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427 results for “modularity”
Data from: Evolutionary covariation in geometric morphometric data: analyzing integration, modularity, and allometry in a phylogenetic context
Quantifying integration and modularity of evolutionary changes in morphometric traits is crucial for understanding how organismal shapes evolve. For this purpose, comparative studies are necessary, which need to take into account the phylogenetic structure of interspecific data. This study applies several of the standard tools of geometric morphometrics, which mostly have been used in intraspecific studies, in the new context of analyzing integration and modularity based on comparative data. Morphometric methods such as principal component analysis, multivariate regression, partial least squares and modularity tests can be applied to phylogenetically independent contrasts of shape data. We illustrate this approach in an analysis of cranial evolution in 160 species from all orders of birds. Mapping the shape information onto the phylogeny indicates that there is a significant phylogenetic signal in skull shape. Multivariate regression of independent contrasts of shape on independent contrasts of size reveals clear evolutionary allometry. Regardless of whether or not a correction for allometry is used, evolutionary integration between the face and braincase is strong, and tests reject the hypothesis that the face and braincase are separate evolutionary modules. These analyses can easily be applied to other taxa and can be combined with other morphometric tools to address a wide range of questions about evolutionary patterns and processes.
Data from: Conserved but flexible modularity in the zebrafish skull: implications for craniofacial evolvability
Morphological variation is the outward manifestation of development and provides fodder for adaptive evolution. Because of this contingency, evolution is often thought to be biased by developmental processes and functional interactions among structures, which are statistically detectable through forms of covariance among traits. This can take the form of substructures of integrated traits, termed modules, which together comprise patterns of variational modularity. While modularity is essential to an understanding of evolutionary potential, biologists currently have little understanding of its genetic basis, nor its temporal dynamics over generations. To address these open questions we compared patterns of craniofacial modularity among laboratory strains, defined mutant lines and a wild population of zebrafish (Danio rerio). Our findings suggest that relatively simple genetic changes can have profound effects on covariance, without greatly affecting craniofacial shape. Moreover, we show that instead of completely deconstructing the covariance structure among sets of traits, mutations cause shifts among seemingly latent patterns of modularity suggesting that the skull may be predisposed toward a limited number of phenotypes. This new insight may serve to greatly increase the evolvability of a population by providing a range of 'preset' patterns of modularity that can appear readily and allow for rapid evolution.
Data from: What affects the predictability of evolutionary constraints using a G-matrix? The relative effects of modular pleiotropy and mutational correlation
Phenotypic traits do not always respond to selection independently from each other and often show correlated responses to selection. The structure of a genotype-phenotype map (GP map) determines trait covariation, which involves variation in the degree and strength of the pleiotropic effects of the underlying genes. It is still unclear, and debated, how much of that structure can be deduced from variational properties of quantitative traits that are inferred from their genetic (co)variance matrix (G-matrix). Here we aim to clarify how the extent of pleiotropy and the correlation among the pleiotropic effects of mutations differentially affect the structure of a G-matrix and our ability to detect genetic constraints from its eigen decomposition. We show that the eigenvectors of a G-matrix can be predictive of evolutionary constraints when they map to underlying pleiotropic modules with correlated mutational effects. Without mutational correlation, evolutionary constraints caused by the fitness costs associated with increased pleiotropy are harder to infer from evolutionary metrics based on a G-matrix's geometric properties because uncorrelated pleiotropic effects do not affect traits' genetic correlations. Correlational selection induces much weaker modular partitioning of traits' genetic correlations in absence then in presence of underlying modular pleiotropy.
Data from: Mutation rules and the evolution of sparseness and modularity in biological systems
Biological systems exhibit two structural features on many levels of organization: sparseness, in which only a small fraction of possible interactions between components actually occur; and modularity – the near decomposability of the system into modules with distinct functionality. Recent work suggests that modularity can evolve in a variety of circumstances, including goals that vary in time such that they share the same subgoals (modularly varying goals), or when connections are costly. Here, we studied the origin of modularity and sparseness focusing on the nature of the mutation process, rather than on connection cost or variations in the goal. We use simulations of evolution with different mutation rules. We found that commonly used sum-rule mutations, in which interactions are mutated by adding random numbers, do not lead to modularity or sparseness except for in special situations. In contrast, product-rule mutations in which interactions are mutated by multiplying by random numbers – a better model for the effects of biological mutations – led to sparseness naturally. When the goals of evolution are modular, in the sense that specific groups of inputs affect specific groups of outputs, product-rule mutations also lead to modular structure; sum-rule mutations do not. Product-rule mutations generate sparseness and modularity because they tend to reduce interactions, and to keep small interaction terms small.
