NSF Postdoctoral Fellowship in Biology FY 2020: Developing a maize meristem model to assess the impact of CLAVATA signaling on yield traits

本行动资助NSF国家植物基因组计划2020财年生物学博士后研究奖学金。该奖学金支持奖学金获得者在主办实验室的研究和培训计划，该奖学金获得者还提出了扩大生物学参与的计划。Penelope Lindsay博士的研究和培训计划的标题是“开发玉米分生组织模型，以评估CLAVATA信号对产量性状的影响”。该奖学金的主办机构是冷泉港实验室，赞助科学家是大卫·杰克逊博士。美国是世界上最大的玉米生产国，年产量为3.84亿吨。随着环境的变化和全球人口的迅速增长，我们需要在最大限度地减少农业用地的同时最大限度地提高玉米产量。提高玉米单株产量的一种方法是增加每穗的产子量。玉米穗起源于一组未分化的干细胞，称为顶分生组织。玉米品系之间细微的遗传变化会影响分生组织的生长，并对产量产生重大影响。该项目将建立一个计算框架，以了解基因如何共同调节分生组织并形成穗和种子。玉米品系非常多样化，这将成为我们发现这些基因网络差异如何影响玉米穗形成的优势。该项目将为该研究员提供玉米遗传学和基因组学方面的培训，以及通过合作研究收集的生物信息学和数学建模技术。植物遗传学的推广将通过在纽约布鲁克林的社区实验室GenSpace对高中生和教师进行植物生物学培训来实现。本项目旨在通过分析嵌套关联图谱（NAM）建立者来了解玉米穗发育的复杂调控。嵌套关联图谱是一组分生组织和花序大小都不同的玉米品系。这些系的精确表型和转录组学分析将为玉米花序分生组织模型的开发提供信息。该模型将用于在计算机上调节空间和定量基因表达，以预测对玉米产量的影响。这些预测可以应用于精确育种，以最大限度地提高每株作物的产量，减少土地使用并最大限度地减少农业环境影响。该项目产生的数据将在同行评审的出版物中共享，并在国家科学会议上发表。此外，本项目产生的转录组学数据将上传到NCBI基因表达综合数据库（https://www.ncbi.nlm.nih.gov/geo/）。通过对玉米花序分生系统的遗传控制建模生成的代码将在GitHub (https://github.com/).This)上共享，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值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. Penelope Lindsay is “Developing a maize meristem model to assess the impact of CLAVATA signaling on yield traits". The host institution for the fellowship is Cold Spring Harbor Laboratory and the sponsoring scientist is Dr. David Jackson.The U.S. is the world’s largest producer of maize, producing 384 million tons annually. With a changing environment and burgeoning global population, we need to maximize maize yield while minimizing agricultural land use. One way to increase maize yield per plant is to increase the amount of seed produced per ear. The maize ear arises from a group of undifferentiated stem cells called the apical meristem. Subtle genetic changes between maize lines affect meristem growth and can have big impacts on yield. This project will build a computational framework to understand how genes function together to regulate the meristem and to form the ear and seeds. Maize lines are very diverse, and this will be used to our advantage to find how differences in these gene networks contribute to making the maize ear. This project will provide the fellow with training in maize genetics and genomics, coupled with bioinformatics and mathematical modeling techniques gleaned through collaborative research. Outreach in plant genetics will occur through High School student and teacher training in plant biology at GenSpace, a community lab space in Brooklyn, NY.This project aims to understand the complex regulation of maize ear development through analysis of the nested association mapping (NAM) founders, a diverse panel of maize lines which vary in both meristem and inflorescence size. Precise phenotypic and transcriptomic analysis of these lines will inform the development of a maize inflorescence meristem model. The model will be used to modulate spatial and quantitative gene expression in silico to generate predictions for effects on maize yield. These predictions can be applied in precision breeding to maximize yield per plant, reducing land use and minimizing agricultural environmental impact. Data generated from this project will be shared in peer-reviewed publications and be presented at national scientific conferences. In addition, transcriptomic data generated from this project will be uploaded to the NCBI Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/). Code generated from modeling the genetic control of the maize inflorescence meristem will be shared on GitHub (https://github.com/).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.