Early and accurate detection of the causal pathogen Phytophthora sojae is crucial for effective prevention and control of root and stem rot and seedling damping-off of soybean. In the present study, a novel isothermal amplification assay was developed for detecting P. sojae. This 25 min assay included a two-step approach. First, a pair of novel primers, PSYPT-F and PSYPT-R were used to amplify a specific fragment of the Ypt1 gene of P. sojae in a 20 min recombinase polymerase amplification (RPA) step. Second, lateral flow dipsticks (LFD) were used to detect and visualize RPA amplicons of P. sojae within 5 min. This RPA-LFD assay was specific to P. sojae. It yielded negative detection results against 24 other Phytophthora, one Globisporangium, and 14 fungal species. It was also found to be sensitive, detecting as low as 10 pg of P. sojae genomic DNA in a 50-μL reaction. Furthermore, P. sojae was detected from artificially inoculated hypocotyls of soybean seedlings using this novel assay. In a comparative evaluation using 130 soybean rhizosphere samples, this novel assay consistently detected P. sojae in 55.4% of samples, higher than other three methods, including loop-mediated isothermal amplification (54.6%), conventional PCR (46.9%), and leaf-disc baiting (38.5–40.0%). Results in this study indicated that this rapid, specific, and sensitive RPA-LFD assay has potentially significant applications to diagnosing Phytophthora root and stem rot and damp-off of soybean, especially under time- and resource-limited conditions.

On the basis of its downy mildew–like morphology, the litchi downy blight pathogen was previously named Peronophythora litchii. Recently, however, it was proposed to transfer this pathogen to Phytophthora clade 4. To better characterize this unusual oomycete species and important fruit pathogen, we obtained the genome sequence of Phytophthora litchii and compared it to those from other oomycete species. P. litchii has a small genome with tightly spaced genes. On the basis of a multilocus phylogenetic analysis, the placement of P. litchii in the genus Phytophthora is strongly supported. Effector proteins predicted included 245 RxLR, 30 necrosis-and-ethylene-inducing protein-like, and 14 crinkler proteins. The typical motifs, phylogenies, and activities of these effectors were typical for a Phytophthora species. However, like the genome features of the analyzed downy mildews, P. litchii exhibited a streamlined genome with a relatively small number of genes in both core and species-specific protein families. The low GC content and slight codon preferences of P. litchii sequences were similar to those of the analyzed downy mildews and a subset of Phytophthora species. Taken together, these observations suggest that P. litchii is a Phytophthora pathogen that is in the process of acquiring downy mildew–like genomic and morphological features. Thus P. litchii may provide a novel model for investigating morphological development and genomic adaptation in oomycete pathogens.

Over the last decade, RNA-seq has produced a massive amount of plant transcriptomic sequencing data deposited in public databases. Reanalysis of these public datasets can generate additional novel hypotheses not included in original studies. However, the large data volume and the requirement for specialized computational resources and expertise present a barrier for experimental biologists to explore public repositories. Here, we introduce PlantExp (https://biotec.njau.edu.cn/plantExp), a database platform for exploration of plant gene expression and alternative splicing profiles based on 131 423 uniformly processed publicly available RNA-seq samples from 85 species in 24 plant orders. In addition to two common retrieval accesses to gene expression and alternative splicing profiles by functional terms and sequence similarity, PlantExp is equipped with four online analysis tools, including differential expression analysis, specific expression analysis, co-expression network analysis and cross-species expression conservation analysis. With these online analysis tools, users can flexibly customize sample groups to reanalyze public RNA-seq datasets and obtain new insights. Furthermore, it offers a wide range of visualization tools to help users intuitively understand analysis results. In conclusion, PlantExp provides a valuable data resource and analysis platform for plant biologists to utilize public RNA-seq. datasets.

RXLR effectors, a class of secreted proteins that are transferred into host cells to manipulate host immunity, have been reported to widely exist in oomycetes, including those from genera Phytophthora, Hyaloperonospora, Albugo, and Saprolegnia. However, in Pythium species, no RXLR effector has yet been characterized, and the origin and evolution of such virulent effectors are still unknown. Here, we developed a modified regular expression method for de novo identification of RXLRs and characterized 359 putative RXLR effectors in nine Pythium species. Phylogenetic analysis revealed that all oomycetous RXLRs formed a single superfamily, suggesting that they might have a common ancestor. RXLR effectors from Pythium and Phytophthora species exhibited similar sequence features, protein structures, and genome locations. In particular, there were significantly more RXLR proteins in the mosquito biological control agent P. guiyangense than in the other eight Pythium species, and P. guiyangense RXLRs might be the result of gene duplication and genome rearrangement events, as indicated by synteny analysis. Expression pattern analysis of RXLR-encoding genes in the plant pathogen P. ultimum detected transcripts of the majority of the predicted RXLR genes, with some RXLR effectors induced in infection stages and one RXLR showing necrosis-inducing activity. Furthermore, all predicted RXLR genes were cloned from two biocontrol agents, P. oligandrum and P. periplocum, and three of the RXLR genes were found to induce a defense response in Nicotiana benthamiana. Taken together, our findings represent the first evidence of RXLR effectors in Pythium species, providing valuable information on their evolutionary patterns and the mechanisms of their interactions with diverse hosts.

Phytophthora species are oomycete plant pathogens that cause great economic and ecological impacts. The Phytophthora genus includes over 180 known species, infecting a wide range of plant hosts, including crops, trees, and ornamentals. We sequenced the genomes of 31 individual Phytophthora species and 24 individual transcriptomes to study genetic relationships across the genus. De novo genome assemblies revealed variation in genome sizes, numbers of predicted genes, and in repetitive element content across the Phytophthora genus. A genus-wide comparison evaluated orthologous groups of genes. Predicted effector gene counts varied across Phytophthora species by effector family, genome size, and plant host range. Predicted numbers of apoplastic effectors increased as the host range of Phytophthora species increased. Predicted numbers of cytoplasmic effectors also increased with host range but leveled off or decreased in Phytophthora species that have enormous host ranges. With extensive sequencing across the Phytophthora genus, we now have the genomic resources to evaluate horizontal gene transfer events across the oomycetes. Using a machine-learning approach to identify horizontally transferred genes with bacterial or fungal origin, we identified 44 candidates over 36 Phytophthora species genomes. Phylogenetic reconstruction indicates that the transfers of most of these 44 candidates happened in parallel to major advances in the evolution of the oomycetes and Phytophthora spp. We conclude that the 31 genomes presented here are essential for investigating genus-wide genomic associations in genus Phytophthora. [ ] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .