NSF Postdoctoral Fellowship in Biology FY 2020: Reconstructing spatial-temporal responses to drought in Arabidopsis and rice using time series single-cell transcriptomics

这一行动为NSF国家植物基因组计划2020财年生物学博士后研究奖学金提供了资金。该奖学金支持在东道主实验室为该研究员制定的研究和培训计划，该研究员还提出了扩大生物学参与度的计划。特雷弗·M·诺兰博士这一奖学金的研究和培训计划的标题是“使用时间序列单细胞转录组学重建拟南芥和水稻对干旱的时空反应”。该奖学金的主办机构是杜克大学，赞助科学家是菲利普·N·本菲博士。干旱是一种毁灭性的环境压力，造成数十亿美元的损失，并导致与天气有关的作物产量不稳定。大量的研究致力于确定在干旱期间可以提高植物存活率的策略；然而，已被证明提高抗旱性的大多数因素与植物生长和生产力下降有关。要培育长势良好并能抵御干旱的植物，重要的是要了解干旱反应发生的时间和地点，以及干旱平息后植物如何恢复。该项目将通过使用创新技术来应对这一挑战，该技术允许在单个细胞中监测基因活动。该研究员将从该项目中接受发育生物学、单细胞基因组学、生物信息学和实验室管理方面的培训。为了增加更广泛的科学参与，该研究员还将指导寄主实验室机构中代表性较低的群体的学生。为了确定干旱和恢复的时空反应，该研究员将使用涉及单细胞基因组学、计算建模和表型分析的综合方法。首先，在干旱胁迫和恢复后的不同时间，基因表达谱将在单细胞分辨率下进行。这将允许构建空间和时间分辨的基因调控网络，用于优先处理参与抗旱和恢复的基因。这些预测将在生物组织的多个水平上得到验证，包括通过共焦显微镜和光片显微镜的细胞和组织，使用时间推移成像的全植物干旱表型，以及跨两个物种：拟南芥和水稻。模型植物拟南芥的加入将使预测得到快速和全面的检验。对水稻这一重要作物的平行分析将使已识别的基因能够直接应用于改善作物在干旱期间的表现。由此产生的数据集、预测模型和植物路线将被公开提供，并作为指导未来干旱研究的宝贵资源。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。

This action funds an NSF National Plant Genome Initiative Postdoctoral Research Fellowship in Biology for FY 2020. 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 Dr. Trevor M. Nolan is "Reconstructing spatial-temporal responses to drought in Arabidopsis and rice using time series single-cell transcriptomics" The host institution for the fellowship is Duke University and the sponsoring scientist is Dr. Philip N. Benfey.Drought is a devastating environmental stress that causes billions of dollars in damages and contributes to weather-related instability in crop yield. A great deal of research has been devoted to identifying strategies that can improve plant survival during drought; however, the majority of factors that have been shown to promote drought resistance are associated with decreased plant growth and productivity. To engineer plants that grow well and withstand drought, it is important to understand when and where drought responses occur and how plants recover once drought subsides. This project will address this challenge through the use of innovative technology that allows gene activity to be monitored in individual cells. The Fellow will receive training in developmental biology, single-cell genomics, bioinformatics and lab management from this project. To increase broader participation in science, the Fellow will also mentor students from underrepresented groups at the host-lab institution.In order to define the spatio-temporal responses to drought and recovery the Fellow will use an integrated approach involving single-cell genomics, computational modeling, and phenotyping. First, gene expression will be profiled at single-cell resolution at different times after drought stress and recovery. This will allow construction of spatially and temporally resolved gene regulatory networks that will be used to prioritize genes involved in drought resistance and recovery. These predictions will be tested at several levels of biological organization including cells and tissues via confocal and light sheet microscopy, whole plant drought phenotypes using time lapse imaging, and across two species: Arabidopsis and rice. The inclusion of a model plant, Arabidopsis, will allow predictions to be quickly and comprehensively tested. Parallel analysis of rice, an important crop plant, will enable the direct application of the identified genes to improve crop performance during drought. The resulting datasets, predictive models and plant lines will be made publicly available and serve as a valuable resource to guide future studies on drought.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.