TY - JOUR

T1 - Comprehensive analysis of gene regulatory dynamics, fitness landscape, and population evolution during sexual reproduction

AU - Okubo, Kenji

AU - Kaneko, Kunihiko

PY - 2022/10/14

Y1 - 2022/10/14

N2 - The fitness landscape is a critical concept in biophysics, evolutionary biology, and genetics that depicts fitness in the genotype space and visualizes the relationship between genotype and fitness. However, the fitness landscape is challenging to characterize because the quantitative relationships between genotype and phenotype and their association to fitness has not been comprehensively well described. To address this challenge, we adopted gene regulatory networks to determine gene expression dynamics. We analyzed how phenotype and fitness are shaped by the genotype in two-gene networks. A two-by-two matrix provided the two-gene regulatory network in which a vector with two angle values (Theta) was introduced to characterize the genotype. Mapping from this angle vector to phenotypes allowed for the classification of steady-state expression patterns of genes into seven types. We then studied all possible fitness functions given by the Boolean output from the on/off expression of the two genes. The possible fitness landscapes were obtained as a function of the genetic parameters Theta. Finally, the evolution of the population distribution under sexual reproduction was investigated in the obtained landscape. We found that the distribution was restricted to a convex region within the landscape, resulting in the branching of population distribution, including the speciation process.

AB - The fitness landscape is a critical concept in biophysics, evolutionary biology, and genetics that depicts fitness in the genotype space and visualizes the relationship between genotype and fitness. However, the fitness landscape is challenging to characterize because the quantitative relationships between genotype and phenotype and their association to fitness has not been comprehensively well described. To address this challenge, we adopted gene regulatory networks to determine gene expression dynamics. We analyzed how phenotype and fitness are shaped by the genotype in two-gene networks. A two-by-two matrix provided the two-gene regulatory network in which a vector with two angle values (Theta) was introduced to characterize the genotype. Mapping from this angle vector to phenotypes allowed for the classification of steady-state expression patterns of genes into seven types. We then studied all possible fitness functions given by the Boolean output from the on/off expression of the two genes. The possible fitness landscapes were obtained as a function of the genetic parameters Theta. Finally, the evolution of the population distribution under sexual reproduction was investigated in the obtained landscape. We found that the distribution was restricted to a convex region within the landscape, resulting in the branching of population distribution, including the speciation process.

KW - fitness landscape

KW - gene regulatory network

KW - sexual reproduction

KW - NETWORK

KW - MODEL

KW - ROBUSTNESS

KW - DOMINANCE

KW - INDUCTION

U2 - 10.1088/1367-2630/ac9549

DO - 10.1088/1367-2630/ac9549

M3 - Journal article

VL - 24

JO - New Journal of Physics

JF - New Journal of Physics

SN - 1367-2630

IS - 10

M1 - 103017

ER -