The case of Eric Davidsons Gene Regulatory Networks, from idea to revolutionary science

Extended Evolution:Regulatory Networks and Niche Construction in Development, Evolution and HistoryManfred D. LaubichlerArizona State UniversitySanta Fe InstituteMarine Biological LaboratoryMax Planck Institute for the History of Science

1Johns Challenge for Future Work:

How to fill in remaining conceptual gaps between autocatalysis and multiple networks?

Or to quote Jorge Wagensberg:

Between an amoeba and man, something must have happened!!!Reflections on The Emergence of Organizations and Markets from the Perspective of Evolutionary Theory

1. A productive case of transdisciplinary exchange2. Needs to based on current (and future) evolutionary theory, not an outdated versionMain Challenges

1. For Evolutionary Theory: Integrating regulatory network and niche construction perspectives; Integrating mechanisms related to the origin of variation (novelty) with evolutionary dynamics; developing an adequate conception of history; developing a unified conception for molecular to cultural and knowledge evolution

2. For P&P: Incorporating developmental and evolutionary conceptions; Gaining a better understanding of the relationships and dynamics between networks and contextsThe standard historical narrative of Evolutionary BiologyDarwinMendel/Morgan &Population GeneticsModern SynthesisEvo DevoCommon Descent, Natural Selection, Gradualism, Open Question of Inheritance Rules of transmission genetics, Physical Basis of Heredity,Genes as abstractions (factors), statistical approaches, OpenQuestions related to effects of genes (other than statistical)

Common explanatory framework: (adaptive) dynamics of populations are the primaryexplanation for phenotypic evolution, developmental mechanisms aresecondary (complexity of the genotype-phenotype map)

Dynamics of Alleles connected toAdaptation and Speciation; Simple Genotype-Phenotype MapGradualismComplex GTPT Map, constraints, conservation, comparisonto complete the Modern SynthesisAn alternative history of Developmental EvolutionDarwinBoveri, Cell Biology &EntwicklungsmechanikKhn, Goldschmidt &Developmental PhysiologicalGeneticsRegulatory Evolution,GRNs & SyntheticExperimental EvolutionCommon Descent, Natural Selection, Gradualism, Open Question of Inheritance,Developmental Considerations about the Origin of Variation Role of the Nucleus in Development and Heredity, Experimental Approaches, Speculative Ideas about theHereditary Material as a Structured System governing Development

Common explanatory framework: Mechanistic Explanation of Development and Evolution as primary; Development as the Origin of Phenotypic Variation, Adaptive Dynamics as secondary

Physiological Gene Action, Macroevolution, GenePathways

The Britten-Davidson Model (1969)A conceptual/logical Framework for Developmental Evolution Logical structure of regulation of gene activity Based on a hierarchical and functional structure of the genome Explicit recognition as a mechanism of phenotypic evolution Offered a constructive-mechanistic alternative theory of phenotypic evolution

Open Question: Specific Structure of the Network (->experimental challenge)

Underlying Assumptions in Evolutionary Theory about Phenotypic Evolution:=> Mutations will get you there=> Problem: What is the Effect of a Mutation=> Problem: What is the Structure of the Genotype-Phenotype Map

Part of the long quest to understand the origins of variation and the patterns of phenotypic diversity (think body plans)ProblemBoth sides in the current debate between the primacy of regulatory or standard adaptive evolution have ample empirical evidence

=> This is a debate about epistemology, not data (but data help)

Measuring Pleiotropy: Mouse Skeletal Characters

Measuring Pleiotropy: Stickleback Skeletal Characters

The data on genetic pleiotropysuggest

which, together with over three decades of molecular developmental biology,lead to =>

Eric Davidsons Concept of Gene Regulatory Networks

Gene Regulatory Networks as the Foundation for Developmental EvolutionProcess Diagram (from Peter and Davidson 2009)The dynamic n-dimensional regulatory genomeTraditional definition:=> Genome is often equated with the complete DNA sequence

However,=> Genome is the entirety of the hereditary information of an organism=> heredity involves a whole range of complex regulatory processes and mechanisms (development)=> heredity therefore implies the unfolding of the genetic information in space and time during development and evolution(1) the regulatory genome is thus a spatial-temporal sequence of regulatory states(2) the regulatory genome anchors all other regulatory processes that affect development, heredity and therefore evolution

