BACKGROUND:Accurate assessment of disease severity is essential for evaluating fungicide performance and breeding disease-resistant crop varieties. Manual scoring of infection on individual leaf discs is labor-intensive and variable, while traditional computer vision methods require manual parameter tuning and lack robustness. Existing deep learning approaches often struggle to simultaneously localize leaf discs and accurately segment disease symptoms, limiting their practical application. RESULTS:We developed SporaScan, an automated pipeline combining YOLO v8n for leaf disc localization, Mobile SAM for background removal, and UNet for sporulation segmentation. It achieved high accuracy (mAP@50 >99%, mIoU@50 >96%), with background removal reducing misclassification (0.21% for sporulation and 2.75% for leaf discs). Severity estimates showed strong agreement with manual annotations (R2 = 0.99). In a blind test, technicians selected SporaScan as superior in 37.2% of cases, manual annotation in 26.2%, and equal performance in 36.6% (P < 0.001). Compared with Mask R-CNN, the sequential design improved accuracy and efficiency. CONCLUSION:These results demonstrate that SporaScan provides an efficient and practical approach for automated assessment of downy mildew severity, supporting applications in disease evaluation, breeding, and fungicide assessment (http://116.10.197.212:9060/segment/#/). © 2026 Society of Chemical Industry.

To defend against pathogen invasion, plants deploy a variety of strategies, among which salicylic acid (SA), a key plant defense hormone, plays crucial roles in enhancing host resistance to biotrophic and semibiotrophic microbes. Although numerous studies elucidated mechanisms of the SA signaling pathway, many questions remain. In this study, we show that the group IIc WRKY transcription factor VvWRKY8 is involved in grape (Vitis vinifera) defense responses to the oomycete pathogen Plasmopara viticola, as indicated by transcriptome analyses. VvWRKY8 increases the expression of defense-related genes and SA accumulation, thereby promoting grape resistance to P. viticola. Further analyses reveal that VvWRKY8 is recruited to the promoters of VvCBP60g and VvSARD1, which encode two key regulators of SA biosynthesis, and upregulates their transcription. Moreover, VvWRKY8 transcription is induced by SA and by two bZIP transcription factors, VvTGA2a and VvTGA2b, which cooperate with the SA receptors VvNPR1 and VvNPR3 to modulate the expression of SA-responsive genes. Collectively, our results indicate that a positive feedback loop involving VvWRKY8 and the SA pathway components VvCBP60g, VvSARD1, and VvTGA2a/2b functions in response to P. viticola attack in grapevine.

Grapevine downy mildew caused by Plasmopara viticola (Pv) is one of the most devastating diseases of grapevine in China. To understand the origin and pathogenicity of Chinese Pv, a total of 193 single-sporangiophore isolates were obtained from 14 Chinese major viticulture areas. Phylogenetic analyses suggest that Chinese Pv isolates originate from North America and belong to the P. viticola clade aestivalis. Host range experiments reveal that Chinese Pv are able to infect a wide range of Vitis species from different geographic origins, including Eurasian species Vitis vinifera, North American species V. aestivalis, V. riparia, and V. rupestris, and East Asian Vitis species V. davidii, V. amurensis, and V. hancockii. Analyses of the interactions between Pv isolates and grapevines reveal that the virulence of Pv isolates is correlated with the occurrence time and magnitude of hypersensitive response-mediating leaf necrosis in grape leaves caused by Pv. These understandings of genetic diversity and pathogenicity of Chinese Pv isolate would be useful to develop strategies for controlling grapevine downy mildew spread.