Data from: Modular color evolution facilitated by a complex nanostructure in birds
The way in which a complex trait varies, and thus evolves, is critically affected by the independence, or modularity, of its subunits. How modular designs facilitate phenotypic diversification is well studied in non-ornamental (e.g., cichlid jaws), but not ornamental traits. Diverse feather colors in birds are produced by light absorption by pigments and/or light scattering by nanostructures. Such structural colors are deterministically related to the nanostructures that produce them and are therefore excellent systems to study modularity and diversity of ornamental traits. Elucidating if and how these nanostructures facilitate color diversity relies on understanding how nanostructural traits covary, and how these traits map to color. Both of these remain unknown in an evolutionary context. Most dabbling ducks (Anatidae) have a conspicuous wing patch with iridescent color caused by a two-dimensional photonic crystal of small (100–200 nm) melanosomes. Here, we ask how this complex nanostructure affects modularity of color attributes. Using a combination of electron microscopy, spectrophotometry, and comparative methods, we show that nanostructural complexity causes functional decoupling and enables independent evolution of different color traits. These results demonstrate that color diversity is facilitated by how nanostructures function and may explain why some birds are more color-diverse than others.
Data from: Directional selection can drive the evolution of modularity in complex traits
Modularity is a central concept in modern biology, providing a powerful framework for the study of living organisms on many organizational levels. Two central and related questions can be posed in regard to modularity: How does modularity appear in the first place, and what forces are responsible for keeping and/or changing modular patterns? We approached these questions using a quantitative genetics simulation framework, building on previous results obtained with bivariate systems and extending them to multivariate systems. We developed an individual-based model capable of simulating many traits controlled by many loci with variable pleiotropic relations between them, expressed in populations subject to mutation, recombination, drift, and selection. We used this model to study the problem of the emergence of modularity, and hereby show that drift and stabilizing selection are inefficient at creating modular variational structures. We also demonstrate that directional selection can have marked effects on the modular structure between traits, actively promoting a restructuring of genetic variation in the selected population and potentially facilitating the response to selection. Furthermore, we give examples of complex covariation created by simple regimes of combined directional and stabilizing selection and show that stabilizing selection is important in the maintenance of established covariation patterns. Our results are in full agreement with previous results for two-trait systems and further extend them to include scenarios of greater complexity. Finally, we discuss the evolutionary consequences of modular patterns being molded by directional selection.
Data from: Drosophila wing modularity revisited through a quantitative genetic approach
To predict the response of complex morphological structures to selection it is necessary to know how the covariation among its different parts is organized. Two key features of covariation are modularity and integration. The Drosophila wing is currently considered a fully integrated structure. Here, we study the patterns of integration of the Drosophila wing and test the hypothesis of the wing being divided into two modules along the proximo-distal axis, as suggested by developmental, biomechanical, and evolutionary evidence. To achieve these goals we perform a multilevel analysis of covariation combining the techniques of geometric morphometrics and quantitative genetics. Our results indicate that the Drosophila wing is indeed organized into two main modules, the wing base and the wing blade. The patterns of integration and modularity were highly concordant at the phenotypic, genetic, environmental, and developmental levels. Besides, we found that modularity at the developmental level was considerably higher than modularity at other levels, suggesting that in the Drosophila wing direct developmental interactions are major contributors to total phenotypic shape variation. We propose that the precise time at which covariance-generating developmental processes occur and/or the magnitude of variation that they produce favor proximo-distal, rather than anterior-posterior, modularity in the Drosophila wing.
Data from: The relative efficiency of modular and non-modular networks of different size
Most biological networks are modular but previous work with small model networks has indicated that modularity does not necessarily lead to increased functional efficiency. Most biological networks are large, however, and here we examine the relative functional efficiency of modular and non-modular neural networks at a range of sizes. We conduct a detailed analysis of efficiency in networks of two size classes: 'small' and 'large', and a less detailed analysis across a range of network sizes. The former analysis reveals that while the modular network is less efficient than one of the two non-modular networks considered when networks are small, it is usually equally or more efficient than both non-modular networks when networks are large. The latter analysis shows that in networks of small to intermediate size, modular networks are much more efficient that non-modular networks of the same (low) connective density. If connective density must be kept low to reduce energy needs for example, this could promote modularity. We have shown how relative functionality/performance scales with network size, but the precise nature of evolutionary relationship between network size and prevalence of modularity will depend on the costs of connectivity.
