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Part II
EPISTEMOLOGICAL APPROACHES TO BIOCOMPLEXITY ASSESSMENT

The sphere of biological phenomena interpretable in the light of evolution is vast, so perhaps it is not surprising that researchers from many different scientific backgrounds and orientations have weighed in on how best to approach the study of complex adaptations. The chapters in Part II will illustrate some of this diversity.

In Chapter 2, Robert Hazen, Patrick Griffin, James Carothers, and Jack Szostak raise two important related questions: What actually is meant by biological “complexity” and how might complexity be quantified? The authors suggest that a hallmark of any complex system (physical or biological) is its potential to perform a quantifiable operation. Starting with that premise, they formally define a metric—functional information—that basically describes the fraction of all possible configurations of the system that possess a specified degree of function. Although this metric may be difficult to apply in the real world (because it requires knowledge of all possible configurations and the degree of function of each), it nonetheless may have heuristic merit for studying the properties of complex systems. The authors illustrate this approach using their virtual world of computer programs that self-replicate, mutate, and adapt by natural selection.

In 1975, Mary-Claire King and Allan Wilson popularized an earlier idea by Roy Britten and Eric Davidson (1969) that evolutionary changes in gene regulation—rather than DNA sequence mutations in protein-coding exons per se—were largely responsible for phenotypic evolution and the emergence of complex adaptations. This sentiment has since become mainstream, as reflected in several papers in the current volume.



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Part II EPISTEMOLOGICAL APPROACHES TO BIOCOMPLEXITY ASSESSMENT T he sphere of biological phenomena interpretable in the light of evolution is vast, so perhaps it is not surprising that researchers from many different scientific backgrounds and orientations have weighed in on how best to approach the study of complex adaptations. The chapters in Part ii will illustrate some of this diversity. in Chapter 2, robert hazen, Patrick Griffin, James Carothers, and Jack szostak raise two important related questions: What actually is meant by biological “complexity” and how might complexity be quantified? The authors suggest that a hallmark of any complex system (physical or bio- logical) is its potential to perform a quantifiable operation. starting with that premise, they formally define a metric—functional information—that basically describes the fraction of all possible configurations of the system that possess a specified degree of function. Although this metric may be difficult to apply in the real world (because it requires knowledge of all possible configurations and the degree of function of each), it nonetheless may have heuristic merit for studying the properties of complex systems. The authors illustrate this approach using their virtual world of computer programs that self-replicate, mutate, and adapt by natural selection. in 1975, Mary-Claire King and Allan Wilson popularized an earlier idea by roy Britten and eric Davidson (1969) that evolutionary changes in gene regulation—rather than DnA sequence mutations in protein- coding exons per se—were largely responsible for phenotypic evolution and the emergence of complex adaptations. This sentiment has since become mainstream, as reflected in several papers in the current volume. 2

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2 / Part II in Chapter 3, John Gerhart and Marc Kirschner accept the notion that regu- latory changes are of central importance, and indeed they argue that most key phenotypic evolution over the past 600 million years has resulted from altered usage patterns in a large set of otherwise conserved core genetic components that direct organismal development and physiology. in the “theory of facilitated variation” by Gerhart and Kirschner, several regula - tory features of the genome collude to foster more phenotypic evolution with less genetic change than would otherwise have been possible. in Chapter 4, Adam Wilkins examines the converse of evolutionary plasticity: phenotypic constraint. it has long been evident that phylogenetic legacies and developmental contingencies restrict (albeit to a debatable degree) the suite of evolutionary pathways potentially available to any species. Wilkins proposes that in addition to these conventionally recog - nized inhibitors of phenotypic evolution, inherent constraints also oper- ate at the levels of interacting genes and complex genetic networks. if molecular biologists can illuminate the genetic biases that constrain as well as promote the evolution of particular phenotypes, it might become possible, Wilkins argues, to specify the relative probabilities of alternative evolutionary trajectories (at least over the short term) for particular lin - eages. Traditionally, this kind of predictability about evolutionary futures had been regarded as essentially impossible. in the final chapter of Part ii, Michael lynch reminds us that mecha- nistic explanations of phenotypic evolution that emerge from the fields of developmental biology and molecular genetics cannot violate the funda - mental dynamics of the evolutionary process as elucidated by a century of work in theoretical population genetics. regardless of which genes underlie complex or other phenotypes, their microevolutionary dynamics remain governed by the forces of mutation, gene flow, natural selection, recombination, and random genetic drift. The point, however, is not to claim priority for one discipline over another, but rather to emphasize that any evolutionary model that disregards population genetic reality does so at its peril. To illustrate his argument, lynch examines the ineluctable consequences of genetic drift, especially in small populations, and he highlights a wide assortment of genic and genomic phenomena that make sense only after accounting for variation among taxa in the relative power of nonadaptive evolutionary forces.