An Integrated Phenomics Approach to Identifying the Genetic Basis for Maize Root Structure and Control of Plant Nutrient Relations

识别玉米根结构遗传基础和植物养分关系控制的综合表型组学方法

• 批准号: 1638507
• 负责人: Christopher Topp
• 金额: $ 393.05万
• 依托单位: Donald Danforth Plant Science Center
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638507&HistoricalAwards=false
• 关键词: Integrated; Phenomics; Approach; Identifying; Genetic

Increasing the yield and sustainability of crop production in a changing climate is one of the foremost challenges of our time. Corn is the most important crop in the United States, but despite steady increases in corn production, projected yields fall short of demands. Furthermore, petroleum-based nitrogen fertilizers have been identified as a primary driver of pollution of major waterways in the U.S. and globally. This project focuses on root systems, the "hidden-half" of plants, that are responsible for all of the water, nitrogen, and other nutrient acquisition. It leverages advanced imaging techniques, some of which were developed in the medical and industrial research sectors, to analyze the structure of root systems. Root structures from corn varieties that are known to be superior in nitrogen acquisition will be compared those that are inferior, and the genes that control root-nitrogen interactions will be identified. This will directly benefit corn and other crop breeders, and thus a major sector of U.S. agriculture, through identification of genes that control root growth and efficient nitrogen acquisition. An additional objective is to train the next generation of scientists by establishing after-school and summer educational programs for middle-school to undergraduate students. These trainees will gain first-hand experience building, programming, and employing plant imaging systems using 3D printers and affordable microprocessors.Realizing the enormous potential of root systems to boost and stabilize crop yields under stress and to reduce unsustainable levels of fertilizer use will require a thorough understanding of their genetics and physiology. Image-based phenotyping has enabled high-throughput and accurate measurements of roots, but despite many new and promising methods, each has inherent tradeoffs that limit their individual power. This project employs an integrated root phenomic and physiological profiling approach to resolve the genetic basis and functional consequences of maize root architecture. It will profile the root architecture of two maize populations in four complementary ways: 3D/4D imaging of young plants in a gel based system, optical and X-ray based imaging of root crowns excavated from the field, and minirhizotron imaging of roots growing across the soil profile in the field. Quantitative genetic analyses from each of these methods will allow identification of the genes controlling these traits. Additionally, this integrated analysis of identical genotypes will generate the most comprehensive comparison of root phenotyping methods to date. One population will be selected from screening of the NAM parent lines in the first two years of the project, the other population will be the Illinois Protein Strain Recombinant Inbreds (IPSRIs). Over five years, this approach will address the following aims: 1. Identify genes driving phenotypic variation of root architecture, 2. Identify genes controlling phenotypic plasticity of root architecture to nitrogen supply, 3. Determine the functional impacts of root architecture on plant nitrogen status, elemental content and seed quality.

在不断变化的气候中提高作物产量和可持续性是我们这个时代面临的最大挑战之一。玉米是美国最重要的作物，但尽管玉米产量稳步增长，预计产量仍低于需求。此外，石油基氮肥已被确定为美国和全球主要水道污染的主要驱动因素。该项目的重点是根系，植物的“隐藏的一半”，负责所有的水，氮和其他养分的获取。它利用先进的成像技术，其中一些是在医疗和工业研究部门开发的，以分析根系的结构。将已知在氮吸收方面具有上级的玉米品种的根结构与较差的品种进行比较，并鉴定控制根-氮相互作用的基因。这将直接有利于玉米和其他作物育种者，因此是美国农业的主要部门，通过识别控制根系生长和有效氮素吸收的基因。另一个目标是通过为中学到大学生建立课后和暑期教育方案来培养下一代科学家。这些学员将获得使用3D打印机和价格实惠的微处理器构建、编程和使用植物成像系统的第一手经验。要实现根系在逆境下提高和稳定作物产量以及减少不可持续的肥料使用水平方面的巨大潜力，需要对根系的遗传学和生理学有全面的了解。基于图像的表型分析已经实现了对根部的高通量和准确测量，但是尽管有许多新的和有前途的方法，但每种方法都有固有的权衡，限制了它们各自的能力。本项目采用综合的根系表型和生理分析方法来解决玉米根构型的遗传基础和功能后果。它将以四种互补的方式对两个玉米种群的根系结构进行分析：在基于凝胶的系统中对幼苗进行3D/4D成像，对从田间挖掘的根冠进行基于光学和X射线的成像，以及对田间土壤剖面中生长的根系进行微型电子成像。这些方法的定量遗传分析将允许识别控制这些性状的基因。此外，这种对相同基因型的综合分析将产生迄今为止最全面的根表型方法比较。在项目的前两年，将从NAM亲本系的筛选中选择一个群体，另一个群体将是伊利诺伊蛋白株重组近交系（IPSRI）。在五年内，这一方法将实现以下目标：1。确定驱动根构型表型变异的基因，2。确定控制根构型对氮素供应的表型可塑性的基因。确定根构型对植物氮素状况、元素含量和种子质量的功能性影响。

项目成果

Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures

• DOI: 10.1105/tpc.19.00015
• 发表时间: 2019-08-01
• 期刊: PLANT CELL
• 影响因子: 11.6
• 作者: Jiang, Ni;Floro, Eric;Topp, Christopher N.
• 通讯作者: Topp, Christopher N.

Comprehensive 3D phenotyping reveals continuous morphological variation across genetically diverse sorghum inflorescences

• DOI: 10.1111/nph.16533
• 发表时间: 2020-04-16
• 期刊: NEW PHYTOLOGIST
• 影响因子: 9.4
• 作者: Li, Mao;Shao, Mon-Ray;Topp, Christopher N.
• 通讯作者: Topp, Christopher N.

Segmenting Root Systems in X-Ray Computed Tomography Images Using Level Sets

• DOI: 10.1109/wacv.2018.00070
• 发表时间: 2018-03
• 期刊: 2018 IEEE Winter Conference on Applications of Computer Vision (WACV)
• 作者: A. Tabb;K. Duncan;C. Topp

The Persistent Homology Mathematical Framework Provides Enhanced Genotype-to-Phenotype Associations for Plant Morphology

• DOI: 10.1104/pp.18.00104
• 发表时间: 2018-08-01
• 期刊: PLANT PHYSIOLOGY
• 影响因子: 7.4
• 作者: Li, Mao;Frank, Margaret H.;Topp, Christopher N.
• 通讯作者: Topp, Christopher N.

Stomatal conductance, xylem water transport, and root traits underpin improved performance under drought and well-watered conditions across a diverse panel of maize inbred lines

• DOI: 10.1016/j.fcr.2019.02.001
• 发表时间: 2019-03-15
• 期刊: FIELD CROPS RESEARCH
• 影响因子: 5.8
• 作者: Gleason, Sean M.;Cooper, Mitchell;Comas, Louise H.
• 通讯作者: Comas, Louise H.