| Literature DB >> 34849893 |
Nobuto Takeuchi1,2, Namiko Mitarai2,3, Kunihiko Kaneko2,4.
Abstract
Numerous living systems are hierarchically organized, whereby replicating components are grouped into reproducing collectives-e.g., organelles are grouped into cells, and cells are grouped into multicellular organisms. In such systems, evolution can operate at two levels: evolution among collectives, which tends to promote selfless cooperation among components within collectives (called altruism), and evolution within collectives, which tends to promote cheating among components within collectives. The balance between within- and among-collective evolution thus exerts profound impacts on the fitness of these systems. Here, we investigate how this balance depends on the size of a collective (denoted by N) and the mutation rate of components (m) through mathematical analyses and computer simulations of multiple population genetics models. We first confirm a previous result that increasing N or m accelerates within-collective evolution relative to among-collective evolution, thus promoting the evolution of cheating. Moreover, we show that when within- and among-collective evolution exactly balance each other out, the following scaling relation generally holds: Nmα is a constant, where scaling exponent α depends on multiple parameters, such as the strength of selection and whether altruism is a binary or quantitative trait. This relation indicates that although N and m have quantitatively distinct impacts on the balance between within- and among-collective evolution, their impacts become identical if m is scaled with a proper exponent. Our results thus provide a novel insight into conditions under which cheating or altruism evolves in hierarchically organized replicating systems.Entities:
Keywords: Price equation; group selection; major evolutionary transitions; multilevel selection; power law; quantitative genetics
Mesh:
Year: 2022 PMID: 34849893 PMCID: PMC9208640 DOI: 10.1093/genetics/iyab182
Source DB: PubMed Journal: Genetics ISSN: 0016-6731 Impact factor: 4.402