Activating photosynthesis in non-photosynthetic cells for improved crop productivity

激活非光合细胞的光合作用以提高作物生产力

• 批准号: 1804786
• 金额: --
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1804786
• 关键词: Activating; photosynthesis; non; photosynthetic; cells

Theme: Agriculture and Food SecurityPhotosynthesis is the basis of life, and underpins crop productivity. Enhancing photosynthesis is high on the BBSRC agenda, as it is recognised that photosynthesis controls the yield potential of crops, and this needs to be increased to feed the future.The leaves of many of our most important crops develop to contain cells that fail to "green up" and accumulate photosynthetic apparatus. Why this is, and the mechanisms that repress photosynthesis gene expression in these cells, are not understood. Using rice as a model, we have identified when this repression occurs during leaf development. The project builds on these findings and will use state-of-the-art approaches developed by the lab to isolate cell-types that will either become fully green and photosynthetic (mesophyll) or fail to do so (bundle sheath). High throughput sequencing (eg RNA-SEQ, DNAaseI-SEQ) and bioinformatics analysis will be used to understand this repression of photosynthesis in cells of the leaf. The long-term aim is then to activate photosynthesis in these non-photosynthetic leaf cells to increase photosynthetic capacity of the leaf and increase productivity.This project is relevant to Agriculture and Food Security as increasing photosynthesis would enable the yield potential of crops to be increased. The work would also generated World Class Bioscience. Because rice is the model that is used for this research, core findings as well as those that are serendipitous can be translated into this major crop rapidly. Due to significant synteny within cereal genomes, findings from rice can also be used to guide improvements in other major cereal crops.The project is interdisciplinary, combining wet-lab analysis with training and use of bioinformatics and statistical analysis of big data. The student would be immersed in a laboratory that routinely uses these approaches, and contains members with expertise in both areas.

主题：农业和粮食安全光合作用是生命的基础，是作物生产力的基础。提高光合作用是BBSRC议程的重点，因为人们认识到光合作用控制着作物的产量潜力，这需要提高以满足未来的需求。我们许多最重要的作物的叶子发育成含有不能“变绿色”和积累光合机构的细胞。为什么会这样，以及抑制这些细胞中光合作用基因表达的机制还不清楚。以水稻为模型，我们已经确定了这种抑制发生在叶片发育过程中。该项目建立在这些发现的基础上，并将使用实验室开发的最先进的方法来分离细胞类型，这些细胞类型要么完全变成绿色和光合作用（叶肉），要么不能这样做（束鞘）。高通量测序（例如RNA-SEQ、DNAaseI-SEQ）和生物信息学分析将用于理解叶细胞中光合作用的这种抑制。长期目标是激活这些非光合作用叶片细胞的光合作用，以提高叶片的光合作用能力，提高生产力。该项目与农业和粮食安全相关，因为增加光合作用将提高作物的产量潜力。这项工作也将产生世界级的生物科学。由于水稻是用于这项研究的模型，核心发现以及那些偶然发现可以迅速转化为这种主要作物。由于谷物基因组中存在显著的同线性，水稻的研究结果也可用于指导其他主要谷物作物的改良。该项目是跨学科的，将湿实验室分析与生物信息学和大数据统计分析的培训和使用相结合。学生将沉浸在一个实验室，经常使用这些方法，并包含在这两个领域的专业知识的成员。