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PERSPECTIVE: COMPLEX ADAPTATIONS AND THE EVOLUTION OF EVOLVABILITY
Abstract
The problem of complex adaptations is studied in two largely disconnected research traditions: evolutionary biology and evolutionary computer science. This paper summarizes the results from both areas and compares their implications. In evolutionary computer science it was found that the Darwinian process of mutation, recombination and selection is not universally effective in improving complex systems like computer programs or chip designs. For adaptation to occur, these systems must possess "evolvability," i.e., the ability of random variations to sometimes produce improvement. It was found that evolvability critically depends on the way genetic variation maps onto phenotypic variation, an issue known as the representation problem. The genotype-phenotype map determines the variability of characters, which is the propensity to vary. Variability needs to be distinguished from variations, which are the actually realized differences between individuals. The genotype-phenotype map is the common theme underlying such varied biological phenomena as genetic canalization, developmental constraints, biological versatility, developmental dissociability, and morphological integration. For evolutionary biology the representation problem has important implications: how is it that extant species acquired a genotype-phenotype map which allows improvement by mutation and selection? Is the genotype-phenotype map able to change in evolution? What are the selective forces, if any, that shape the genotype-phenotype map? We propose that the genotype-phenotype map can evolve by two main routes: epistatic mutations, or the creation of new genes. A common result for organismic design is modularity. By modularity we mean a genotype-phenotype map in which there are few pleiotropic effects among characters serving different functions, with pleiotropic effects falling mainly among characters that are part of a single functional complex. Such a design is expected to improve evolvability by limiting the interference between the adaptation of different functions. Several population genetic models are reviewed that are intended to explain the evolutionary origin of a modular design. While our current knowledge is insufficient to assess the plausibility of these models, they form the beginning of a framework for understanding the evolution of the genotype-phenotype map.
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CANALIZATION OF DEVELOPMENT AND THE INHERITANCE OF ACQUIRED CHARACTERS
WADDINGTON, C. H. (1942) · Nature · doi:10.1038/150563a0 · Cited by 3,255
EVOLUTIONARY QUANTITATIVE GENETICS: HOW LITTLE DO WE KNOW?
Barton, N. H., & Turelli, M. (1989) · Annual Review of Genetics · doi:10.1146/annurev.ge.23.120189.002005 · Cited by 686 · cited 1×
“Quantitative phenotypic variation is measured by the phenotypic, genetic and environmental variance or any other statistical measure of dispersion (Falconer 1981; Barton and Turelli 1989).”
Research works printed but not linked: 90
- Akam, 1988, Homeotic genes and the control of segment diversity, Development, 104, 123, 10.1242/dev.104.Supplement.123 · DOI
- Alberch, 1983, Morphological variation in the neotropical salamander genus Bolitoglossa, Evolution, 37, 906, 10.1111/j.1558-5646.1983.tb05620.x · DOI
- Altenberg, 1985, Knowledge representation in the genome: new genes, exons, and pleiotropy, Genetics, 110, s41
- Altenberg, 1994, The evolution of evolvability in genetic programming, 47
- Altenberg, 1995a, The Schema theorem and the Price's theorem, 23
- Altenberg, 1995b, Genome growth and the evolution of the genotype-phenotype map, 205, 10.1007/3-540-59046-3_11 · DOI
- Altenberg, 1987, Selection, generalized transmission, and the evolution of modifier genes. I. The reduction principle, Genetics, 117, 559, 10.1093/genetics/117.3.559 · DOI
- Banzhaf, 1994, Genotype-phenotype mapping and neutral variation-A case study in genetic programming, 322, 10.1007/3-540-58484-6_276 · DOI · Paper page
- Bonner, 1988, The evolution of complexity
- Bossert, 1967, Mathematical optimization: Are there abstract limits on natural selection?, 35
- Bremermann, 1966, Global properties of evolution processes, 3
- Bulmer, 1980, The mathematical theory of quantitative genetics
- Bürger, 1994, On the distribution of the mean and variance of a quantitative trait under mutation-selection-drift balance, Genetics, 138, 901, 10.1093/genetics/138.3.901 · DOI
