ERA-CAPS: From genes to shape: Towards development of a computable flower

ERA-CAPS：从基因到形状：迈向可计算花的发展

基本信息

批准号：
1826567
负责人：
Elliot Meyerowitz
金额：
$ 45.3万
依托单位：
California Institute of Technology
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-15 至 2021-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1826567&HistoricalAwards=false
关键词：
ERA CAPS genes shape Towards

项目摘要

Plants have typical shapes, and one part of each plant, the flower, has a shape and structure characteristic of the species. How growing plants create flower shapes is unknown. Understanding how flowers acquire shape is important flowers are major sources of human food. Earlier work has shown that the shape that flowers take depends on the expression of regulatory genes in the growing flowers, and on the mechanical properties of the walls of the floral cells. This project will create computer models of flowers that show all of the cells and cell walls at several stages of floral growth and add to those models the physical properties of the walls (measured by several biophysical methods) and the patterns of gene expression that create the cell walls and regulate floral shape. By comparing these patterns, the team will develop hypotheses about how the combination of changing gene expression and changing mechanical properties lead to changes in cell shape and size, and therefore to the development of flower shape. They will test the hypotheses and the models by changing wall mechanical properties experimentally and seeing if the computer model predicts the shape changes seen in the experiments. The outcomes will provide tools with wide applicability to crop plants, enabling researchers and breeders access to genes and processes that contribute to establishing floral shape. Educational efforts focus on training students and post-docs in cutting edge interdisciplinary approaches that merge biology and mathematical modeling.This project will develop a tool called the "Computable Flower" that permits the user to (i) integrate data on geometry, gene expression and biomechanics and (ii) explore, interpret and generate hypotheses based on data supported by mechanistic modeling approaches. The tool therefore provides an integrated description in the form of a 3D dynamic template of the growing flower bud. The Computable Flower will be populated with existing or novel quantitative datasets coming from experimental and computational techniques concerning the spatial distribution of regulatory molecules such as transcription factors and hormones, and the spatial expression patterns of genes involved in cell wall synthesis and remodeling which operate downstream and upstream from these regulatory networks. Information on the spatial organization and properties of structural elements of the developing flower, including cell wall stiffness, microtubule orientation and cellulose microfibril organization will be added to the template. Following this, temporal information will be included, showing correlations of gene expression, mechanical properties of the tissue, and changes in geometry. This will lead to computational models and hypotheses regarding biochemical, physical and geometrical properties with simulation outcomes quantitatively compared with experimental data. Predictions coming from the modeling will guide experiments using domain-specific perturbation of genes that influence microtubule and wall status. These transgenic lines will then be subjected to detailed quantitative growth studies to test the validity of the model or to refine it. The overall result will be a path to calculate floral phenotype from genotype that includes mechanical properties of tissues and their role in morphogenesis. The broader impact will include potential applications in agriculture as well as training of students and postdocs in the combination of experimental and computational developmental biology.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

植物具有典型的形状，每种植物的一部分（即花）具有该物种的形状和结构特征。生长中的植物如何形成花朵形状尚不清楚。了解花朵如何形成形状很重要花朵是人类食物的主要来源。早期的研究表明，花朵的形状取决于生长中花朵中调控基因的表达，以及花细胞壁的机械特性。该项目将创建花卉的计算机模型，显示花卉生长各个阶段的所有细胞和细胞壁，并向这些模型添加细胞壁的物理特性（通过多种生物物理方法测量）以及创建花卉的基因表达模式。细胞壁并调节花的形状。通过比较这些模式，研究小组将提出关于改变基因表达和改变机械特性的组合如何导致细胞形状和大小的变化，从而导致花形状的发展的假设。他们将通过实验改变壁的力学特性并查看计算机模型是否预测实验中看到的形状变化来测试假设和模型。研究结果将为农作物提供广泛适用的工具，使研究人员和育种者能够获得有助于建立花形的基因和过程。教育工作的重点是培训学生和博士后采用融合生物学和数学建模的前沿跨学科方法。该项目将开发一种称为“可计算花”的工具，允许用户（i）集成几何、基因表达和生物力学；(ii) 根据机械建模方法支持的数据探索、解释和生成假设。因此，该工具以生长花蕾的 3D 动态模板的形式提供集成描述。可计算花将填充来自实验和计算技术的现有或新颖的定量数据集，这些数据集涉及转录因子和激素等调节分子的空间分布，以及参与下游和细胞壁合成和重塑的基因的空间表达模式。这些监管网络的上游。有关正在发育的花的空间组织和结构元素特性的信息，包括细胞壁刚度、微管方向和纤维素微纤维组织，将添加到模板中。接下来，将包括时间信息，显示基因表达的相关性、组织的机械特性和几何形状的变化。这将产生有关生化、物理和几何特性的计算模型和假设，并与实验数据进行定量比较的模拟结果。来自模型的预测将指导使用影响微管和管壁状态的基因的特定领域扰动进行的实验。然后，这些转基因品系将接受详细的定量生长研究，以测试模型的有效性或对其进行完善。总体结果将是从基因型计算花表型的路径，其中包括组织的机械特性及其在形态发生中的作用。更广泛的影响将包括农业中的潜在应用，以及对实验和计算发育生物学相结合的学生和博士后的培训。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响进行评估，被认为值得支持审查标准。