NSF Postdoctoral Fellowship in Biology FY 2020: Untangling the Environmental and Genetic Drivers of Phenological Timing in Red Oak (Quercus rubra) to Improve Predictions

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。Meghan Blumstein这一奖学金的研究和培训计划的标题是《解开红橡树(Quercus Rubra)物候时间的环境和遗传驱动因素以改进气候预测》。该奖学金的主办机构是功能生态和进化中心(蒙彼利埃，FR)和麻省理工学院(MIT)，赞助科学家是David des Marais博士和Isabelle Chuine博士。森林每年通过光合作用吸收很大比例的碳排放，使其成为减缓全球变化的关键参与者。因此，了解树木每年开始和结束光合作用的时间对于预测未来变暖至关重要。广泛的研究表明，树木的落叶时间受遗传和环境两方面的影响。然而，到目前为止，还没有研究将我们对这两个驱动因素的理解及其相互作用结合到一个框架中。这项研究将通过阐明环境和遗传如何相互作用来改变北美红橡树(Quercus Rubra)的落叶时间来满足这一需求。更广泛的影响包括扩大来自代表性不足群体的学生的参与，以及产生新的基因组和表型资源，这些资源将提高预测落叶时间的能力，并为制定旨在加快适应当地环境变化的个体向北迁移的辅助迁徙保护方案提供指导。该研究员的培训目标包括基因组学、基因表达谱、生态生理学和基于过程的建模。该项目将以一种新颖的方式利用广泛分布的物候相机系统(物候摄像头)来量化红橡树落叶变异的遗传和环境驱动因素，并将其整合到基于过程的模型中。具体目标包括：1)对生长在Pphocam“视棚”中的红橡树个体进行基因测序。这些序列将被用于推导种群结构并开发一组与物候计时相关的候选基因座；2)实验操作从一组个体的萌发后收集的树枝，以解析出导致变异的环境和遗传驱动因素；3)通过转录组学收集基因表达数据，以进一步精炼候选基因座；以及4)修改现有的基于过程的模型结构，以测试有关纳入种群结构、遗传变异和局部适应如何改善模型性能和改变我们的预测的假设。该项目将通过旨在增加STEM领域多样性的暑期和学期计划，为研究生和本科生提供广泛的指导和研究培训。此外，该研究员将通过美国和法国国家物候学网络的公民科学项目参加公共推广活动，通过麻省理工学院政策实验室参与公民参与，并指导所有基因组数据将在硬木基因组项目开源数据库(https://www.hardwoodgenomics.org/).Keywords：生命规则、预测建模、基因组学、基因x环境相互作用、使用物候学相机获取图像、红橡树(Quercus Rubra))上公开提供。

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 Meghan Blumstein is "Untangling the Environmental and Genetic Drivers of Phenological Timing in Red Oak (Quercus rubra) to Improve Climate Predictions". The host institutions for the fellowship are the Center for Functional Ecology and Evolution (Montpellier, FR) and the Massachusetts Institute of Technology (MIT) and the sponsoring scientists are Drs. David Des Marais and Isabelle Chuine. Forests absorb a large proportion of carbon emissions each year via photosynthesis, making them a key player in mitigating global change. Thus, knowing when trees start and end photosynthesis each year is essential to predicting future warming. Extensive research has shown that the timing of leaf-out in trees is governed by both genetics and environment. However, no study to date has combined our understanding of these two drivers and their interaction into one framework. This study will address this need by elucidating how environment and genetics interact to alter leaf-out timing in the North American species red oak (Quercus rubra). Broader impacts include broadening participation of students from underrepresented groups and the generation of new genomic and phenotypic resources that will improve the ability to predict leaf-out timing and provide guidance for setting up assisted migration conservation programs aimed to speed the movement of locally adapted individuals northward in pace with environmental change. Training objectives for the Fellow include genomics, gene expression profiling, ecophysiology, and process-based modeling. This project will leverage a wide-spread system of phenological cameras (phenocams) in a novel way to quantify the genetic and environmental drivers of leaf-out variation in red oak and integrate this into a process-based model. Specific objectives include: 1) genetically sequencing red oak individuals growing in phenocam "viewsheds". These sequences will be used to derive population structure and develop a set of candidate loci associated with phenological timing; 2) experimentally manipulating twigs collected after budset from a subset of individuals to parse out the environmental versus genetic drivers of variation; 3) collecting gene expression data via transcriptomics to further refine candidate loci; and, 4) modifying existing process-based model structures to test hypotheses regarding how the inclusion of population structure, genetic variation, and local adaptation can improve model performance and alter our predictions. This project will provide a broad array of mentoring and research training for graduate and undergraduate students via summer and term-time programs aimed at increasing diversity in STEM fields. In addition, the Fellow will participate in public outreach via the U.S. and French National Phenological Networks' citizen science programs, civic engagement via the MIT Policy Lab, and mentoring All genomic data will be made publicly available on the Hardwood Genomics Project open-source database (https://www.hardwoodgenomics.org/).Keywords: Rules of Life, predictive modeling, genomics, genotype x environment interactions (GxE), image acquisition using phenological cameras, red oak (Quercus rubra)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.