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（花朵）具有该物种的形状和结构特征。种植植物如何产生花形是未知的。了解花朵如何获得形状是重要的花是人类食物的主要来源。较早的工作表明，花所采取的形状取决于生长花中调节基因的表达以及花细胞壁的机械性能。该项目将创建花朵的计算机模型，这些模型在花卉生长的几个阶段显示所有细胞和细胞壁，并添加到这些模型的壁的物理特性（通过几种生物物理方法测量）以及创建细胞壁并调节花卉形状的基因表达模式。通过比较这些模式，团队将提出关于改变基因表达和改变机械性能的组合的假设，从而导致细胞形状和大小的变化，从而导致花形的发展。他们将通过实验更改墙壁机械性能来测试假设和模型，并查看计算机模型是否预测了实验中看到的形状变化。结果将为作物植物提供广泛适用的工具，使研究人员和育种者能够使用有助于建立花卉形状的基因和过程。教育努力专注于培训学生和培训后的跨学科方法，合并生物学和数学建模。本项目将开发一种称为“可计算花”的工具，该工具允许用户（i）基于通过机械模型的数据支持的基于数据支持的假设来集成几何，基因表达和（II）的几何数据，基因表达和（II）。因此，该工具以生长花蕾的3D动态模板的形式提供了集成的描述。可计算的花将填充现有或新颖的定量数据集，该数据集来自有关调节分子（例如转录因子和激素）的空间分布的实验和计算技术，以及与细胞壁合成和重塑相关的基因的空间表达模式，这些模式可在这些调节网络中操作下游和上游。有关开发花的结构元素的空间组织和特性的信息，包括细胞壁刚度，微管方向和纤维素微纤维组织。之后，将包括时间信息，显示基因表达，组织的机械性能以及几何形状的变化的相关性。与实验数据相比，这将导致有关生化，物理和几何特性的计算模型和假设，并具有定量的模拟结果。来自建模的预测将使用影响微管和壁状态的基因的域特异性扰动指导实验。然后，这些转基因线将进行详细的定量生长研究，以测试模型的有效性或完善模型。总体结果将是从基因型中计算花卉表型的途径，该型号包括组织的机械性能及其在形态发生中的作用。更广泛的影响将包括在实验和计算发展生物学结合使用的农业中的潜在应用，以及对学生和博士后的培训。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的审查标准通过评估来进行评估的。