understanding of innova/on in biological systems 2. Innova/ons in complex adap/ve systems (CAS) are governed by a set of isomorphic principles Two Case studies 1. Phenotypic evolu/on in biological systems 2. Innova/on in knowledge systems—the history of science
Revolu0on?— And, if so, what kind of Scien0ﬁc Revolu0on is it? (Kuhn read through the lenses of biology) => A revolu/on that has been in the making for a long /me => Accumula/on of transforma/ve changes in the genome of evolu/onary theory => Visible shiT in the body-‐plan/phenotype of evolu/onary theory emerging over the last 15+years
Mendel/Morgan & Popula0on Gene0cs Modern Synthesis Evo Devo Common Descent, Natural Selec/on, Gradualism, Open Ques)on of Inheritance Rules of transmission gene/cs, Physical Basis of Heredity, Genes as abstrac/ons (factors), sta/s/cal approaches, Open Ques/ons related to eﬀects of genes (other than sta/s/cal) Common explanatory framework: (adap/ve) dynamics of popula/ons are the primary explana/on for phenotypic evolu/on, developmental mechanisms are secondary (complexity of the genotype-‐phenotype map) Dynamics of Alleles connected to Adapta/on and Specia/on; Simple Genotype-‐Phenotype Map Gradualism Complex GT—PT Map, constraints, conserva/on, comparison “to complete the Modern Synthesis”
Cell Biology & Entwicklungsmechanik Kühn, Goldschmidt & Developmental Physiological Gene0cs Regulatory Evolu0on, GRNs & Synthe0c Experimental Evolu0on Common Descent, Natural Selec/on, Gradualism, Open Ques/on of Inheritance, Developmental Considera)ons about the Origin of Varia)on Role of the Nucleus in Development and Heredity, Experimental Approaches, Specula/ve Ideas about the Hereditary Material as a Structured System governing Development Common explanatory framework: Mechanis/c Explana/on of Development and Evolu/on as primary; Development as the Origin of Phenotypic Varia/on, Adap/ve Dynamics as secondary Physiological Gene Ac/on, Macroevolu/on, Gene Pathways
Developmental Evolu0on • Logical structure of “regula/on of gene ac/vity” • Based on a hierarchical and func/onal structure of the genome • Explicit recogni/on as a mechanism of phenotypic evolu/on • Oﬀered a construc/ve-‐mechanis/c alterna/ve theory of phenotypic evolu/on Open Ques/on: Speciﬁc Structure of the Network (-‐>experimental challenge)
=> “Muta/ons will get you there” => Problem: What is the Eﬀect of a Muta/on => Problem: What is the Structure of the Genotype-‐ Phenotype Map Part of the long quest to understand the origins of varia/on and the pagerns of phenotypic diversity (think body plans)
=> Genome is oTen equated with the complete DNA sequence However, => Genome is the en/rety of the hereditary informa/on of an organism => heredity involves a whole range of complex regulatory processes and mechanisms (development) => heredity therefore implies the unfolding of the gene/c informa/on in space and /me during development and evolu/on (1) the genome is thus a spa/al-‐temporal sequence of regulatory states (2) the genome anchors all other regulatory processes that aﬀect development and heredity
transform one organism in front or our eyes into another” Synthe'c Experimental Evolu'on “to mold arbitrary abnormali/es into true experiments…” • Requires both detailed knowledge AND a clear theore/cal framework of developmental evolu/on •Transforms research on phenotypic evolu/on => Compara/ve GRN research => emphasis on the mechanisms of (genomic) regulatory control => Experimental interven/on (re-‐ construc/ng GRNs) Erwin and Davidson, 2009
and Evolu/on is primary; Development as the Origin of Phenotypic Varia/on, Adap/ve Dynamics as secondary The combina)on of empirical data—from many recent empirical studies—and new computa)onal approaches allows us to fulﬁll the promise of developmental evolu)on as a mechanis)c science
1. Explore the future evolu)onary poten)al of a given genome based on the introduc/on of known gain of func/on elements 2. Reconstruct speciﬁc evolu)onary trajectories (=> compara/ve analysis of GRNs based on phylogene/c hypotheses) 3. Develop predic)ons of evolu)onary transi)ons (for experimental veriﬁca/on) 4. Further reﬁne the hierarchical expansion of the GRN perspec)ve to include the eﬀects of post-‐transcrip/onal and environmental/epigene/c regulatory systems Future Direc/ons Synthe0c in silico experimental evolu0on
of Science! Challenges! => The Shortcomings of the Biographical Model => The Need for Transparency => The Need for Novel Publica/on Forms Real! Problems! => The Increasing Orders of Magnitude Gap and the “Model Scien/st” Trap Questions! => How to Detect Novel/es (Inventions and Innovations)? => How to Detect Diﬀusion/Dissemina/on? => How to Detect the Eﬀects of Epistemologies, Technologies and the Social Structure of Science?
genera/ons) => detailed reconstruc/ons of phenotypic innova/ons => corresponding understanding of underlying gene/c changes => new phenotypes are the consequence of rearrangements of complex genomic networks
=> Complex Networks and Graphs => Inven/on and Innova/on => Hierarchical Expansion of Causal Networks, including Social Networks => Causal Networks Involving Many Diﬀerent Kinds of Elements => Contextual Meaning => Developmental Evolu/onary Dynamics The Common Theoretical Core also Enables the Use of Shared Methodologies!
1970 1980 “Modern Evolu/onary Synthesis” Anthony David Bradshaw (1926 - 2008)! “...man has only exercised inﬂuence on the vegeta/on for the last six thousand years, which gives little chance for the bulk of the vegeta/on to evolve in rela/on to these eﬀects.” 1948 “We are brought up to think that the /me scale of evolu/on is millennia. This may be true for the history of life but it is not true for the immediate process of evolution within species.” 1965 Experimental Taxonomy Genecology
on his ideas about scale. 2. The methods that he chose were inﬂuenced heavily by the network of researchers that he was a part of. 4. His ideas about scale were stabilized by a network of other concepts, which were themselves objects of debate. (e.g. “ecotype”) 3. That network of researchers was shaped enormously by the institutional context (agricultural development) in which he operated. Some Clues:
1970 1980 “Modern Evolu/onary Synthesis” “Experimental Taxonomy” / “Genecology” “Popula/on Biology” / “Evolu/onary Ecology” Changes in priori/es and paradigm for agricultural development. Debates about sampling methods, and rela/onships to concepts and interpreta/on. Lots of boundary-‐work surrounding “genecology” and “experimental taxonomy.” Ins/tu/onal disagreements about epistemology (e.g. Edinburgh vs. Birmingham) ?! Evolu/onary Popula/on Ecology From Whence? And How?
a complex interplay between internal and external condi/ons 2. The origin of varia/on (phenotypic of scien/ﬁc) is a consequence of changes to the (internal) complex regulatory networks that govern CAS 3. These isomorphic proper/es enable a transfer of both concepts and methods between diﬀerent ﬁelds concerned with innova/on 4. Developmental Evolu/on is a more adequate mechanis/c framework for understanding innova/on than simple popula/on dynamics
Wagner Jane Maienschein Robert Page Bert Hölldobler Jürgen Renn Doug Erwin Colin Allen Hans-‐Jörg Rheinberger Horst Bredekamp Olof Leimar Sander van der Leeuw Graduate Students: Erick Peirson Kate MacCord Guido Caniglia Yawen Zhou Lijing Jiang Nah Zhang Steve Elliog Julia Damerow Mark Uleg For Financial Support: Na/onal Science Founda/on Max Planck Society WissenschaTskolleg zu Berlin Arizona State University