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

项目负责人：栾生（美国加州大学伯克利分校）项目负责人：Peggy leaux（美国加州大学伯克利分校）项目负责人：Rod Wing（美国亚利桑那大学）和Bin Han（中国科学院国家基因研究中心）植物生长对阳光、二氧化碳、水和矿物质的需求最低。虽然阳光和二氧化碳丰富，但水和矿物质是作物生产的主要限制因素。尽管对水分利用效率和耐旱性的研究已经开展了大量的工作，但对植物养分利用效率和对土壤低营养状况的耐受性机制的研究却很少。不知道如何提高作物的养分利用效率，导致大量使用肥料，这种做法危及环境和可持续农业。该项目的总体目标是利用全基因组方法全面了解谷物作物高钾利用效率的基因网络。选择水稻作为模型是因为其丰富的遗传和基因组资源以及易于转化。具体目的如下：(1)表征水稻基因组中编码的所有k转运蛋白的生物学作用。由于钾离子不被代谢，因此有效的吸收和分配是植物钾离子利用效率提高的关键。剖析水稻中所有钾转运蛋白的作用将生成钾离子在整个谷物作物中运动的“路线图”，并提供提高效率的可能方法；(2)鉴定水稻低钾耐受性相关基因位点和个体基因。水稻地方品种在低钾耐受性方面表现出巨大的自然变异，这种变异可以通过基于测序的关联图谱与基因联系起来，从而加快qtl的鉴定；(3)开展基于rna -seq的比较转录组分析，鉴定参与低钾响应和适应的基因。通过比较“高度耐受”和“高度敏感”的地方品种对低钾条件的转录组，将确定两种表型组之间差异表达的基因，并对其与表型变异的相关性进行评分；(4)整合目标1-3的数据集，构建基因调控网络。这一变革性的知识将为标记辅助的经典育种以及基因工程方法奠定基础，以提高谷物作物对钾的利用效率，减少作物生产中肥料的使用。这将对社会和教育产生一系列更广泛的影响。水稻是最重要的粮食作物之一，养活了世界上一半以上的人口。了解水稻耐低钾机制将为选育低肥高产、保护环境和促进农业可持续发展的水稻（及其他谷物）品种提供知识基础。该项目将本科和研究生教育整合到研究的各个方面。将开展外展活动，包括通过与生物技术伙伴和STEM项目合作，培训服务不足的高中和社区大学生，向这些学生介绍现代生物学技术和知识，以提高他们对科学事业的兴趣。所有序列数据和注释将通过水稻基因组注释项目（http://rice.plantbiology.msu.edu/）访问。所有由表达谱生成的序列将存入GenBank、Plant expression Database （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/).