Sequencing the air to identify plant pathogens before they decimate crops

对空气进行测序，在植物病原体消灭农作物之前识别它们

• 批准号: 2870487
• 金额: --
• 依托单位: University of East Anglia
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2870487
• 关键词: Sequencing; air; identify; plant; pathogens

Airborne crop pathogens pose a serious threat to food security and are responsible for devastating loss of yield. Early detection can enable farmers to take targeted action to reduce losses. In wheat, fungaldiseases alone are estimated to cause losses averaging 21% (>160 million tonnes), with three cereal rusts amongst the most damaging. Yellow rust, caused by P. striiformis, is a constant threat to UK wheat production. All current pathogen detection regimes for yellow rust rely on analysis post plant damage. However, in this project, we will deploy a state-of-the-art sequencing based diagnostic to detect and monitor yellow rust pathogens present within captured air samples. Crucially, we hope to be able to demonstrate the ability to distinguish different genotypes/pathotypes. Such an approach would allow much earlier, more targeted treatment regimes.

空气传播的作物病原体对粮食安全构成严重威胁，并造成毁灭性的产量损失。早期发现可以使农民采取有针对性的行动，以减少损失。在小麦中，仅真菌病害估计就造成平均21%（> 1.6亿吨）的损失，其中三种谷物锈病是最具破坏性的。由条锈菌引起的条锈病一直威胁着英国的小麦生产。所有目前的病原体检测制度的黄锈病依赖于分析植物损害后。然而，在这个项目中，我们将部署一种最先进的基于测序的诊断方法，以检测和监测捕获的空气样本中存在的黄锈病病原体。最重要的是，我们希望能够证明区分不同基因型/病理型的能力。这种方法将允许更早、更有针对性的治疗方案。