The developed RT-RPA assays provide a practical tool for routine virus surveillance, certification of virus-free planting material, thereby contributing to improved stress resilience and sustainable mango production.
Abstract
Plant viral diseases pose a major threat to perennial fruit crops, where infections often remain latent and persist over long periods, facilitating unnoticed spread through planting material. Recent advances in high-throughput sequencing (HTS) have greatly expanded knowledge of plant viral diversity and plant-virus interactions, including the identification of emerging and re-emerging viruses. However, translating virome-level discoveries into practical disease management tools remains a significant challenge, particularly for field-level surveillance and sustainable crop protection. Mango (Mangifera indica), a globally important fruit crop, exemplifies this gap, as virus infections are poorly correlated with visible symptoms and reliable on-site diagnostic tools are limited. In this study, HTS was employed to reconfirm the presence of mangifera indica latent virus (MiLV) and mangifera virus 1 (MaV-1) in mango plants and to generate validated genomic information for diagnostic assay development. Building on these data, reverse transcription-recombinase polymerase amplification (RT-RPA) assays were developed and optimized for rapid virus detection. The assays operated efficiently under isothermal conditions (40 °C) within 25 min. The MiLV RT-RPA assay enabled direct detection from crude leaf extracts without the need of RNA purification, whereas MaV-1 detection required purified RNA as template. Sensitivity analysis showed that the MiLV RT-RPA assay detected viral RNA up to 0.01 fg µl⁻¹ (equivalent to a 10⁻¹⁰ dilution of 100 ng µl⁻¹ RNA) and MaV-1 up to 0.1 ng µl⁻¹ showed complete concordance with RT-PCR (Cohen's K = 1.00). Validation using field-collected symptomatic and asymptomatic samples demonstrated complete concordance with conventional RT-PCR. The detection of both viruses in young grafted plants showed the potential role of vegetative propagation in virus dissemination and emphasizes the importance of screening both scion and rootstock materials. This study demonstrates how HTS-based insights into plant viral diversity can be effectively translated into rapid, field-deployable molecular diagnostics. The developed RT-RPA assays provide a practical tool for routine virus surveillance, certification of virus-free planting material, thereby contributing to improved stress resilience and sustainable mango production.
To protect global strawberry production, clean plant programs rely on rigorous certification and quarantine testing to prevent the spread of disease. For decades, biological graft indexing has been the "gold standard" for virus detection; however, it often fails to identify viruses that remain latent in single infections or viruses requiring extended periods to induce symptoms. High throughput sequencing (HTS) offers an alternative that identifies all known and emerging viruses independent of the nucleotide sequences of their genomes including those undetected by traditional bioassays. This study compared HTS with graft indexing using 73 virus-infected donor plants, 584 indicator clones, and two replicates to evaluate HTS as a replacement for conventional graft bioassay testing. Donor material was analyzed via HTS and simultaneously grafted onto two replicates of four Fragaria indicator clones (UC-4, UC-5, UC-10, UC-11). Indicator symptoms were monitored weekly over eight weeks and again following natural dormancy. The RT-qPCR/RT-PCR testing for virus transmission was also conducted at eight weeks and after dormancy. HTS identified viral infections in all donor plants, detecting 17 different viruses across eight families, and revealing mixed infections in 75% of plants. In contrast, 83% of indicators developed symptoms within the current standard of eight weeks post graft. Only 61% of the indicator plants displayed symptoms both before and after dormancy, while 7% remained asymptomatic throughout despite receiving grafts from HTS-positive donors. Given the limitations of biological indexing, this research strongly supports the integration of HTS as a frontline detection tool to enhance the reliability and efficiency of certification programs.
Daniel Fager, M. Al Rwahnih, D. Mollov· Plant Disease· 0 citations
Sweet potato (Ipomoea batatas (L.) Lam) is an important global food crop, but its production is threatened by numerous viral pathogens. More than 30 RNA and DNA viruses have been reported worldwide, making rapid and accurate detection essential for disease management, epidemiological surveillance, germplasm exchange, and resistance breeding. Although previous reviews have addressed sweet potato viruses and individual diagnostic methods, a comprehensive synthesis of emerging molecular technologies remains limited. This review addresses that gap by critically integrating recent advances from PCR-based and isothermal assays to high-throughput sequencing, CRISPR-based diagnostics, biosensors, nanotechnology, and artificial intelligence-driven detection platforms. Conventional approaches, including symptom observation, biological indexing, electron microscopy, and ELISA, have contributed to early virus identification but often lack the sensitivity, specificity, and speed needed for modern diagnostics. Molecular and isothermal techniques have substantially improved detection accuracy and enabled rapid identification and field-deployable diagnostics of diverse and mixed infections, while sequencing, CRISPR, biosensors, and AI-based platforms offer greater capacity for detecting novel and emerging viruses. This review discusses the comparative evaluation of molecular technologies for sweet potato virus detection in terms of diagnostic performance, cost-effectiveness, speed, and suitability for both laboratory and field applications, while highlighting future priorities for next-generation virus diagnostics. Integrating portable and high-throughput diagnostic platforms will strengthen virus surveillance, support virus-free planting material production, and promote sustainable sweet potato production worldwide.
