Integrated Transcriptomic and Metabolomic Profiling Reveals the Antagonistic and Synergistic Crosstalk During Co-Infection of Potato Virus Y and Potato Spindle Tuber Viroid

Integrated Transcriptomic and Metabolomic Profiling Reveals the Antagonistic and Synergistic Crosstalk During Co-Infection of Potato Virus Y and Potato Spindle Tuber Viroid | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 3 October 2025 V1 Latest version Share on Integrated Transcriptomic and Metabolomic Profiling Reveals the Antagonistic and Synergistic Crosstalk During Co-Infection of Potato Virus Y and Potato Spindle Tuber Viroid Authors : Wajahat Hussain , Meijia Wu , Yicong Wu , Guangyan Li , Yonghong Zhou 0000-0002-7194-5402 [email protected] , and Dianqiu Lv Authors Info & Affiliations https://doi.org/10.22541/au.175952228.86175455/v1 258 views 131 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Plants often face multiple pathogens attacks at once, but how they handle these complex infections at the molecular level is not well understood. This study uses transcriptomic and metabolomic analyses to explore the interaction between potato virus Y (PVY), a protein-coding RNA virus, and potato spindle tuber viroid (PSTVd), a non-coding RNA pathogen, which often infects plants together. Samples from different potato fields showed that PVY strong presence and frequently pairs with PSTVd, suggesting PVY helps PSTVd persist. Observations of plant symptoms confirmed PVY dominant role, causing severe stunting and yellowing, while PSTVd milder effects were hidden in co-infected plants. Transcriptomic data revealed PVY broadly alters plant processes like photosynthesis, carbon use, and immune responses, while PSTVd targets specific pathways, such as protein modification and plant-pathogen interactions. Co-infection boosted these effects, triggering strong increases in defense-related TF, e.g., WRKY, NAC, MYC, and hormone signalling. Metabolite analysis showed major changes in hormones, especially cytokinins and jasmonates, with zeatin production as a key shared pathway. Weighted Gene Co-expression Network Analysis (WGCNA) identified unique gene groups for each infection, with co-infection showing enhanced immune and metabolic activity. Integrated gene-metabolite networks confirmed PVY leading role, linking key genes, e.g., AHP1/4, PYL1/8, COI1, to hormones like cytokinin, jasmonoyl-isoleucine and abscisic acid. These findings suggest PVY drives strong immune responses, while PSTVd may rely on PVY suppression of plant defenses to survive, offering new insights into managing complex plant diseases. Integrated Transcriptomic and Metabolomic Profiling Reveals the Antagonistic and Synergistic Crosstalk During Co-Infection of Potato Virus Y and Potato Spindle Tuber Viroid Wajahat Hussain1, 2, 3†, Meijia Wu2†, Yicong Wu2, Guangyan Li1, 2, 3, Yonghong Zhou1, 2, 3, *, Dianqiu Lv1, 2, 3, * 1 Integrative Science Center of Germplasm Creation in Western China (CHONGQING) Science City, Chongqing Technology Innovation Center of Breeding, Southwest University, Chongqing 401329, China 2 College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China 3 Chongqing Key Laboratory of Biology and Genetic Breeding for Tuber and Root Crops, Southwest University, Chongqing 400715, China †These authors contributed equally to this work. *Corresponding Authors: Dianqiu Lv ( [email protected] ), Yonghong Zhou ( [email protected] ) Abstract Plants often face multiple pathogens attacks at once, but how they handle these complex infections at the molecular level is not well understood. This study uses transcriptomic and metabolomic analyses to explore the interaction between potato virus Y (PVY), a protein-coding RNA virus, and potato spindle tuber viroid (PSTVd), a non-coding RNA pathogen, which often infects plants together. Samples from different potato fields showed that PVY strong presence and frequently pairs with PSTVd, suggesting PVY helps PSTVd persist. Observations of plant symptoms confirmed PVY dominant role, causing severe stunting and yellowing, while PSTVd milder effects were hidden in co-infected plants. Transcriptomic data revealed PVY broadly alters plant processes like photosynthesis, carbon use, and immune responses, while PSTVd targets specific pathways, such as protein modification and plant-pathogen interactions. Co-infection boosted these effects, triggering strong increases in defense-related TF, e.g., WRKY, NAC, MYC, and hormone signalling. Metabolite analysis showed major changes in hormones, especially cytokinins and jasmonates, with zeatin production as a key shared pathway. Weighted Gene Co-expression Network Analysis (WGCNA) identified unique gene groups for each infection, with co-infection showing enhanced immune and metabolic activity. Integrated gene-metabolite networks confirmed PVY leading role, linking key genes, e.g., AHP1/4, PYL1/8, COI1, to hormones like cytokinin, jasmonoyl-isoleucine and abscisic acid. These findings suggest PVY drives strong immune responses, while PSTVd may rely on PVY suppression of plant defenses to survive, offering new insights into managing complex plant diseases. Keywords : potato virus Y, potato spindle tuber viroid, co-infection, transcriptomics, metabolomics, hormone signalling Introduction: In an era of increasing agricultural demands and environmental stresses, crops face relentless challenges from a multitude of pathogens. These threats persist across both natural and agricultural ecosystems, where they can severely compromise plant growth, yield, and survival (Singh et al., 2023, Biswas and Das, 2024). Among these threats, plant viruses and viroids rank among the most destructive, capable of causing severe economic losses and threatening global food security (Jones, 2021, Aslam et al., 2024, Sastry, 2013). These microscopic intracellular parasites invade plant tissues, hijack host cellular machinery for replication, and induce disease (Sharma et al., 2025). Viroids are particularly unique unlike viruses, they consist solely of a small, naked RNA molecule, typically about ten times smaller than viral genomes, and lack a protective protein coat (Agrios, 2009, Zhang et al., 2024). Within this diverse group of pathogens, potato virus Y (PVY) and potato spindle tuber viroid (PSTVd) are especially concerning due to their global prevalence and devastating impact on Solanaceous crops such as potato, tobacco, pepper, and tomato. (Torrance and Talianksy, 2020, Sial et al., 2025). PVY, a member of the Potyviridae family, is one of the most economically damaging plant viruses. It is known for its ability to induce a range of symptoms, including leaf deformation and mosaic patterns, necrosis, which significantly impair plant growth and productivity (Yang et al., 2021, Quenouille et al., 2013). PVY is primarily transmitted by aphids in a non-persistent manner (Bhoi et al., 2022) Based on the difference in the viral nucleotide sequence, PVY is classified into several strains, including PVYN, PVYO, and PVYC, each exhibiting different pathogenic characteristics and eliciting varying responses in host plants (Cuevas et al., 2012). PVY RNA genome encodes several proteins that interfere with host cellular processes, triggering complex defense responses (Kozieł et al., 2021, Baebler et al., 2020). PSTVd is a viroid, the smallest known nucleic pathogen of plants (Owens et al., 2012, Zhang et al., 2024). PSTVd is the model member of the Pospiviroidae family. Unlike viruses, viroids consist solely of a short strand of circular, single-stranded non-coding RNA without a protein coat (Sano, 2021). Despite its simplicity, PSTVd causes severe diseases in susceptible plants, including foliar deformation, arbuscular and short plant. Additionally, PSTVd disrupts tuber development, leading to irregularities in shape and size (Katsarou et al., 2016b, Fujibayashi et al., 2021). PSTVd is mechanically transmitted through infected plant material, vegetative propagation techniques, and also by aphids (Afanasenko et al., 2022a). The pathogenicity of PSTVd is attributed to its ability to hijack the host’s RNA silencing machinery, leading to the disruption of normal gene expression (Kochetov et al., 2021). The obligate intracellular nature of these plant pathogens limits chemical intervention to their insect vectors, as they cannot be directly targeted outside a host cell. Breeding plants for viral tolerance or resistance through marker-assisted selection offers an alternative control method. This approach relies heavily on deciphering the molecular mechanisms behind a plant’s natural defenses (Piquerez et al., 2014, Nicaise, 2014). However, the study of global transcriptomic and metabolomic responses in plants provides valuable insights into the complex interactions between host plants and pathogens. Transcriptomics, which involves the comprehensive analysis of RNA transcripts produced by the genome, helps in understanding how plants regulate gene expression in response to pathogen attacks (Lowe et al., 2017). Metabolomics, on the other hand, focuses on the systematic study of chemical processes involving metabolites, offering a snapshot of the metabolic state of the organism under specific conditions (Chen et al., 2022). These omics technologies have revolutionized plant pathology by enabling the identification of key molecular pathways and metabolites involved in plant defense mechanisms. Various studies have shown that PVY infection triggers a cascade of defense-related gene expressions, including those involved in the synthesis of pathogenesis-related (PR) proteins, reactive oxygen species (ROS) scavenging enzymes, and secondary metabolites such as phenolics and alkaloids (Ross et al., 2022, Stare et al., 2019). These responses are part of the plant’s innate immune system, aimed at restricting viral replication and spread. Similarly, PSTVd infection leads to extensive reprogramming of the host transcriptome and metabolome. The viroid interaction with the host RNA silencing machinery not only disrupts normal gene expression but also affects key metabolic pathways. For instance, PSTVd-infected plants exhibit changes in the levels of phytohormones, such as salicylic acid and jasmonic acid, which play crucial roles in plant defense signaling (Milanović et al., 2019). Additionally, metabolomic studies have highlighted alterations in primary metabolites like sugars and amino acids, as well as secondary metabolites that are involved in defense responses (Bagherian et al., 2016). Despite extensive research on single-pathogen interactions, the molecular mechanisms governing how plants integrate concurrent biotic stress signals remain poorly understood (Dutt et al., 2022, Abdullah et al., 2017). This knowledge gap is particularly critical for economically important crops like potato (Solanum tuberosum ), which are susceptible to a range of pathogens, including RNA viruses and non-coding RNA viroids. This study aims to investigate the interplay between PVY and PSTVd during co-infection in potato plants using a comprehensive approach that integrates field surveys, phenotypic assessments, and multi-omics analyses. We hypothesize that PVY acts as the dominant pathogen, shaping host responses and potentially facilitating PSTVd persistence, while the host employs distinct signaling and metabolic strategies to cope with this dual infection. By elucidating these mechanisms, this research seeks to contribute to a deeper understanding of multi-pathogen interactions and inform the development of targeted disease management strategies to mitigate the impact of PVY and PSTVd on potato production. Our study provides novel insights into the molecular crosstalk underlying complex pathogen interactions and contributes to a broader understanding of plant defense regulation under mixed biotic stress. Materials and Methods 2.1 Field Sampling and Symptom Assessment A comprehensive field survey was conducted during the autumn growing season to investigate the occurrence and distribution of major viral and viroid pathogens affecting potato crops in Chongqing, southwestern China. Field sampling was carried out in three key potato cultivation regions: Wulong, Wuxi, and Hechuan. Symptomatic plants were randomly selected based on visible virus-like symptoms, including leaf rolling, mosaic patterns, interveinal chlorosis, dark green blistering, leaf crinkling, and vein necrosis. For each plant, the third fully expanded leaf from the apex was harvested as a representative sample. A total of 256 samples were collected across all sites. Each sample was photographed in situ to document symptom type, labeled, and stored in sterile collection bags. Samples were temporarily stored at 4 °C in the field and later transferred to the laboratory, where they were stored at -80 °C until further processing. Symptom categories were recorded and later correlated with molecular detection results. This sampling strategy aimed to capture the natural variation in disease expression and to support downstream. 