Abstract
AbstractsSelf-sustained oscillation is a fundamental property of circadian rhythms and has been repeatedly tested since the early days of circadian research, resulting in the discovery of almost all organisms possessing self-sustained circadian oscillations. However, the evolutionary advantage of self-sustainability has been only speculatively discussed. In this theoretical study, we sought the environmental constraints and selection pressure that drive the acquisition or degeneration of self-sustainability through the process of evolution. We considered a random gene regulatory network dynamics under light cycles and optimized the network structure using an evolutionary algorithm. By designing the fitness function in the evolutionary algorithm, we investigated the environmental conditions that led to the evolution of the self-sustained oscillators. Then, we found that (i) networks showing self-sustained oscillation under constant light conditions are much rarer than those showing damped oscillation and hourglass-type behaviour, and (ii) among several types of fitness-based optimization, networks with self-sustainability property have a markedly high fitness score, especially when we assume that a network has to generate a constantly periodic expression profile regardless of day length. This study was the first to show that seasonality facilitated the evolution of the self-sustained circadian clock, which was consistent with empirical records.
Publisher
Cold Spring Harbor Laboratory
Cited by
1 articles.
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