Data from: Integration and modularity of teleostean pectoral fin shape and its role in the diversification of acanthomorph fishes
Phenotypic integration and modularity describe the strength and pattern of interdependencies between traits. Integration and modularity have been proposed to influence the trajectory of evolution, either acting as constraints or facilitators. Here, we examine trends in the integration and modularity of pectoral fin morphology in teleost fishes using geometric morphometrics. We compare the fin shapes of the highly diverse radiation of acanthomorph fishes to lower teleosts. Integration and modularity are measured using two-block partial least squares analysis and the covariance ratio coefficient between the radial bones and lepidotrichia of the pectoral fins. We show that the fins of acanthomorph fishes are more tightly integrated but also more morphologically diverse and faster evolving compared to non-acanthomorph fishes. The main pattern of shape covariation in non-acanthomorphs is concordant with the main trajectory of evolution between non-acanthomorphs and acanthomorphs. Our findings support a facilitating role for integration during the acanthomorph diversification. Potential functional consequences and developmental mechanisms of fin integration are discussed.
The new modular Sforzesco brace (MI-brace) is as effective as the classical one: a retrospective controlled study from a prospective cohort
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Fig. 4 in Functional And Phylogenetic Aspect In Modularity Of Palearctic Mustelids (Carnivora, Mustelidae) Mandible
Fig. 4. Phylogeny tree with the average shapes for species. Raw Procrustes coordinates are used for visualization. Reference (grey outline) is an overall average shape. MagniFIcation scale for shapes is 1.5.
Cheating interactions favor modularity in mutualistic networks
<p>A fundamental fact about mutualisms is that these mutually beneficial interactions often harbor cheaters that benefit from the use of resources and services without providing any positive feedback to the other players. The role of cheaters on the evolutionary dynamics of mutualisms has long been recognized, yet their broader consequences to the community level, and beyond species they interact with, is still poorly understood. Because mutualisms form networks that often involve dozens to hundreds of species, indirect effects generated by cheaters may cascade through the whole community, reshaping trait evolution. Here, we study how harboring cheating interactions can influence coevolution in mutualistic networks. We combine a coevolutionary model, empirical data on animal-plant mutualistic networks, and numerical simulations and show that a higher frequency of cheating interactions in a network can lead to the formation of groups of species phenotypically similar to each other and distinct from other groups, generating higher trait disparity. The resulting clustered trait patterns, in turn, change the patterns of interaction in simulated networks, fostering the formation of modules of interacting species. Our results indicate that cheaters contribute to generate phenotypic clusters in mutualistic networks, counteracting selection for convergence imposed by mutualists, and favoring the emergence of modules of interacting species. Based on these results, we suggest that cheaters might be a fundamental element for our understanding of the evolution of mutualistic networks.</p>
Data acquired by Modular-E robot in Quinta do Seixo on 07-07-2022
<p>Data acquired by Modular-E robot in Quinta do Seixo on 07-07-2022</p>
Supplementary Material: Emergent Orchestras: A Modular Framework for Musical Robot Swarms
<p>Supplementary Material containing the experiments described in the article.</p>
Data from: Low modularity and specialization in a commensalistic epiphyte–phorophyte network in a tropical cloud forest
Species interactions can shape the structure of natural communities. Such sets of interactions have been described as complex ecological networks, an example of which is the commensal network formed by epiphyte–phorophyte interactions. Vascular epiphytes germinate and grow on phorophytes (support trees), assuming a horizontal distribution (among the phorophyte species) and a vertical distribution (from the base of the tree trunk to the crown of phorophytes, i.e., through ecological zones). Here we investigated the organization of these structural dimensions of the epiphyte–phorophyte network in a Brazilian tropical montane cloud forest. The analyzed network, comprising 66 epiphyte species and 22 phorophyte species, exhibited a nested structure with a low degree of specialization, a typical pattern for epiphyte–phorophyte networks in forests. The network was slightly modular, with 65% of the species common to three modules, and had vertical structure corresponding to the vertical organization of the phorophytes. The size (diameter at breast height) of phorophyte individuals influenced the network structure, possibly due to the increase in habitat area, the time available for colonization by epiphytes, and a greater number of microenvironments. We found that the distribution of the epiphyte species differed between the phorophyte ecological zones, with greater richness in the lower portions and greater abundance in the upper portions of the phorophytes. The results provide relevant guidance for future research on the characteristics and the vertical and horizontal organization of vascular epiphyte and phorophyte networks.