2.2 Reverse Transcription PCR for Pathogen Detection in Potato Plants Leaf samples from symptomatic potato plants were collected, immediately frozen in liquid nitrogen, and RNA was extracted from symptomatic leaves using TRIzol reagent (Invitrogen, Carlsbad, CA, USA), following the manufacturer’s instructions. RNA purity and integrity was verified by 1% agarose gel electrophoresis, and concentration and purity were assessed using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The cDNA was synthesized from 1000 ng of total RNA using a reverse transcription kit (Hifair® Ⅲ 1st Strand cDNA Synthesis SuperMix, Yeasen) and following the its intructions. PCR amplifications were carried out individually using pathogen-specific primers targeting Potato virus S (PVS), Potato virus M (PVM), Potato virus X (PVX), Potato virus Y (PVY), Potato virus A (PVA), Potato leafroll virus (PLRV), and Potato spindle tuber viroid (PSTVd). Primers used in this study were shown in Supplementary information Table S1. The amplification program consisted of initial denaturation at 94°C for 5 min, followed by 35 cycles of denaturation at 94°C for 30 s, primer annealing at 58°C for 30 s, and extension at 72°C for 60 s, and a final extension at 72°C for 7 min. PCR products were analyzed by electrophoresis on 1.5% agarose gels stained with ethidium bromide and visualized under UV illumination. Specific amplified bands indicated the presence of viral infection in tested samples, compared to DNA ladder standards. 2.3 Plant Material and Growth Conditions Two plant species were used in this study: potato ( Solanum tuberosum ) cultivar ‘Kexin 18’ (K18) and Nicotiana benthamiana . Virus and viroid free potato plantlets of the K18 cultivar selected for its known susceptibility to a wide range of viral and viroid pathogens were propagated in vitro using nodal segments cultured on Murashige and Skoog (MS) medium under sterile conditions. Cultures were maintained at 24 °C with a 16 h light / 8 h dark photoperiod. For acclimatization, rooted plantlets were gently removed, washed free of culture medium, and incubated in distilled water for 24 h. The plants were then transplanted into plastic pots containing a 3:1 (v/v) mixture of peat and vermiculite, covered with transparent plastic film to maintain humidity. After 48 h, the film was removed, and plants were grown in a controlled chamber at 24 °C (light, 16 h) / 22 °C (dark, 8 h). Potato plants at the five-leaf stage were selected for viral and viroid inoculations. N. benthamiana seeds were evenly sown in seedling trays containing the same 3:1 peat-to-vermiculite substrate and germinated under identical environmental conditions (25 °C light / 22 °C dark, 16 h/8 h photoperiod). After 10 days, uniformly growing seedlings were transplanted into pots and maintained under the same conditions. Plants at the three-leaf stage were used for Potato virus Y (PVY) and Potato spindle tuber viroid (PSTVd) inoculation experiments. 2.4 Inoculation of PVY and PSTVd PVY inoculation is done by mechanical inoculation. Leaves of potato plant carrying PVYN were collected and homogenized in 3 times volume of phosphate buffer (PB, pH 7.2). The viral crude extract (20 μL) was dropped onto N. benthamiana and potato leaves. After sprinkling quartz sands, the leaf surface was rubbed gently to make wounds. Quartz sands were washed away be water after 3 hours. The mock was treated with phosphate buffer. Disease symptoms were observed on systemic leaves on 14 days post-inoculation. PSTVd was inoculated into the plant by Agrobacterium tumefaciens. Agrobacterium GV3101::pMP90::pSOUP containing plasmid pCAMBIA1300::35S::PSTVd-S (severe strain of PSTVd, GenBank X58388.1) stored at - 80 ℃ was streaked on YEB solid medium plates containing rifampicin and kanamycin and incubated at 28°C for 2 days. A single colony was inoculated into 5 mL of YEB liquid medium containing antibiotics, and shaken at 200 rpm overnight at 28°C. The overnight culture was then used to inoculate 50 mL of YEB liquid medium containing antibiotics. After shaking for approximately 6 hours until the OD600 reached about 0.5, the Agrobacterial culture was centrifuged at 8000 rpm for 10 minutes to collect the cells, which were then resuspended in an equal volume of MES solution and incubated at 28°C for 3 hours. The Agrobacterium suspension was infiltrated into 2-3 leaves of each N. benthamiana plant using a needleless syringe. The inoculated plants were placed in the dark at 23°C for 48 hours, then moved back to normal growth conditions. 2.5 RT-qPCR Analysis of PVY, PSTVd, and Differentially Expressed Genes Total RNA extraction and cDNA synthesis were conducted as detailed in the RT-PCR methodology section, utilizing TRIzol reagent (Invitrogen, Carlsbad, CA, USA) and the Hifair® III 1st Strand cDNA Synthesis SuperMix (Yeasen) from 1000 ng of RNA. For quantification of Potato virus Y (PVY) accumulation in potato leaves, RT-qPCR was performed using a CFX Connect Real-Time PCR System (Bio-Rad, Hercules, CA, USA) with iTaq Universal SYBR® Green Supermix (Bio-Rad). Primers targeted the PVY coat protein (CP) encoding gene, with Actin as the housekeeping gene for normalization (primer sequences listed in Supplementary Table S4). The reaction mixture (20 μL) contained 1 μL cDNA, 10 μL SYBR Green Supermix, and 0.3 μM of each primer. The thermal cycling program included an initial denaturation at 95°C for 30 s, followed by 40 cycles of 95°C for 5 s, 60°C for 10 s, and 72°C for 10 s, with a melt curve analysis from 60°C to 95°C at a ramp rate of 0.5°C/s to confirm product specificity. For Potato spindle tuber viroid (PSTVd) quantification in N. benthamiana leaves, a probe-based RT-qPCR assay was adapted from Qiu et al. (2020). Reactions were conducted using the Premix EXTaqTM (Probe qPCR) kit (TaKaRa, Kusatsu, Japan) on the same CFX Connect system. The 10 μL reaction mixture comprised 5 μL SYBR Green Supermix, 0.2 μL of each primer (10 μmol/L), 0.4 μL probe (10 μmol/L), 0.8 μL cDNA, and nuclease-free water. The cycling conditions included an initial denaturation at 95°C for 10 min, followed by 45 cycles of 95°C for 10 s, 60°C for 50 s, and 72°C for 1 s. Primer and probe sequences are provided in Supplementary Table S4. To validate differentially expressed genes (DEGs) identified from transcriptome sequencing, RT-qPCR was performed using the CFX Connect system with a 10 μL reaction containing 1 μL cDNA, 0.25 μL of each primer (10 μmol/L), 5 μL iTaq Universal SYBR® Green Supermix (Bio-Rad), and nuclease-free water. The NbActin gene served as the internal control, and primers targeted DEGs (sequences in Supplementary Table S4). The thermal profile consisted of an initial denaturation at 95°C for 30 s, followed by 40 cycles of 95°C for 5 s, 60°C for 10 s, and 72°C for 30 s, concluded by a melt curve analysis. All reactions were conducted in triplicate for both biological (n=3) and technical replicates to ensure reproducibility. Relative expression levels for PVY, PSTVd, and DEGs were calculated using the 2^(-ΔΔCt) method, with normalization to Actin or NbActin and calibration against mock-inoculated controls. Each treatment was set up for 3 biological replicates and each reaction was performed 3 technical replicates. 2.6 RNA Extraction, Library Preparation, and Sequencing Total RNA was extracted from systemic leaves of N. benthamiana plant using TRIzol reagent (above mention). RNA purity and integrity were evaluated using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Only high-quality RNA samples (RIN > 7.0) were used for library construction. RNA-seq library construction and sequencing were performed by Gene Denovo Biotechnology Co., Ltd. (Guangzhou, China). Libraries were prepared using the Illumina TruSeq RNA Sample Prep Kit (Illumina, San Diego, CA, USA) according to the manufacturer’s protocol. Pooled libraries were sequenced on an Illumina NovaSeq 6000 platform, generating paired-end 150 bp (PE150) reads. Raw reads were processed using Cutadapt v1.9.1 to remove adapter sequences and low-quality bases (quality score < 20, minimum length 75 bp). Clean reads were aligned to the N. benthamiana reference genome using HISAT2 (Kim et al., 2015). Gene expression levels were calculated as Fragments Per Kilobase of transcript per Million mapped reads (FPKM). Differential gene expression analysis was conducted using DESeq2 and edgeR, with genes showing |log₂ fold change| ≥ 1 and FDR < 0.05 considered differentially expressed (DEGs). GO enrichment analysis was performed using GOseq v1.34.1, with significantly enriched GO terms identified at adjusted p ≤ 0.05. KEGG pathway analysis was conducted using internal scripts based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Kanehisa and Goto, 2000). 2.7 Transcription Factor (TF) Identification To identify transcription factors among the DEGs, all DEG sequences were aligned to the Plant Transcription Factor Database (PlantTFDB v3.0) using BLAST, with an E-value threshold of 1e−5. TF family classification was based on conserved DNA-binding domains and sequence homology. The identified TFs were subsequently categorized by family and analyzed for differential expression patterns across infection treatments. 2.8 Weighted Gene Co-expression Network Analysis (WGCNA) To identify gene co-expression modules and potential hub genes associated with PVY, PSTVd, and PVY-PSTVd co-infection in Nicotiana benthamiana, a Weighted Gene Co-expression Network Analysis (WGCNA) was conducted using the WGCNA R package (version 4.0.3). Raw RNA-Seq expression data were first filtered to remove low-expression genes, retaining only those with fragments per kilobase of transcript per million mapped reads (FPKM) ≥ 1 in at least one condition. The soft-thresholding power (β) was determined using the pickSoftThreshold function to ensure scale-free topology, and a β value of 10 was selected. An adjacency matrix was constructed based on pairwise Pearson correlation coefficients between genes and transformed into a Topological Overlap Matrix (TOM) to reduce noise and spurious associations. Genes with similar expression patterns were grouped into modules using average linkage hierarchical clustering, with a minimum module size of 30. Modules with high similarity (cut height = 0.25) were merged to yield the final module set. Module-trait relationships were calculated by correlating module eigengenes with different treatment groups (Mock, PVY, PSTVd, and PVY-PSTVd). Modules with significant associations were selected for further analysis. Hub genes within these modules were defined by high module membership (kME > 0.8) and gene significance. Expression heatmaps were generated for the top 10 highly connected genes per module. Functional enrichment of candidate hub genes was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Transcription factors were identified by querying PlantTFDB (v5.0), and gene regulatory networks were visualized in Cytoscape (v3.9.1), highlighting key TF families with the top 10 gene. 2.9 Metabolomic Analysis The same N. benthamiana samples used for transcriptomic analysis were employed for metabolomic profiling to ensure consistency in biological material. Systemic leaves were harvested at 21 days post-inoculation (dpi) from plants infected with PVY, PSTVd, or co-infected with both, as well as from mock-inoculated controls. Each biological replicate consisted of pooled leaves from five plants, with three biological replicates per treatment group. Approximately 100 mg of frozen tissue was finely ground using liquid nitrogen. Metabolites were extracted by vortexing the powder in a 0.1% formic acid and 80% methanol solution. Following a 5-minute incubation on ice, the samples were centrifuged at 15,000 × g for 5 minutes at 4 °C. The resulting supernatants were diluted to 60% with LC-MS-grade water, filtered through 0.22 μm membranes, and centrifuged again under the same conditions. The extracts were analyzed using a Vanquish UHPLC system coupled with an Orbitrap Q Exactive mass spectrometer (Thermo Fisher Scientific, USA) in both positive and negative ionization modes. All LC-MS/MS analyses and raw data processing were performed by Cloud Metware platform (https://cloud.metware.cn/). Metabolite identification was based on accurate mass, retention time, and MS/MS fragmentation patterns, using a combination of public databases (such as KEGG, HMDB, and Metlin) and proprietary spectral libraries. Data normalization and statistical analysis were conducted to assess metabolite variation among treatments. Differentially accumulated metabolites (DAMs) were identified using a combination of variable importance in projection (VIP ≥ 1) from partial least squares discriminant analysis (PLS-DA) and Student’s t-test (p < 0.05). Metabolite annotation and pathway mapping were carried out using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Kanehisa and Goto, 2000). 2.10 Statistical, Bioinformatic, and Integrated Data Analysis Statistical analyses were performed using GraphPad Prism v10.0 (https://www.graphpad.com/). All experiments were conducted with three biological replicates, each consisting of pooled leaf samples from three individual plants. Differences among treatments were assessed using one-way ANOVA, followed by Tukey’s post hoc test for multiple comparisons. Error bars in graphs represent the standard deviation (SD, n = 3). For integrative analysis, Pearson correlation coefficients were calculated between the expression levels of differentially expressed genes (DEGs) and the abundance of DAMs. Pairs with |r| ≥ 0.8 and p < 0.05 were considered significantly correlated. Joint pathway analysis was conducted using the KEGG database to identify common biological pathways affected at both the transcriptomic and metabolomic levels. The Cytoscape v3.10.1 (Shannon et al., 2003) was used to construct gene-metabolite regulatory networks, highlighting hub genes, key metabolites, and hormone-related modules responsive to PVY, PSTVd, and co-infection. Results 3.1 Field Survey Reveals High Prevalence of PVY and Recurrent Co-infection with PSTVd To assess the distribution and complexity of viral and viroid infections in potato crops under natural conditions, a field survey was conducted across major potato-growing regions. A total of 256 symptomatic potato leaf samples were collected and subjected to RT-PCR detection for the presence of seven major pathogens, potato virus Y (PVY), potato virus X (PVX), potato virus M (PVM), potato virus S (PVS), potato virus A (PVA), potato leafroll virus (PLRV), and potato spindle tuber viroid (PSTVd) (Figure 1(A-H) and Figure S1). Single infections accounted for 26.6% of all cases, with PVY being the most frequently detected pathogen (28 samples, 25.4%), followed closely by PVX (26 samples). Other viruses, such as PLRV, PVM, PVS, and PVA, were detected at lower frequencies. PSTVd was detected in only one sample as a single infection, underscoring its low incidence in isolation under natural conditions (Figure 1I and 1J). In contrast, co-infections were prevalent, comprising over 70% of all cases (Figure 1J). The most common combination was PVX-PVY (63 samples), followed by multiple virus-virus and virus-viroid combinations. Notably, PSTVd was not observed in any high-frequency virus-virus interactions, but instead was detected exclusively in co-infections primarily with PVY across double, triple, and quadruple infection categories (Table S2). In total, PSTVd was present in 12 co-infected samples, highlighting a consistent co-occurrence pattern with PVY and suggesting a possible epidemiological or biological dependency (Figure 1K). Symptom-based analysis revealed leaf rolling and mosaic patterns as the most frequent field symptoms. PVY and PVX were consistently dominant across symptom categories, including leaf roll, mosaic leaf, and dark green blister spots, while PSTVd was infrequently detected even among symptomatic tissues (Table S2). Based on this field-based evidence, we selected PVY and PSTVd as the focus of subsequent molecular analyses. This selection was informed by the following considerations: the recurrent and unique nature of PVY-PSTVd co-infection in field samples; the limited understanding of virus-viroid interactions at the molecular level compared to virus-virus interactions; the regulatory importance of PSTVd, a recognized quarantine pathogen in many regions; and the biological contrast between the two pathogens PVY being a protein-coding RNA virus, and PSTVd being a non-coding RNA viroid that relies entirely on host machinery for replication and pathogenicity. Importantly, the detection of PSTVd predominantly in co-infections, especially alongside PVY, raises the possibility that co-infection facilitates its persistence or transmission under field conditions. Figure 1. Field-based assessment of virus and viroid infection patterns in symptomatic potato samples. (A-H) Representative leaf symptoms observed in infected plants:(A) Interveinal chlorosis; (B) Leaf rolling; (C) Necrosis at leaf margins; (D) Crinkled leaf edges; (E) Interveinal browning; (F) Dark green blister spots; (G) Mosaic leaf pattern; (H) Vein necrosis on the abaxial (underside) leaf surface. (I) Disease detection rates of major potato-infecting viruses and viroid (PVY, PVX, PVA, PVM, PVS, PLRV, and PSTVd) based on RT-PCR analysis of field-collected samples. (J) Proportion of infection types categorized by complexity. (K) Frequency of PVY and PSTVd infection. 3.2 Phenotypic and Molecular Responses to PSTVd, PVY Single and Co-infection in Host plants To evaluate the effects of PVY, PSTVd, and their co-infection on plant development and pathogen accumulation, we performed phenotypic, molecular, and RT-PCR analyses on N. benthamiana and potato plants at 21 dpi. In N. benthamiana , distinct visual symptoms were observed among treatments. PSTVd-infected plants exhibited mild leaf rolling and slight stunting, while PVY-infected plants showed severe leaf curling and growth inhibition. However, co-infected plants displayed symptoms nearly identical to those of PVY only infection characterized by pronounced chlorosis, leaf deformation, and significant dwarfing (Figure 2A-B). This suggests that PVY dominates the phenotypic outcome during co-infection, potentially masking the visible effects of the non-coding RNA pathogen PSTVd. The phenotypic analysis confirmed this trend, the plant height was significantly reduced in both PVY and PVY-PSTVd groups compared to mock and PSTVd, with no significant difference between the two co-infected and PVY-only plants (Figure 2C). At the molecular level, PSTVd accumulation was highest in single infections but slightly reduced in co-infected plants, indicating possible interference or competition during replication (Figure 2D). Conversely, PVY coat protein (PVY-CP) transcript levels were significantly elevated in both PVY and co-infection treatments. Although the increase in co-infection was marginal compared to PVY-only, this supports the notion that PVY replication is sustained or even modestly enhanced in the presence of PSTVd (Figure 2E). Thus, phenotypic and molecular data collectively suggest a dominant role for PVY in driving disease severity during co-infection, while PSTVd may be suppressed both symptomatically and molecular level. These results were further corroborated in potato ( Solanum tuberosum) plants (Figure S2). Co-infection led to the most severe stunting, tuber deformation, and biomass loss compared to single infections. RT-PCR validation showed similar infection patterns, with PVY accumulation maintained and PSTVd signal reduced in the co-infection context (Figure S2A-G). Together, these findings suggest that PVY imposes a stronger molecular and phenotypic footprint during dual infection, potentially facilitating a synergistic disruption of host physiology while simultaneously masking PSTVd-associated responses Figure 2. Phenotypic and molecular effects of PVY and PSTVd single and co-infection in Nicotiana benthamiana: (A) Phenotypic images of N. benthamiana plants under Mock, PSTVd, PVY, and PVY-PSTVd conditions, with a scale bar of 3 cm.(B) Close-up images of symptomatic leaves showing varying degrees of stunting and chlorosis across treatments. (C) Comparison of plant height (cm) at 21 dpi. (D) PSTVd accumulation (expressed as 102 copies/µL) measured by RT-qPCR (E). Relative expression levels of PVY coat protein (PVY-CP). Statistical significance was assessed using one-way ANOVA followed by Tukey’s post hoc test. Asterisks indicate significant differences: **P ≤ 0.01, ***P ≤ 0.001; ns = not significant. 3.3 Transcriptomic Analysis Revealed Distinct Gene Expression Patterns Between PSTVd and PVY Single and Co-infection To investigate the host transcriptional response to PSTVd, PVY, and their co-infection (PVY-PSTVd), we selected N. benthamiana as a model system for RNA sequencing. Unlike potato, which has a complex and polyploid genome, N. benthamiana offers a well-characterized diploid genome, higher susceptibility to viral and viroid infection, and more consistent infection dynamics under controlled conditions. We performed RNA sequencing on systemic leaves from infected and mock-treated N. benthamiana plants. Principal component analysis (PCA) was conducted to assess the overall variance among samples and consistency of biological replicates based on gene expression profiles (Figure 3A). The PCA revealed clear separation among the treatment groups along the first principal component (PC1), which explained 90% of the variance, and the second component (PC2), accounting for 5%. Replicates within the mock and PSTVd single infection groups clustered closely together, indicating high consistency and repeatability. In contrast, the PVY single infection and PVY-PSTVd co-infection groups displayed more dispersion among replicates, suggesting greater variability in host gene expression in response to these treatments. These results confirm the reliability of the RNA-seq data and justify the use of these samples for downstream differential expression analysis. Volcano plot analysis of four key pairwise comparisons (Figure 3B) showed that the largest transcriptional shift occurred in the mock versus PVY-PSTVd comparison, with 10,615 genes significantly upregulated and 4,962 downregulated. PVY infection alone induced 10,206 upregulated genes, whereas PSTVd infection alone altered only 1,510 upregulated genes, indicating that co-infection exerts a cumulative or potentially synergistic impact on host gene expression. A Venn diagram of differentially expressed genes (DEGs) (Figure 3C) revealed 7,605 DEGs shared across all comparisons, with 1,687 and 2,352 genes uniquely regulated in the mock versus PVY and mock versus PVY-PSTVd comparisons, respectively. The PVY versus PSTVd comparison identified 1,047 unique DEGs, underscoring the distinct transcriptomic signatures elicited by each pathogen. Together, these results provide a comprehensive overview of host transcriptomic responses under viral, viroid, and co-infection stress, suggesting both shared and distinct regulatory networks are activated depending on the infection scenario. Figure 3. Identification of Differentially Expressed Genes ( DEGs) and KEGG pathway enrichment analysis of DEGs in Nicotiana benthamiana. (A) Principal component analysis (PCA) plot of normalized transcriptomic data, with PC1 accounting for 90% and PC2 for 5% of variance, showing separation of Mock (green), PSTVd (yellow), PVY (pink), and PVY-PSTVd (purple) groups; 95% confidence ellipses are shown. (B) Volcano plots displaying the number and distribution of upregulated (red) and downregulated (green) genes in four key pairwise comparisons (Mock vs. PSTVd, Mock vs. PVY, Mock vs. PVY-PSTVd, and PVY vs. PSTVd). (C) Venn diagram of DEGs from key pairwise comparisons reveals both unique and shared gene expression changes between Mock vs. PSTVd, PVY, and PVY-PSTVd comparisons, including PVY vs. PSTVd overlap. (D-G) KEGG pathways enriched across pairwise comparisons: (D) Mock vs. PSTVd, (E) Mock vs. PVY, (F) Mock vs. PVY-PSTVd and PVY vs. PSTVd. 3.4 Pathway Enrichment Analysis Reveals Major Transcriptomic Shifts Driven by PVY and PSTVd Single and Co-Infections in Nicotiana benthamiana The number of DEGs in each term was calculated, and the main biological functions of the DEGs were determined through GO functional significance enrichment analysis. It was found that the DEGs of PVY-PSTVd co-infected plants were annotated into 65 secondary GO categories within three primary GO categories: biological processes, cellular components, and molecular functions. Among these, there were 7, 6, and 2 GO categories, respectively, with more than 1000 gene annotations. Gene Ontology (GO) enrichment analysis was conducted on all differentially expressed genes (DEGs) from PSTVd single infection, PVY single infection, PVY-PSTVd co-infection, and the direct PVY vs. PSTVd comparison. For PSTVd single infection, DEGs were significantly enriched (adjusted P < 0.05) in molecular functions such as kinase activity (GO:0016301, 171 genes), phosphotransferase activity (GO:0016773, 137 genes), and protein kinase activity (GO:0004672, 136 genes), and in biological processes including protein phosphorylation (GO:0006468, 136 genes), recognition of pollen (GO:0048544, 28 genes), and tyrosine metabolic process (GO:0006572, 22 genes) (Figure S3A). These results suggest a multifaceted response involving phosphorylation and reproductive processes. For PVY single infection, DEGs were significantly enriched (adjusted P < 0.05) in cellular components such as plastids (GO:0009536, 28 genes), chloroplasts (GO:0009507, 28 genes), and thylakoids (GO:0009579, 36 genes), and in biological processes including photosynthesis (GO:0015979, 28 genes) and monocarboxylic acid metabolism (GO:0032787, 28 genes) (Figure S3B). This indicates a pronounced effect on photosynthetic and metabolic pathways. PVY-PSTVd co-infection exhibited significant enrichment in biological processes such as single-organism catabolic process (GO:0044712, 839 genes) and monocarboxylic acid metabolic process (GO:0032787, 780 genes), and in cellular components including chloroplast thylakoid (GO:0009534, 298 genes) and chloroplast part (GO:0044434, 625 genes), reinforcing a PVY-driven influence on photosynthetic and catabolic pathways (Figure S3C). The PVY vs. PSTVd comparison revealed significant enrichment in cellular components such as chloroplast part (GO:0044434, 498 genes) and thylakoid (GO:0009579, 324 genes), and in biological processes including monocarboxylic acid metabolic process (GO:0032787, 550 genes), highlighting distinct pathogen-specific transcriptional responses (Figure S3D). These findings suggest that PVY and its co-infection predominantly impact photosynthetic and catabolic machinery, whereas PSTVd triggers a broader, enzyme-centric response, potentially reflecting their distinct replication strategies. To further elucidate the interaction between biological functions and genes and systematically investigate the response mechanism of N. benthamiana to single and co-infections, KEGG enrichment analysis was performed on all DEGs, focusing on the top 20 pathways (Figure 3). For Mock vs. PSTVd, KEGG analysis identified 328 DEGs enriched in key pathways (adjusted P < 0.05), including plant-pathogen interaction (ko04626, 42 genes), biosynthesis of secondary metabolites (ko01110, 104 genes), and MAPK signaling pathway (ko04016, 29 genes), alongside metabolic pathways such as glutathione metabolism (ko00480, 21 genes), and phenylpropanoid biosynthesis (ko00940, 24 genes) (Figure 3D). For Mock vs. PVY, KEGG analysis revealed 3238 DEGs enriched in global and overview maps (ko01100, 885 genes), biosynthesis of secondary metabolites (ko01110, 885 genes), and carbon metabolism (ko01200, 252 genes), with significant contributions from photosynthesis-antenna proteins (ko00196, 61 genes) and protein processing in the endoplasmic reticulum (ko04141, 200 genes) (Figure 3E). For Mock vs. PVY-PSTVd, KEGG analysis identified 3243 DEGs enriched in global and overview maps (ko01100, 894 genes), biosynthesis of secondary metabolites (ko01110, 894 genes), and carbon metabolism (ko01200, 263 genes), with notable contributions from photosynthesis-antenna proteins (ko00196, 62 genes) and glutathione metabolism (ko00480, 82 genes) (Figure 3F). For PVY vs. PSTVd combination KEGG analysis enriched 2120 DEGs in global and overview maps (ko01100, 1123 genes), metabolic pathways (ko01100, 1123 genes), and carbon metabolism (ko01200, 173 genes), with significant enrichment in plant hormone signal transduction (ko04075, 156 genes) and biosynthesis of secondary metabolites (ko01110, 668 genes) (Figure 4G). However, PSTVd uniquely affects secondary metabolism (104 genes) and signaling (42 genes in plant-pathogen interaction), while PVY and co-infection dominate metabolic and photosynthetic pathways with higher DEG counts (e.g., 885, 894, and 1123 genes, respectively). This suggests that PVY’s replication strategy drives large-scale transcriptomic changes, whereas PSTVd elicits a more targeted, enzyme-centric response. 3.5 Differential Expression of Host Genes Involved in RNA Silencing, Immunity, Cell Wall Remodeling, and Photosynthesis Transcriptome profiling revealed that PVY, PSTVd, and their co-infection triggered distinct and overlapping transcriptional reprogramming across key functional categories, including RNA silencing, immune signaling, photosynthesis/stress response, and cell wall remodeling (Figure S4A-D). PVY infection led to a strong upregulation of core RNA silencing components such as AGO1A/B, AGO2, RDR1, and RDR6, highlighting its dominant role in activating antiviral defense. PSTVd also modulated this pathway, but to a lesser extent, with moderate induction of DCL1, DRB2, and HEN1, indicating viroid-triggered silencing engagement. Immune signaling genes were robustly induced by PVY, including PR1, PR2, EDS1, PAD4, and PAL2, and this response was further amplified under co-infection. While PSTVd alone activated some immune components (e.g., SGT1, XDH1, CAT2), its overall impact was milder, lacking the systemic immune signatures observed with PVY. Interestingly, PSTVd uniquely influenced stress- and redox-associated genes such as VCS, PCMP-E16, and ZHD1, suggesting a distinct oxidative and stress response profile. In the photosynthesis module, both PVY and PSTVd suppressed genes like CHLM, POR1, and PGR5, although repression was more pronounced with PVY, indicating differential energy resource reallocation. Co-infection intensified these effects and strongly upregulated stress markers like SBP1 and MLP423. Finally, genes involved in cell wall remodeling and secondary metabolism, including PAL1, CCR1, CAD1, and COMT1, were broadly activated under PVY and co-infection, whereas PSTVd induced more selective responses. Overall, these patterns demonstrate that while PVY is the primary driver of transcriptional reprogramming, PSTVd contributes uniquely to silencing, stress, and redox signaling, and their co-infection leads to additive or synergistic gene expression changes across key functional categories. 3.6 Transcription Factor-Mediated Regulatory Responses and Pathway Enrichment under PSTVd and PVY Infection To elucidate transcriptional regulatory dynamics during single and mixed viroid and viral infections in N. benthamiana, we analyzed the expression of transcription factor (TF) families and their associated functional pathways. Bar plot analysis (Figure S8A) revealed the extent of transcriptional perturbation induced by each condition. PVY infection triggered the strongest response, with 482 upregulated and 381 downregulated genes compared to mock. PSTVd infection showed a more moderate effect (82 upregulated, 6 downregulated), while the PVY vs. PSTVd comparison yielded 372 upregulated and 317 downregulated genes, highlighting substantial divergence in their regulatory impacts. Furthermore, bHLH, MYB, WRKY, NAC, ERF, and C2H2 families were strongly enriched across infected samples, with particularly high relative abundance observed under PVY and co-infection conditions (Figure S5A). Venn diagram analysis (Figure S5B) showed PVY induced the highest number of unique TFs 113, while 86 were identified under co-infection and 38 under PSTVd. A conserved core of 19 TFs was shared across all treatments, indicating overlapping transcriptional defense modules. Gene Ontology (GO) enrichment analysis revealed distinct functional responses of N. benthamiana to PSTVd, PVY, and their co-infection (Figure S6, S7). In PSTVd-infected plants, the enrichment was predominantly associated with transcriptional regulation processes, highlighting a targeted reprogramming of host gene expression. Notably enriched terms included regulation of transcription, DNA-templated (Gene Number: 276), regulation of nucleobase-containing compound metabolic process (Gene Number: 402), and RNA biosynthetic process (Gene Number: 399). In contrast, PVY infection induced a broader spectrum of metabolic regulatory pathways, with significantly enriched terms such as regulation of metabolic process (Gene Number: 578), regulation of macromolecule metabolic process (Gene Number: 634.5), and regulation of cellular metabolic process (Gene Number: 691), indicating a more extensive reprogramming of cellular metabolism. The co-infection condition triggered the most extensive GO enrichment, combining elements of both transcriptional and metabolic regulation. Enriched terms included regulation of metabolic process (Gene Number: 733.75), regulation of macromolecule metabolic process (Gene Number: 801), regulation of cellular metabolic process (Gene Number: 592), RNA metabolic process (Gene Number: 599.25), and heterocycle biosynthetic process (Gene Number: 733.75), suggesting a highly coordinated and intensified host response. Furthermore, a direct comparison between PVY and PSTVd infections reinforced these observations, with enrichment skewed toward metabolic processes in PVY. Key terms included regulation of metabolic process (Gene Number: 492.5), regulation of macromolecule metabolic process (Gene Number: 550), and regulation of cellular metabolic process (Gene Number: 607.5), underscoring PVY’s broader impact on host metabolism compared to PSTVd’s more transcriptionally focused effects. To provide functional context to the observed transcriptional changes, KEGG pathway enrichment analysis was conducted (Figure S8 B-E). In PSTVd-infected plants, several signaling-related pathways were significantly enriched, including plant hormone signal transduction (29 DEGs), MAPK signaling pathway (17 DEGs), and plant-pathogen interaction (15 DEGs), suggesting early modulation of hormone-mediated and defense-associated signaling cascades. PVY-infected plants exhibited broader systemic reprogramming, with enrichment in plant hormone signal transduction (68 DEGs), MAPK signaling (28 DEGs), and circadian rhythm (8 DEGs), indicating PVY’s extensive influence on both stress and developmental pathways. In the co-infection, plant hormone signal transduction remained the most enriched pathway (63 DEGs), followed by MAPK signaling (27 DEGs) and circadian rhythm (8 DEGs), reflecting a synergistic activation of key regulatory networks under combined viral and viroid stress. Notably, the direct comparison between PVY and PSTVd infections revealed a higher number of differentially regulated genes in plant hormone signal transduction (73 DEGs) and MAPK signaling (36 DEGs), reinforcing the notion that PVY elicits a more robust signaling response than PSTVd. Collectively, these results underscore the dynamic interplay between hormone signaling and stress-responsive pathways during single and co-infections. Furthermore we analyses (Figure S5 C, D) treatment-specific TF expression patterns across infection conditionss. In single infections, PSTVd up-regulated TFs such as ERF5, WRKY70, and NAC014, associated with stress and defense responses, while down-regulating BZIP34 and KUA1, linked to growth and development, indicating a shift toward pathogen defense. PVY infection strongly up-regulated TFs including WRKY28, WRKY70, and NAC071, reflecting enhanced stress signaling, while down-regulating BZIP34 and OFP4, suggesting suppression of developmental processes. During co-infection, antagonistic crosstalk was evident, with PSTVd-induced up-regulation of ERF5, WRKY70, and NAC014 suppressed, potentially mediated by PVY induced down-regulation of regulatory TFs like BZIP53, indicating PVY’s dominance in transcriptional control. Synergistic enrichment occurred with enhanced expression of TFs such as NAC021 and TIFY10A, associated with jasmonic acid and defense pathways, alongside SCL3, linked to gibberellin signaling, suggesting an adaptive regulatory response to dual infection. Overall, these findings highlight the central involvement of the WRKY, NAC, BZIP, ERF, and MYB TF families in orchestrating the plant’s responses, with distinct members contributing uniquely to PSTVd, PVY, and co-infection scenarios. 3.7 Co-expression Network Analysis Reveals Infection-Specific Gene Modules in Response to PSTVd, PVY, and Co-infection To dissect the transcriptional regulatory networks underlying N. benthamiana responses to PSTVd, PVY, and their co-infection, we conducted a Weighted Gene Co-expression Network Analysis (WGCNA) using normalized gene expression profiles from all infection conditions. This analysis identified distinct co-expression modules representing groups of genes with highly correlated expression patterns across the Mock, PSTVd, PVY, and PVY-PSTVd treatments. Network topology analysis ensured robust module detection. An optimal soft-thresholding power (β = 10) was selected based on the scale-free topology criterion, as indicated by a model fit index (R²) exceeding 0.9 and an appropriate reduction in mean connectivity (Figure S9A). Hierarchical clustering of gene expression profiles revealed eight distinct modules, each assigned a unique color, signifying functionally coherent gene clusters (Figure 4A). The clustering distances among modules reflected their transcriptional similarity; for instance, the brown and green modules clustered closely, indicating shared expression dynamics, while the turquoise module formed a distinct cluster, suggesting a unique regulatory pattern or biological role (Figure S9B). Module eigengene expression patterns highlighted infection-specific trends. The turquoise module showed high expression in Mock plants but was downregulated under all infection conditions. In contrast, the brown and green modules exhibited increased expression predominantly in PSTVd-infected plants. The yellow and black modules were more closely associated with PVY infection, while the blue module, although upregulated under co-infection, also showed high expression in PVY alone treatment, implying that the transcriptional response during co-infection is largely driven by PVY (Figure 4B). These relationships were further supported by eigengene correlation analysis, which showed strong positive associations between modules with similar expression trends and negative correlations between those with opposing patterns (Figure S9C). Moreover, a gene-level expression heatmap (Figure S9D) revealed that the brown module is enriched for genes with high expression, reinforcing its potential regulatory significance during PSTVd infection. Overall, WGCNA effectively identified functionally relevant gene modules that capture the complexity of plant transcriptional responses to viroid and viral infections. Figure 4: Weighted Gene Co-expression Network Analysis (WGCNA) of differentially expressed genes (DEGs) in Nicotiana benthamiana under PSTVd, PVY, and PVY-PSTVd co-infection. (A) Clustering dendrogram of genes based on topological overlap dissimilarity, with each leaf representing a gene and major branches forming eight modules labeled by distinct colors. (B) Heatmap of correlation coefficients (r) between modules and samples (Mock, PSTVd, PVY, PVY-PSTVd), with p-values in parentheses; red indicates positive correlation, and blue indicates negative correlation. (C) Expression patterns of the top 10 hub genes from the brown module, highly correlated with PSTVd. (D) Transcription factors (TFs) are present in the brown module. (E) Network analysis of TFs and the top 10 hub genes from the brown module, with darker brown indicating higher connectivity of TF. (F) Expression patterns of the top 10 hub genes from the yellow module, highly correlated with PVY. (G) TFs present in the yellow module. (H) Network analysis of TFs and the top 10 hub genes from the yellow module, with darker brown indicating higher connectivity of TF. (I) Expression patterns of the top 10 hub genes from the blue module, highly correlated with PVY-PSTVd co-infection (J), TFs present in the blue module. (K) Network analysis of TFs and the top 10 hub genes from the blue module, with darker brown indicating higher connectivity of TF. 3.8 Co-expression Network Analysis Reveals Distinct and Synergistic Regulatory Modules in Response to PSTVd, PVY, and Co-infection To gain deeper insights into the molecular mechanisms driving the plant’s response to PSTVd, PVY, and their co-infection, one representative co-expression module was selected from each infection condition based on eigengene expression patterns and biological relevance (Figure 4, Figure S10A, S11A,12A). Specifically, the brown module was selected for PSTVd, the yellow module for PVY, and the blue module for PVY-PSTVd co-infection. These modules demonstrated strong associations with their respective conditions and were enriched for genes involved in stress responses and regulatory pathways. Gene Ontology (GO) and KEGG enrichment analyses revealed condition-specific biological signatures. The PSTVd-associated brown module was enriched in metabolic processes, intracellular compartments, molecular binding and catalytic activities, with KEGG pathways highlighting glutathione metabolism, metabolic pathway, and secondary metabolite biosynthesis, suggestive of redox regulation and structural adaptation (Figure S10 B and C). The PVY-associated yellow module showed similar GO categories but with higher gene counts and additional enrichment in sulfur metabolism, glutathione pathways, and plant-pathogen interaction, reflecting a detoxification- and defense-oriented response (Figure S11 B and C). Notably, the co-infection-responsive blue module exhibited the most extensive enrichment, including amino acid biosynthesis, carbon metabolism, and multi-hormonal signaling pathways, indicating enhanced transcriptional activity and metabolic coordination during combined stress (Figure S12 B and C). Expression analysis of the top 10 hub genes and all transcription factor (TF) genes from each condition-specific module, brown (n = 9), yellow (n = 4), and blue (n = 21), revealed clear condition-dependent activation patterns. Heatmap analysis demonstrated distinct transcriptional signatures associated with PSTVd, PVY, and co-infection. In the PSTVd-responsive brown module, most upregulated genes corresponded to novel or uncharacterized transcripts with putative roles in defense and cellular organization (Figure 4C). These included LOX2 (lipid signaling), EXO84A (vesicle trafficking), kinesin-13A (cytoskeletal remodeling), and Fanconi anemia-like genes (genome maintenance). Transcription factors identified in this module included members of the AP2-EREBP, ARR-B, bHLH, LOB, and WRKY families (Figure 4D). In the PVY-associated yellow module, upregulated hub genes such as NFP, FER, CHH14, UBP1, and TDX were linked to immune signaling, chromatin remodeling, and oxidative stress responses (Figure 4F). Key TFs in this module included AP2-EREBP, ARR-B, and NAC family genes (Figure 4G). Furthermore, the co-infection-specific blue module featured strong induction of genes involved in protein turnover (UBC28), hormonal regulation (ERF1, MYC2, JAZ1), and immune coordination (WRKY6, NAC21) (Figure 4I, J). Interestingly, blue module genes were also highly expressed in PVY-infected plants but not in PSTVd-infected plants. This indicates that PVY is the primary inducer of this transcriptional program, and PSTVd alone is insufficient to activate these immune and stress-responsive genes. However, their expression was further enhanced under co-infection, suggesting a synergistic effect. The lack of induction under PSTVd alone highlights asymmetric transcriptional crosstalk, with PVY exerting dominant regulatory influence. Network topology analysis further revealed distinct TF connectivity patterns. In the PSTVd-responsive network, central TF hubs included WRKY51, MYB15, LBD2, and bHLH41 (Figure 4E). In the PVY network, ABR1 and NAC022 were the most highly connected regulators (Figure 4H). The co-infection network displayed the highest complexity and connectivity, with central TFs including ERF071, MYC2, C3H, SCL3, HSF24, HSFB3, NAP1, NAC021, JA2L, NAC071, JUB1, PLATZ, TIFY10A, and multiple WRKY family members (WRKY4, WRKY6, WRKY11, WRKY28) (Figure 4K). The co-expression of JA, SA, and ET pathway regulators within the same module points to integrated immune reprogramming under co-infection. Collectively, these findings reveal a divergence of host transcriptional responses under individual infections and a transcriptionally synergistic immune activation under co-infection. The differential module activity and expression patterns provide compelling evidence of antagonistic crosstalk during single infections and synergistic immune reprogramming during PVY-PSTVd co-infection, in line with the central hypothesis of this study. 