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Cracking open the blackbox of genotype–phenotype map: crossing the explanatory gap between micro- and macroevolution.

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Title: Cracking open the blackbox of genotype–phenotype map: crossing the explanatory gap between micro- and macroevolution.
Authors: Pavlicev, Mihaela1 (AUTHOR)
Source: Evolution. Feb2026, Vol. 80 Issue 2, p301-311. 11p.
Subjects: Microevolution, Macroevolution, Population genetics, Natural selection, Morphogenesis, Phenotypic plasticity
Abstract: A key insight of evolutionary genetics is that the evolvability of a population depends crucially on the amount and distribution of heritable phenotypic variation across traits. Because this insight focuses on segregating variation, the traits that do not vary among individuals but differ among higher taxa are ignored. Slowly evolving traits, like body plan organization and homologs, are nevertheless essential because they set the phenotypic boundary conditions within which variation segregates. Therefore, understanding long-term evolutionary change requires understanding the principles that control variation in varying AND conserved traits, in addition to understanding how drift and selection influence segregating population variation. In this perspective, I propose that this understanding is attainable if we acknowledge that different processes, which map sequence variation to phenotypic variation, have different capacities to produce variation and evolve. I suggest decomposing the GP map according to types of processes with different variational properties. For vertebrates, these are morphogenesis, growth, and maintenance. This perspective allows us to focus on how these processes interact under the influence of natural selection and delineate the conditions leading to different patterns of evolutionary change. [ABSTRACT FROM AUTHOR]
Copyright of Evolution is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: Cracking open the blackbox of genotype–phenotype map: crossing the explanatory gap between micro- and macroevolution.
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  Data: <searchLink fieldCode="AR" term="%22Pavlicev%2C+Mihaela%22">Pavlicev, Mihaela</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Evolution%22">Evolution</searchLink>. Feb2026, Vol. 80 Issue 2, p301-311. 11p.
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  Data: <searchLink fieldCode="DE" term="%22Microevolution%22">Microevolution</searchLink><br /><searchLink fieldCode="DE" term="%22Macroevolution%22">Macroevolution</searchLink><br /><searchLink fieldCode="DE" term="%22Population+genetics%22">Population genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+selection%22">Natural selection</searchLink><br /><searchLink fieldCode="DE" term="%22Morphogenesis%22">Morphogenesis</searchLink><br /><searchLink fieldCode="DE" term="%22Phenotypic+plasticity%22">Phenotypic plasticity</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: A key insight of evolutionary genetics is that the evolvability of a population depends crucially on the amount and distribution of heritable phenotypic variation across traits. Because this insight focuses on segregating variation, the traits that do not vary among individuals but differ among higher taxa are ignored. Slowly evolving traits, like body plan organization and homologs, are nevertheless essential because they set the phenotypic boundary conditions within which variation segregates. Therefore, understanding long-term evolutionary change requires understanding the principles that control variation in varying AND conserved traits, in addition to understanding how drift and selection influence segregating population variation. In this perspective, I propose that this understanding is attainable if we acknowledge that different processes, which map sequence variation to phenotypic variation, have different capacities to produce variation and evolve. I suggest decomposing the GP map according to types of processes with different variational properties. For vertebrates, these are morphogenesis, growth, and maintenance. This perspective allows us to focus on how these processes interact under the influence of natural selection and delineate the conditions leading to different patterns of evolutionary change. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Evolution is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1093/evolut/qpaf236
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 301
    Subjects:
      – SubjectFull: Microevolution
        Type: general
      – SubjectFull: Macroevolution
        Type: general
      – SubjectFull: Population genetics
        Type: general
      – SubjectFull: Natural selection
        Type: general
      – SubjectFull: Morphogenesis
        Type: general
      – SubjectFull: Phenotypic plasticity
        Type: general
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      – TitleFull: Cracking open the blackbox of genotype–phenotype map: crossing the explanatory gap between micro- and macroevolution.
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              Text: Feb2026
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              Y: 2026
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            – TitleFull: Evolution
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