Analyzing and Expanding Gene Regulatory Networks

Sub-circuit Repertoire of Developmental GRNs

Logic Reconstruction of a Developmental GRN

The Developmental Evolution of the Superorganism18

A Hierarchical Expansion of the GRN FrameworkDevelopmental Evolution in Social Insects: Regulatory Networks from Genes to Societies

More than a Century later Boveri realizedto transform one organism in front or our eyes into anotherSynthetic Experimental Evolution

to mold arbitrary abnormalities intotrue experiments

Requires both detailed knowledge AND a clear theoretical framework of developmental evolution

Transforms research on phenotypic evolution=> Comparative GRN research=> emphasis on the mechanisms of (genomic) regulatory control=> Experimental intervention (re-constructing GRNs)Erwin and Davidson, 2009

Novel Computational Possibilities

Peter et al., 2012

Peter et al., 2012Further development of computational GRN models for multiple systems to:

1. Explore the future evolutionary potential of a given genome based on the introduction of known gain of function elements

2. Reconstruct specific evolutionary trajectories (=> comparative analysis of GRNs based on phylogenetic hypotheses)

3. Develop predictions of evolutionary transitions (for experimental verification)

4. Further refine the hierarchical expansion of the GRN perspective to include the effects of post-transcriptional and environmental/epigenetic regulatory systems

Future DirectionsSynthetic in silico experimental evolution

Co-evolutionary Dynamics of Biology, Material Culture and Knowledge: The Neolithic Revolution

Jared Diamond, et al. Science 300, 597 (2003)Spread of the neolithic revolutionComputational History of Science uses a variety of computational tools and techniques to aid historical and philosophical study of the life sciences. The rapidly declining cost of computing power and the increasing availability of both primary and secondary materials in digital formats makes it possible to translate historical and philosophical questions into computationally tractable ones. Computational approaches can range from simple term-frequency analysis of large scientific corpora, to complex reconstructions of the social, material, and conceptual fabrics of scientific fields using both automated and supervised procedures.

1.2.3.Historical settings & relationshipsTopology of research literatureConceptual relationshipsChange Over Time1950194019301920196019701980e.g. innovation at plant breeding stations (time/resources, interdisciplinarity)

e.g. Birmingham - Edinburgh controversy

Computational Analysis of Eric Davidsons Investigative Pathway

Cytoscape616 unique nodes.1591 edges.~30% of stage 1 datasethttps://www.youtube.com/embed/Zab15Jga8roTextcombine many different relationship typesdraw in metadata (e.g. coauthorship) from data repository

Genecology ProjectCollaborations among ecological geneticists and evolutionary ecologists surrounding key participants in a controversy over methods for modeling adaptive phenotypic plasticity during the early 1990s. Generated using the Vogon text-annotation and network-building tool. Each relationship is rooted in a precise location in a text stored in the Digital HPS Community Repository. Part of the doctoral dissertation research project, "Ecology, Evolution, and Development: The Conceptual Foundations of Adaptive Phenotypic Plasticity in Evolutionary Ecology." (http://devo-evo.lab.asu.edu/phenotypic-plasticity)

Question: How can we asses the influence of a Research Program?

Closeness Centrality

Conclusions1. Innovation/Inventions in CAS are the product of a complex interplay between internal and external conditions (regulatory networks and niche construction)

2. The origin of variation (phenotypic of scientific) is a consequence of changes to the (extended) complex regulatory networks that govern CAS

3. These isomorphic properties enable a transfer of both concepts and methods between different fields concerned with innovation

4. Extended Evolution is a more adequate mechanistic framework for understanding innovation/invention than simple population dynamicsAcknowledgmentsFor intellectual discussions/collaborations:Eric DavidsonGnter WagnerJane MaienscheinRobert PageBert HlldoblerJrgen RennDoug ErwinColin AllenHans-Jrg RheinbergerHorst BredekampOlof LeimarSander van der Leeuw

Graduate Students:Erick PeirsonKate MacCordGuido CanigliaYawen ZhouLijing JiangNah ZhangSteve ElliottJulia DamerowMark UlettFor Financial Support:

National Science FoundationStiftung MercatorSmart Family FoundationMax Planck SocietyWissenschaftskolleg zu BerlinArizona State University