Principles of Robust Developmental Patterning

描述（由申请人提供）：许多发育组织的模式是由形态形成因子的梯度控制的。形态发生梯度的一个重大挑战是产生不易被遗传或环境扰动改变的模式。最有可能驱动形态梯度系统进化的各种扰动是生物体经常面临的：由于温度波动引起的生物化学和生理变化，营养状况的改变以及基因表达的随机性。这种扰动是多因素的，即它们同时影响许多基因产物和过程。尽管研究人员最近开始探索形态梯度如何承受单基因表达水平的变化，但我们的初步研究表明，实现对多因素扰动的稳健性可能需要根本不同的策略。我们将通过数学、计算和实验方法的结合来研究这个问题。工作将集中在一个最具特征的形态梯度，BMP梯度模式的幼虫昆虫翅盘。最初，我们将使用建模和实验来探索这种梯度如何响应遗传扰动的组合，以确定管理“鲁棒性权衡”的规则。接下来，我们将测试假设BMP梯度系统的架构反映了对温度波动的鲁棒性优化的驱动。第三，我们将确定Jbrin/cer基因（BMP梯度的关键下游靶点）的复杂调控结构如何有助于整个系统的稳健性。最后，我们将确定在同一梯度系统中部署两种BMP配体-十足体（Dpp）和玻璃底船（Gbb）的方式也有助于图案的鲁棒性。了解形态梯度系统用来抵御现实世界扰动的策略，对于解释为什么人类发育在大多数时候都能如此准确地进行至关重要，也是了解正常发育失败（即出生缺陷）如何以及为什么会出现的必要的第一步。

DESCRIPTION (provided by applicant): The patterning of many developing tissues is controlled by gradients of morphogens. A significant challenge for morphogen gradients is to produce patterns that are not easily altered by genetic or environmental perturbations. The kinds of perturbations most likely to have driven the evolution of morphogen gradient systems are those that organisms face frequently: changes in biochemistry and physiology due to fluctuations in temperature, alterations in nutritional status, and the stochasticity of gene expression. Such perturbations are multifactorial, i.e. they affect many gene products and processes at the same time. Although investigators have recently begun to explore how morphogen gradients might withstand changes in the expression levels of single genes, our preliminary studies suggest that achieving robustness to multifactorial perturbations may require fundamentally different strategies. We will investigate this question through a combination of mathematical, computational and experimental approaches. Work will focus on one of the best-characterized morphogen gradients, the BMP gradient that patterns the larval insect wing disc. Initially, we will use both modeling and experiments to explore how this gradient responds to combinations of genetic perturbations, in order to identify rules that govern "robustness tradeoffs". Next, we will test the hypothesis that the architecture of the BMP gradient system reflects a drive toward optimization of robustness to temperature fluctuations. Third, we will identify ways in which the complex regulatory architecture of the Jbrin/cer gene, a key downstream target of the BMP gradient, contributes to robustness of the overall system. Finally, we will identify ways in which the deployment of two BMP ligands- decapentaplegic (Dpp) and glass bottom boat (Gbb) in the same gradient system also contributes to the robustness of patterning. Understanding the strategies used by morphogen gradient systems to withstand real-world perturbations is critical for explaining why human development proceeds so accurately most of the time, and is a necessary first step toward a general understanding of how and why failures of normal development, i.e. birth defects, arise.