally possible assuming very simple induction and morphogenesis. Our simulations suggest that elongation, invagination, evagination, condensation and anisotropic growth are the morphogenetic transformations more likely to appear from changes in cell properties and behaviors. We also found some parallels between our simulations and the morphologies of simple animals, some early stages of animal development and fossils attributed to early animals., (© 2024 The Author(s). Journal of Experimental Zoology Part B: Molecular and Developmental Evolution published by Wiley Periodicals LLC.)

During development, cells are subject to stochastic fluctuations in their positions (i.e. cell-level noise) that can potentially lead to morphological noise (i.e. stochastic differences between morphologies that are expected to be equal, e.g. the right and left sides of bilateral organisms). In this study, we explore new and existing hypotheses on buffering mechanisms against cell-level noise. Many of these hypotheses focus on how the boundaries between territories of gene expression remain regular and well defined, despite cell-level noise and division. We study these hypotheses and how irregular territory boundaries lead to morphological noise. To determine the consistency of the different hypotheses, we use a general computational model of development: EmbryoMaker. EmbryoMaker can implement arbitrary gene networks regulating basic cell behaviors (contraction, adhesion, etc.), signaling and tissue biomechanics. We found that buffering mechanisms based on the orientation of cell divisions cannot lead to regular boundaries but that other buffering mechanisms can (homotypic adhesion, planar contraction, non-dividing boundaries, constant signaling and majority rule hypotheses). We also explore the effects of the shape and size of the territories on morphological noise., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2023. Published by The Company of Biologists Ltd.)

Evolutionary biology is paying increasing attention to the mechanisms that enable phenotypic plasticity, evolvability, and extra-genetic inheritance. Yet, there is a concern that these phenomena remain insufficiently integrated within evolutionary theory. Understanding their evolutionary implications would require focusing on phenotypes and their variation, but this does not always fit well with the prevalent genetic representation of evolution that screens off developmental mechanisms. Here, we instead use development as a starting point, and represent it in a way that allows genetic, environmental and epigenetic sources of phenotypic variation to be independent. We show why this representation helps to understand the evolutionary consequences of both genetic and non-genetic phenotype determinants, and discuss how this approach can instigate future areas of empirical and theoretical research., (© 2022 The Authors. BioEssays published by Wiley Periodicals LLC.)

Animal coloration is often expressed in periodic patterns that can arise from differential cell migration, yet how these processes are regulated remains elusive. We show that a female-limited polymorphism in dorsal patterning (diamond/chevron) in the brown anole is controlled by a single Mendelian locus. This locus contains the gene CCDC170 that is adjacent to, and coexpressed with, the Estrogen receptor-1 gene, explaining why the polymorphism is female limited. CCDC170 is an organizer of the Golgi-microtubule network underlying a cell's ability to migrate, and the two segregating alleles encode structurally different proteins. Our agent-based modeling of skin development demonstrates that, in principle, a change in cell migratory behaviors is sufficient to switch between the two morphs. These results suggest that CCDC170 might have been co-opted as a switch between color patterning morphs, likely by modulating cell migratory behaviors.

Background: Biological evolution exhibits an extraordinary capability to adapt organisms to their environments. The explanation for this often takes for granted that random genetic variation produces at least some beneficial phenotypic variation in which natural selection can act. Such genetic evolvability could itself be a product of evolution, but it is widely acknowledged that the immediate selective gains of evolvability are small on short timescales. So how do biological systems come to exhibit such extraordinary capacity to evolve? One suggestion is that adaptive phenotypic plasticity makes genetic evolution find adaptations faster. However, the need to explain the origin of adaptive plasticity puts genetic evolution back in the driving seat, and genetic evolvability remains unexplained., Results: To better understand the interaction between plasticity and genetic evolvability, we simulate the evolution of phenotypes produced by gene-regulation network-based models of development. First, we show that the phenotypic variation resulting from genetic and environmental perturbation are highly concordant. This is because phenotypic variation, regardless of its cause, occurs within the relatively specific space of possibilities allowed by development. Second, we show that selection for genetic evolvability results in the evolution of adaptive plasticity and vice versa. This linkage is essentially symmetric but, unlike genetic evolvability, the selective gains of plasticity are often substantial on short, including within-lifetime, timescales. Accordingly, we show that selection for phenotypic plasticity can be effective in promoting the evolution of high genetic evolvability., Conclusions: Without overlooking the fact that adaptive plasticity is itself a product of genetic evolution, we show how past selection for plasticity can exercise a disproportionate effect on genetic evolvability and, in turn, influence the course of adaptive evolution., (© 2021. The Author(s).)

