RESEARCH-PGR: Exploring the genetics of drought resistance with field-based phenomics and biophysical process-based modeling

无论环境条件如何，植物都需要适当的水化状态。尽管这是植物生命的基本特性，但负责调节植物水分状态的遗传和分子过程尚未完全了解。这种知识的缺乏限制了种植能够在更少的水分下茁壮成长或能够抵御极端气候的作物的能力。该项目旨在通过将生理和分子性状数据与计算方法相结合来揭示控制植物水分状态的机制，从而解决这一知识差距。棉花是世界上最重要的纤维作物，它将被用于研究基因表达与确保干旱条件下生长和生产力的关键、适应压力的植物性状的可量化变化之间的关系。利用这些数据，将开发一个计算模型来模拟棉花生长对环境和土壤水分条件的响应，以便在计算机上测试植物性状的各种组合，以预测植物在各种条件下的表现。该项目将提供数据和工具，帮助确定和量化负责赋予干旱适应能力的遗传机制。获得的信息可以被更广泛的社区用于作物改良和水资源管理——这是一个关键方面，因为农业受到可用水资源减少的威胁。这些工具和技术还将被整合到本科生的研究机会中，以帮助为下一代科学家提供培训和教育，以应对气候变化造成的生存威胁所导致的作物不安全问题。控制和调节作物水分运动的遗传机制尚不清楚，这限制了在缺水条件下提高作物抗逆性的能力。这种知识差距的存在是因为表征基因型特异性抗旱性状的方法是时间和劳动密集型的，并且不能扩展到遗传信息丰富的人群。此外，目前严重缺乏量化基因型变异和生理表现变化之间的功能联系的方法，这些联系是在响应波动的环境条件的时间基础上进行的。弥补这一差距的一种方法是使用基于生物物理过程的模型（bpm），它基于基本的物理、化学和生物学理论模拟复杂系统。本项目旨在通过：1)确定在干旱条件下生长的植物以转录和生物物理机制为特征的分子和表型响应的时间动态；2)利用这些数据开发能够模拟基因型特异性参数的BPM，以捕获对水分限制的驯化反应；3)利用表征棉花水分平衡生理过程的模型衍生表型揭示棉花抗旱性的遗传基础。总之，我们的建议旨在缩小抗旱性的基因型与表型差距，以提高作物的抗旱性，同时为剖析作物植物的应力适应性状提供一个范例。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。

Plants require proper hydration status regardless of environmental conditions. Despite this fundamental property of plant life, the genetic and molecular processes responsible for regulating plant water status are not fully understood. This lack of knowledge limits the ability to develop crops that can thrive with less water or are able to withstand climatic extremes. This project seeks to address this knowledge gap by combining physiological and molecular trait data with computational approaches to reveal the mechanism(s) responsible for controlling plant water status. Cotton, the world’s most important fiber crop, will be used to study how gene expression relates to quantifiable changes in key, stress-adaptive plant traits responsible for ensuring growth and productivity under drought conditions. Using these data, a computational model will be developed to simulate cotton growth in response to environmental and soil water conditions so that various combinations of plant traits can be tested in silico to predict how plants may perform under a variety of conditions. This project will provide data and tools to help identify and quantify the genetic mechanisms responsible for conferring drought adaptation. Information gained can be used by the broader community for crop improvement and managing water resources – a critical aspect as agriculture is threatened by reduced water availability. The tools and techniques will also be integrated into undergraduate research opportunities to help provide training and education for the next generation of scientists to combat crop insecurity due to existential threats posed by climate change. The genetic mechanisms that control and regulate water movement in crop plants is poorly understood, limiting the ability to enhance crop resiliency under water limited conditions. This knowledge gap exists because the methods for characterizing genotype-specific drought resistance traits are time and labor intensive and do not scale to genetically informative populations. Additionally, current methods to quantify the functional connections between genotypic variation and altered physiological performance on a temporal basis in response to fluctuating environmental conditions are severely lacking. One approach to bridge this gap is the use of biophysical process-based models (BPMs), which simulate complex systems based on fundamental physical, chemical, and biological theory. This project aims to address the lack of knowledge surrounding the genetic mechanisms controlling plant water dynamics by: 1) determining the temporal dynamics of molecular and phenotypic responses characterized by transcriptional and biophysical mechanisms in plants grown under drought conditions; 2) utilizing these data to develop a BPM capable of simulating genotype-specific parameters that capture acclimation response to water limitation; and 3) uncovering the genetic basis of drought resistance in cotton by using model-derived phenotypes that represent the physiological processes regulating water balance in cotton. In sum, our proposal seeks to close the genotype-to-phenotype gap for drought resistance to improve crop resiliency while providing a paradigm for dissecting stress-adaptive traits in 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.