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

2020 财年 NSF 生物学博士后奖学金：开发玉米分生组织模型以评估 CLAVATA 信号对产量性状的影响

基本信息

批准号：
2010642
负责人：
Penelope Lindsay
金额：
$ 21.6万
依托单位：
Lindsay, Penelope L
依托单位国家：
美国
项目类别：
Fellowship Award
财政年份：
2021
资助国家：
美国
起止时间：
2021-01-01 至 2023-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2010642&HistoricalAwards=false
关键词：
NSF Postdoctoral Fellowship Biology FY

项目摘要

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.

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。该奖学金支持该研究员在主办实验室的研究和培训计划，该研究员还提出了一项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，每年生产3.84亿吨。随着环境的变化和全球人口的迅速增长，我们需要最大限度地提高玉米产量，同时最大限度地减少农业用地的使用。提高单株玉米产量的一种方法是增加每穗的种子产量。玉米穗由一组称为顶端分生组织的未分化干细胞产生。玉米品系之间微妙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发挥作用来调节分生组织并形成穗和种子。玉米品系非常多样化，这将有助于我们发现这些基因网络的差异如何有助于形成玉米穗。该项目将为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纽约布鲁克林社区实验室 GenSpace 的高中生和教师植物生物学培训进行。该项目旨在通过分析嵌套关联图谱 (NAM) 的创建者（分生组织和花序大小各异的多种玉米品系）来了解玉米穗发育的复杂调控。这些品系的精确表型和转录组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中调节空间和定量基因表达，以生成对玉米产量影响的预测。这些预测可应用于精准育种，以最大限度地提高单株产量、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出版物中共享，并在国家科学会议上展示。此外，该项目生成的转录组数据将上传至 NCBI 基因表达综合库 (https://www.ncbi.nlm.nih.gov/geo/)。通过对玉米花序分生组织的遗传控制进行建模而生成的代码将在 GitHub (https://github.com/) 上共享。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。