Catherine M. May Dr. Manfred Laubichler Arizona State ... · theoretical “tools,” which may...
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Developmental Evolution Darwin struggled to understand the source of variation and novelty. Today, molecular and developmental biology allow us to address these issues. Developmental Evolution is a mechanistic model that serves to bridge evolutionary and developmental processes. Developmental Evolution focuses on phenotypic evolution. Phenotypes are the product of ancient biological programs that follow Boolean circuit logic, built into Gene Regulatory Networks. The challenge is: “Moving beyond the catching proclamations of a “genetic toolkit” for development and the importance of “regulatory evolution” for phenotypic transformations, we are currently trying to develop a conceptual, theoretical and empirical framework that will allow us to integrate the populations-based models of microevolution with our understanding of the principles for development and their implications for macroevolution” (Laubichler 2005). Finding new ways to explore theoretical frameworks is a promising direction for developmental evolution. Multi-Dimensional Thinking New conceptual models need to be constructed to understand the multidimensional forces that interact in evolution. Constructing virtual “theory models” is a helpful way to explore the dimensions of developmental evolution, such as: hierarchy, complex causal relationships, different temporal scales, constraints on variation, and vertical integration. For example, Developmental Constraints are manifestations of how developmental processes can limit the phenotypic expressions of molecular variation. Modeling in 4D space, such limits can visually manipulated. This help to illustrate such concepts as: Phenotypic Latency: Evolution can occur on many hierarchical levels, not all of which are phenotypically visible. Molecular changes can accumulate over time, setting the stage for a phenotypically visible mutation event. Such dynamics of “punctuated equilibrium” can, for instance, be the results of gradual accumulation of transposable elements or a mutation in the molecular and developmental control systems that suppress TE activity. This research was funded in part by the Howard Hughes Medical Institute. Special acknowledgements to the Center for Biology and Society, Arizona State University. Cig-regulatory “signatures” may help identify changes in gene regulatory networks. The circuit logic can be modeled in 4D for experimental developmental biology (Autodesk Maya 2010). Catherine M. May Arizona State University Dr. Manfred Laubichler Sources Hamilton, A. Bechtel, W. (2007). Reduction, Unity and the Integration of Science: Biological, Behavioral and Social Sciences. Handbook of the Philosophy of Science: General Philosophy of Science – Focal Issues: 377-430. Laubichler, M. (2005). “The Changing Role of the Embryo in Evolutionary Thought: Roots of Evo Devo.” Science 309(5737): 1019-1020. Lippman et al. (2003) Distinct Mechanisms Determine Transposon Inheritance and Methylation via siRNA and Histone modification. PlOS Biology 1(3): 420-428. Mills, R. Bennett, A. Iskow, R. Luttig, C. Tsui, C. Pittard, S. Devine, S. (2007). “Recently Mobilized Transposons in the Human and Chimpanzee Genomes.” American Society of Human Genetics. 78(4): 671-679. Schoener, T. (2011). The Newest Synthesis: Understanding the Interplay of Evolutionary and Ecological Dynamics. Science 331(6016):426-429. Piriyapongsa et al. (2007). Origin and Evolution of Human MicroRNAs from Transposable Elements. Genetics Society of America 176(2007): 1332-1337. Xu et al. (2010). Partitioning of Histone H3-H4 Tetramers During DNA Replication Dependent Chromatin Assembly. Science 328 (94): 94-98 Zeh et al. (2009). Transposable Elements and an Epigenetic Basis for Punctuated Equilibria. Genes and Genome 31 (2009) 715-726. Novelty and Stability Virtual Synthetic Biology The Tentative Nature of Science What if these model are wrong? Great!! The hope is to create a theoretical medium, from which to collaborate and communicate ideas about developmental evolution. Virtual Synthetic Biology offers a forum to explore mistakes in “theory modeling. Playing the role of virtual designer requires solving evolutionary problems. In order to do this, the designer must innovate solutions or derive solutions from nature using virtual biomimicry. Participating in synthetic-based experimentation teaches powerful theoretical “tools,” which may transform science, as we know it. The proximate causes of evolution lie in the complex interactions of development in its genomic, epigenetic and environmental dimensions that generate phenotypic variation. Heritability and differential reproduction subsequently determine the fate of these variants over multiple generations. Standard evolutionary models have treated the generation of variation as a black box. Empirical and theoretical research in developmental evolution opens this black box. 4D modeling strategies are an important heuristic devise to investigate the consequences of integrating development into evolutionary models, especially with regard to explanations of evolutionary innovations and novelty. MAYA is a platform for 4D virtual modeling that allows exploratory research in virtual synthetic biology. MAYA is fully equipped with all the features necessary to create a fully functioning creature that is built on monomers (with embedded Boolean logic), connected by relationships and hierarchies, which can transform in time and space, according to a synthetic gene regulatory network. MAYA allows the user to immediately understand the complex levels of thinking required for navigating theoretical frameworks of developmental evolution. 4D Virtual Modeling broadens the base for mathematical modeling in biology. As MAYA is intuitive and easy to learn, it is also an important pedagogical tool that enables students to learn how to compose “theory models” therefore teaching them how to synthesize knowledge more effectively and with new levels of complexity. Entire networks may evolve, piercing through multiple hierarchical levels Molecules with complex chemical interactions can be modeled. A model of the mathematical structure, of the progressive integration, information systems feeding into another. Biological Information System Plug-in, across dimensions Bridge
Transcript of Catherine M. May Dr. Manfred Laubichler Arizona State ... · theoretical “tools,” which may...
