Evolution of Gene Regulatory Networks by Fluctuating Selection and Intrinsic Constraints
نویسندگان
چکیده
Various characteristics of complex gene regulatory networks (GRNs) have been discovered during the last decade, e.g., redundancy, exponential indegree distributions, scale-free outdegree distributions, mutational robustness, and evolvability. Although progress has been made in this field, it is not well understood whether these characteristics are the direct products of selection or those of other evolutionary forces such as mutational biases and biophysical constraints. To elucidate the causal factors that promoted the evolution of complex GRNs, we examined the effect of fluctuating environmental selection and some intrinsic constraining factors on GRN evolution by using an individual-based model. We found that the evolution of complex GRNs is remarkably promoted by fixation of beneficial gene duplications under unpredictably fluctuating environmental conditions and that some internal factors inherent in organisms, such as mutational bias, gene expression costs, and constraints on expression dynamics, are also important for the evolution of GRNs. The results indicate that various biological properties observed in GRNs could evolve as a result of not only adaptation to unpredictable environmental changes but also non-adaptive processes owing to the properties of the organisms themselves. Our study emphasizes that evolutionary models considering such intrinsic constraining factors should be used as null models to analyze the effect of selection on GRN evolution.
منابع مشابه
Bistability in feedback circuits as a byproduct of evolution of evolvability
Noisy bistable dynamics in gene regulation can underlie stochastic switching and is demonstrated to be beneficial under fluctuating environments. It is not known, however, if fluctuating selection alone can result in bistable dynamics. Using a stochastic model of simple feedback networks, we apply fluctuating selection on gene expression and run in silico evolutionary simulations. We find that ...
متن کاملH∞ Sampled-Data Controller Design for Stochastic Genetic Regulatory Networks
Artificially regulating gene expression is an important step in developing new treatment for system-level disease such as cancer. In this paper, we propose a method to regulate gene expression based on sampled-data measurements of gene products concentrations. Inherent noisy behaviour of Gene regulatory networks are modeled with stochastic nonlinear differential equation. To synthesize feed...
متن کاملEvolution under Fluctuating Environments Explains Observed Robustness in Metabolic Networks
A high level of robustness against gene deletion is observed in many organisms. However, it is still not clear which biochemical features underline this robustness and how these are acquired during evolution. One hypothesis, specific to metabolic networks, is that robustness emerges as a byproduct of selection for biomass production in different environments. To test this hypothesis we performe...
متن کاملModeling gene regulatory networks: Classical models, optimal perturbation for identification of network
Deep understanding of molecular biology has allowed emergence of new technologies like DNA decryption. On the other hand, advancements of molecular biology have made manipulation of genetic systems simpler than ever; this promises extraordinary progress in biological, medical and biotechnological applications. This is not an unrealistic goal since genes which are regulated by gene regulatory ...
متن کاملCell–cell signaling drives the evolution of complex traits: introduction—lung evo-devo
Physiology integrates biology with the environment through cell-cell interactions at multiple levels. The evolution of the respiratory system has been "deconvoluted" (Torday and Rehan in Am J Respir Cell Mol Biol 31:8-12, 2004) through Gene Regulatory Networks (GRNs) applied to cell-cell communication for all aspects of lung biology development, homeostasis, regeneration, and aging. Using this ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 6 شماره
صفحات -
تاریخ انتشار 2010