Deep learning (DL) models have shown exceptional accuracy in plant disease identification, yet their practical utility for farmers remains limited due to a lack of professional and actionable guidance. To bridge this gap, we developed CDIP-ChatGLM3, an innovative framework that synergizes a state-of-the-art DL-based computer vision model with a fine-tuned large language model (LLM), designed specifically for Crop Disease Identification and Prescription (CDIP). EfficientNet-B2, evaluated among 10 DL models across 48 diseases and 13 crops, achieved top performance with 97.97 % +/- 0.16 % accuracy at a 95 % confidence level. Building on this, we fine-tuned the widely used ChatGLM3-6B LLM using Low-Rank Adaptation (LoRA) and Freeze-tuning, optimizing its ability to deliver precise disease management prescriptions. We compared two training strategies-multi-task learning (MTL) and Dual-stage Mixed Fine-Tuning (DMT)-using a different combination of domain-specific and general datasets. Freeze-tuning with DMT led to substantial performance gains, achieving a 33.16 % improvement in BLEU-4 and a 27.04 % increase in the Average ROUGE F-score, surpassing the original model and state-of-the-art competitors such as Qwen-max, Llama-3.1-405B-Instruct, and GPT-4o. The dual-model architecture of CDIPChatGLM3 leverages the complementary strengths of computer vision for image-based disease detection and LLMs for contextualized, domain-specific text generation, offering unmatched specialization, interpretability, and scalability. Unlike resource-intensive multimodal models that blend modalities, our dual-model approach maintains efficiency while achieving superior performance in both disease identification and actionable prescription generation.

China holds the largest apple cultivation area globally, yet yields per hectare remain relatively low. Despite substantial government investment in modern orchard technologies, adoption remains limited among farmers. This study investigates the economic and sociological drivers of technology uptake, focusing on how information sources shape adoption behavior. Based on 382 farmer surveys across major apple-producing provinces, the study examines (1) farmers’ preferences for agricultural information sources, (2) the influence of demographic characteristics on those preferences, and (3) the differential effects of specific sources on the adoption of key technologies, including dwarf rootstocks and virus-free seedlings. Results show that agri-chemical dealers (ACDs) and farmer peers (FPs) are the most commonly used information channels. Access to advice from local experts (EXPs) significantly increases the likelihood of adopting dwarf rootstocks, while information from ACDs promotes the use of virus-free seedlings. In contrast, reliance on personal farming experience is negatively associated with technology uptake. These findings highlight the need to strengthen formal information dissemination systems and better integrate trusted local actors like ACDs and EXPs into agricultural extension. Targeted information delivery can improve adoption efficiency, promote evidence-based decision-making, and support the modernization and sustainability of China’s apple sector.

Plasmopara viticola that causes grapevine downy mildew disease in viticulture regions is among the 10 most relevant pathogens worldwide. It secretes a large arsenal of effectors to facilitate colonisation by perturbing host immunity. However, the underlying mechanisms by which P. viticola effectors disturb grapevine defence are still largely unknown. In this study, we report that PvRXLR10, an RXLR effector with a WY domain, promotes P. viticola infection in grapevine and Phytophthora parasitica colonisation in Nicotiana benthamiana. PvRXLR10 interacts with a host patatin-like protein VvipPLA-IIδ2 with phospholipase A2 activity. The WY domain of PvRXLR10 is not responsible for cell death suppression in N. benthamiana but is necessary for PvRXLR10 interaction with VvipPLA-IIδ2. Overexpression and RNAi-mediated suppression of VvipPLA-IIδ2 expression in Vitis vinifera consistently showed that this protein positively regulates plant immunity in response to P. viticola infection. Interestingly, we found that VvipPLA-IIδ2 partially associates with PvRXLR10 at the endoplasmic reticulum (ER). Reverse transcription-quantitative PCR (RT-qPCR) analysis showed that the expression of VvipPLA-IIδ2 was suppressed by PvRXLR10 during P. viticola infection. The overexpression of VvipPLA-IIδ2 in V. vinifera induced higher expression of genes related to jasmonic acid (JA) biosynthesis, signalling pathways and defence response. The evidence indicates the important roles of VvipPLA-IIδ2 in grapevine immunity and P. viticola effector PvRXLR10 targets this protein to promote its infection.

