Abstract

During development of biological organisms, multiple complex structures are formed. In many instances, these structures need to exhibit a high degree of order to be functional, although many of their constituents are intrinsically stochastic. Hence, it has been suggested that biological robustness ultimately must rely on complex gene regulatory networks and clean-up mechanisms. Here we explore developmental processes that have evolved inherent robustness against stochasticity. In the context of the Drosophila eye disc, multiple optical units, ommatidia, develop into crystal-like patterns. During the larva-to-pupa stage of metamorphosis, the centers of the ommatidia are specified initially through the diffusion of morphogens, followed by the specification of R8 cells. Establishing the R8 cell is crucial in setting up the geometric, and functional, relationships of cells within an ommatidium and among neighboring ommatidia. Here we study an PDE mathematical model of these spatio-temporal processes in the presence of parametric stochasticity, defining and applying measures that quantify order within the resulting spatial patterns. We observe a universal sigmoidal response to increasing transcriptional noise. Ordered patterns persist up to a threshold noise level in the model parameters. In accordance with prior qualitative observations, as the noise is further increased past a threshold point of no return, these ordered patterns rapidly become disordered. Such robustness in development allows for the accumulation of genetic variation without any observable changes in phenotype. We argue that the observed sigmoidal dependence introduces robustness allowing for sizable amounts of genetic variation and transcriptional noise to be tolerated in natural populations without resulting in phenotype variation.

Highlights

  • Deterministic outcomes from inherently stochastic componentsBiological systems are intrinsically noisy but produce deterministic outcomes

  • We start with a model of coupled differential equations that describe morphogenetic pattern formation for R8 cell specification on the Drosophila eye disc obtained from [7], an article expanding on the work of [8]

  • To quantify disorder in the emerging activated R8 cell patterns, the nearest neighbor distance and angle probably distribution functions were computed for various noise levels in the diffusion coefficients Du, Ds. (Later we will discuss the effect of stochasticity on other model parameters)

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Summary

Introduction

Deterministic outcomes from inherently stochastic componentsBiological systems are intrinsically noisy but produce deterministic outcomes. Threshold response to stochasticity in morphogenesis body plan and differentiate cells. The expression of a gene depends on the probabilistic outcomes of several factors, such as molecular binding affinities, processivity, and regulatory sequence interactions. Genetically identical cells produce morphogen transcripts in asynchronous bursts and in varying quantities [1]. It is essential to investigate how ordered deterministic structures are formed from underlying stochastic components, such as gene expression. As an approximation to the stochastic nature of morphogenesis, parametric variation is introduced in the partial differential equations of the mathematical model. Earlier studies have addressed robustness of developmental processes, termed as canalization [2], which remain a subject of great interest today [3,4,5,6]. We analyze the response of a developmental system to noise quantitatively from a statistical physics perspective

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