MCA-PGR: Genetic and Genomic Approaches to Understanding Low-K Tolerance in Rice

Pi：Seng Luan(加州大学伯克利分校)Copi：Peggy Lemaux(加州大学伯克利分校)主要合作者：Rod Wing(亚利桑那大学)和Bin han(中国科学院国家基因研究中心)植物生长最低限度需要阳光、二氧化碳、水和矿物质。虽然阳光和二氧化碳充足，但水和矿物质是作物产量的主要限制因素。尽管人们对水分利用效率和抗旱性进行了广泛的研究，但在了解植物养分利用效率和对土壤低养分状况的耐受机制方面的研究还很少。由于不知道如何提高作物的养分利用效率，大量使用化肥是一种危害环境和可持续农业的做法。该项目的总体目标是利用全基因组方法全面了解谷类作物钾利用效率高的基因网络。水稻因其丰富的遗传和基因组资源以及易于转化而被选为模式作物。具体目标如下：(1)研究水稻基因组中编码的所有K转运蛋白的生物学功能。由于K+不被代谢，K+的有效吸收和分配是植物高效利用K+的关键。剖析所有钾转运体在水稻中的作用，将产生一张K+在整个谷类作物中移动的“路线图”，并提供可能的方法来提高效率；(2)确定与水稻耐低钾有关的遗传位点和单个基因。水稻地方品种在耐低钾方面表现出巨大的自然变异，这些变异可以通过基于测序的关联作图与基因连锁，从而加快QTL的识别；(3)进行基于RNA序列的比较转录组分析，并找出与低K响应和适应有关的基因。通过比较“高耐性”和“高敏感”地方品种与低钾条件下的转录本，将识别这两个表型群体之间的差异表达基因，并对其与表型变异的相关性进行评分；以及(4)整合目标1-3的数据集，以组装一个基因调控网络。这一变革性的知识将为标记辅助经典育种以及基因工程方法奠定基础，以提高谷类作物的钾素利用效率，减少作物生产中化肥的使用。将对社会和教育产生一些更广泛的影响。大米是最重要的粮食作物之一，养活了世界一半以上的人口。了解水稻耐低钾的机制，将为培育水稻品种(和其他谷类)以最少的化肥获得高产、保护环境和促进农业可持续发展提供知识基础。该项目将本科生和研究生教育融入研究的各个方面。将开展外展活动，包括通过与生物技术合作伙伴和STEM计划合作对服务不足的高中生和社区大学生进行培训，向这些学生介绍现代生物技术和知识，目的是提高他们对科学职业的兴趣。所有序列数据和注释都将通过水稻基因组注释项目(http://rice.plantbiology.msu.edu/).)获得表达谱分析产生的所有序列将保存在GenBank、植物表达数据库(http://www.plexdb.org/)和PlantGDB(http://www.plantgdb.org/).

PI: Sheng Luan (University of California, Berkeley)CoPI: Peggy Lemaux (University of California, Berkeley)Key Collaborators: Rod Wing (University of Arizona)and Bin Han (National Center for Gene Research, Chinese Academy of Sciences) Plant growth minimally requires sunlight, CO2, water, and minerals. While sunlight and CO2 are abundant, water and minerals are major limiting factors for crop production. Although extensive research effort has been directed to studying water use efficiency and drought tolerance, much less effort has been expended on understanding the mechanisms of plant nutrient use efficiency and tolerance to low-nutrient status in the soil. Not knowing how to increase nutrient use efficiency in crops resorts to heavy use of fertilizers, a practice that endangers environment and sustainable agriculture. The overall goal of this project is to provide a comprehensive understanding of the gene networks responsible for high potassium (K)-use efficiency in cereal crops using genome-wide approaches. Rice is chosen as a model because of its rich genetic and genomic resources and its ease of transformation. The specific objectives are as follows: (1) to characterize the biological roles of all K-transporters encoded in the rice genome. As K+ is not metabolized, effective uptake and distribution of K+ hold the key for high K+ use efficiency in plants. Dissecting the roles of all K-transporters in rice will generate a "road map" of K+ movement throughout a cereal crop and provide possible ways to improve efficiency; (2) to identify genetic loci and individual genes associated with low-K tolerance in rice. Rice landraces display dramatic natural variations in low-K tolerance and such variations can be linked to genes using sequencing-based association mapping that would speed up the identifications of QTLs; (3) to conduct RNA-seq-based comparative transcriptome analysis and identify genes involved in low-K response and adaptation. By comparing transcriptomes of "highly tolerant" and "highly sensitive" landraces to the low-K condition, differentially expressed genes between the two phenotypic groups will be identified and their relevance to phenotypic variations will be scored; and (4) to integrate the datasets from Objectives 1-3 to assemble a gene regulatory network. This transformative knowledge will lay the foundation for marker-assisted classical breeding as well as genetic engineering approaches to improve K-use efficiency in cereal crops and reduce the use of fertilizers in crop production. A number of broader impacts to society and education will be achieved. Rice is one of the most important food crops, feeding more than half of the world's population. Understanding the mechanisms of low-K tolerance in rice will provide a knowledge base for breeding rice varieties (and other cereals) that produce high yield with minimal fertilizer use, protecting environment and contributing to sustainability of agriculture. This project integrates undergraduate and graduate education into all aspects of the research. Outreach activities will be undertaken that include training of underserved high school and community college students through collaboration with Biotech Partners and STEM program to introduce these students to modern biology techniques and knowledge with the goal of increasing their interest in science careers. All sequence data and annotations will be accessible through the Rice Genome Annotation Project (http://rice.plantbiology.msu.edu/). All sequences generated from expression profiling will be deposited at GenBank, the Plant Expression Database (http://www.plexdb.org/) and PlantGDB (http://www.plantgdb.org/).