3.9 Metabolomic Profiling Reveals Distinct Signatures in PSTVd, PVY, and Co-infected Potato Plants N. benthamiana plants were subjected to single PSTVd infection, single PVY infection, and PVY-PSTVd co-infection. Hormonal metabolic responses were analyzed using widely targeted metabolomics via UPLC-MS. A total of 88 hormone-related metabolites were detected, including 2 abscisic acids, 26 auxins, 36 cytokinins, 1 ethylene, 10 gibberellins, 9 jasmonic acids, 2 salicylic acids, and 2 strigolactones (Table S3). PSTVd infection alone resulted in a relatively balanced number of differentially accumulated hormone-related metabolites (DAMs), with 11 metabolites upregulated and 11 downregulated compared to mock plants. In contrast, PVY infection induced a more substantial alteration in hormone profiles, with 30 upregulated and 9 downregulated DAMs. Co-infection with PVY and PSTVd led to the highest number of DAMs, including 35 upregulated and 9 downregulated metabolites, suggesting a possible additive or synergistic effect on hormone metabolism. Notably, comparison between PVY and PSTVd-infected plants (PVY vs PSTVd) revealed 9 upregulated and 30 downregulated DAMs, indicating divergent regulation of hormone pathways between these two pathogens (Figure 5A). To further examine the overlap of hormone-related metabolic changes across infection conditions, we constructed a Venn diagram of differentially accumulated hormone metabolites (Figure 5B). Thirteen DAMs were commonly altered across all four pairwise comparisons, while additional metabolites were uniquely regulated in individual conditions, highlighting both shared and specific hormonal responses to infection. (Figure 5B). These common metabolites were mainly from the auxin, cytokinin, gibberellin, and jasmonic acid classes. Further class-based statistical analysis revealed that cytokinins and auxins were the most affected hormone groups across treatments, with strikingly more downregulated metabolites observed in co-infected plants (Figure 5C). Figure 5. Metabolomic profiling and pathway enrichment analysis of Nicotiana benthamiana plants under PSTVd, PVY, and PSTVd-PVY co-infection. (A) Bar chart showing the number of upregulated (UP) and downregulated (DOWN) metabolic pathways across Mock vs. PSTVd, Mock vs. PVY, and Mock vs. PVY-PSTVd conditions. (B) Venn diagram illustrating the overlap of enriched pathways among the three comparisons. (C) Bar chart of pathway enrichment counts for upregulated and downregulated pathways. (D-G) KEGG enrichment scatter plots for (D) Mock vs. PSTVd, (E) Mock vs. PVY, (F) Mock vs. PVY-PSTVd, and (G) PVY vs. PSTVd. 3.10 KEGG Enrichment Analysis of Differential Metabolites To investigate the metabolic reprogramming induced by PSTVd, PVY, and their co-infection, KEGG enrichment analysis was conducted on significantly altered metabolites in N. benthamiana . Each infection condition triggered distinct metabolic responses, as reflected in the enrichment patterns. Under PSTVd infection, the most significantly enriched pathways included biosynthesis of various alkaloids, plant hormone signal transduction, and zeatin biosynthesis, indicating strong activation of alkaloid production and alterations in cytokinin signaling. Moderate enrichment was observed in pathways related to secondary metabolism and amino acid derivatives, such as biosynthesis of secondary metabolites and 2-oxocarboxylic acid metabolism, while minor enrichment occurred in aminoacyl-tRNA biosynthesis and cofactor biosynthesis, suggesting modest shifts in protein synthesis and redox regulation (Figure 5D). In PVY-infected plants, zeatin biosynthesis and diterpenoid biosynthesis showed the highest enrichment, reflecting pronounced activation of cytokinin and terpenoid metabolism. Moderate enrichment was also detected in amino acid biosynthesis and glucosinolate pathways, implying a role for nitrogen metabolism and secondary defense mechanisms. Other pathways displayed minimal enrichment, suggesting a more selective metabolic adjustment compared to PSTVd infection (Figure 5E). Co-infection with PVY and PSTVd resulted in strong enrichment of zeatin biosynthesis, followed by moderate enrichment in biosynthesis of various plant secondary metabolites and glucosinolate biosynthesis. The overall enrichment pattern highlighted an enhanced hormonal and secondary metabolic response, although most additional pathways exhibited limited differential activity (Figure 5F). When comparing PVY and PSTVd directly, zeatin biosynthesis and the biosynthesis of various alkaloids showed substantial enrichment differences, underscoring the divergent regulation of cytokinin and alkaloid metabolism. PVY-infected plants additionally showed higher enrichment in diterpenoid biosynthesis and cofactor-related pathways, supporting a broader activation of terpenoid and redox systems compared to PSTVd (Figure 5G). Together, these results demonstrate condition-specific metabolic reprogramming in response to single and co-infections. Notably, zeatin biosynthesis emerged as a commonly enriched pathway across all conditions, while PSTVd and PVY each activated distinct metabolic signatures. These findings support the presence of antagonistic metabolic crosstalk and synergistic hormone-associated responses under co-infection. 3.11 Hormone Profiling Reveals Differential Regulation Under Single and Co-infection Conditions Quantification of hormone levels in N. benthamiana under PSTVd, PVY, and PVY-PSTVd co-infection revealed distinct patterns of hormonal modulation. PSTVd infection led to a significant accumulation of cytokinin-related compounds such as 2CltZ and tZOG, which were markedly elevated compared to mock and PVY-infected plants. In contrast, these hormones were dramatically reduced under PVY and PVY-PSTVd co-infection, indicating that PVY antagonizes PSTVd-induced cytokinin accumulation (Figure S13A, C). OPDA, a jasmonate precursor, also showed increased levels under PSTVd and PVY infections but was significantly suppressed under co-infection, suggesting interference in jasmonate biosynthesis during the combined infection (Figure S13B). Levels of GA20, a gibberellin precursor, were significantly higher in PVY- and co-infected plants compared to mock and PSTVd, with co-infection resulting in the highest accumulation, reflecting a synergistic induction of gibberellin metabolism (Figure S13D). Tryptophan (TRP), a key precursor for auxin and secondary metabolites, showed significant elevation under PVY and co-infection, whereas it was suppressed in PSTVd-infected plants, again suggesting an antagonistic influence of PSTVd on TRP metabolism (Figure S13E). tZR levels increased across all treatments compared to the mock control, with a more pronounced accumulation observed in PVY-infected and PVY-PSTVd co-infected plants. These hormone profiling results highlight complex antagonistic and synergistic hormonal crosstalk during single and mixed infections, with PVY exerting dominant suppression over PSTVd-induced hormone accumulation while enhancing specific hormone pathways under co-infection. 3.10 Integrated Gene-Metabolite Networks Reveal Distinct Molecular Responses to PSTVd, PVY, and Their Co-infection To investigate the coordinated molecular responses between gene expression and metabolic changes during PSTVd and PVY infections in N. benthamiana, we performed an integrative transcriptome-metabolome correlation analysis. Differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) were analyzed using Pearson correlation (|r| > 0.8, p < 0.05) to identify potential regulatory relationships between gene expression and metabolite levels. From these, we selected the top 50 genes exhibiting significant correlations with multiple metabolites, suggesting their roles as transcriptional hubs. Conversely, 20 metabolites, highly correlated with a wide range of genes, indicated their involvement in broad transcriptional responses under viroid and viral stress. Under PSTVd infection, correlations predominantly involved hormone metabolites associated with cytokinin, jasmonate, and abscisic acid (ABA) conjugation pathways, cZR, tZR, tZOG, OPDA, ABA, and DHZR, which were positively linked to genes such as AGO7, SOG1, CYP81C13, YSL2, YSL3, HSP17.5, ERF034, SWEET17, NPF6.2, and CYP707A4 (Figure S14A). These associations point to the activation of growth-related and nutrient signaling pathways. In contrast, PVY infection is particularly from the auxin, cytokinin, gibberellin, and jasmonate pathways. Notably, SEC, GLAK1, CML22, SPL15, and PAT16 were positively correlated with IAA, IAA-Asp, tZ, tZR, GA3, and JA, suggesting their involvement in hormone-driven transcriptional reprogramming. Other positively correlated genes included HSP70, PRAT1G1, TSJT1, SOT17, and GTE6, which together indicate the activation of growth signaling cascades alongside defense responses (Figure S14B). In PVY-PSTVd co-infection, several genes showed significant positive correlations with metabolites involved in hormonal growth and defense signaling. For example, the PAP1 gene, which is associated with defense responses, was positively correlated with IAA-Asp, tZR, and GA19, indicating its involvement in both growth and immune signaling. Similarly, WRKY26, a transcription factor involved in salicylic acid (SA) and jasmonate (JA) signaling, displayed strong positive correlations with metabolites such as SA, JA, JA-Ile, and ABA, suggesting its role in the regulation of immune responses during co-infection. The DART1 gene, linked to auxin signaling, showed positive correlations with IAA-Asp and IAA-Gly, further emphasizing its role in growth regulation. In contrast, STY13, involved in stress responses, was positively correlated with tZR (cytokinin) and GA19 (gibberellin), suggesting a cross-talk between growth and defense signaling pathways. In addition, SBT3.17, a gene involved in stress-related responses, showed positive correlations with both IAA-Val-Me and tZR, reinforcing the integration of growth and immune responses in co-infected plants. Conversely, several genes exhibited negative correlations with growth-related metabolites. The CYP82C4 gene, involved in cytochrome P450-mediated metabolic processes, was negatively correlated with IAA-Gly, JA-Ile, and ABA, indicating a potential role in suppressing growth and modulating stress signaling pathways. Similarly, OXPI1, a gene associated with plant immune regulation, displayed negative correlations with IAA-Asp, tZ, and JA-Ile, suggesting its involvement in downregulating growth-associated pathways under co-infection conditions (Figure S15A). A direct comparison between PVY and PSTVd infections revealed distinct correlation profiles. Metabolites such as IAA-Asp, tZR, GA19, and JA-Ile showed differential associations with genes like WRKY26, SBT3.17, PAP1, OXPI1, and STY13, highlighting divergent regulation of hormone signaling pathways (Figure S15 B). Network analyses further underscored these differences. Bipartite networks constructed from the top 20 genes and top 10 metabolites demonstrated condition-specific connectivity patterns. PSTVd networks featured tightly interconnected modules centered on Cytocynin hormone-related precursor (Figure S14C), while PVY networks were dominated by mostly growth and defense hormone hubs (Figure S14D). The co-infection network revealed mixed regulatory structures, integrating elements of both growth and immune responses (Figure S15C). In PVY vs. PSTVd comparisons, distinct transcript-metabolite interactions underscored the differential prioritization of defense over development, or vice versa (Figure S15D). These findings reveal distinct molecular strategies employed by N. benthamiana in response to PSTVd, PVY, and their co-infection. 