NSF Postdoctoral Fellowship in Biology FY 2021: Establishing parametric variability as a driver of plasticity across genotypes with diverse life histories ...

本行动资助2021财年美国国家科学基金会植物基因组生物学博士后研究奖学金。该奖学金支持奖学金获得者在主办实验室的研究和培训计划，该奖学金获得者还提出了扩大生物学参与的计划。Renee Dale奖学金的研究和培训计划的标题是“通过新颖的数学建模框架，建立参数变异性作为具有不同生活史的基因型可塑性的驱动因素”。该奖学金的主办机构是Donald Danforth植物科学中心，赞助科学家是Ivan Baxter博士和Shankar Mukherji博士。气候变化增加了极端环境条件发生的频率和严重程度。具有灵活性（“可塑性”）的生物体可以迅速适应这些变化。植物需要特别灵活，因为如果环境突然改变，它们就无法移动。确定允许灵活性的机制变得越来越重要。由于了解整个植物生命周期的可塑性需要大量的信息，因此需要模型和计算方法。提出了一种新的方法，利用来自不同环境的数百种植物来识别植物的灵活性。据推测，来自极端环境的植物会更灵活，有更多的生长模式。建模将用于识别不同的增长模式，并了解潜在的机制。研究结果可用于植物育种计划，以提高作物的抗逆性，该方法可用于了解其他物种的生长情况。拟议的研究将为PI提供数学（生物随机性），生物学（定量遗传学，生态学和植物生理学）和计算（Python编码和高性能计算）方面的培训和发展机会。这项工作的影响将通过开发和传播一款教育电子游戏来扩大，旨在提高代表性不足的个人的多样性和包容性。这款电子游戏将以一种轻松的方式向高中生介绍这些概念，避开社会对数学的负面看法。将开发一个新的数学模型框架，以确定具有不同生态进化背景的数百种植物基因型的可塑性驱动过程。将应用一系列植物生理和生长过程的数学模型。模型参数将使用贝叶斯参数估计来估计，提供基因型内部和基因型之间的参数分布。这将提供一个概念性框架，通过整合数学、计算和生物学理论来理解可塑性。驱动可塑性的过程具有农业意义，因为作物适应和响应日益增加的环境胁迫的能力是至关重要的。模型参数将映射到基因组位点，这可以用于育种计划，以测试模型预测，这些位点将赋予可塑性，并改善作物植物。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This action funds an NSF Plant Genome Postdoctoral Research Fellowship in Biology for FY 2021. The fellowship supports a research and training plan in a host laboratory for the Fellow who also presents a plan to broaden participation in biology. The title of the research and training plan for this fellowship to Renee Dale is "Establishing parametric variability as a driver of plasticity across genotypes with diverse life histories through a novel mathematical modeling framework". The host institution for the fellowship is the Donald Danforth Plant Science Center and the sponsoring scientists are Dr. Ivan Baxter and Dr. Shankar Mukherji.Changes in climate increase the frequency and severity of extreme environmental conditions. Organisms with the ability to be flexible (“plasticity”) can rapidly adapt to these changes. Plants need to be especially flexible since they cannot move if their environment suddenly changes. Identifying the mechanisms that allow flexibility is increasingly important. Due to the amount of information needed to understand plasticity throughout the plant life cycle, models and computational approaches are needed. A new method is proposed to identify ways that plants are flexible using hundreds of plants coming from diverse environments. It is hypothesized that plants from extreme environments will be more flexible, with more modes of growth. Modeling will be used to identify different modes of growth and understand the underlying mechanisms. The results could be used in plant breeding programs to improve crop resilience and the approach can be used to understand the growth of other species. The proposed research will provide the PI with training and development opportunities in mathematics (biological stochasticity), biology (quantitative genetics, ecology, and plant physiology), and computation (Python coding and high-performance computing). The impact of this work will be broadened through the development and dissemination of an educational video game, intended to improve diversity and inclusion of under-represented individuals. The video game will introduce these concepts to high school students in a low-stress way, circumventing the negative social perceptions of math.A novel mathematical modeling framework will be developed to identify processes driving plasticity across hundreds of plant genotypes with diverse eco-evolutionary backgrounds. A family of mathematical models of plant physiology and growth processes will be applied. Model parameters will be estimated using Bayesian parameter estimation, providing parametric distributions within and between genotypes. This will provide a conceptual framework to understand plasticity by integrating mathematical, computational, and biological theory. Processes driving plasticity have agricultural significance, as the ability of crops to adapt and respond to increasing environmental stress is paramount. Model parameters will be mapped to genomic loci, which could be used in breeding programs to test model predictions that such loci will confer plasticity, and to improve crop plants.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.