Reducing Epistasis and Pleiotropy Can Avoid the Survival of the Flattest Tragedy

Author:

Mehra Priyanka1ORCID,Hintze Arend12ORCID

Affiliation:

1. Department for MicroData Analytics, Dalarna University, 791 88 Falun, Sweden

2. BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA

Abstract

This study investigates whether reducing epistasis and pleiotropy enhances mutational robustness in evolutionary adaptation, utilizing an indirect encoded model within the “survival of the flattest” (SoF) fitness landscape. By simulating genetic variations and their phenotypic consequences, we explore organisms’ adaptive mechanisms to maintain positions on higher, narrower evolutionary peaks amidst environmental and genetic pressures. Our results reveal that organisms can indeed sustain their advantageous positions by minimizing the complexity of genetic interactions—specifically, by reducing the levels of epistasis and pleiotropy. This finding suggests a counterintuitive strategy for evolutionary stability: simpler genetic architectures, characterized by fewer gene interactions and multifunctional genes, confer a survival advantage by enhancing mutational robustness. This study contributes to our understanding of the genetic underpinnings of adaptability and robustness, challenging traditional views that equate complexity with fitness in dynamic environments.

Publisher

MDPI AG

Reference52 articles.

1. Smith, J.M., and Szathmary, E. (1997). The Major Transitions in Evolution, OUP Oxford.

2. Information theory in molecular biology;Adami;Phys. Life Rev.,2004

3. Thompson, E.G., and Galitski, T. (2012). Quantifying and analyzing the network basis of genetic complexity. PLoS Comput. Biol., 8.

4. Genotypic complexity of Fisher’s geometric model;Hwang;Genetics,2017

5. Lehre, P.K., and Haddow, P.C. (2003, January 8–12). Developmental mappings and phenotypic complexity. Proceedings of the The 2003 Congress on Evolutionary Computation, CEC’03, Canberra, Australia.

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