Deciphering the cannabis-powdery mildew interactions using genomics

使用基因组学破译大麻与白粉病的相互作用

• 批准号: RGPIN-2022-04391
• 负责人: Joly, David
• 金额: $ 2.04万
• 依托单位: Université de Moncton
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=745014
• 关键词: Deciphering; cannabis; powdery; mildew; interactions

Plant diseases are responsible for considerable losses each year and threaten global food security. Breeding crop resistance to pathogens is usually considered as the most environmentally friendly method for managing diseases and reducing losses. However, one of the challenges is to ensure that such resistance is effective and durable. The long-term objective of my research program is to improve our fundamental knowledge on plant immunity and microbial virulence, which will help develop new strategies toward durable and sustainable disease resistance in important agricultural crops. Recent advances in genetics and genomics can contribute to unravel the complexity of plant-microbe interactions and decipher the genes and mechanisms that underlie resistance. These represent a game-changing approach that will fundamentally alter the way we generate disease resistant plants. Indeed, such knowledge can greatly benefit crop improvement through better-informed breeding strategies that exploit diverse forms of resistance at different scales, from the genome of a single plant to the plant varieties deployed within a region. In this installment, we aim to dissect the genetic and molecular basis of the cannabis-powdery mildew interaction with the goal of identifying pathogenicity and resistance determinants. We hypothesize that the rapid expansion of cultivated areas of cannabis has had a profound impact on the population structure of powdery mildew, and that the intricate coevolutionary patterns between cannabis and powdery mildew trace back to a myriad of defense mechanisms among cannabis accessions. To address these hypotheses, we will first investigate the population dynamics of cannabis powdery mildew and use a variety of omics approaches to determine the key players of this interaction. This will be accomplished through the research activities proposed in the Discovery Grant: Aim 1 - Pathogenomics of cannabis powdery mildew; Aim 2 - Identification of sources of resistance from a cannabis diversity panel; Aim 3 - Characterization of cellular and molecular mechanisms underlying PM resistance. Significance: There is an urgent need for a coordinated effort to quantify the genetic diversity of cannabis, especially with regards to disease resistance. We now have approaches and resources to exploit the vast genetic variation present in the cannabis germplasm and streamline application of this knowledge directly into improvement programs. This will greatly accelerate the development of varieties which are less dependent on the use of pesticides, not only decreasing cultivation costs but also the environmental risks instigated by chemical control. Moreover, our research program represents a unique training opportunity for HQP in both experimental and computational science, which are highly needed skills required to sustain the biosciences sector and will provide excellent preparation for a range of career paths.

植物病害每年造成相当大的损失，并威胁到全球粮食安全。培育作物对病原体的抗性通常被认为是管理疾病和减少损失的最环境友好的方法。然而，挑战之一是确保这种抵抗是有效和持久的。我的研究计划的长期目标是提高我们对植物免疫和微生物毒力的基础知识，这将有助于开发重要农作物持久和可持续抗病性的新策略。遗传学和基因组学的最新进展有助于解开植物-微生物相互作用的复杂性，并破译抗性背后的基因和机制。这些代表了一种改变游戏规则的方法，将从根本上改变我们生产抗病植物的方式。事实上，这种知识可以通过更明智的育种战略大大有利于作物改良，这些战略可以在不同规模上利用不同形式的抗性，从单一植物的基因组到在一个区域内部署的植物品种。 在这一部分中，我们的目标是剖析大麻-白粉病相互作用的遗传和分子基础，以确定致病性和抗性决定因素。我们假设大麻种植面积的迅速扩大对白粉病的种群结构产生了深远的影响，大麻和白粉病之间复杂的共同进化模式可以追溯到大麻种质中的无数防御机制。 为了解决这些假设，我们将首先调查大麻白粉病的种群动态，并使用各种组学方法来确定这种相互作用的关键参与者。这将通过发现补助金中提出的研究活动来实现：目标1 -大麻白粉病的病原体学;目标2 -从大麻多样性小组中确定抗性来源;目标3 -表征PM抗性的细胞和分子机制。重要性：迫切需要协调努力，对大麻的遗传多样性进行量化，特别是在抗病性方面。我们现在有方法和资源来利用大麻种质中存在的巨大遗传变异，并将这些知识直接应用于改进计划。这将大大加快对农药使用依赖性较低的品种的开发，不仅降低种植成本，而且降低化学控制引发的环境风险。此外，我们的研究计划为HQP在实验和计算科学方面提供了独特的培训机会，这是维持生物科学部门所需的高度必要技能，并将为一系列职业道路提供良好的准备。