Department of Entomology and Plant Pathology and NC Plant Sciences Initiative, North Carolina State University, Raleigh, NC 27606, U.S.A.
Department of Plant Biology, Michigan State University, East Lansing, MI 48824, U.S.A.
Mol Plant Microbe Interact. 2024 Mar;37(3):315-326. doi: 10.1094/MPMI-09-23-0146-FI. Epub 2024 Apr 1.
In 2015, sweetpotato producers in the United States experienced one of the worst outbreaks of black rot recorded in history, with up to 60% losses reported in the field and packing houses and at shipping ports. Host resistance remains the ideal management tool to decrease crop losses. Lack of knowledge of biology represents a critical barrier for the deployment of resistance to black rot in sweetpotato. In this study, we scanned the recent near chromosomal-level assembly for putative secreted effectors in the sweetpotato isolate AS236 using a custom fungal effector annotation pipeline. We identified a set of 188 putative effectors on the basis of secretion signal and in silico prediction in EffectorP. We conducted a deep RNA time-course sequencing experiment to determine whether modulates effectors in planta and to define a candidate list of effectors expressed during infection. We examined the expression profile of two isolates, a pre-epidemic (1990s) isolate and a post-epidemic (2015) isolate. Our in planta expression profiling revealed clusters of co-expressed secreted effector candidates. Based on fold-change differences of putative effectors in both isolates and over the course of infection, we suggested prioritization of 31 effectors for functional characterization. Among this set, we identified several effectors that provide evidence for a marked biotrophic phase in during infection of sweetpotato storage roots. Our study revealed a catalog of effector proteins that provide insight into infection mechanisms and represent a core catalog to implement effector-assisted breeding in sweetpotato. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
2015 年,美国的甘薯种植者经历了有记录以来最严重的黑腐病爆发之一,田间、包装厂和运输港口的损失高达 60%。利用宿主抗性仍然是减少作物损失的理想管理工具。对生物学缺乏了解是在甘薯中部署黑腐病抗性的一个关键障碍。在这项研究中,我们使用定制的真菌效应物注释管道,对甘薯分离株 AS236 的最近近染色体水平组装进行了潜在分泌效应物的扫描。我们根据分泌信号和 EffectorP 中的计算机预测,在基于假设的效应物上确定了一组 188 个潜在效应物。我们进行了深度 RNA 时间过程测序实验,以确定是否在植物体内调节效应物,并定义在感染过程中表达的候选效应物列表。我们检查了两个分离株(一个是流行前(20 世纪 90 年代)分离株,一个是流行后(2015 年)分离株)的表达谱。我们的植物内表达谱分析揭示了一组共表达的分泌效应物候选物。基于两个分离株和感染过程中假定效应物的差异倍数,我们建议对 31 个效应物进行功能特征分析。在这一组中,我们鉴定了几个效应物,为在甘薯贮藏根感染过程中提供了证据,证明了在中存在明显的生物营养期。我们的研究揭示了一个效应蛋白目录,为了解感染机制提供了深入的了解,并代表了在甘薯中实施效应辅助育种的核心目录。