SGER: Isolating Quantitative Kernel Traits With Near Infrared Spectroscopy

SGER：利用近红外光谱分离定量内核性状

• 批准号: 0404560
• 负责人: Andrew Settles
• 金额: $ 10万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-12-01 至 2004-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0404560&HistoricalAwards=false
• 关键词: SGER; Isolating; Quantitative; Kernel; Traits

This Small Grant for Exploratory Research will provide proof of concept funding for the use of single-kernel near infrared reflectance (NIR) and transmittance (NIT) spectroscopy for high-throughput identification and genetic analysis of seed composition mutants of corn. This is a high-risk project because seed composition is highly variable, and the genetic basis of seed composition is poorly understood. This is in part because the biosynthetic pathways and physiological process that influence seed development are complex. In addition, these phenotypes are highly sensitive to environmental influence and therefore difficult to study. The approach is potentially of high payoff both because of high scientific interest in the processes that control seed composition, and because these traits have very high commercial value.Inbred Uniform Mu corn mutant populations will be screened for changes in oil, protein, carbohydrate and caloric content using NIR. Mutants will be tested for heritability. To gauge the relative effects of genotype versus environment, all putative mutants will be sampled from lines grown in two field seasons. Novel statistical methods will be developed for analyzing the complex data sets derived from NIR analysis.This project takes an interdisciplinary approach that incorporates novel engineering, plantgenetics, and statistical methods to isolate single-locus quantitative traits of agricultural importance. Because these traits are likely to be Mutator transposon-tagged, there is the potential to rapidly identify genes that affect quantitative compositional traits in corn seeds.

这项探索性研究的小额赠款将提供概念验证资金，用于使用单核近红外反射（NIR）和透射（NIT）光谱技术对玉米种子组成突变体进行高通量鉴定和遗传分析。这是一个高风险的项目，因为种子成分是高度可变的，种子成分的遗传基础知之甚少。这部分是因为影响种子发育的生物合成途径和生理过程是复杂的。此外，这些表型对环境影响高度敏感，因此难以研究。该方法是潜在的高回报，因为在控制种子成分的过程中的高度科学兴趣，因为这些性状具有非常高的商业价值。将使用近红外光谱筛选油，蛋白质，碳水化合物和热量含量的变化，自交的Uniform Mu玉米突变群体。将检测突变体的遗传性。为了衡量基因型与环境的相对影响，所有推定的突变体将从两个田间季节生长的品系中取样。本项目将开发新的统计方法，用于分析近红外分析的复杂数据集。本项目采用跨学科的方法，将新的工程学、植物遗传学和统计学方法结合起来，分离具有农业重要性的单基因座数量性状。由于这些性状很可能是Mutator转座子标记的，因此有可能快速鉴定影响玉米种子中数量组成性状的基因。