A Developmental Systems Perspective on Epistasis: Computational Exploration of Mutational Interactions in Model Developmental Regulatory Networks

Ben Lehner,Jayson Gutiérrez

doi:10.1371/journal.pone.0006823

Abstract

The way in which the information contained in genotypes is translated into complex phenotypic traits (i.e. embryonic expression patterns) depends on its decoding by a multilayered hierarchy of biomolecular systems (regulatory networks). Each layer of this hierarchy displays its own regulatory schemes (i.e. operational rules such as +/− feedback) and associated control parameters, resulting in characteristic variational constraints. This process can be conceptualized as a mapping issue, and in the context of highly-dimensional genotype-phenotype mappings (GPMs) epistatic events have been shown to be ubiquitous, manifested in non-linear correspondences between changes in the genotype and their phenotypic effects. In this study I concentrate on epistatic phenomena pervading levels of biological organization above the genetic material, more specifically the realm of molecular networks. At this level, systems approaches to studying GPMs are specially suitable to shed light on the mechanistic basis of epistatic phenomena. To this aim, I constructed and analyzed ensembles of highly-modular (fully interconnected) networks with distinctive topologies, each displaying dynamic behaviors that were categorized as either arbitrary or functional according to early patterning processes in the Drosophila embryo. Spatio-temporal expression trajectories in virtual syncytial embryos were simulated via reaction-diffusion models. My in silico mutational experiments show that: 1) the average fitness decay tendency to successively accumulated mutations in ensembles of functional networks indicates the prevalence of positive epistasis, whereas in ensembles of arbitrary networks negative epistasis is the dominant tendency; and 2) the evaluation of epistatic coefficients of diverse interaction orders indicates that, both positive and negative epistasis are more prevalent in functional networks than in arbitrary ones. Overall, I conclude that the phenotypic and fitness effects of multiple perturbations are strongly conditioned by both the regulatory architecture (i.e. pattern of coupled feedback structures) and the dynamic nature of the spatio-temporal expression trajectories displayed by the simulated networks.

Highlights

The relationship between the information contained in the genetic material and biological traits or functions (genotypephenotype mappings (GPMs)) has represented a major challenge in biology, in which much research efforts have been devoted in the last decades [1,2,3]
I introduce a definition of epistasis from a developmental systems perspective as a guideline for the interpretation of my simulation results: Epistasis is the phenomenon in which the effects of diverse allelic configurations and mutational combinations propagate in a non-linear fashion through the regulatory schemes and control parameters governing the spatio-temporal expression trajectories of developmental networks
The analysis of mutational trajectories over each ensemble of networks modeled show that the average tendency in the form successively accumulated mutations induce a fitness decline in arbitrary networks is clearly indicative of negative epistasis

Summary

Introduction

The relationship between the information contained in the genetic material and biological traits or functions (genotypephenotype mappings (GPMs)) has represented a major challenge in biology, in which much research efforts have been devoted in the last decades [1,2,3]. Previous investigations on complex GPMs support the idea that phenotypic traits emerge as a result of the concerted action of many genes and their products, which tend to selforganize into regulatory networks (i.e. transcripional and cell signaling systems) below the scale of an entire genome or proteome [5,6,7,8] These findings have revealed, to a large extent, the contents of these biological black boxes, suggesting that highlymodular regulatory networks are the mechanisms underlying complex GPMs. One of the major difficulties toward the understanding and predictions of complex GPMs is the presence of a pervasive phenomenon referred to as epistasis, in which the phenotypic effects of genes are dependent on the genomic/genetic context in which they are embedded. With the fluorishing of systems biology, studies on GPMs have revealed that they are brought about dynamically via the action of complex molecular networks, wherein intricate functional dependencies among molecules and regulatory processes naturally emerge This new research paradigm has provided substantial evidence supporting the idea that epistatic phenomena are pervasive at higher levels of biological organization above the genetic material. In addition to the characterization of genetic principles of GPMs, which have traditionally been encompassed under the umbrella of genetic architecture (i.e. ploidy, dominance, penetrance, expressivity, etc.), emphasis should be made on mechanistic descriptions and quantitative properties of molecular networks (i.e. regulation, control, dynamics, design principles, self-organization, emergence, etc)

Methods

Results

Conclusion