Department of Plant Genetics, Breeding and Biotechnology, Institute of Biology, Warsaw University of Life Sciences, Warsaw, Poland.
Department of Applied Entomology, Institute of Horticultural Sciences, Warsaw University of Life Sciences, Warsaw, Poland.
Sci Rep. 2024 Apr 5;14(1):8020. doi: 10.1038/s41598-024-58249-7.
The two-spotted spider mite (TSSM), Tetranychus urticae, is among the most destructive piercing-sucking herbivores, infesting more than 1100 plant species, including numerous greenhouse and open-field crops of significant economic importance. Its prolific fecundity and short life cycle contribute to the development of resistance to pesticides. However, effective resistance loci in plants are still unknown. To advance research on plant-mite interactions and identify genes contributing to plant immunity against TSSM, efficient methods are required to screen large, genetically diverse populations. In this study, we propose an analytical pipeline utilizing high-resolution imaging of infested leaves and an artificial intelligence-based computer program, MITESPOTTER, for the precise analysis of plant susceptibility. Our system accurately identifies and quantifies eggs, feces and damaged areas on leaves without expert intervention. Evaluation of 14 TSSM-infested Arabidopsis thaliana ecotypes originating from diverse global locations revealed significant variations in symptom quantity and distribution across leaf surfaces. This analytical pipeline can be adapted to various pest and host species, facilitating diverse experiments with large specimen numbers, including screening mutagenized plant populations or phenotyping polymorphic plant populations for genetic association studies. We anticipate that such methods will expedite the identification of loci crucial for breeding TSSM-resistant plants.
二斑叶螨（TSSM），又称棉叶螨，是最具破坏性的刺吸式食草动物之一，可侵害超过 1100 种植物，包括许多温室和大田作物，这些作物具有重要的经济意义。其极高的繁殖力和短的生命周期导致了对农药的抗性发展。然而，植物中的有效抗性基因仍然未知。为了推进植物-螨虫相互作用的研究，并鉴定对 TSSM 具有免疫作用的基因，需要有效的方法来筛选具有大量遗传多样性的种群。在这项研究中，我们提出了一个利用受感染叶片的高分辨率成像和基于人工智能的计算机程序 MITESPOTTER 来精确分析植物易感性的分析流程。我们的系统无需专家干预即可准确识别和量化叶片上的卵、粪便和受损区域。对来自不同全球地点的 14 种 TSSM 感染拟南芥生态型的评估表明，叶片表面的症状数量和分布存在显著差异。这种分析流程可以适应各种害虫和宿主物种，便于进行各种具有大量标本数量的实验，包括筛选突变异种植物种群或对多态性植物种群进行表型分析以进行遗传关联研究。我们预计，这些方法将加速鉴定对培育 TSSM 抗性植物至关重要的基因座。
