Evolution and maintenance of phenotypic plasticity

Unjin Lee, Emily N. Mortola, Eun-jin Kim, Manyuan Long

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
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We introduce a novel framework for exploring the evolutionary consequences of phenotypic plasticity (adaptive and non-adaptive) integrating both genic and epigenetic effects on phenotype via stochastic differential equations and in-silico selection. In accordance with the most significant results derived from prior models, we demonstrate how plasticity is differentially favored when subjected to small vs large environmental shifts, how plasticity is transiently favorable while accommodating a new environment, and how plasticity decreases during epochs where the environment remains stable (canalization). In contrast to these models, however, by allowing the same phenotypic value to be produced via two different paths, i.e. deterministic, genic, vs stochastic, epigenetic mechanisms, we demonstrate when genic contributions alone cannot produce an optimal phenotype, plastic, epigenetic contributions will instead fully accommodate new environments, allowing for both adaptive and non-adaptive plasticity to evolve. Furthermore, we show that while rates of phenotypic accommodation are relatively constant under a wide range of selective conditions, selection will favor the most efficient route to adaptation: deterministic, genic response, or stochastic, plastic response. As a result, plasticity may evolve or canalization may occur within a given epoch depending on the relative mutation rate of genic and epigenetic contributions to phenotype, highlighting the importance of genetic conflict on the evolution of plasticity.
Original languageEnglish
Article number104791
Number of pages14
Early online date14 Oct 2022
Publication statusPublished - 1 Dec 2022

Bibliographical note

This is an open access article under the CC BY-NC-ND license.


Funding Information: . U.L. is funded in part by GM7197-42. M.L. was supported by the National Science Foundation grant NSF2020667 and the National Institutes of Health grant 1R01GM116113-01A1 .


  • Evolution
  • Plasticity
  • Environmental variability
  • Adaptation
  • Mutation-selection-drift balance
  • Stochastic differential equations


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