BACKGROUND: Crop diseases can lead to significant yield losses and food shortages if not promptly identified and managed by farmers. With the advancements in convolutional neural networks (CNN) and the widespread availability of smartphones, automated and accurate identification of crop diseases has become feasible. However, although previous studies have achieved high accuracy (>95%) under laboratory conditions (Lab) using mixed data sets of multiple crops, these models often falter when deployed under field conditions (Field). In this study, we aimed to evaluate disease identification accuracy under Lab, Field, and Mixed (Lab and Field) conditions using an assembled data set encompassing 14 diseases of apple (Malus x domestica Borkh.), potato (Solanum tuberosum L.), and tomato (Solanum lycopersicum L.). In addition, we investigated the impact of model architectures, parameter sizes, and crop-specific models (CSMs) on accuracy, using DenseNets, ResNets, MobileNetV3, EfficientNet, and VGG Nets. RESULT:Our results revealed a decrease in accuracy across all models from Lab (98.22%) to Mixed (91.76%) to Field (71.55%) conditions. Interestingly, disease classification accuracy showed minimal variation across model architectures and parameter sizes: Lab (97.61-98.76%), Mixed (90.76-92.31%), and Field (68.56-73.81%). Although CSMs were found to reduce inter-crop disease misclassifications, they also led to a slight increase in intra-crop misclassifications. CONCLUSION: Our findings underscore the importance of enriching data representation and volumes over employing new model architectures. Furthermore, the need for more field-specific images was highlighted. Ultimately, these insights contribute to the advancement of crop disease identification applications, facilitating their practical implementation in farmer's fields. (c) 2024 Society of Chemical Industry.

Monitoring spores is crucial for predicting and preventing fungal- or oomycete-induced diseases like grapevine downy mildew. However, manual spore or sporangium detection using microscopes is time-consuming and labor-intensive, often resulting in low accuracy and slow processing speed. Emerging deep learning models like YOLOv8 aim to rapidly detect objects accurately but struggle with efficiency and accuracy when identifying various sporangia formations amidst complex backgrounds. To address these challenges, we developed an enhanced YOLOv8s, namely, AFM-YOLOv8s, by introducing an Adaptive Cross Fusion module, a lightweight feature extraction module FasterCSP (Faster Cross-Stage Partial Module), and a novel loss function MPDIoU (Minimum Point Distance Intersection over Union). AFM-YOLOv8s replaces the C2f module with FasterCSP, a more efficient feature extraction module, to reduce model parameter size and overall depth. In addition, we developed and integrated an Adaptive Cross Fusion Feature Pyramid Network to enhance the fusion of multiscale features within the YOLOv8 architecture. Last, we utilized the MPDIoU loss function to improve AFM-YOLOv8s’ ability to locate bounding boxes and learn object spatial localization. Experimental results demonstrated AFM-YOLOv8s’ effectiveness, achieving 91.3% accuracy (mean average precision at 50% IoU) on our custom grapevine downy mildew sporangium dataset—a notable improvement of 2.7% over the original YOLOv8 algorithm. FasterCSP reduced model complexity and size, enhanced deployment versatility, and improved real-time detection, chosen over C2f for easier integration despite minor accuracy trade-off. Currently, the AFM-YOLOv8s model is running as a backend algorithm in an open web application, providing valuable technical support for downy mildew prevention and control efforts and fungicide resistance studies.

Tandem gene duplication is an important process in plant adaptive evolution, but the generation mechanism and expression characteristics of tandem duplicated (TD) genes and their roles in plant stress response have not been rigorously investigated. Here, we take grapevine (V. vinifera) as an example to show that recent large-scale tandem gene duplication, mediated by long terminal repeat retrotransposons, promotes the expansion of specific gene families involved in response to biotic stress, biosynthesis of various secondary metabolites and adaptive evolution. More importantly, compared with interspersed duplicated genes, TD genes exhibit a position and synergistic effect, and multifaceted overactivity and play key roles in response to biotic stress caused by pathogens such as P. viticola (downy mildew) and Erysiphe necator (powdery mildew). The higher co-expression level of TD genes is not only reflected in the co-response to biotic stress, but also universal in various tissues and developmental stages. This may be related to a higher level of co-regulation and a higher transcription factor regulatory efficiency, as well as sequence similarity within gene clusters. Moreover, most TD genes are expressed asymmetrically, while maintaining a relative balance, which may be beneficial for the retention and functional differentiation of the TD genes. These findings not only advance our understanding of the evolution of the V. vinifera genome and the evolution dynamics of the TD genes which has often been overlooked, but also provide guidance for the directional selection in breeding work.