- Bürger, 1989, How much heritable variation can be maintained in finite populations by mutation-selection balance?, Evolution, 43, 1748, 10.1111/j.1558-5646.1989.tb02624.x · DOI
- Buss, 1987, The evolution of individuality
- Cheverud, 1995, Epistasis and its contribution to genetic variance components, Genetics, 130, 1455, 10.1093/genetics/139.3.1455 · DOI · Paper page
- Clayton, 1955, Mutation and quantitative variation, Am. Nat., 89, 151, 10.1086/281874 · DOI
- Davidor, 1991, Epistasis variance: A viewpoint on GA-hardness, 1, 23
- Eden, 1967, Inadequacies of neo-darwinian evolution as a scientific theory, 5
- Endler, 1986, Natural selection in the wild
- Eshel, 1973, Clone-selection and optimal rates of mutation, J. App. Prob., 10, 728, 10.1017/S0021900200095930 · doi:10.1017/s0021900200095930
- Falconer, 1981, Introduction to quantitative genetics
- Fogel, 1966, Artificial intelligence through simulated evolution
- Fontana, 1994, The arrival of the fittest, Bull. Math. Biol., 56, 1
- Forrest, 1993, Towards a stronger building-block hypothesis: Effects of relative building-block fitness on GA performance, 109
- Foster, 1992, Mechanisms of directed mutation, Genetics, 131, 783, 10.1093/genetics/131.4.783 · DOI · Paper page
- Frazzetta, 1975, Complex adaptations in evolving populations
- Friedberg, 1959, A learning machine, IBM J. Res. Dev., Part II, 3, 183
- Gimelfarb, 1989, Genotypic variation for a quantitative character maintained under stabilizing selection without mutation: Epistasis, Genetics, 123, 217, 10.1093/genetics/123.1.217 · doi:10.1093/genetics/123.1.217
- Goldberg, 1989, Genetic algorithms in search, optimization and machine learning
- Goodman, 1955, Fact, fiction, forecast
- Gould, 1977, Ontogeny and phylogeny
- Halder, 1995, Induction of ectopic eyes by targeted expression of the eyeless gene in Drosophila, Science, 267, 1788, 10.1126/science.7892602 · DOI · Paper page
- Holland, 1992, Adaptation in natural and artificial systems, 10.7551/mitpress/1090.001.0001 · DOI · Paper page
- Jones, 1995, Evolutionary algorithms, fitness landscapes and search
- Jones , T. S. Forrest 1995 Fitness distance correlation as a measure of problem difficulty for genetic algorithms 184 192 in L. J. Eshelman Proceedings of the sixth international conference on genetic algorithms
- Kauffman, 1989, Adaptation on rugged fintess landscapes, 1, 527
- Kimura, 1965, A stochastic model concerning the maintenance of genetic variability in quantitative characters, Proc. Nat. Acad. Sci. USA, 54, 731, 10.1073/pnas.54.3.731 · DOI · Paper page
- Kingman, 1978, A simple model for the balance between selection and mutation, J. App. Prob., 15, 1, 10.1017/S0021900200105534 · doi:10.1017/s0021900200105534 · Paper page
- Koza, 1992, Genetic programming: On the programming of computers by means of natural selection
- Lazebnyi, 1991, Fitness of experimental populations of Drosophila melanogaster under directional and stabilizing selection, Genetika, 27, 1726
- Lande, 1975, The genetic covariance between characters maintained by pleiotropic mutation, Genetics, 94, 203, 10.1093/genetics/94.1.203 · DOI · Paper page
- Lehmann, 1988, Aspects of the problem of knowledge representation, Siemens Forsch. Entwicklungsber., 17, 45
- Lerner, 1968, Heredity, Evolution, and Society
- Levinton, 1988, Genetics, paleontology and macroevolution
- MacKay, 1992, Polygenic mutation in Drosophila melanogaster: Stimates from divergence among inbred strains, Evolution, 46, 300, 10.1111/j.1558-5646.1992.tb02039.x · DOI
- Maynard Smith, 1985, Developmental constraints and evolution, Quart. Rev. Biol., 60, 265, 10.1086/414425 · DOI · Paper page
- Mühlenbein, 1995, Analysis of selection, mutation and recombination in genetic algorithms, 142
- Müller, 1991, Novelty in evolution: Restructuring the concept, Annu. Rev. Ecol. Syst., 22, 229, 10.1146/annurev.es.22.110191.001305 · doi:10.1146/annurev.es.22.110191.001305 · Paper page
- Needham, 1933, On the dissociability of the fundamental processes in ontogenesis, Biol. Rev., 8, 180, 10.1111/j.1469-185X.1933.tb01153.x · DOI
- Price, 1970, Selection and covariance, Nature, 227, 520, 10.1038/227520a0 · DOI · Paper page
- Raff , R. A. The shape of life Univ. of Chicago Press Chicago, IL
- Raff, 1983, Embryos, genes, and evolution
- Ray, 1992, An approach to the synthesis of life, 371
- Rechenberg, 1973, Evolutionsstrategie
- Rechenberg, 1994, Evolutionsstrategie '94
