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Evolutionary trade-offs and the structure of polymorphisms.

Hila Sheftel1, Pablo Szekely1, Avi Mayo1

  • 1Department Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|April 11, 2018
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Genetic polymorphisms align with evolutionary trade-offs, creating optimal multi-tasking organisms. This study reveals how genetic variations shape populations facing multiple demands, impacting biology and medicine.

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Area of Science:

  • Evolutionary biology
  • Population genetics
  • Quantitative genetics

Background:

  • Organisms exhibit genetic variations known as polymorphisms, crucial for understanding biological and medical traits.
  • Evolutionary trade-offs arise when optimizing for multiple tasks simultaneously, leading to necessary compromises in organismal traits.
  • Previous research identified the Pareto front as a geometric representation of these trade-offs, but lacked genetic insights.

Purpose of the Study:

  • To investigate how population polymorphism structure is influenced by evolution under multi-task trade-offs.
  • To determine the genetic underpinnings of adaptation to complex environments with competing demands.

Main Methods:

  • Simulated a multi-task selection scenario where populations evolved towards the Pareto front.
  • Analyzed the phenotypic effects of prevalent polymorphisms and epistatic interactions in relation to the Pareto front.
  • Examined the impact of asexual reproduction, genetic drift, and linkage on polymorphism structure.

Main Results:

  • Prevalent polymorphisms exhibited pleiotropic effects that aligned with the Pareto front geometry.
  • Epistatic interactions between polymorphisms were also found to be parallel to the Pareto front.
  • Alignment was observed in asexual populations but weakened under strong drift or linkage, leading to complex, canceling allele effects.

Conclusions:

  • Aligned polymorphism structure facilitates the production of offspring capable of multi-task optimization across diverse environmental niches.
  • This genetic alignment is a key factor in how populations adapt to environments requiring simultaneous optimization of multiple traits.
  • Understanding these genetic mechanisms is vital for both fundamental biology and medical applications related to genetic variation.