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

2020 财年 NSF 生物学博士后奖学金：利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响应

• 批准号: 2010686
• 负责人: Trevor Nolan
• 金额: $ 21.6万
• 依托单位: Nolan, Trevor M
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2010686&HistoricalAwards=false
• 关键词: NSF; Postdoctoral; Fellowship; Biology; FY

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.

该行动资助了2020财年NSF国家植物基因组计划生物学博士后研究奖学金。该研究金支持研究员在东道实验室的研究和培训计划，研究员还提出了扩大生物学参与的计划。本奖学金的研究和培训计划的标题为特雷弗M博士。Nolan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Philip N.本报告指出，干旱是一种破坏性的环境压力，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可以提高干旱期间植物存活率的策略;然而，已被证明可以提高抗旱性的大多数因素都与植物生长和生产力下降有关。为了使植物生长良好并能抵御干旱，重要的是要了解干旱反应发生的时间和地点，以及一旦干旱消退，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性。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。为了提高对科学的更广泛参与，研究员还将指导来自东道实验室机构代表性不足群体的学生。为了确定对干旱和恢复的时空响应，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，基因表达将在干旱胁迫和恢复后的不同时间以单细胞分辨率进行分析。这将允许构建空间和时间分辨的基因调控网络，用于优先考虑参与抗旱和恢复的基因。这些预测将在生物组织的几个层次上进行测试，包括通过共聚焦和光片显微镜观察细胞和组织，使用延时成像进行全植物干旱表型，以及在两个物种之间进行测试：拟南芥和水稻。包括一个模式植物，拟南芥，将允许预测进行快速和全面的测试。对水稻这一重要作物的平行分析将使已鉴定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，预测模型和植物线将公开提供，并作为一个宝贵的资源，以指导未来的干旱研究。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Protocol for fast scRNA-seq raw data processing using scKB and non-arbitrary quality control with COPILOT.

• DOI: 10.1016/j.xpro.2022.101729
• 发表时间: 2022-12-16
• 期刊: STAR PROTOCOLS
• 作者: Hsu, Che-Wei;Shahan, Rachel;Nolan, Trevor M.;Benfey, Philip N.;Ohler, Uwe
• 通讯作者: Ohler, Uwe

A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants.

• DOI: 10.1016/j.devcel.2022.01.008
• 发表时间: 2022-02-28
• 期刊: DEVELOPMENTAL CELL
• 影响因子: 11.8
• 作者: Shahan, Rachel;Hsu, Che-Wei;Nolan, Trevor M.;Cole, Benjamin J.;Taylor, Isaiah W.;Greenstreet, Laura;Zhang, Stephen;Afanassiev, Anton;Vlot, Anna Hendrika Cornelia;Schiebinger, Geoffrey;Benfey, Philip N.;Ohler, Uwe
• 通讯作者: Ohler, Uwe

Single-cell analysis of cell identity in the Arabidopsis root apical meristem: insights and opportunities.

• DOI: 10.1093/jxb/erab228
• 发表时间: 2021-05
• 期刊: Journal of experimental botany
• 影响因子: 6.9
• 作者: R. Shahan;Trevor M. Nolan;P. Benfey

Brassinosteroid gene regulatory networks at cellular resolution in the Arabidopsis root.

• DOI: 10.1126/science.adf4721
• 发表时间: 2023-03-31
• 期刊: SCIENCE
• 影响因子: 56.9
• 作者: Nolan, Trevor M.;Vukasinovic, Nemanja;Hsu, Che-Wei;Zhang, Jingyuan;Vanhoutte, Isabelle;Shahan, Rachel;Taylor, Isaiah W.;Greenstreet, Laura;Heitz, Matthieu;Afanassiev, Anton;Wang, Ping;Szekely, Pablo;Brosnan, Aiden;Yin, Yanhai;Schiebinger, Geoffrey;Ohler, Uwe;Russinova, Eugenia;Benfey, Philip N.
• 通讯作者: Benfey, Philip N.

Plasmodesmata mediate cell-to-cell transport of brassinosteroid hormones

• DOI: 10.1038/s41589-023-01346-x
• 发表时间: 2023-06
• 期刊: Nature chemical biology
• 影响因子: 14.8
• 作者: Yaowei Wang;Jessica Pérez-Sancho;M. Platre;B. Callebaut;M. Smokvarska;Karoll Ferrer;Yongming Luo;Trevor M. Nolan;Takeo Sato;Wolfgang Busch;P. Benfey;M. Kvasnica;Johan M. Winne;E. Bayer;Nemanja Vukašinović;E. Russinova