The survival prospects of threatened species or populations can sometimes be improved by adaptive change. Such evolutionary rescue is particularly relevant when the threat comes from changing environments, or when long-term population persistence requires range expansion into new habitats. Conservation biologists are therefore often interested in whether or not populations or lineages show a disposition for adaptive evolution, that is, if they are evolvable. Here, we discuss four alternative perspectives that target different causes of evolvability and outline some of the key challenges those perspectives are designed to address. Standing genetic variation provides one familiar estimate of evolvability. Yet, the mere presence of genetic variation is often insufficient to predict if a population will adapt, or how it will adapt. The reason is that adaptive change not only depends on genetic variation, but also on the extent to which this genetic variation can be realized as adaptive phenotypic variation. This requires attention to developmental systems and how plasticity influences evolutionary potential. Finally, we discuss how a better understanding of the different factors that contribute to evolvability can be exploited in conservation practice., (© 2021 The Authors. Evolution & Development published by Wiley Periodicals LLC.)

Cell differentiation in multicellular organisms requires cells to respond to complex combinations of extracellular cues, such as morphogen concentrations. Some models of phenotypic plasticity conceptualise the response as a relatively simple function of a single environmental cues (e.g. a linear function of one cue), which facilitates rigorous analysis. Conversely, more mechanistic models such those implementing GRNs allows for a more general class of response functions but makes analysis more difficult. Therefore, a general theory describing how cells integrate multi-dimensional signals is lacking. In this work, we propose a theoretical framework for understanding the relationships between environmental cues (inputs) and phenotypic responses (outputs) underlying cell plasticity. We describe the relationship between environment and cell phenotype using logical functions, making the evolution of cell plasticity equivalent to a simple categorisation learning task. This abstraction allows us to apply principles derived from learning theory to understand the evolution of multi-dimensional plasticity. Our results show that natural selection is capable of discovering adaptive forms of cell plasticity associated with complex logical functions. However, developmental dynamics cause simpler functions to evolve more readily than complex ones. By using conceptual tools derived from learning theory we show that this developmental bias can be interpreted as a learning bias in the acquisition of plasticity functions. Because of that bias, the evolution of plasticity enables cells, under some circumstances, to display appropriate plastic responses to environmental conditions that they have not experienced in their evolutionary past. This is possible when the selective environment mirrors the bias of the developmental dynamics favouring the acquisition of simple plasticity functions-an example of the necessary conditions for generalisation in learning systems. These results illustrate the functional parallelisms between learning in neural networks and the action of natural selection on environmentally sensitive gene regulatory networks. This offers a theoretical framework for the evolution of plastic responses that integrate information from multiple cues, a phenomenon that underpins the evolution of multicellularity and developmental robustness., Competing Interests: The authors have declared that no competing interests exist.

During cleavage, different cellular processes cause the zygote to become partitioned into a set of cells with a specific spatial arrangement. These processes include the orientation of cell division according to: an animal-vegetal gradient; the main axis (Hertwig's rule) of the cell; and the contact areas between cells or the perpendicularity between consecutive cell divisions (Sachs' rule). Cell adhesion and cortical rotation have also been proposed to be involved in spiral cleavage. We use a computational model of cell and tissue biomechanics to account for the different existing hypotheses about how the specific spatial arrangement of cells in spiral cleavage arises during development. Cell polarization by an animal-vegetal gradient, a bias to perpendicularity between consecutive cell divisions (Sachs' rule), cortical rotation and cell adhesion, when combined, reproduce the spiral cleavage, whereas other combinations of processes cannot. Specifically, cortical rotation is necessary at the 8-cell stage to direct all micromeres in the same direction. By varying the relative strength of these processes, we reproduce the spatial arrangement of cells in the blastulae of seven different invertebrate species., (© 2017. Published by The Company of Biologists Ltd.)

Motivation: The transformation of the embryo during development requires complex gene networks, cell signaling and gene-regulated cell behaviors (division, adhesion, polarization, apoptosis, contraction, extracellular matrix secretion, signal secretion and reception, etc.). There are several models of development implementing these phenomena, but none considers at the same time the very different bio-mechanical properties of epithelia, mesenchyme, extracellular matrix and their interactions., Results: Here, we present a new computational model and accompanying open-source software, EmbryoMaker, that allows the user to simulate custom developmental processes by designing custom gene networks capable of regulating cell signaling and all animal basic cell behaviors. We also include an editor to implement different initial conditions, mutations and experimental manipulations. We show the applicability of the model by simulating several complex examples of animal development., Availability and Implementation: The source code can be downloaded from: http://www.biocenter.helsinki.fi/salazar/software.html., Contact: isalazar@mappi.helsinki.fi, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)