LiT: Life History Responses to Genetic and Environmental Perturbations in Arabidopsis thaliana

LiT：拟南芥生活史对遗传和环境扰动的反应

• 批准号: 0924059
• 负责人: Johanna Schmitt
• 金额: $ 60万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0924059&HistoricalAwards=false
• 关键词: LiT; Life; History; Responses; Genetic

In order to flower during favorable conditions, plants use information from multiple environmental signals, such as day length, temperature, and winter chilling. However, global warming will alter not only temperatures, but also the timing and length of the growing season, and may thus create a mismatch between formerly accurate cues and the actual timing of those events. For example, warmer winters may not allow sufficient chilling to trigger flowering, resulting in delayed flowering despite earlier spring warming. This project will therefore explore the sensitivity of seasonal timing to genetic and environmental change. The study will take advantage of information and tools available for the genetic model species Arabidopsis thaliana, a weedy annual relative of crops such as canola, cabbage, broccoli, turnips, and mustard. It will combine a predictive mathematical model with field and controlled chamber experiments. The research will ask: 1. How does genetic variation in winter chilling requirements affect flowering time in natural seasonal environments? 2. How does natural selection act upon this variation in natural environments? 3. How will higher temperatures predicted by global warming scenarios affect seasonal timing of flowering? Predictions of the model will be tested experimentally in controlled chamber environments simulating effects of warming temperatures predicted for the end of the 21st century. If the model is accurate, warming temperatures and reduced winter chilling will alter seasonal timing and the relative timing of different genetic variants. Accurate timing of plant seasonal events - such as leaf emergence, flowering, fruiting and senescence - is critical for crop and forestry yields, as well as for the survival of wild species in the face of climate change. The results of this study will therefore be important for predicting how crops, weeds, forest trees, and wild plant communities will respond to global warming. The modeling approach will be a significant advance from traditional crop models and may improve their generality and predictive ability. This project will provide career opportunities and training for two female scientists: a postdoctoral researcher and a Ph.D researcher returning to the workforce after a career interruption. It will also provide research opportunities to several undergraduates, and will support development of a classroom module on plant responses to climate change for Rhode Island high school teachers.

为了在有利的条件下开花，植物利用来自多种环境信号的信息，如白天的长度，温度和冬季寒冷。然而，全球变暖不仅会改变温度，还会改变生长季节的时间和长度，因此可能会在以前准确的线索和这些事件的实际时间之间造成不匹配。例如，温暖的冬天可能不允许足够的寒冷来触发开花，导致尽管春季变暖较早，但开花延迟。因此，本项目将探讨季节性时间对遗传和环境变化的敏感性。这项研究将利用遗传模式物种拟南芥（Arabidopsis thaliana）的信息和工具，拟南芥是油菜、卷心菜、花椰菜、芜菁和芥菜等作物的一年生杂草。 它将联合收割机与现场和控制室实验相结合。该研究将问：1。冬季需冷量的遗传变异如何影响自然季节环境中的开花时间？2.在自然环境中，自然选择是如何作用于这种变异的？3.全球变暖情景预测的更高温度将如何影响季节性开花时间？该模型的预测将在受控室环境中进行实验测试，模拟预测的21世纪末变暖温度的影响。如果该模型是准确的，那么气温升高和冬季寒冷减少将改变季节性时间和不同遗传变异的相对时间。植物季节性事件-如叶片出现、开花、结果和衰老-的准确时间对于作物和林业产量以及面对气候变化的野生物种的生存至关重要。因此，这项研究的结果对于预测农作物、杂草、林木和野生植物群落如何应对全球变暖至关重要。该建模方法将是传统作物模型的一个重大进步，并可能提高其通用性和预测能力。该项目将为两名女科学家提供职业机会和培训：一名博士后研究员和一名博士研究员在职业中断后重返工作岗位。它还将为几名本科生提供研究机会，并将支持为罗得岛高中教师开发一个关于植物对气候变化的反应的课堂模块。