【Objective】The objective of this study is to clone glycosyl hydrolase genes from Plasmopara viticola (PvGHs), analyze their characteristics and expression patterns in infected grape leaves, and the abilities to inhibit or promote programmed cell death (PCD) and affect Phytophthora nicotianae infection in tobacco leaves, so as to provide a theoretical basis for further study on mechanism of regulating host plant immunity.【Method】Eight PvGHs with full-length were amplified by RT-PCR from P. viticola Pv5-27 strain. The sequences of these eight PvGHs and encoded proteins were analyzed by bioinformatics. Yeast signal peptide trap system (SST) was used to verify the secretory activity of the PvGH proteins. The expression pattern of PvGHs during infection grape leaves was detected by qRT-PCR. At the same time, eight PvGH effector proteins were transiently expressed in Nicotiana benthamiana by Agrobacterium-mediated PVX virus expression system. Moreover, their inhibitory abilities to inhibit INF1- and BAX-triggered PCD and to promote P. nicotianae infection were also analyzed.【Result】The sequences of eight PvGHs were completely consistent with the prediction in genome sequence, with the length of 1 092 to 1 392 bp, encoding 364-464 amino acids, respectively. The similarity with homologous proteins from other oomycetes was as high as 60.62%-86.36%. None of them had transmembrane domains. Their secondary structures were quite different from each other, and their tertiary structures were less similar to those of other proteins, which showed a very unique tertiary structure. SingalP 5.0 software was used to predict signal peptide of these proteins. It was found that all the PvGH proteins contained signal peptide sequences of 20-26 aa in length. However, the SST verification results showed that PvG09279 and PvG13517 do not have secretion activity. The retention, deletion or replacement of signal peptide sequences of the eight PvGH proteins could inhibit the BAX-triggered PCD and all these PvGH proteins could promote P. nicotianae infection in tobacco leaves. It suggests that the potential virulence of eight PvGH effectors does not dependent on the signal peptide. The up-regulated expression of PvGHs in the early stage of infection of P. viticola further indicated that PvGHs play an important role in the interaction between pathogen and host.【Conclusion】During downy mildew infection, PvGHs secreted by P. viticola are involved in pathogenic process by inhibiting the host PTI response.

[目的]构建华东葡萄遗传连锁图谱,并定位其抗灰霉病QTL,为华东葡萄种质资源的高效利用及其抗灰霉病基因发掘提供理论基础.[方法]以高感灰霉病的欧洲葡萄赤霞珠为母本、抗灰霉病的华东葡萄1058-2为父本,以二者杂交F1代128株单株为群体材料,利用GBS(Genotyping-by-sequencing)简化基因组测序技术开发SNP分子标记,应用JoinMap 4.0构建遗传连锁图谱,使用MapQTL 6.0对F1代抗灰霉病表型进行抗灰霉病QTL定位.与葡萄参考基因组PN40024进行比对分析,筛选QTL区间的抗病候选基因.[结果]2019和2020年杂交F1代群体的灰霉病抗性多为中抗及以上.在亲本之间共鉴定到6357个SNP分子标记.挑选出在染色体上均匀分布的654个SNP分子标记用于构建华东葡萄遗传连锁图谱.该图谱包含19个连锁群,总长度为1843.67 cM,SNP分子标记间平均遗传距离为2.82 cM.根据2019和2020年的F1群体灰霉病表型数据,连续两年在LG9连锁群上定位到1个与灰霉病抗性连锁的QTL,命名为Rbc1.该QTL与SNP分子标记np6008紧密连锁,在2019和2020年表型中可解释的变异率分别为13.1％和12.6％.参考葡萄基因组PN40024的物理图谱和基因注释信息,Rbc1位于9号染色体物理距离5969～12345 kb内,在这个QTL区间含有45个与抗病性相关的基因,编码含有LRR结构域的受体激酶和推测的抗病蛋白.[结论]葡萄灰霉病抗性是多基因控制的数量性状,抗性亲本华东葡萄1058-2中存在抗病的主效QTL.筛选出的45个与抗病性相关的基因可能参与调控葡萄灰霉病抗性,后续可作为候选基因进一步解析华东葡萄1058-2灰霉病抗性功能.

综述植物病原菌糖基水解酶(glycoside hydrolases,GHs)基因家族的分类、酶活功能、在病原菌中的分布特征,以及在病原菌侵染过程中发挥的作用等方面的研究进展,重点分析植物病原菌GHs在病原菌侵染过程中的作用:作为毒力因子/致病因子促进病原菌侵染、作为激发子或病原体相关分子模式(PAMPs)诱导植物免疫、将植物细胞壁分解为损伤相关分子模式(DAMPs)诱导植物免疫、特异性结合或分解病原/微生物相关分子模式(P/MAMPs)抑制植物免疫.在此基础上,总结并展望植物病原菌GHs调控植物免疫的分子机制及存在的问题,为深入研究GHs的更多功能提供参考,同时也为作物改良及病害防控策略中更好地利用这些GHs家族成员提供思路.