3.11 Integrated KEGG Analysis Reveals Altered Hormone Signaling and Gene Regulation in Nicotiana benthamiana under PVY-PSTVd Co-infection KEGG enrichment analysis of differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) in N. benthamiana under PVY and PSTVd co-infection compared to a mock control revealed significant enrichment in the plant hormone signal transduction pathway (Ko04075). Specifically, 173 DEGs were enriched in this pathway, and metabolomic analysis identified three DAMs: dihydrozeatin riboside (DHZR, a cytokinin precursor), abscisic acid (ABA), and jasmonoyl-isoleucine (JA-Ile), al also enriched in the same pathway (Figure 6). To investigate the interplay between gene expression and metabolite accumulation, we conducted an integrated analysis of DEGs and DAMs within this pathway under PVY-PSTVd co-infection. Cytokinin levels were significantly lower in coinfected plants compared to the mock control. Cytokinins regulate critical plant growth processes via the CRE1 receptor, which transfers phosphate groups to AHP proteins and downstream response regulators (ARRs). Six DEGs were identified in the cytokinin signaling pathway, with Niben101Scf02217g06006 regulating AHP expression, thereby influencing DHZR accumulation and cytokinin-mediated growth responses. In coinfected plants, ABA levels were significantly reduced compared to the mock control. ABA regulates key physiological processes, such as seed dormancy and stomatal closure, by binding to PYR/PYL/RCAR receptors, inhibiting PP2C phosphatases, and activating SnRK2 protein kinases. These kinases phosphorylate transcription factors (e.g., ABFs), modulating gene expression at transcriptional and post-translational levels. We identified 18 DEGs in the ABA signaling pathway, nine of which (Niben101Scf00104g00003, Niben101Scf01512g03003, Niben101Scf01897g07006, Niben101Scf02085g21007, Niben101Scf07590g01002, Niben101Scf11944g02005, Niben101Scf17640g00003, Niben101Scf18347g00015, Niben101Scf34542g00004 ) were downregulated and associated with PYL receptor synthesis, suggesting their role in modulating ABA-mediated responses to co-infection. Conversely, JA-Ile levels were significantly elevated in coinfected plants. Jasmonates, critical for plant defense and environmental adaptation, are recognized by the COI1 receptor, which activates the transcription factor MYC2 to induce defense-related gene expression. Four DEGs in the jasmonate signaling pathway were upregulated, including Niben101Scf03500g01002, which directly regulates COI1 expression, enhancing defense responses to pathogen stress. To further validate the accuracy of the transcriptome sequencing results, we performed qRT-PCR to assess the expression of several differentially expressed genes (DEGs). We selected nine key targeted genes involved in hormone signal transduction pathways, whose expression trends were consistent with the RNA-seq data, thereby confirming the reliability of the transcriptomic analysis. These DEGs, including AHP4, AHP1, PYL1, PYL8, PYL4, PYL2, and COI1, are critical regulators of cytokinin, ABA, and JA-Ile signaling pathways, respectively. Figure 6. Schematic representation of gene-metabolite interactions in hormone signaling pathways under PVY-PSTVd co-infection in N. benthamiana. (A) cytokinin biosynthesis (zeatin biosynthesis), (B) abscisic acid (ABA) biosynthesis, and (C) jasmonic acid (JA) biosynthesis and signaling pathways. Heatmap blocks represent the relative expression levels of genes across treatment groups. Discussion Plants frequently face simultaneous challenges from multiple pathogens in natural environments, yet the detailed molecular mechanisms by which hosts integrate concurrent biotic stress signals remain poorly characterized (Penteriche et al., 2025, Fujita et al., 2006). This is particularly relevant in mixed infections involving mechanistically distinct pathogens, such as RNA viruses and non-coding RNA viroids, which can activate overlapping yet antagonistic host responses. Our combined field survey and multi-omics approach, including phenotypic, molecular, transcriptomic, and metabolomic analyses, investigated the dynamics of co-infection between Potato virus Y (PVY) and Potato spindle tuber viroid (PSTVd), two economically significant pathogens. Our results revealed that PVY not only dominates in field prevalence but also drives phenotypic severity and molecular outcomes during co-infection, effectively masking PSTVd-associated effects. In field-collected samples, PSTVd was rarely detected alone but consistently co-occurred with PVY (Figure 1), suggesting potential biological dependence or PVY-facilitated transmission, possibly via immune suppression or enhanced systemic movement. A similar observation was previously reported in Solanum brevidens , where PVY accumulation increased when co-infected with TMV or PSTVd (VALKONEN, 1992). Phenotypic assessments in N. benthamiana and potato confirmed PVY dominance in symptom expression (Figure 7A). Both PVY-infected and co-infected plants exhibited pronounced stunting, chlorosis, and leaf deformation, while PSTVd alone induced only mild leaf curling. Molecular analysis further showed reduced PSTVd RNA accumulation under co-infection, whereas PVY coat protein transcripts remained high or slightly increased (Figure 2). These findings are consistent with earlier studies indicating that viruses often outcompete viroids during mixed infections (Afanasenko et al., 2022b). Transcriptomic profiling further reinforced PVY’s dominance during co-infection. Principal Component Analysis (PCA) and correlation-based clustering revealed extensive transcriptional reprogramming in PVY and PVY-PSTVd treatments, with co-infection producing distinct gene expression profiles not observed in single infections but mostly affected similarly to PVY (Figure 3). This pattern aligns with previous findings from Prunus persica infected by both PLMVd and PNRSV, where co-infection elicited a more complex host transcriptomic response than either pathogen alone (Herranz et al., 2013). Functional enrichment analyses via Gene Ontology (GO) and KEGG further clarified the divergence in host responses (Figure 4). PSTVd infection alone upregulated pathways involved in protein phosphorylation and plant-pathogen interaction, consistent with its reliance on host transcriptional and signaling machinery for replication. While these specific enrichments emerged from our analysis, similar host manipulations have been noted in earlier studies. (Zheng et al., 2017, Więsyk et al., 2018), reinforcing the broader role of viroids in modulating host regulatory machinery. In contrast, PVY and co-infection significantly enriched pathways related to photosynthesis, carbon metabolism, and secondary metabolite biosynthesis, indicating viral modulation of host energy metabolism and defense reprogramming. Such reallocation of metabolic resources has been reported in other PVY-infected systems, where plants coordinate energy production with activation of biosynthetic defense processes to balance growth and immunity under viral stress (Kogovšek et al., 2016, Zrimec et al., 2024). Furthermore, transcriptome profiling revealed that in the defense pathway, PVY strongly activated immune signaling, including the induced strong upregulation of PR genes as well as PAD4 and EDS1, indicative of receptor-mediated defense activation. This observation mirrors broader immune induction observed in transcriptome analyses during PVY infection in potato (S. tuberosum) (Cao et al., 2020), and is consistent with mechanistic evidence from N. benthamiana showing that PAD4 and EDS1 mediate NLR-dependent immune signaling cascades (Wang et al., 2024). PSTVd alone triggered only a mild immune response, suggesting limited recognition by host receptors, consistent with its non-coding nature (Owens, 2007). In the RNA silencing pathway, PVY significantly induced key components such as DCLs, RDRs, and AGOs, reflecting activation of antiviral RNAi machinery. This mirrors earlier functional studies in tomato, where silencing DCL and AGO genes altered the plant’s response to PVY (Kwon et al., 2020), and research in potato demonstrating that StRDR1 contributes to basal resistance against PVY and related viruses (Hunter et al., 2016). PSTVd had a minimal effect, with modest changes in DCL1 and DRBs, supporting earlier observations that viroid-derived small RNAs primarily mediate host gene regulation rather than defense, consistent with prior studies showing that PSTVd-derived small RNAs chiefly regulate host gene expression rather than initiating robust antiviral responses (Di Serio et al., 2023, Katsarou et al., 2016a). Both PVY and PSTVd suppressed genes involved in photosynthesis, such as CHLM and PGR5, but repression was more pronounced under PVY infection and PVY-PSTVd co-infection. In parallel, stress-responsive genes, including SBP1 and MLP423, were strongly induced under co-infection, indicating elevated oxidative and stress signaling. Additionally, genes associated with cell wall remodeling and secondary metabolism (e.g., PAL1, CCR1) were significantly upregulated under PVY alone, and even more so in co-infected plants, whereas PSTVd alone elicited only mild changes. These findings align with previous studies that show PVY infection causes broad downregulation of photosynthesis-related genes, while simultaneously activating defense-related and secondary metabolism gene patterns reported in potato and N. benthamiana (Xu et al., 2023, Manasseh et al., 2024). Similarly, cell‑wall and stress-related gene induction during PVY infection has been observed in comparative transcriptome studies (Otulak-Kozieł et al., 2018). Moreover, Transcription factor (TF) profiling revealed that PVY triggers extensive activation of diverse TF families, including WRKY, NAC, ERF, MYB, and bHLH, which are well-established regulators of stress and hormone-mediated defense responses. In contrast, PSTVd elicited a more selective transcriptional response, with upregulation of specific defense-related TFs such as WRKY70, ERF5, and NAC014, while concurrently suppressing growth-associated TFs like BZIP34, indicating a strategic shift toward defense prioritization. Notably, during co-infection, a complex interplay emerged: PVY-mediated suppression of some PSTVd-induced TFs underscored PVY’s dominant regulatory influence, while synergistic upregulation of JA and GA pathway TFs such as TIFY10A and SCL3 suggested transcriptional crosstalk. These patterns align with established roles of WRKY and NAC TFs in coordinating salicylic acid (SA), jasmonic acid (JA), and MAPK signaling cascades during plant immune responses. Together, these highlight how