Evolutionary trade-offs and the structure of polymorphisms

Hila Sheftel, Pablo Szekely, Avi Mayo, Guy Sella, Uri Alon

Research output: Contribution to journalArticlepeer-review

Abstract

Populations of organisms show genetic differences called polymorphisms. Understanding the effects of polymorphisms is important for biology and medicine. Here, we ask which polymorphisms occur at high frequency when organisms evolve under trade-offs between multiple tasks. Multiple tasks present a problem, because it is not possible to be optimal at all tasks simultaneously and hence compromises are necessary. Recent work indicates that trade-offs lead to a simple geometry of phenotypes in the space of traits: phenotypes fall on the Pareto front, which is shaped as a polytope: a line, triangle, tetrahedron etc. The vertices of these polytopes are the optimal phenotypes for a single task. Up to now, work on this Pareto approach has not considered its genetic underpinnings. Here, we address this by asking how the polymorphism structure of a population is affected by evolution under trade-offs. We simulate a multi-task selection scenario, in which the population evolves to the Pareto front: the line segment between two archetypes or the triangle between three archetypes. We find that polymorphisms that become prevalent in the population have pleiotropic phenotypic effects that align with the Pareto front. Similarly, epistatic effects between prevalent polymorphisms are parallel to the front. Alignment with the front occurs also for asexual mating. Alignment is reduced when drift or linkage is strong, and is replaced by a more complex structure in which many perpendicular allele effects cancel out. Aligned polymorphism structure allows mating to produce offspring that stand a good chance of being optimal multi-taskers in at least one of the locales available to the species. This article is part of the theme issue ‘Self-organization in cell biology’.

Original languageEnglish
Article number20170105
JournalPhilosophical Transactions of the Royal Society B: Biological Sciences
Volume373
Issue number1747
DOIs
StatePublished - 26 May 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 The Author(s) Published by the Royal Society. All rights reserved.

Keywords

  • Complex traits
  • Multi-task evolution
  • Pareto task inference
  • Quantitative genetic variation
  • Quantitative trait loci

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences

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