Data from: A modular framework characterizes micro- and macroevolution of Old World monkey dentitions
The study of modularity can provide a foundation for integrating development into studies of phenotypic evolution. The dentition is an ideal phenotype for this as it is developmentally relatively simple, adaptively highly significant, and evolutionarily tractable through the fossil record. Here, we use phenotypic variation in the dentition to test a hypothesis about genetic modularity. Quantitative genetic analysis of size variation in the baboon dentition indicates a genetic modular framework corresponding to tooth type categories. We analyzed covariation within the dentitions of six species of Old World monkeys (OWMs) to assess the macroevolutionary extent of this framework: first by estimating variance–covariance matrices of linear tooth size, and second by performing a geometric morphometric (GM) analysis of tooth row shape. For both size and shape, we observe across OWMs a framework of anterior and postcanine modules, as well as submodularity between the molars and premolars. Our results of modularity by tooth type suggest that adult variation in the OWM dentition is influenced by early developmental processes such as odontogenesis and jaw patterning. This study presents a comparison of genotypic modules to phenotypic modules, which can be used to better understand their action across evolutionary time scales.
Data from: Gregarious suspension feeding in a modular Ediacaran organism
Reconstructing Precambrian eukaryotic paleoecology is pivotal to understanding origins of the modern, animal-dominated biosphere. Here, we combine new fossil data from southern Namibia with computational fluid dynamics (CFD) testing between competing feeding models for the Ediacaran taxon Ernietta. In addition, we perform simulations for multiple individuals, allowing us to analyze hydrodynamics of living communities. We show Ernietta lived gregariously, forming shallow marine aggregations in the latest Ediacaran, 548-541 Ma. We demonstrate enhanced vertical mixing of the water column above aggregations, and preferential redirection of current into body cavities of downstream individuals. These results support reconstruction of Ernietta as a macroscopic Ediacaran suspension feeder, and moreover provide a convincing paleoecological advantage to feeding in aggregations analogous to those recognized in many extant marine metazoans. These results provide some of the oldest evidence of commensal facilitation by macroscopic eukaryotes yet recognized in the fossil record.
Figure 1 from: Haston E, Cubey R, Pullan M, Atkins H, Harris D (2012) Developing integrated workflows for the digitisation of herbarium specimens using a modular and scalable approach. ZooKeys 209: 93-102. https://doi.org/10.3897/zookeys.209.3121
Figure 1 - Diagrammatic overview of the digitisation workflows at the Royal Botanic Garden Edinburgh (RBGE)
Figure 3 from: Molino J, Lubiana Alves T, Ferreira-Camargo L, Croce M, Tanaka A, Buson F, Ribeiro P, Campos-Salazar A, Antonio E, Maizel A, Siratuti V, Costa C, Wlodarczyk S, de Souza Lima R, Mello F, Mayfield S, Carvalho J (2016) Chimeric spider silk production in microalgae: a modular bionanomaterial. Research Ideas and Outcomes 2: e9342. https://doi.org/10.3897/rio.2.e9342
Figure 3 - Cassette construction to be inserted in C. renhardtii nuclear genome for the expression of desired proteins. Promoter hsp70A/rbcs2: fusion of the promoters hsp70A and rbcs2 (Eichler-Stahlberg et al. 2009, Schroda et al. 2000). Sh-Ble: gene that gives resistance to Zeomycin. 2A: self-cleavage peptide obtained from Foot and Mouth Disease Virus (FMDV) (Rasala et al. 2012). PS: Secretion signal peptide of the gene Ars1. GOI: gene of interest coding the proteins to be used in the project. His: coding sequence of six histidines (histidine tag). RbcS2 3'UTR: terminal sequence (untranslated region) of the gene RbcS2 (Fuhrmann et al. 1999)
Figure 1 from: Molino J, Lubiana Alves T, Ferreira-Camargo L, Croce M, Tanaka A, Buson F, Ribeiro P, Campos-Salazar A, Antonio E, Maizel A, Siratuti V, Costa C, Wlodarczyk S, de Souza Lima R, Mello F, Mayfield S, Carvalho J (2016) Chimeric spider silk production in microalgae: a modular bionanomaterial. Research Ideas and Outcomes 2: e9342. https://doi.org/10.3897/rio.2.e9342
Figure 1 - Project overview. Schematic representation of spider web structure from macro to nano scale. A representation of: enzybiotic protein from a bacteriophage; a spider silk protein with repetitive domains and N and C terminals; host expression system Chlamydomonas reinhardtii and a chimeric protein envisioned in this project; and the final product, a biopatch produced from recombinant silk proteins and chimeric proteins.
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