Quantitative Trait Locus Editing for Crop Improvement

作物研究取得的里程碑式的成就现在使人们能够利用创新的方法快速有效地应对棘手的挑战。这些成就包括DNA序列和与单个作物物种内大量品种的生产力和质量相关的特征的测量，强大的计算方法和数据管理工具，对植物生物学(包括对环境的反应)的日益详细的分子理解，以及精确测试特定DNA序列功能的新方法。在这些资源和工具的基础上，该项目将解决长期存在的挑战，即识别导致数量差异的性状的DNA序列，称为“数量性状座位”(QTL)，并使它们适合于作物改良。虽然QTL是作物生产力的关键决定因素，但对它们的研究一直非常困难，对它们的了解也很少。本项目重点研究水稻这一全球重要作物品种的抗病、感病和耐酸性土壤的QTL。该项目将分离与高水平的这些性状相关的DNA序列，并通过将它们转移到表现出低水平性状的水稻品种中并测量结果来测试这些序列是否起作用。该项目将提高对作物对病虫害和恶劣土壤条件造成的压力的抵抗力的了解，并提高作物生产力。更广泛地说，该项目将建立有效的方法，将个体之间的变异与导致这种变异的DNA序列联系起来，这不仅对植物研究有用，而且对包括医学在内的其他生命科学也很有用。该项目将进一步惠及社会，将其研究目标与教育活动和材料结合起来，这些活动和材料将使公众参与并告知公众，并增加代表不足群体的成员的参与。其中包括为小型大学本科生开设的综合课堂和研究体验计划，为植物生物学家举办的培训讲习班，吸引初中生参与的多媒体教育资源，以及一个供公众访问与项目相关的材料、出版物和数据的项目网站(www.ricedivity.org)。此外，该项目将培养不同的初级人员成为独立的科学家，包括大量水稻的基因组和其他基因型别以及表型和关联元数据的汇编，强大的信息学方法和数据管理工具，前所未有的精确编辑植物基因组以探索基因功能的能力，以及对水稻对生物和非生物胁迫反应的日益详细的分子理解，这些都为该项目提供了基础。该项目应用大规模统计遗传学和基因组编辑技术来检测抗病、感病和耐酸性土壤的不同QTL。基于之前NSF奖项和其他地方产生的基因组和表型数据、计算方法和基础设施，包括最近发布的3000份水稻种质的基因组序列，该项目将把每个性状的基因型与表型联系起来，使用基因组编辑在新的遗传背景下对分离的遗传多态进行功能性评估。还将检查每个性状的协变，以测试遗传背景对等位基因活性的影响，在疾病易感性和抗病的情况下，将询问病原体靶标基因的等位基因变异，以寻找纯化或正选择的证据。研究结果将被用来扩大与该项目相关的工具和基因和表型数据的收集，并为社区量身定做这些资源，同时提高对植物对生物和非生物胁迫的抗性的理解和能力。根据该项目的推广目标，面向小型大学本科生的综合课堂和研究体验计划将整合拟议研究的计算和分子生物学方面，并包括在康奈尔大学的研究实验室进行暑期实习。培训讲习班将特别侧重于植物生物学家的基因组编辑，特别是那些来自服务不足和代表性不足群体的植物生物学家；多媒体教育资源将包括故事、播客和互动网络模块，并将通过主要媒体传播；为科学家、普通公众和教育工作者提供的项目网站(www.ricedivity.org)将提供对项目相关材料、方案、出版物和数据的访问(数据将在分析结果发表之时或之前发布)。最后，多机构、跨学科的研究环境将培养不同的初级人员成为有能力、有创造力和协作的独立科学家。

Milestone achievements in crop research now enable difficult challenges to be addressed rapidly and effectively using innovative approaches. These achievements include DNA sequences and measurements of traits relevant to productivity and quality for large numbers of varieties within individual crop species, powerful computational approaches and data management tools, increasingly detailed molecular understanding of plant biology including responses to the environment, and new methods to precisely test the function of particular DNA sequences. Building on these resources and tools, this project will address the longstanding challenge of identifying DNA sequences responsible for traits that vary in a quantitative way, called "quantitative trait loci" (QTL), and making them amenable for crop improvement. While QTL are key determinants of crop productivity, they have been exceedingly difficult to study, and very little is known about them. This project focuses on QTL for disease resistance, disease susceptibility, and tolerance to acid soils in the globally important crop species, rice. The project will isolate DNA sequences associated with high levels of these traits and test whether those sequences are responsible by moving them into rice varieties that show low trait levels and measuring the result. The project will improve understanding of crop resistance to stresses caused by pests and poor soil conditions and lead to improved crop productivity. More broadly, the project will establish effective ways to connect variation across individuals with the DNA sequences that cause that variation, which will be useful not only for plant research, but other life sciences, including medicine. The project will further benefit society by integrating its research objectives with educational activities and materials that will engage and inform the public and increase participation by members of underrepresented groups. These include a combined classroom and research experience program for small-college undergraduates, training workshops for plant biologists, multi-media educational resources to engage middle and high school students, and a project web site (www.ricediversity.org) for public access to project-related materials, publications, and data. Moreover, the project will foster the development of diverse junior personnel into independent scientistsCompilations of genomic and other genotypic as well as phenotypic and associated metadata for large numbers of rice, powerful informatics approaches and data management tools, the unprecedented ability to precisely edit plant genomes to probe gene function, and increasingly detailed molecular understanding of rice responses to biotic and abiotic stresses, together provide a foundation for this project. This project applies large-scale statistical genetics and genome editing technology to examine distinct QTL for disease resistance, disease susceptibility, and acid soil tolerance. Building on genomic and phenotypic data, computational methods, and infrastructure generated under previous NSF awards and elsewhere, including the recently released genome sequences of 3,000 rice accessions, the project will connect genotype to phenotype for each trait, using genome editing to functionally evaluate isolated genetic polymorphism in new genetic backgrounds. Co-variation will also be examined for each trait to test for genetic background effects on allele viability, and in the case of disease susceptibility and resistance, allelic variation in pathogen-targeted genes will be queried for evidence of purifying or positive selection. Findings will be used to expand the tools and the collection of genotypic and phenotypic data associated with the project, and tailor these resources for the community, while improving understanding of and the ability to enhance plant resistance to biotic and abiotic stresses. Under the outreach objectives of the project, the combined classroom and research experience program for small-college undergraduates will integrate computational and molecular biology aspects of the proposed research and include summer internships in the research laboratories at Cornell. The training workshops will focus specifically on genome editing for plant biologists, especially those from underserved and underrepresented groups; the multimedia educational resources will include stories, podcasts, and interactive web modules and will be distributed through major media outlets; the project web site (www.ricediversity.org) for scientists, the general public, and educators will provide access to project-related materials, protocols, publications, and data (data will be released on or before publication of analytical results). Finally, the development of diverse junior personnel into capable, creative, and collaborative independent scientists will be fostered by a multi-institutional, cross-disciplinary research environment.