Enhancing stress tolerance using a phase-dependent stress response

气候变化威胁着全球农作物产量。这些威胁的频率、类型和严重程度因地理位置而异。因此，跨纬度地区种植的作物需要不同的应对策略。为了确保作物生产的未来，该项目将应用基于植物生物钟的富有想象力的作物改良模型，生物钟是一种内部计时器，使植物能够根据日长协调生长与环境。这种内部振荡器，很像人类的生物钟，控制着一天中生理和新陈代谢发生变化的时间。因此，处于压力下的植物会在一天中的特定时间开启和关闭某些基因，以调节生理反应。与压力反应相关的能源成本很高，虽然无限期地启动这些基因可以提供压力耐受性，但它往往会导致产量的显着下降。该项目将测试是否可以通过微调这些基因的开启和关闭来改变反应的时间，并监测对生长的生理影响，从而实现耐冷性。这些测试将在模式植物拟南芥和作物Brassica Rapa上进行，Brassica Rapa是一种多样化的作物，包括大白菜、萝卜、油籽和叶菜品种，这些品种具有广泛的耐寒特性有待研究。科学界将获得用于创建这些修饰的方法和工具，以允许在其他作物系统中针对各种胁迫实施以提高整个美国的产量。目前用于非生物胁迫改良的模型通常依赖于已识别的转录因子(TF)的过度表达，这些转录因子提供了更好的胁迫响应，但以整体生长和产量为代价。作为环境信号的中央积分器，生物钟在维持适当的生理过程的同时，为优化对环境的反应提供了独特的目标。该项目将来自不同甘蓝型油菜和拟南芥的依赖时间的转录组和生理冷胁迫数据整合到时间基因调控网络(GRN)中。这些GRN将被用来识别与耐寒基因相关的时间胁迫调节因子(TSR)。表现耐受和敏感基因之间的时间反应改变的TSR将被选为相依赖的TSR合成结构。CRISPR/Cas9技术将被用来调整敏感基因中天然TSR的表达，以模拟在耐受基因中观察到的模式。将利用PSII效率、生长速率、开花时间和生物量等生理指标来测试这些整合到昼夜节律和/或Diel网络中的相变TSR是否提高了抗逆性。对成功改变的基因类型进行转录组分析将以时间分辨率进行，以确定GRN重组的程度并改进未来的模型预测。除了提供将这种方法应用于其他作物的数据分析工具和技术外，还将向中学生引入植物胁迫教育模块，向他们介绍植物生物学，并帮助他们为基于STEM的职业生涯做好准备。该奖项由植物基因组研究计划和综合组织系统部门的生理机制和生物力学计划共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Climate change threatens global crop production. These threats vary in frequency, type and severity depending on geographic location. As a consequence, crops grown across latitudinal zones require diverse coping strategies. To ensure the future of crop production, this project will apply an imaginative model for crop improvement based on the plant’s circadian clock, an internal timekeeper that enables plants to coordinate growth with the environment in accordance with the daylength. This internal oscillator, much like the human circadian clock, controls when physiological and metabolic changes occur throughout the day. As a result, plants under stress turn on and off certain genes at specific times of day to modulate physiological responses. The energy cost associated with a stress response is high and while turning these genes on indefinitely can provide stress tolerance it often leads to a significant reduction in yield. This project will test whether cold stress tolerance can be achieved by modifying the timing of the response through fine-tuning when these genes are turned on and off and monitoring the physiological impact on growth. These tests will be performed in the model plant Arabidopsis and crop Brassica rapa, a diverse crop that includes Chinese cabbage, turnip, oilseed and leafy vegetable varieties that have a wide range of cold tolerance traits to be studied. The methods and tools used to create these modifications will be made available to the scientific community to allow for implementation in other crop systems against a variety of stresses to improve yield throughout the U.S.Current models for abiotic stress improvement often rely on over-expression of identified transcription factors (TFs) that confer improved stress response but come at a cost to overall growth and yield. As a central integrator of environmental signals, the circadian clock provides a unique target for optimizing responses to the environment while maintaining proper physiological processes. This project incorporates time dependent transcriptome and physiological cold stress datasets from diverse B. rapa and Arabidopsis genotypes into temporal gene regulatory networks (GRNs). These GRNs will be used to identify Temporal Stress Regulator (TSR) TFs that are associated with cold tolerant genotypes. TSRs showing altered temporal responses between tolerant and sensitive genotypes will be selected for phase-dependent TSR synthetic constructs. CRISPR/Cas9 techniques will be used to adjust the expression of the native TSR in the sensitive genotype to mimic the pattern observed in the tolerant genotype. These phase-altered TSRs that are integrated into the circadian and/or diel networks will be tested for improved stress tolerance using physiological measures of PSII efficiency, growth rate, flowering time and biomass. Transcriptome profiling of successfully altered genotypes will be performed with temporal resolution to identify the degree of GRN reorganization and improve future model predictions. In addition to providing data analysis tools and techniques for applying this method to other crops, a plant stress education module will be introduced to middle school students to introduce them to plant biology and help prepare them for STEM-based careers.This award was co-funded by the Plant Genome Research Program and the Physiological Mechanisms and Biomechanics Program in the Division of Integrative Organismal Systems.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.