DNA & RNA Sensing Lab, University of Trás-os-Montes e Alto Douro, Department of Genetics and Biotechnology, School of Life Science and Environment, Vila Real, Portugal.
BioISI - Biosystems & Integrative Sciences Institute, University of Lisboa, Faculty of Sciences, Lisbon, Portugal.
Methods Mol Biol. 2023;2967:53-62. doi: 10.1007/978-1-0716-3358-8_5.
Crop producers are under great pressure to produce more and better food items. Effective control of crop pathogens is fundamental to guaranteeing food safety and reducing economic losses. Therefore, their identification throughout the production chain is of utmost interest. To achieve this goal, genomic analysis tools are currently being developed allowing to control crop production more effectively.Genomic analysis in some samples is difficult, mostly due to the sample's intrinsic characteristics, i.e., high levels of phenols, fatty acids (e.g., oleaginous fruits, such as olives), and carbon hydrates (e.g., honey), among others. Additionally, some samples yield very low DNA recovery with high content of contaminants, imposing protocol improvements to overcome these difficulties.Here we present protocols focused on qPCR and HRM to detect the presence of fungal pathogens collected from plant-derived samples.
农作物生产者承受着生产更多更好食品的巨大压力。有效控制作物病原体是保证食品安全和减少经济损失的基础。因此，在整个生产链中对它们进行鉴定是非常重要的。为了实现这一目标，目前正在开发基因组分析工具，以更有效地控制作物生产。对某些样本进行基因组分析是困难的，主要是由于样本的内在特性，如高水平的酚类物质、脂肪酸（例如，油性水果，如橄榄）和碳水化合物（例如，蜂蜜）等。此外，一些样本的 DNA 回收率非常低，且含有高浓度的污染物，这就需要改进方案来克服这些困难。在这里，我们介绍了一些专注于 qPCR 和 HRM 的方案，以检测从植物样本中采集到的真菌病原体的存在。