【Objective】The objective of this study is to clone the chalcone synthase gene CHS1 in different resistant grape varieties, clarify the expression pattern under the infection of Botrytis cinerea and Plasmopara viticola, verify the subcellular localization and function of CHS1, and to provide a basis for exploring the broad-spectrum resistance mechanism of CHS1.【Method】CHS1 genes were cloned from the leaf cDNAs of Vitis quinquangularis ‘Yeniang-2’, Vitis vinifera ‘Thompson Seedless’ and Vitis amurensis ‘Shuanghong’. The differences in the nucleic acid sequence and physicochemical properties of CHS1 protein were analyzed by bioinformatics. Expression patterns of CHS1 in different varieties during B. cinerea and P. viticola infection were also detected by qRT-PCR. The expression vector was constructed, and the transient expression technology mediated by Agrobacterium was used to verify the subcellular localization and disease resistance function in the leaves of tobacco and ‘Thompson Seedless’ tissue culture seedlings.【Result】The CHS1 is highly conserved among different grape varieties. The full length of ORF is 1 182 bp, which encodes 393 amino acids. The predicted molecular weight of the encoded protein is 42.92 kD, which is a stable hydrophilic protein. After being infected by B. cinerea, the expression patterns of VqCHS1 and VvCHS1 were similar, but the expression level of VqCHS1 in the resistant variety ‘Yejiang-2’ was significantly higher. After being infected by P. viticola, VaCHS1 and VvCHS1 showed different expression pattern changes. The expression level of VaCHS1 in the resistant variety ‘Shuanghong’ continued to increase, while the expression level of VvCHS1 gradually decreased. The results of subcellular localization showed that CHS1 protein is distributed in the cytoplasm and nucleus, but it is mainly localized in the nucleus. Compared with the negative control, the ‘Thompson Seedless’ leaves overexpressing VaCHS1 showed stronger resistance to gray mold and downy mildew after artificial inoculation.【Conclusion】The expression level of CHS1 in resistant varieties is higher than that in susceptible varieties, and overexpression of CHS1 can increase the resistance of susceptible grape varieties to gray mold and downy mildew.

Grapevine downy mildew (DM) is a destructive oomycete disease of viticulture worldwide. MrRPV1 is a typical TIR-NBS-LRR type DM disease resistance gene cloned from the wild North American grapevine species Muscadinia rotundifolia . However, the molecular basis of resistance mediated by MrRPV1 remains poorly understood. Downy mildew-susceptible Vitis vinifera cv. Shiraz was transformed with a genomic fragment containing MrRPV1 to produce DM-resistant transgenic Shiraz lines. Comparative transcriptome analysis was used to compare the transcriptome profiles of the resistant and susceptible genotypes after DM infection. Transcriptome modulation during the response to P. viticola infection was more rapid, and more genes were induced in MrRPV1 -transgenic Shiraz than in wild-type plants. In DM-infected MrRPV1 -transgenic plants, activation of genes associated with Ca 2+ release and ROS production was the earliest transcriptional response. Functional analysis of differentially expressed genes revealed that key genes related to multiple phytohormone signaling pathways and secondary metabolism were highly induced during infection. Coexpression network and motif enrichment analysis showed that WRKY and MYB transcription factors strongly coexpress with stilbene synthase ( VvSTS ) genes during defense against P. viticola in MrRPV1 -transgenic plants. Taken together, these findings indicate that multiple pathways play important roles in MrRPV1- mediated resistance to downy mildew.

卵菌是一类可以侵染动植物以及微生物的病原菌.植物病原卵菌会导致很多农作物、经济作物产生病害,造成巨大的经济损失.效应蛋白在植物病原卵菌侵染寄主的过程中发挥关键作用.本文概述病原卵菌分泌的效应蛋白RXLR和CRN的挖掘方法、转运机制以及靶标蛋白筛选的最新研究进展.这些信息可为深入揭示效应蛋白RXLR和CRN的致病机理和与寄主互作机制等提供理论指导,也为未来植物抗病育种和绿色防控等提供研究方向和策略.

