The arrival of novel variation in gene-regulatory networks

点击翻译按钮获取中文摘要

Evolutionary theory has been a cornerstone in understanding the biological intricacies of life.. While much of our research efforts have focussed on natural selection, the preceding step in the evolutionary process-the generation of phenotypic variation- is much less explored. This project endeavors to unravel the principles of this crucial step by employing computational techniques to delve into the impact of random mutations on the emergence of novel phenotypes within gene-regulatory networks (GRNs). These intricate systems of interconnected genes and their regulatory elements work in concert to control the gene expression levels in a cell. These networks play a fundamental role in determining the precise timing and extent of gene activation or repression, influencing the development, function, and response of organisms to their environment.The initial phase of the investigation will revolve around Boolean threshold networks, analyzing the frequency of outputs in response to mutations that alter the network's topology. This foundational exploration aims to lay the groundwork for comprehending the role of structural changes in shaping the phenotypic landscape of GRNs. Moving beyond simplified Boolean models, the project will advance to more realistic differential equation models of GRNs, incorporating established models for various biological phenomena such as the Drosophila circadian rhythm, the budding-yeast cell-cycle, and a Rat growth-factor signaling factor.In this subsequent stage, the focus will shift from modifying network topologies to varying parameter values within fixed topologies. This approach mirrors the effects of random mutations on GRN outputs and enables the investigation of whether wild-type outputs are predisposed to emerge prominently under random parameter sampling. The hypothesis under scrutiny posits that the normal, wild-type outputs of GRNs stand out as particularly probable outcomes amid the diverse array of possibilities resulting from random mutations.As the project unfolds, insights gleaned from these random variation models will be harnessed to delve into the broader implications for evolutionary dynamics. The exploration will extend to the study of fitness landscapes associated with the GRNs, shedding light on how the interplay between mutation-induced variations and natural selection shapes the evolutionary trajectory of biological systems. By employing novel computational tools and leveraging diverse modeling approaches, this project aims not only to unravel the intricate relationship between random mutations and phenotypic variation but also to contribute to a deeper understanding of the evolutionary forces that govern the emergence and persistence of specific traits within gene-regulatory networks. In doing so, it aspires to broaden our knowledge of the nuanced mechanisms steering the complex dance of life's evolution.