Literature DB >> 28565291

PERSPECTIVE: COMPLEX ADAPTATIONS AND THE EVOLUTION OF EVOLVABILITY.

Günter P Wagner1, Lee Altenberg2.   

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. © 1996 The Society for the Study of Evolution.

Keywords:  Adaptation; evolution of development; evolutionary computation; genetic representations; modularity; pleiotropy; quantitative genetics

Year:  1996        PMID: 28565291     DOI: 10.1111/j.1558-5646.1996.tb02339.x

Source DB:  PubMed          Journal:  Evolution        ISSN: 0014-3820            Impact factor:   3.694


  194 in total

1.  On the evolution of primitive genetic codes.

Authors:  Günter Weberndorfer; Ivo L Hofacker; Peter F Stadler
Journal:  Orig Life Evol Biosph       Date:  2003-10       Impact factor: 1.950

2.  Modularity, individuality, and evo-devo in butterfly wings.

Authors:  Patricia Beldade; Kees Koops; Paul M Brakefield
Journal:  Proc Natl Acad Sci U S A       Date:  2002-10-21       Impact factor: 11.205

3.  Evolvability is a selectable trait.

Authors:  David J Earl; Michael W Deem
Journal:  Proc Natl Acad Sci U S A       Date:  2004-08-02       Impact factor: 11.205

4.  Fitness variation across subtle environmental perturbations reveals local modularity and global pleiotropy of adaptation.

Authors:  Grant Kinsler; Kerry Geiler-Samerotte; Dmitri A Petrov
Journal:  Elife       Date:  2020-12-02       Impact factor: 8.140

5.  The impact of artificial selection on morphological integration in the appendicular skeleton of domestic horses.

Authors:  Pauline Hanot; Anthony Herrel; Claude Guintard; Raphaël Cornette
Journal:  J Anat       Date:  2018-01-08       Impact factor: 2.610

6.  The origin of subfunctions and modular gene regulation.

Authors:  Allan Force; William A Cresko; F Bryan Pickett; Steven R Proulx; Chris Amemiya; Michael Lynch
Journal:  Genetics       Date:  2005-03-21       Impact factor: 4.562

7.  Modulation of base-specific mutation and recombination rates enables functional adaptation within the context of the genetic code.

Authors:  Taison Tan; Leonard D Bogarad; Michael W Deem
Journal:  J Mol Evol       Date:  2004-09       Impact factor: 2.395

8.  Evolution can favor antagonistic epistasis.

Authors:  Michael M Desai; Daniel Weissman; Marcus W Feldman
Journal:  Genetics       Date:  2007-08-24       Impact factor: 4.562

9.  Additive, epistatic, and environmental effects through the lens of expression variability QTL in a twin cohort.

Authors:  Gang Wang; Ence Yang; Candice L Brinkmeyer-Langford; James J Cai
Journal:  Genetics       Date:  2013-12-02       Impact factor: 4.562

10.  Phenotypic integration and modularity drives skull shape divergence in the Arctic fox (Vulpes lagopus) from the Commander Islands.

Authors:  Alberto Martín-Serra; Olga Nanova; Ceferino Varón-González; Germán Ortega; Borja Figueirido
Journal:  Biol Lett       Date:  2019-09-25       Impact factor: 3.703

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