[目的]分析预测葡萄霜霉菌糖基水解酶(Glycoside hydrolases,GHs)基因家族,为深入研究GHs基因在葡萄霜霉菌致病过程中的作用机理提供理论依据.[方法]利用SignalP 5.0 Server、Cluster W、MEGA 6.0和MEME等生物信息学相关软件对已发表的葡萄霜霉菌全基因组60个GHs基因的基本特征、基因组分布特点及其编码蛋白保守基序、结构域和亚细胞定位等进行生物信息学分析.[结果]葡萄霜霉菌60个GHs基因编码的蛋白长度在128～774 aa,且大部分集中在200～500 aa,其中53个蛋白具有信号肽,蛋白质分子量在14.90～85.45 kD,理论等电点(pI)在3.85～10.39;这些基因在基因组中分布不均匀,其中有27个GHs基因存在串联重复和成簇聚集分布现象,数目最多的3个GHs家族(GH131、GH17和GH6)集中分布在7个scaffold中;序列比对和系统发育进化树分析发现,串联重复和成簇聚集分布的GHs基因处于同一个分支中;motif富集分析发现3个不同的motif,且motif2在葡萄霜霉菌GH6、GH17和GH131等3个家族基因中保守,结构域分析推测大部分GHs家族基因均参与细胞壁的生物过程;亚细胞定位预测结果表明,有53个GHs蛋白定位于细胞外,3个定位在细胞质内,4个定位于线粒体上.[结论]葡萄霜霉菌在侵染寄主的过程中可能会分泌多种GHs酶类来破坏细胞壁的结构,以帮助其在寄主植物中成功定殖.

BACKGROUND:Paphiopedilum hirsutissimum is a member of Orchidaceae family that is famous for its ornamental value around the globe, it is vulnerable due to over-exploitation and was listed in Appendix I of the Convention on International Trade in Endangered Species of Wild Fauna and Flora, which prevents its trade across borders. Variation in flower color that gives rise to different flower patterns is a major trait contributing to its high ornamental value. However, the molecular mechanism underlying color formation in P. hirsutissimum still remains unexplored. In the present study, we exploited natural variation in petal and labellum color of Paphiopedilum plants and used comparative transcriptome analysis as well as pigment measurements to explore the important genes, metabolites and regulatory pathways linked to flower color variation in P. hirsutissimum.RESULT:We observed that reduced anthocyanin and flavonoid contents along with slightly higher carotenoids are responsible for albino flower phenotype. Comparative transcriptome analysis identified 3287 differentially expressed genes (DEGs) among normal and albino labellum, and 3634 DEGs between normal and albino petals. Two genes encoding for flavanone 3-hydroxylase (F3H) and one gene encoding for chalcone synthase (CHS) were strongly downregulated in albino labellum and petals compared to normal flowers. As both F3H and CHS catalyze essentially important steps in anthocyanin biosynthesis pathway, downregulation of these genes is probably leading to albino flower phenotype via down-accumulation of anthocyanins. However, we observed the downregulation of major carotenoid biosynthesis genes including VDE, NCED and ABA2 which was inconsistent with the increased carotenoid accumulation in albino flowers, suggesting that carotenoid accumulation was probably controlled at post-transcriptional or translational level. In addition, we identified several key transcription factors (MYB73, MYB61, bHLH14, bHLH106, MADS-SOC1, AP2/ERF1, ERF26 and ERF87) that may regulate structural genes involved in flower color formation in P. hirsutissimum. Importantly, over-expression of some of these candidate TFs increased anthocyanin accumulation in tobacco leaves which provided important evidence for the role of these TFs in flower color formation probably via regulating key structural genes of the anthocyanin pathway.CONCLUSION:The genes identified here could be potential targets for breeding P. hirsutissimum with different flower color patterns by manipulating the anthocyanin and carotenoid biosynthesis pathways.

