Abstract

The earliest models for how morphogen gradients guide embryonic patterning failed to account for experimental observations of temporal refinement in gene expression domains. Following theoretical and experimental work in this area, dynamic positional information has emerged as a conceptual framework to discuss how cells process spatiotemporal inputs into downstream patterns. Here, we show that diffusion determines the mathematical means by which bistable gene expression boundaries shift over time, and therefore how cells interpret positional information conferred from morphogen concentration. First, we introduce a metric for assessing reproducibility in boundary placement or precision in systems where gene products do not diffuse, but where morphogen concentrations are permitted to change in time. We show that the dynamics of the gradient affect the sensitivity of the final pattern to variation in initial conditions, with slower gradients reducing the sensitivity. Second, we allow gene products to diffuse and consider gene expression boundaries as propagating wavefronts with velocity modulated by local morphogen concentration. We harness this perspective to approximate a PDE model as an ODE that captures the position of the boundary in time, and demonstrate the approach with a preexisting model for Hunchback patterning in fruit fly embryos. We then propose a design that employs antiparallel morphogen gradients to achieve accurate boundary placement that is robust to scaling. Throughout our work we draw attention to tradeoffs among initial conditions, boundary positioning, and the relative timescales of network and gradient evolution. We conclude by suggesting that mathematical theory should serve to clarify not just our quantitative, but also our intuitive understanding of patterning processes.

Highlights

  • Spatial patterning of gene expression, especially during embryonic development, has fascinated theoretical and experimental researchers throughout the past century

  • We suggest that future research into dynamic positional information would benefit from perspectives that link local and global behaviors, as well as from mathematical theory that builds our intuitive understanding alongside more data-driven approaches

  • For each case we suggest a scheme to improve the reproducibility of boundary placement when initial conditions may vary across embryos; in the system without diffusion, this scheme is identical to one that improves the precision of a boundary when initial conditions vary among cells

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Summary

Introduction

Spatial patterning of gene expression, especially during embryonic development, has fascinated theoretical and experimental researchers throughout the past century. Gene expression domains shift over time, as indicated by experimental evidence from fruit flies [18, 21,22,23,24,25], scuttle flies [26], and vertebrate neural tube [27] To explain these observed behaviors, researchers have investigated stochastic influences [28, 29], the structure of biochemical networks [30], protein diffusion [20], biomechanical forces including cell sorting or aggregation [31,32,33], and the temporal evolution of upstream patterns [15]

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