A genetic dissection of traits required for sustainable water use in rice using Genome Wide Association Studies (GWAS)

水稻灌溉使用了世界上三分之一的发达淡水供应，而且往往是不可持续的。在孟加拉国，60%的水稻生产是在冬季种植的，主要使用地下水。这导致了沿海地区地下水位的下降和咸水的进入。孟加拉国某些地区使用的地下水含有高浓度的砷，导致稻米中这种一类人类致癌物的浓度达到危险水平。减少灌溉需求应使取水更加可持续，并减少砷暴露。促进这一变化将有助于英国履行其对联合国千年发展目标的承诺，并对通过消费大米和大米制品而暴露于砷的英国人口有直接好处。在孟加拉国，一种新的、被大力推广的灌溉方案被称为干湿交替灌溉（AWD），它在提高产量的同时减少了20-50%的用水量。但目前尚不清楚为什么全驱能起作用，关键是它是否可持续。此外，还没有开展工作来确定与传统淹水作物生产相比，AWD适应（适宜性）的遗传变异。本项目将通过以下方式解决这些缺点：i)水稻适应AWD的基因筛选（利用基因组测序技术的进展）；Ii)土壤在干湿循环过程中的化学和物理分析；iii)对AWD在水稻中引起的变化进行详细的生理和转录组学表征；iv)采用系统生物学方法确定负责适应AWD的代谢途径。利用与加尔各答大学、阿萨姆农业大学、孟加拉国水稻研究所和国际水稻研究所建立的伙伴关系，我们将从孟加拉地区生产300个适合boro种植的地方水稻品种。这将被测序到1倍基因组覆盖，以提供大约。利用上海中国科学院的韩斌最近首创的一种创新方法，研究了300万个单核苷酸多态性。这一人群将在孟加拉国的常规洪水和AWD下进行筛查，第一季在一个地点，第二季在三个地点。将收集农艺数据，以便评估对AWD的适应情况。将对同一地点（两年）的芽和籽粒进行17种宏量和微量元素的分析，以详细描述重要植物和人类营养相关元素的吸收和芽-籽粒转运。这两组数据都将进行全基因组关联定位，以确定与性状相关的基因组区域和候选基因，并确定是否有任何特定元素与对AWD的适应性有关。将对土壤化学和强度进行详细的分析，以揭示正在发生的影响植物生长的物理/化学变化。同时，测量植物激素的空间（茎叶）和时间分析，以评估植物生长何时以及如何受到AWD的影响。一项补充性转录组学研究将显示哪些基因，从哪些途径受到AWD的影响。生成的数据将被纳入从RiceCyc数据库开发的基因组尺度代谢模型。这将提供可测试的假设，即在不同的水/土壤化学情况下，哪些代谢途径对生长很重要，以及最可能合适的基因型。这些假设将在最后一年得到验证。所有的数据都将被整合到公众可访问的存储库中，而水稻品种面板将对绘制其他性状（如耐旱、耐盐、耐寒和耐热性）具有极大的价值。所获得的产出将证明对世界各地的水稻研究人员和育种者以及对易发洪水地区的需氧作物感到关切的任何人都是有价值的。

Rice irrigation uses 1/3rd of the world's developed freshwater supplies, and is often unsustainable. In Bangladesh, 60% of the county's rice production is grown in the winter 'boro' season using predominantly groundwater. This results in lowering of water tables and ingress of saline water in coastal areas. The groundwater used in some parts of Bangladesh contains high concentrations of arsenic (As) which leads to dangerous concentrations of this class one human carcinogen in rice grain. Reducing irrigation demand should make water extraction more sustainable and reduce As exposure. Contributing to this change would help the UK meet its commitment to the UN Millennium Development Goals, and have direct benefit to the UK population exposed to As through consumption of rice and rice products. In Bangladesh, a new, heavily promoted irrigation scheme called alternate wetting and drying (AWD) reduces water use by 20-50% while increasing yield. But it is unknown why AWD works, and crucially if it is sustainable. Also, no work has yet been conducted to determine genetic variation for adaption (suitability) to AWD over conventional flooded crop production. This project will address these shortcomings by combining; i) a genetic screen for rice genes responsible for adaptation to AWD (exploiting advances in genome sequencing technology); ii) a chemical and physical analysis of the soil during cycles of wetting and drying; iii) a detailed physiological and transcriptomic characterisation of the changes that AWD causes in the rice plant and iv) a systems biology approach to identifying the metabolic pathways that are responsible for adaptation to AWD. Using established partnerships with the University of Calcutta, Assam Agricultural University, the Bangladesh Rice Research Institute and the International Rice Research Institute we will produce a collection of 300 rice landraces from the Bengal region suitable for boro cultivation. This will be sequenced to 1 x genome coverage to provide approx. 3 million single nucleotide polymorphisms using an innovative approach recently pioneered by Bin Han at the Chinese Academy of Science in Shanghai. This population will be screened under conventional flooding and AWD in Bangladesh in one site in the first season and three sites in the second season. Agronomic data will be collected to allow adaptation to AWD to be assessed. Shoots and grain in one site (both years) will be analysed for 17 macro and micro elements to provide a detailed description of uptake and shoot-grain translocation of the important plant and human nutrition-relevant elements. Both sets of data will be subjected to genome wide association mapping to identify the genomic regions and candidate genes associated with the traits and to identify if any specific element is related to adaptability to AWD. Detailed analysis of soil chemistry and strength will be conducted to reveal the physical/chemical changes taking place that affect plant growth. At the same time, spatial (stems and leaves) and temporal analysis of plant hormones will be measured to assess when and how plant growth is affected by AWD. A complementary transcriptomic study will show which genes, from which pathways, are being affected by AWD. The data generated will be incorporated in to a genome-scale metabolic model developed from the RiceCyc database. This will provide testable hypothesis of what metabolic pathways are important for growth in different water/soil chemistry scenarios and the most likely suitable genotypes. These hypotheses will be validated in the final year. All data will be integrated into publically accessible repositories and the panel of rice cultivars will be immensely valuable for mapping other traits such as drought, salt, cold and heat tolerance. Outputs obtained will prove valuable to researchers and breeders on rice throughout the world and to anyone concerned about aerobically-grown crops in flood-prone areas.