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The Structure and Plasticity of the Phenotype as a Network Phenomenon. George Kampis Basler Chair Spring 2007, ETSU, Johnson City, TN. Gene environment interaction. Variability of expression (G) Plasticity of development (G x E) Variability of phenotype (E)
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The Structure and Plasticity of the Phenotype as aNetwork Phenomenon George Kampis Basler Chair Spring 2007, ETSU, Johnson City, TN
Gene environment interaction • Variability of expression (G) • Plasticity of development (G x E) • Variability of phenotype (E) • Complete model (as large as the world) • Here one segment, the organism
Historical/Autobiographical • Waddington, C.H., ed. 1972. Towards a Theoretical Biology,vols. 1-4. Edinburgh: Edinburgh University Press. • 1970s-1980s: Biological Systems Theory • S. Kauffman, R. Rosen, H. Pattee, B. Goodwin, S. Oyama, F.J. Varela… • Ridicule, e.g. • „deconstructivists of the gene” (Dennett 1995: DDI)
Kampis, G. 1991: Self-Modifying Systems: A New Framework for Dynamics,Information, andComplexity, Pergamon, Oxford-New York, pp 543+xix.
A down-to-Earth picture Genes • 1970-1980: 10-100 million genes • 1985: 1 million genes • Human Genome Project: 100,000 genes • 2001: 30,000 genes • 2003: 20,000 genes • Out of which Drosophila alone has 5,000 Gene products (PIM) • 1980-85: 1,000- x,000 E.Coli • 2003: 20,000 Drosophila • 2007: 35,000 (?) yeast
More on down-to-Earth complexity Brute force Relevant complexity time
One sentence metaphors… • Structure Genes • Structure and function Genes „plus” • Function Network regulation, pleiotropy, epistasis, etc.. • Numbers shrinking (increasing): proportions change • Transparency disappears Complexity of representation
Summary so far • We are not smarter, we just know more.
Some examples for networks • Drosophila PIM (2003) • Yeast PIM (2006)
Causality and explanation • Event view • If A then B (… if not A not B…) etc • Contributing causes • If A (and B and C) then B • Multiple causation • If A (or B or C) then B • Network causation • If (network ) then B
Network causation • Not event like (c.f. gravitation, symmetry) • Not individuated • Handles (on trait development): • „Classical” (vary nodes: percolation of effects) • „Nonclassical”: network transformations
The organism as a network 10 9 15 24 3 23 4 55 64 23 12 54 67 89 25 39 19 51 43 4 32 e.g. blue eye • (dyamic) phenotpye vector, PIM and developmental network (map) behind • Representation problem (mixed nodes, mixed edges) • Proteins, properties, …
A unified framework for.. • Gene expression • Development • Adaptation • Learning and environmental induction • Phenotype plasticity • …
Genes: your outside is in • Genes are „hidden” inside net topology • For phenotype to phenotype interactions • Most nodes are distant, „nontransparent” • The whole network is the target of selection • How does it permit/evoke different subnetworks w/ different properties interactor replicator
Network transformations • Growing network: stability, connectivity • Strong links vs weak links • Edge removal/addition w. phase transition (e.g. star/SF)
Connectivity/stability in ecosystems • Translates as a diversity/stability problem in ecology • May-Wigner theorem (1971): low connectivity stabilizes • McCann (2000): high diversity/generalist species stabilize • In cells: e.g. the role of chaperons • Hubs (not the genes ?!) • Topological „side” effects
NaNu in a new skin • Old question: how much responsibility is exported from G to E (e.g. default envir.) • New question: how much of the environment effects is internally controlled • Network props not modifiable are few and far between
Summary • Not, G, E, or GxE • But rather x, where x = network topology • A dominant and independent causal factor
Not considered in this talk • Modularity (e.g. HOX genes, segments) • Self organization (e.g. spatial perturbation) • Hierarchical levels (Cells, Organs, etc.) • Modes of inheritance and their roles • … and many other issues