Microorganisms in grape skins play vital roles in grapevine health, productivity, wine quality and organoleptic properties. To investigate microbial diversity of muscadine grape skins, 16S and ITS sequences of 30 samples from six muscadine (Muscadinia rotundifolia Michx.) cultivars grown in Guangxi, China, were sequenced using Illumina Novaseq platform. A total of 7,317 bacterial operational taxonomic units (OTUs) and 1,611 fungal OTUs were obtained, and clustered into 38 bacterial and 7 known fungal phyla. The dominant bacterial phyla were Proteobacteria, Firmicutes, Bacteroidetes, Planctomycetes, Actinobacteria, Verrucomicrobia, Acidobacteria, and Patescibacteria, and the dominant genera were Lelliottia, Prevotella_9, Escherichia-Shigella, Lactobacillus, Pseudomonas, Akkermansia, Faecalibacterium, Rahnella, and Acinetobacter. For fungi, the dominant phyla were Ascomycota, Basidiomycota, and Mortierellomycota, and the dominant genera were Acaromyces, Uwebraunia, Penicillium, Zygosporium, Ilyonectria, Aspergillus, Neodevriesia, Strelitziana, Mortierella, and Fusarium. Alpha diversity analysis and Kruskal-Wallis H test demonstrated that microbial diversity and composition were affected by the cultivar. The Pearson correlation analysis of species revealed complex interactions among microbes. PICRUSt2 predicted that the metabolism of carbohydrates, cofactors, vitamins, amino acids, terpenoids, polyketides, lipids and biosynthesis of other secondary metabolites were abundant. These results contribute to understanding the uniqueness of muscadine grapes and the links among microorganisms in grape skins.

Downy mildew, caused by Plasmopara viticola, is a major disease that affects grapevines, and a few resistance (R) genes have been identified thus far. In order to identify R genes, we investigated F-1 progeny from a cross between the downy mildew-resistant Vitis amurensis 'Shuang Hong' and the susceptible Vitis vinifera 'Cabernet Sauvignon'. The P. viticola-resistance of the progeny varied continuously and was segregated as a quantitative trait. Genotyping-by-sequencing was used to construct linkage maps. The integrated map spanned 1898.09 cM and included 5603 single nucleotide polymorphisms on 19 linkage groups (LGs). Linkage analysis identified three quantitative trait loci (QTLs) for P. viticola resistance: 22 (Rpv22) on LG 02, Rpv23 on LG15, and Rpv24 on LG18. The phenotypic variance contributed by these three QTLs ranged from 15.9 to 30.0%. qRT-PCR analysis of R-gene expression in these QTLs revealed a CC-NBS-LRR disease resistance gene RPP8, two LRR receptor-like serine/threonine-protein kinases, a serine/threonine-protein kinase BLUS1, a glutathione peroxidase 8, an ethylene-responsive transcription factor ERF038, and a transcription factor bZIP11 were induced by P. viticola, and these genes may play important role in P. viticola response.

[目的]构建霜霉菌侵染后葡萄叶片的酵母双杂交cDNA文库,筛选致病因子在寄主葡萄体内的互作靶标,为葡萄霜霉病菌致病的分子机理研究提供材料基础.[方法]以一年生欧亚种葡萄西拉盆栽苗为试验材料,提取并等量混合霜霉菌侵染后0、12、18、24和36 h的葡萄叶片总RNA,利用基于Gateway技术的CloneMiner II cDNA文库构建试剂盒:首先将cDNA与pDONR222载体进行BP重组反应连接,连接产物转化大肠杆菌DH10B感受态细胞构建初级文库;然后初级文库质粒与pGADT7-DEST载体通过LR重组反应,重组反应产物转化大肠杆菌DH10B感受态细胞构建次级文库;再随机挑取次级文库转化Y187酵母菌株构建酵母双杂交cDNA文库;最后利用ImageJ软件和PCR反应分别统计库容量和鉴定重组率.[结果]构建的初级文库库容量为4.6×107 CFU,次级文库库容量为2.7×107 CFU,均达到构建cDNA文库的标准.酵母双杂交cDNA文库的插入片段主要集中在1000～2000 bp,且具有很好的多态性,文库质量较高.[结论]构建的霜霉菌诱导葡萄叶片酵母双杂交cDNA文库符合酵母双杂交筛选要求,可用于筛选霜霉菌致病效应蛋白在寄主体内的靶标及霜霉菌侵染寄主葡萄早期抑制寄主免疫过程中的致病机理研究.