Developmental EvolutionDarwin struggled to understand the source of variation and novelty. Today,molecular and developmental biology allow us to address these issues. Developmental Evolution is a mechanistic model that serves to bridgeevolutionary and developmental processes.
Developmental Evolution focuses on phenotypic evolution. Phenotypes are the product of ancient biological programs that follow Boolean circuit logic, built into Gene Regulatory Networks. The challenge is:
“Moving beyond the catching proclamations of a “genetic toolkit” for development and the importance of “regulatory evolution” for phenotypic transformations, we are currently trying to develop a conceptual, theoretical and empirical framework that will allow us to integrate the populations-based models of microevolution with our understanding of the principles for development and their implications for macroevolution” (Laubichler 2005).
Finding new ways to explore theoretical frameworks is a promising direction for developmental evolution.
Multi-Dimensional ThinkingNew conceptual models need to be constructed to understand the multidimensional forces that interact in evolution. Constructing virtual “theory models” is a helpful way to explore the dimensions of developmental evolution, such as: hierarchy, complex causal relationships, different temporal scales, constraints on variation, and vertical integration. For example, Developmental Constraints are manifestations of how developmental processes can limit the phenotypic expressions of molecular variation. Modeling in 4D space, such limits can visually manipulated. This help toillustrate such concepts as:
Phenotypic Latency: Evolution can occur on many hierarchical levels, not all of which are phenotypically visible. Molecular changes can accumulate over time, setting the stage for a phenotypically visible mutation event. Such dynamics of “punctuated equilibrium” can, for instance, be the results of gradual accumulation of transposable elements or a mutation in the molecular and developmental control systems that suppress TE activity.
This research was funded in part by the Howard Hughes Medical Institute. Special acknowledgements to the Center for Biology and Society, Arizona State University.
Cig-regulatory “signatures” may help identify changes in gene regulatory networks. The circuit logic can be modeled in 4D for experimental developmental biology (Autodesk Maya 2010).
Catherine M. May
Arizona State University
Dr. Manfred Laubichler
SourcesHamilton, A. Bechtel, W. (2007). Reduction, Unity and the Integration of Science: Biological, Behavioral and Social Sciences. Handbook of the Philosophy of Science: General Philosophy of Science – Focal Issues: 377-430.Laubichler, M. (2005). “The Changing Role of the Embryo in Evolutionary Thought: Roots of Evo Devo.” Science 309(5737): 1019-1020. Lippman et al. (2003) Distinct Mechanisms Determine Transposon Inheritance and Methylation via siRNA and Histone modification. PlOS Biology 1(3): 420-428.Mills, R. Bennett, A. Iskow, R. Luttig, C. Tsui, C. Pittard, S. Devine, S. (2007). “Recently Mobilized Transposons in the Human and Chimpanzee Genomes.” American Society of Human Genetics. 78(4): 671-679.Schoener, T. (2011). The Newest Synthesis: Understanding the Interplay of Evolutionary and Ecological Dynamics. Science 331(6016):426-429. Piriyapongsa et al. (2007). Origin and Evolution of Human MicroRNAs from Transposable Elements. Genetics Society of America 176(2007): 1332-1337.Xu et al. (2010). Partitioning of Histone H3-H4 Tetramers During DNA Replication Dependent Chromatin Assembly. Science 328 (94): 94-98Zeh et al. (2009). Transposable Elements and an Epigenetic Basis for Punctuated Equilibria. Genes and Genome 31 (2009) 715-726.
Novelty and Stability
Virtual Synthetic Biology
The Tentative Nature of Science What if these model are wrong? Great!! The hope is to create a theoretical medium, from which to collaborate and communicate ideas about
developmental evolution. Virtual Synthetic Biology offers a forum to explore mistakes in “theory modeling. Playing the role of virtual designer requires solving evolutionary problems. In order to do this, the designer must innovate solutions or derive solutions from nature using virtual biomimicry. Participating in synthetic-based experimentation teaches powerful theoretical “tools,” which may transform science, as we know it.
The proximate causes of evolution lie in the complex interactions of development in its genomic, epigenetic and environmental dimensions that generate phenotypic variation. Heritability and differential reproduction subsequently determine the fate of these variants over multiple generations. Standard evolutionary models have treated the generation of variation as a black box. Empirical and theoretical research in developmental evolution opens this black box. 4D modeling strategies are an important heuristic devise to investigate the consequences of integrating development into evolutionary models, especially with regard to explanations ofevolutionary innovations and novelty.
MAYA is a platform for 4D virtual modeling that allows exploratoryresearch in virtual synthetic biology. MAYA is fully equipped with all the features necessary to create a fully functioning creature that is built on monomers (with embedded Boolean logic), connected by relationships and hierarchies, which can transform in time and space, according to a synthetic gene regulatory network. MAYA allows the user to immediately understand the complex levels of thinking required for navigating theoretical frameworks of developmental evolution. 4D Virtual Modeling broadens the base for mathematical modeling in biology. As MAYA is intuitive and easy to learn, it is also an important pedagogical tool that enables students to learn how to compose “theory models” therefore teaching them how to synthesize knowledge more effectively and with new levels of complexity.
Entire networks may evolve, piercing through multiple hierarchical levels
Molecules with complex chemical interactions can be modeled.
A model of the mathematical structure, of the progressive
integration, information systems feeding into another.
Biological
Information
System Plug-in,
across
dimensions
Bridge
