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

主要研究者：Sheng Luan（University of加州，Berkeley）CoPI：Peggy Lemaux（University of加州，Berkeley）主要合作者：Rod Wing（University of Arizona）和Bin Han（National Center for Gene Research，Chinese Academy）植物生长最低限度地需要阳光、二氧化碳、水和矿物质。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。尽管人们在水分利用效率和耐旱性方面进行了大量的研究，但在了解植物养分利用效率和对土壤低养分状况的耐受性方面的研究却少得多。不知道如何提高作物的养分利用效率，就不得不大量使用化肥，这种做法危害环境和可持续农业。该项目的总体目标是利用全基因组方法全面了解谷类作物中高钾（K）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。具体目标如下：（1）研究水稻基因组中K-转运蛋白的生物学功能。由于K+不被代谢，因此K+的有效吸收和分配是植物高效利用K+的关键。研究水稻钾转运蛋白的作用，将有助于绘制钾在整个谷类作物中转运的“路线图”，并为提高钾转运效率提供可能的途径;（2）鉴定水稻耐低钾相关的遗传位点和基因。水稻地方品种在低钾耐性方面表现出显著的自然变异，利用基于测序的关联作图技术可以将这些变异与基因联系起来，从而加快QTL的鉴定;（3）进行基于RNA-seq的比较转录组分析，鉴定与低钾响应和适应相关的基因。通过比较“高耐受性”和“高敏感性”地方品种对低钾条件的转录组，将鉴定两个表型组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）整合来自目标1-3的数据集以组装基因调控网络。这种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，以提高谷类作物的钾利用效率并减少作物生产中的肥料使用。 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。了解水稻耐低钾的机制将为培育水稻品种（和其他谷物）提供知识基础，这些品种以最少的肥料使用产生高产，保护环境并促进农业的可持续性。该项目将本科和研究生教育融入研究的各个方面。将开展外联活动，包括通过与生物技术合作伙伴和STEM计划合作，培训服务不足的高中和社区大学学生，向这些学生介绍现代生物技术和知识，以提高他们对科学事业的兴趣。所有序列数据和注释将可通过水稻基因组注释项目（http：//rice.plantbiology.msu.edu/）获得。由表达谱生成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/).