overlapping yet distinct TF networks orchestrate tailored transcriptional strategies across single and mixed infections. Co-expression network analysis further resolved condition-specific transcriptional modules in N. benthamiana under PSTVd, PVY, and co-infection scenarios. The PSTVd-associated module was enriched in metabolic and redox-related processes, indicative of a stress-buffering response. Conversely, the PVY-responsive module exhibited stronger activation of immune signaling, sulfur metabolism, and plant-pathogen interaction pathways, consistent with PVY’s known ability to trigger immune activation. The co-infection-specific module was the most complex and transcriptionally active, enriched in hormone signaling, amino acid biosynthesis, and carbon metabolism, suggesting synergistic transcriptional reprogramming. While many co-infection-responsive genes were PVY-driven, their expression was notably amplified in the presence of PSTVd, indicating that the viroid can modulate and enhance PVY-activated networks. Within the PSTVd-responsive module, key TF hubs included WRKY51, MYB15, LBD2, and bHLH41. WRKY51 is recognized for its role in biotic and abiotic stress tolerance, especially in regulating ROS homeostasis and defense-related gene expression (Zhou et al., 2023). MYB15 contributes to stress signaling and secondary metabolism, coordinating drought and pathogen responses (Huang et al., 2023, Khan et al., 2018). bHLH41, a member of the basic helix-loop-helix TF family, integrates hormonal and environmental cues, including jasmonate signaling pathways (Sasaki-Sekimoto et al., 2013). LBD2 (LOB-domain protein) is implicated in regulating organ boundaries and potentially interfaces with stress-responsive pathways, although its exact role in viroid defense remains to be defined (Wu et al., 2023). In the PVY-responsive module, ABR1 and NAC022 emerged as central regulatory TFs. ABR1 (also known as ERF111) is an AP2/ERF family transcription factor that mediates transcriptional responses to abiotic and biotic stress, acting downstream of ABA and ethylene signaling (Pandey et al., 2005). NAC022, part of the NAC family, is closely associated with jasmonic acid and oxidative stress responses, contributing to pathogen defense and regulation of immune-related gene expression (Li et al., 2022, Dong et al., 2024). The co-infection-specific module displayed high transcriptional complexity and featured central TFs including ERF071, MYC2, C3H, SCL3, HSF24, NAC021, TIFY10A, and multiple WRKY family members (WRKY4, WRKY6, WRKY11, WRKY28). MYC2 functions as a master regulator of JA-mediated defense and growth trade-offs, coordinating JAZ feedback loops and integrating JA, SA, and ABA pathways (Luo et al., 2023). TIFY10A (also known as JAZ1) acts as a repressor of jasmonate signaling, modulating downstream defense gene expression in response to JA (Li et al., 2022). SCL3, a GRAS-family TF, functions in gibberellin (GA) signaling by antagonizing DELLA proteins, thereby balancing growth and defense outcomes (Zhang et al., 2011). The multiple WRKY TFs reinforce known functions in pathogen-triggered immunity, while ERF071, NAC021, and C3H TFs integrate hormone signaling and environmental stress cues, orchestrating transcriptional responses under complex infection dynamics (Wang et al., 2023, Viswanath et al., 2023). Metabolomic analyses demonstrated that PVY significantly disrupted hormone homeostasis compared to PSTVd, and co-infection led to the most pronounced changes (Figure 5). while In PSTVd-infected plants, the balance between up- and down-regulated metabolites suggests a moderate, host-buffered response. CK and JA changes were limited, reflecting PSTVd’s milder interference in host signaling likely due to its non-coding nature and dependency on RNA-based regulation. The modest increase in CK metabolites like 2CltZ and tZOG here aligns with their known role in stress mitigation and shoot maintenance (O’Brien and Benková, 2013), possibly aiding systemic movement of PSTVd without provoking severe immunity. PVY infection, however, triggered extensive reprogramming. A strong upregulation of auxin and CK metabolites, alongside suppression of JA and SA, points to PVY-mediated hijacking of growth and hormone networks. Viruses like PVY often manipulate auxin pathways to enhance susceptibility and facilitate replication or movement (Müllender et al., 2021). The enhanced accumulation of tryptophan and gibberellin (GA20) further supports activation of the auxin and GA pathways hallmarks of viral symptom development and growth-defense trade-offs (Zhao and Li, 2021). Simultaneous repression of JA under PVY suggests a strategic viral suppression of defense-related hormonal pathways. Under co-infection, the hormone profile reveals both additive and antagonistic effects. While PVY-driven auxin and CK accumulation remained dominant, key PSTVd-induced hormones particularly CKs were markedly reduced, confirming PVY’s suppressive effect. Interestingly, GA and auxin metabolites were further elevated compared to single infections, indicating synergistic activation of specific hormonal branches. This layered response mirrors complex crosstalk known to occur in mixed infections, where one pathogen amplifies the host’s susceptibility landscape, enhancing the other’s replication or spread (Pan et al., 2021). JA downregulation was most pronounced in co-infection, alongside moderate SA suppression, suggesting a broad dampening of defense hormone pathways. Integrated gene-metabolite analysis revealed strong correlations between key regulatory genes (e.g., WRKY26, PAP1, MYC2) and hormone-related metabolites such as JA-Ile, tZR, and IAA-Asp (Figure 10, S9). The plant hormone signal transduction pathway was the most significantly enriched under co-infection (Ko04075), with key DEGs (e.g., AHP1/4, PYL1/8, COI1) validated by qRT-PCR (Figure S16) confirming the robustness of transcriptomic predictions . Overall, these findings support a model in which PVY functions as a dominant partner in PVY-PSTVd co-infection, actively shaping host transcriptional and metabolic landscapes, repressing PSTVd-related processes, and enhancing immune hormone crosstalk. This disparity can be attributed to several factors. First, PVY, as a protein-encoding virus, elicits a strong host immune response via pathogen-associated molecular patterns (PAMPs) and effectors, triggering widespread gene expression changes associated with pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) (Baebler et al., 2020, Piau and Schmitt-Keichinger, 2023, Wu et al., 2019). Conversely, PSTVd, a non-coding viroid, induces subtler transcriptomic alterations through RNA-based mechanisms, such as interference with host RNA regulation, resulting in a less pronounced immune footprint (Zheng et al., 2017, Owens et al., 2012). Second, the stability of PSTVd titers during co-infection likely stems from distinct replication strategies, with PSTVd replicating in the nucleus and PVY in the cytoplasm, minimizing direct competition (Kozieł et al., 2021, Jiang et al., 2018). Additionally, PVY’s suppression of host RNA silencing, a defense mechanism targeting both viruses and viroids, may inadvertently facilitate PSTVd persistence. These findings highlight the complex interplay of host responses in multi-pathogen infections and underscore the need for further studies to elucidate molecular cross-talk in co-infected plants. Figure 7. Schematic overview of phenotypic, transcriptional, and metabolomic responses of Nicotiana benthamiana under PSTVd, PVY, and co-infection. (A) Symptom gradient showing increasing severity from mock to co-infection, with co-infection causing the strongest phenotype (leaf curling, dwarfism, chlorosis). (B) Transcription factor (TF) regulation identified via Weighted Gene Co-expression Network Analysis (WGCNA), highlighting condition-specific upregulated TFs: PSTVd (purple), PVY (orange), and PVY-PSTVd co-infection (blue). (C) Schematic representation of key biological pathways affected: Defense signaling: PVY acts as a strong immune trigger; PSTVd induces weaker responses. RNA interference (RNAi): PVY enhances RNAi machinery (DCLs, AGOs), while PSTVd shows minimal activation. Photosynthesis and cell wall pathways: PVY triggers stronger suppression of photosynthesis-related genes compared to PSTVd. (D) Differential hormone-related metabolites (DAMs) across comparisons. PVY and co-infection show a higher number of altered metabolites, especially in CK, auxin, and JA pathways, with a strong trend toward upregulation. (E) Integration of key hormone metabolites with gene expression data in co-infection treatment. Upregulation (red) and downregulation (blue) of genes and their associated metabolites are shown for the ABA, JA, and CK pathways. (F) Conceptual model of virus-viroid interactions. PVY dominates in co-infection, leading to antagonistic suppression of PSTVd responses. Co-infection leads to both antagonistic and synergistic hormonal and molecular interactions, shaping the host response. Conclusion This study reveals the detailed relationship between Potato virus Y (PVY) and Potato spindle tuber viroid (PSTVd) during co-infection in potato plants, highlighting PVY’s dominance in driving phenotypic severity, transcriptional reprogramming, and metabolic shifts. Field surveys and multi-omics analyses revealed that PSTVd rarely occurs independently, consistently co-occurring with PVY, likely facilitated by viral-mediated suppression of RNA silencing or enhanced systemic movement. Phenotypic assessments confirmed PVY’s pronounced symptoms (stunting, chlorosis), while molecular profiling showed reduced PSTVd RNA accumulation and robust PVY-driven transcriptomic changes, including activation of PR genes, PAD4, EDS1, and RNA silencing components. Functional enrichment underscored PSTVd’s reliance on host machinery (protein phosphorylation, plant-pathogen interaction) and PVY’s modulation of photosynthesis, carbon metabolism, and defense pathways. Transcription factor and co-expression network analyses demonstrated PVY extensive regulatory influence, with synergistic and antagonistic effects in co-infection, while metabolomic shifts highlighted PVY disruption of hormone homeostasis and amplified crosstalk involving jasmonic acid and salicylic acid. These findings support a model wherein PVY acts as the dominant pathogen, shaping host responses through strong immune activation, while PSTVd persists via distinct replication strategies and possible viral facilitation. 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Keywords metabalome metabolomics potato spindle tuber viroid potato virus y transcriptome transcriptomics Authors Affiliations Wajahat Hussain Southwest University View all articles by this author Meijia Wu Southwest University College of Agronomy and Biotechnology View all articles by this author Yicong Wu Southwest University College of Agronomy and Biotechnology View all articles by this author Guangyan Li Southwest University View all articles by this author Yonghong Zhou 0000-0002-7194-5402 [email protected] Southwest University View all articles by this author Dianqiu Lv Southwest University View all articles by this author Metrics & Citations Metrics Article Usage 258 views 131 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Wajahat Hussain, Meijia Wu, Yicong Wu, et al. Integrated Transcriptomic and Metabolomic Profiling Reveals the Antagonistic and Synergistic Crosstalk During Co-Infection of Potato Virus Y and Potato Spindle Tuber Viroid. 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