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Facilitated variation: how evolution learns from past environments to generalize to new environments.

Parter M, Kashtan N, Alon U - PLoS Comput. Biol. (2008)

Bottom Line: We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals.Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism.The mechanisms for such enhanced generation of novelty (generalization) are analyzed, as is the way that organisms store information in their genomes about their past environments.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.

ABSTRACT
One of the striking features of evolution is the appearance of novel structures in organisms. Recently, Kirschner and Gerhart have integrated discoveries in evolution, genetics, and developmental biology to form a theory of facilitated variation (FV). The key observation is that organisms are designed such that random genetic changes are channeled in phenotypic directions that are potentially useful. An open question is how FV spontaneously emerges during evolution. Here, we address this by means of computer simulations of two well-studied model systems, logic circuits and RNA secondary structure. We find that evolution of FV is enhanced in environments that change from time to time in a systematic way: the varying environments are made of the same set of subgoals but in different combinations. We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals. Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism. The mechanisms for such enhanced generation of novelty (generalization) are analyzed, as is the way that organisms store information in their genomes about their past environments. Elements of facilitated variation theory, such as weak regulatory linkage, modularity, and reduced pleiotropy of mutations, evolve spontaneously under these conditions. Thus, environments that change in a systematic, modular fashion seem to promote facilitated variation and allow evolution to generalize to novel conditions.

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A small number of mutations evokes large useful phenotypic adaptation in systems showing facilitated variation.(A) Beaks of Darwin's finches. (B) RNA secondary structure evolved under modularly varying goals (MVG). (C) Logic circuit evolved under MVG of decomposable Boolean functions.
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pcbi-1000206-g001: A small number of mutations evokes large useful phenotypic adaptation in systems showing facilitated variation.(A) Beaks of Darwin's finches. (B) RNA secondary structure evolved under modularly varying goals (MVG). (C) Logic circuit evolved under MVG of decomposable Boolean functions.

Mentions: Facilitated variation (FV) is made possible by certain features of biological design. One of these is the existence of ‘weak regulatory linkage’ [5],[10],[18], where general and non-instructive signals can trigger large pre-prepared responses. For example, changes in growth hormone concentration at a localized position (limb bud in an embryo) can trigger large useful changes in the shape of the limb, driven by the conserved mechanisms for growth of bones, muscles, blood vessels, and nerves [19]. A good example is the ease of changing beak shapes with any of many possible mutations that affect the concentration of a single morphogenic factor [20] (Figure 1A). In weak regulatory linkage, the information about the output is pre-built into the regulated system without instruction from the regulator, which only selects between states. Such regulatory organization reduces the constraints for evolving new regulations and for generating complex potentially useful phenotypes.


Facilitated variation: how evolution learns from past environments to generalize to new environments.

Parter M, Kashtan N, Alon U - PLoS Comput. Biol. (2008)

A small number of mutations evokes large useful phenotypic adaptation in systems showing facilitated variation.(A) Beaks of Darwin's finches. (B) RNA secondary structure evolved under modularly varying goals (MVG). (C) Logic circuit evolved under MVG of decomposable Boolean functions.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2563028&req=5

pcbi-1000206-g001: A small number of mutations evokes large useful phenotypic adaptation in systems showing facilitated variation.(A) Beaks of Darwin's finches. (B) RNA secondary structure evolved under modularly varying goals (MVG). (C) Logic circuit evolved under MVG of decomposable Boolean functions.
Mentions: Facilitated variation (FV) is made possible by certain features of biological design. One of these is the existence of ‘weak regulatory linkage’ [5],[10],[18], where general and non-instructive signals can trigger large pre-prepared responses. For example, changes in growth hormone concentration at a localized position (limb bud in an embryo) can trigger large useful changes in the shape of the limb, driven by the conserved mechanisms for growth of bones, muscles, blood vessels, and nerves [19]. A good example is the ease of changing beak shapes with any of many possible mutations that affect the concentration of a single morphogenic factor [20] (Figure 1A). In weak regulatory linkage, the information about the output is pre-built into the regulated system without instruction from the regulator, which only selects between states. Such regulatory organization reduces the constraints for evolving new regulations and for generating complex potentially useful phenotypes.

Bottom Line: We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals.Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism.The mechanisms for such enhanced generation of novelty (generalization) are analyzed, as is the way that organisms store information in their genomes about their past environments.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.

ABSTRACT
One of the striking features of evolution is the appearance of novel structures in organisms. Recently, Kirschner and Gerhart have integrated discoveries in evolution, genetics, and developmental biology to form a theory of facilitated variation (FV). The key observation is that organisms are designed such that random genetic changes are channeled in phenotypic directions that are potentially useful. An open question is how FV spontaneously emerges during evolution. Here, we address this by means of computer simulations of two well-studied model systems, logic circuits and RNA secondary structure. We find that evolution of FV is enhanced in environments that change from time to time in a systematic way: the varying environments are made of the same set of subgoals but in different combinations. We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals. Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism. The mechanisms for such enhanced generation of novelty (generalization) are analyzed, as is the way that organisms store information in their genomes about their past environments. Elements of facilitated variation theory, such as weak regulatory linkage, modularity, and reduced pleiotropy of mutations, evolve spontaneously under these conditions. Thus, environments that change in a systematic, modular fashion seem to promote facilitated variation and allow evolution to generalize to novel conditions.

Show MeSH
Related in: MedlinePlus