- Rendel, 1967, Canalization and gene control
- Rich, 1991, Artificial intelligence
- Riedl, 1975, Die Ordnung des Lebendigen
- Rienesl, 1992, Constancy and change of basipodial variation patterns: A comparative study of crested and marbled newts-Triturus cristatus, Triturus marmoratus-and their natural hybrids, J. Evol. Biol., 5, 307, 10.1046/j.1420-9101.1992.5020307.x · doi:10.1046/j.1420-9101.1992.5020307.x
- Scharloo, 1987, Constraints in selection response, 125, 10.1007/978-3-642-72770-2_8 · DOI
- Scharloo, 1988, Selection on morphological patterns, 230, 10.1007/978-3-642-73069-6_25 · doi:10.1007/978-3-642-73069-6_25
- Scharloo, 1991, Canalization: Genetic and developmental aspects, Annu. Rev. Ecol. Syst., 22, 65, 10.1146/annurev.es.22.110191.000433 · DOI
- Schmalhausen, 1949, Factors of evolution
- Schwefel, 1981, Numerical optimization of computer models
- Schwenk, 1995, A utilitarian approach to evolutionary constraint, Zoology, 98, 251
- Simon, 1965, The architecture of complexity, Gen. Syst., 10, 63
- Stadler, 1992, Correlation in landscapes of combinatorial optimization problems, Europhys. Lett., 20, 479, 10.1209/0295-5075/20/6/001 · doi:10.1209/0295-5075/20/6/001
- Stearns, 1993, The evolutionary links between fixed and variable traits, Acta Paleontol. Pol., 38, 1
- Stearns, 1994, Fitness sensitivity and the canalization of life history traits, Evolution, 48, 1438, 10.2307/2410238 · DOI
- Stebbins, 1974, Flowering plants, 10.4159/harvard.9780674864856 · DOI · Paper page
- Turelli, 1988, Phenotypic evolution, constant covariances, and the maintenance of additive variance, Evolution, 42, 1342, 10.2307/2409017 · DOI
- Vermeij, 1970, Adaptive versatility and skeleton construction, Am. Nat., 104, 253, 10.1086/282659 · doi:10.1086/282659
- Vermeij, 1971, Gastropod evolution and morphological diversity in relation to shell geometry, J. Zool., 163, 15, 10.1111/j.1469-7998.1971.tb04522.x · doi:10.1111/j.1469-7998.1971.tb04522.x
- Vermeij, 1973, Biological versatility and earth history, Proc. Nat. Acad. Sci. USA, 70, 1936, 10.1073/pnas.70.7.1936 · DOI
- Vermeij, 1974, Adaptation, versatility and evolution, Syst. Zool., 22, 466, 10.2307/2412953 · DOI
- Waddington, 1957, The strategy of the genes
- Wagner, 1994, Epistasis can facilitate the evolution of reproductive isolation by peak shifts: A two-locus two-allele model, Genetics, 138, 533, 10.1093/genetics/138.2.533 · DOI
- Wagner, 1981, Feedback selection and the evolution of modifiers, Acta Biotheor., 30, 79, 10.1007/BF00047674 · DOI
- Wagner, 1989a, Multivariate mutation-selection balance with constrained pleiotropic effects, Genetics, 122, 223, 10.1093/genetics/122.1.223 · DOI
- Wagner, 1989b, The origin of morphological characters and the biological basis of homology, Evolution, 43, 1157, 10.1111/j.1558-5646.1989.tb02566.x · DOI · Paper page
- Wagner, 1989c, The biological homology concept, Annu. Rev. Ecol. Syst., 20, 51, 10.1146/annurev.es.20.110189.000411 · doi:10.1146/annurev.es.20.110189.000411 · Paper page
- Wagner, 1995, The biological role of homologues: A building block hypothesis, Neues Jahrb. Geol. Paläontol. Abh., 19, 279, 10.1127/njgpa/195/1995/279 · DOI
- Wagner, 1996, Homologues, natural kinds and the evolution of modularity, Am. Zool., 36, 36, 10.1093/icb/36.1.36 · DOI · Paper page
- Wagner, 1985, On the evolution of dominance modifiers II: A non-epuilibrium approach to the evolution of genetic systems, J. Theoret. Biol., 113, 475, 10.1016/S0022-5193(85)80034-5 · DOI
- Weinberger, 1991, Local Properties of Kauffman's N-k model, a tuneably rugged energy landscape, Physic. Rev. A, 44, 6399, 10.1103/PhysRevA.44.6399 · DOI · Paper page
- Weiss, 1990, Duplication with variation: Metameric logic in evolution from genes to morphology, Yearb. Phys. Anthropol., 33, 1, 10.1002/ajpa.1330330503 · DOI
- Winston, 1992, Artificial Intelligence
- Wright, 1964, Stochastic processes in evolution, 199
- Wright, 1968, Evolution and the genetic of populations, 1
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Metadata
- Authors
- Wagner, G. P., & Altenberg, L.
- Venue
- Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 1996-06
- Volume
- 50
- Issue
- 3
- Pages
- 967-976
- ISSN
- 0014-3820 (ISSN-L)
- OpenAlex
- W2022730625
- Cited by
- 1,914
- References
- 2
- FWCI
- 7.42
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- doi.wiley.com/10.1002/tdm_license_1 (tdm)
- onlinelibrary.wiley.com/termsAndConditions (vor, 7669 d)
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