Dosage dependent genes affecting seed composition and weight

合作者：George Casella(佛罗里达大学)、L.Curtis Hannah(佛罗里达大学)和Tamer Kahvei(佛罗里达大学)谷物产量和谷物组成是改善粮食安全和减少农业对环境影响的两个重要目标。谷物表现出籽粒中蛋白质、油和淀粉的数量和质量的遗传变异。人们对控制种子重量和种子成分的分子机制知之甚少。该项目的目标是确定影响玉米种子重量和种子组成的新基因。该项目将重点研究对籽粒有剂量效应的基因。随着正常等位基因数量的增加，剂量效应基因呈现逐步变化，而不是大多数基因的显性-隐性关系。该项目的假设是，这些基因将识别对控制种子成分或种子重量至关重要的关键生物学过程。该项目将开发一种新型的单粒分析仪，利用种子重量和近红外反射光谱来确定单个种子的成分。然后，籽粒分析仪将被用来筛选分离出种子成分或重量差异的玉米家族。表现出与剂量效应一致的分离比的家系将在多个田间环境中进行遗传力测试。最后，将使用基因组学方法来识别与剂量效应有关的突变基因。这项研究预计将识别大约10到20个具有种子剂量效应的基因，以及50个表现出剂量敏感表型的种子突变体。这些结果意义重大，因为它们有望对生物过程有一个新的理解，这些过程对于确定谷物中的最终种子成分和重量至关重要。这些知识将为开发具有理想谷物性状的粮食作物提供基础。更广泛的影响：该项目将在四个层面产生更广泛的影响。(A)研究计划采用跨学科方法，包括：植物遗传学、分子生物学、分析化学、工程学、统计学和计算机科学，以确定与数量籽粒性状有关的基因。这些基因很可能会对谷类种子重量或谷类营养成分产生重大影响。种子重量基因可用于提高产量，而种子组成基因可用于提高人和动物饲料的营养价值。该项目将产生数量性状数据，UniformMu系的侧翼序列标签，确认的生发转座子插入位点，剂量效应突变库，以及对现有核分析仪的改进。所有量化核心数据将通过一个项目网站(待开发)和通过Gramene获得。侧翼序列标签将提交给GenBank GSS数据库，随后的序列分析可在UniformMu项目网站(http://currant.hos.ufl.edu/mutail/).)上获得(B)将开发新的研究工具。该谷物分析仪可用于测定其他谷物和生物样品的成分。分析仪的设计将通过美国农业部谷物营销和生产研究中心(GMPRC)(www.gmprc.ksu.edu)免费提供。(C)开发新的生物资源。该项目将确定基因敲除基因，并将其提交给玉米遗传合作社库存中心，以便分发给其他研究人员。(D)博士后、研究生、本科生和高中生培训是研究计划的一个组成部分。重要的是，本科生研究人员将通过与一所历史悠久的黑人大学合作招募，高中生培训将针对经济困难的学生。

PI: A. Mark Settles (University of Florida)Collaborators: George Casella (University of Florida), L. Curtis Hannah (University of Florida), and Tamer Kahveci (University of Florida)Cereal yield and grain composition are two important targets for improving food security and reducing the environmental impact of agriculture. Cereals show genetic variation in the amount and quality of protein, oil, and starch within the kernel. Little is known about the molecular mechanisms that control seed weight and seed composition. The objective of this project is to identify novel genes that impact seed weight and seed composition in corn. The project will focus on genes with dosage effects on the kernel. Dosage-effect genes show stepwise changes as the number of normal alleles increases instead of the dominant-recessive relationship found for most genes. The project hypothesis is that these genes will identify key biological processes that are important in controlling seed composition or seed weight. The project will develop a novel single kernel analyzer that utilizes seed weights and near infrared reflectance spectroscopy to determine the composition of individual seeds. The kernel analyzer will then be used to screen for families of corn that segregate for differences in seed composition or weight. Families that show segregation ratios consistent with a dosage effect will be tested for heritability in multiple field environments. Finally a genomics approach will be used to identify the mutant genes responsible for the dosage effects. The research is expected to identify approximately ten to twenty genes that have seed dosage effects along with fifty seed mutants that show dosage sensitive phenotypes. These outcomes are significant, because they are expected to develop a novel understanding of the biological processes important for determining final seed composition and weight within cereals. This knowledge will provide a foundation to develop cereal crops with desired grain traits. Broader Impacts: The project will have broader impacts at four levels. (A) The research plan uses an interdisciplinary approach incorporating: plant genetics, molecular biology, analytical chemistry, engineering, statistics, and computer science to identify genes linked to quantitative kernel traits. These genes most likely will have significant impacts on cereal seed weight or cereal nutrient composition. Seed weight genes can be used to improve yield, while seed composition genes can be used to improve the nutritional value of human and animal diets. The project will generate quantitative trait data, flanking sequence tags for UniformMu lines, confirmed germinal transposon insertion sites, dosage-effect mutant stocks, and improvements on existing kernel analyzers. All quantitative kernel data will be available through a project website (to be developed) and through Gramene. Flanking sequence tags will be submitted to the GenBank GSS database and subsequent sequence analyses available at the UniformMu project website (http://currant.hos.ufl.edu/mutail/). (B) New tools for research will be developed. The grain analyzer can be used to determine composition of other grains and biological samples. Analyzer design will be freely available through the USDA Grain Marketing and Production Research Center (GMPRC) (www.gmprc.ksu.edu). (C) New biological resources will be developed. The project will identify and submit gene knockouts to the Maize Genetics Cooperative Stock Center for distribution to other researchers. (D) Post-doctoral, graduate, undergraduate, and high-school student training is an integrated part of the research plan. Importantly, the undergraduate researchers will be recruited through a collaboration with a Historically Black University, and the high school student training will target economically disadvantaged students.