The evolution of heterogeneities altered by mutational robustness, gene expression noise and bottlenecks in gene regulatory networks.

Zhihua Zhang

doi:10.1371/journal.pone.0116167

Abstract

Intra-population heterogeneity is commonly observed in natural and cellular populations and has profound influence on their evolution. For example, intra-tumor heterogeneity is prevalent in most tumor types and can result in the failure of tumor therapy. However, the evolutionary process of heterogeneity remains poorly characterized at both genotypic and phenotypic level. Here we study the evolution of intra-population heterogeneities of gene regulatory networks (GRN), in particular mutational robustness and gene expression noise as contributors to the development of heterogeneities. By in silico simulations, it was found that the impact of these factors on GRN can, under certain conditions, promote phenotypic heterogeneity. We also studied the effect of population bottlenecks on the evolution of GRN. When the GRN population passes through such bottlenecks, neither mutational robustness nor population fitness was observed to be substantially altered. Interestingly, however, we did detect a significant increase in the number of potential “generator” genes which can substantially induce population fitness, when stimulated by mutational hits.

Highlights

Living organisms are always exposed to external and internal perturbations
We studied the evolutionary process of a gene regulatory networks (GRN) model of genotype and phenotype in a cell population and observed interactions among mutation, gene expression noise, mutational robustness and phenotypic heterogeneities
It was revealed that gene expression noise and mutational robustness, apart from population size and mutation rate, are two key factors that drive the evolution of PH

Summary

Introduction

Living organisms are always exposed to external and internal perturbations. In most situations, these perturbations do not have observable effects, essentially because living organisms are robust systems adapted to their environments. The Evolution of Heterogeneities in Gene Regulatory Networks novel phenotypes may be changed in the population during the process of evolution, changes genotypic and phenotypic heterogeneities within the population. The evolutionary process of such population of heterogeneities remains poorly characterized. Genotypic and phenotypic heterogeneity of a population is, in general, not linearly correlated [1]. To quantitatively study heterogeneities, it is necessary to distinguish genotypic from phenotypic heterogeneities and connect the two with a measureable model. Several systems have been used as computational models for this purpose, including RNA secondary structure, protein structure and gene regulatory network (GRN) [3]. We studied the dynamics of genotypic and phenotypic heterogeneities in a population of GRNs. Currently, we lack qualified data and tools for quantitative models of a network, even for small networks. The qualitative binary model has been proven to be a powerful tool for the study of complex systems, and many basic evolutionary principles have been revealed through such systems [4, 5]

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Results

Conclusion