Global gene regulatory networks and abiotic stress

全球基因调控网络和非生物胁迫

• 批准号: RGPIN-2016-04966
• 负责人: Wilkins, Olivia
• 金额: $ 2.62万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=615410
• 关键词: Global; gene; regulatory; networks; abiotic

Drought is a major threat to food security as it results in marked yield reductions in crops such as Asian rice (Oryza sativa), the staple food of 30% of the global population. However, diverse rice cultivars display markedly different responses to drought, thereby suggesting that a comparison of the mechanisms by which different cultivars respond to drought may offer insight into critical molecular factors required for drought response. Control of such responses is mediated through gene regulatory networks (GRNs), defined by the dynamic interactions of protein transcription factors (TFs) and the regulatory regions of their target genes. Physiologically, guard cells are key regulators of the rate at which plants lose water to the atmosphere and it has been suggested that regulation of these cells may be an important determinant of drought sensitivity of diverse cultivars. Thus understanding cell type specific GRNs is a promising avenue for improving crop resistance to environmental stress. I hypothesize that natural variation in the drought tolerance of rice cultivars is determined by genomic changes that manifest as variation in TF activity and in chromatin accessibility; studies in other species suggest that guard cell GRNs are not adequately represented in studies of whole leaves and as such I hypothesize that this may also be the case for rice. My long term goal is to define GRNs and identify transcriptional modules that regulate stomatal function in response to drought. Specific Aims: 1) Characterize drought-responsive GRNs in diverse rice cultivars. I will integrate my transcriptome and chromatin accessibility data with publicly available rice genome sequences to identify regulatory modules associated with divergent drought response phenotypes. 2) Characterize guard cell GRNs in response to drought. I will use high throughput and low input sequencing technologies to investigate the GRNs of isolated guard cells in response to drought. 3) Functionally characterize TFs identified in Objectives 1 and 2 and from the literature. I will use genome-editing techniques (CRISPR-cas9) to examine the roles of candidate TFs identified in Aims 1 and 2 in the drought response. The proposed studies address the fundamental biological question of how gene regulatory networks determine an organism’s capacity to respond to environment stressors. The roles of the identified candidates will be functionally assessed providing possible candidates for crop improvement. The approaches used in these studies will generate biological insight and analytical capabilities that can be applied to other crop plants and other environmental stresses. The outlined studies are feasible as I have the demonstrated expertise and collaborations necessary to complete them. The project offers unique training opportunities for HQP in systems biology using advanced experimental and computational methods.

干旱是粮食安全的主要威胁，因为它导致亚洲水稻等作物的产量显著下降，而亚洲水稻是全球30%人口的主食。然而，不同的水稻品种表现出显着不同的响应干旱，从而表明，不同品种响应干旱的机制的比较可能提供洞察干旱响应所需的关键分子因素。这种反应的控制是通过基因调控网络（GRNs）介导的，由蛋白质转录因子（TF）及其靶基因的调控区域的动态相互作用定义。在生理上，保卫细胞是植物向大气失水速率的关键调节器，并且已经表明这些细胞的调节可能是不同品种的干旱敏感性的重要决定因素。因此，了解细胞类型特异性GRNs是提高作物对环境胁迫抗性的一条有前途的途径。 我推测，水稻品种的耐旱性的自然变化是由基因组的变化，表现为TF活性和染色质可及性的变化;在其他物种的研究表明，保卫细胞GRNs没有充分代表在研究的全叶，因此我推测，这也可能是水稻的情况。我的长期目标是确定GRNs和确定转录模块，调节气孔功能响应干旱。 具体目标： 1)表征不同水稻品种中干旱响应的GRNs。我将把我的转录组和染色质可及性数据与公开的水稻基因组序列相结合，以确定与不同干旱反应表型相关的调控模块。 2)表征保卫细胞GRNs对干旱的响应。我将使用高通量和低输入测序技术来研究隔离的保卫细胞响应干旱的GRNs。 3)对目标1和2以及文献中确定的TF进行功能表征。我将使用基因组编辑技术（CRISPR-cas9）来研究目标1和2中确定的候选TF在干旱应对中的作用。 拟议的研究解决了基因调控网络如何决定生物体应对环境压力的能力的基本生物学问题。将从功能上评估已确定的候选者的作用，为作物改良提供可能的候选者。这些研究中使用的方法将产生生物学见解和分析能力，可应用于其他作物和其他环境压力。概述的研究是可行的，因为我有证明的专业知识和必要的合作来完成它们。该项目提供了独特的培训机会，在系统生物学HQP使用先进的实验和计算方法。