Muhammad Abul Kalam Azad, N. Ibnat, Saleh Shafique Chowdhury et al.· Viruses· 0 citations
Several Begomovirus have become significant plant viruses affecting pepper crops worldwide. In the Philippines, begomoviruses infecting pepper were first documented in 2011 but since then no other studies have been done. As new and emerging begomoviral diseases continue to threaten and hamper crop production, it is important to deal them proactively to mitigate losses. Here, begomoviruses associated with pepper in the country were successfully detected and identified through the combined application of conventional molecular methods and next-generation sequencing (NGS) technologies. Pepper leaf samples exhibiting disease symptoms were gathered from various locations across the country. Presence of begomovirus infection was initially detected through visual observation of its characteristic symptoms (leaf curling/cupping/crinkling, interveinal yellowing of leaves and apical leaf size reduction) and subsequently verified through polymerase chain reaction (PCR) using begomovirus-specific degenerate primers, together with rolling circle amplification (RCA). Emerging begomoviruses in pepper were not detected by restriction enzymes digestion but were identified through NGS-derived sequences. Two known and five unknown begomoviruses were identified from NGS sequences and provided evidence of the presence of emerging known begomoviruses in new areas as well as new begomoviruses of pepper in the Philippines. This is the first study to employ Illumina-NGS technology for the molecular surveillance of begomoviruses infecting pepper in the Philippines.
Keywords: Bioinformatics; next-generation sequencing; phylogenetic analysis, polymerase chain reaction, rolling circle amplification
Maria Lima Pascual, Filomena Sta Cruz· ASEAN Journal of Scientific...· 0 citations
Angular leaf spot, caused by the phytopathogenic bacterium Xanthomonas fragariae, results in considerable yield losses in strawberry production. This pathogen is designated as a quarantine pest in several countries, including South Korea. Therefore, early identification of this pathogen in young plants is essential for preventing disease spread and ensuring rapid eradication. However, intraspecific genetic variation among isolates from different geographic origins imposes challenges for the accurate diagnosis of X. fragariae. In this study, we developed a novel gene marker and primer set (XF-212F/R) through comparative genomic analysis of X. fragariae strains and related bacterial species for pathogen-specific detection. As a result, the XF-212F/R primer set amplified only X. fragariae strains without cross-reactivity to other Xanthomonas spp. or related bacteria. The detection limits of the SYBR Green real-time PCR assay were 1.41 × 102 plasmid copies/μL, 500 fg of genomic DNA, and 1.52 × 103 CFU/mL of bacterial cells. The assay also accurately detected the pathogen from cells directly extracted from infected strawberry leaves, enabling rapid detection without the need for DNA extraction. This diagnostic method showed improved coverage for X. fragariae strains and is suitable for early detection and disease surveillance in strawberry plants.
H. Choi, Sujin Ki, Yong Hwan Lee et al.· Plant Pathology Journal· 0 citations
Sugarcane leaf scald, caused by Xanthomonas albilineans, is difficult to diagnose because latent infections often precede symptom development, allowing infected planting material to disseminate the pathogen unnoticed. Although quantitative PCR (qPCR) has substantially improved pathogen detection, most available assays target conserved ribosomal regions, which can limit species-level discrimination and offer little guidance for interpreting pathogen abundance. Comparative genomic analysis identified Xal_000736 as a candidate species-specific target for assay development. A TaqMan qPCR assay targeting this locus was developed and evaluated using purified genomic DNA, bacterial suspensions, plant matrix-matched standards, six X. albilineans isolates, 21 non-target bacterial strains, and naturally or artificially infected sugarcane samples. Assay performance was directly compared with that of the previously described 16S rRNA-based xal-FR assay. The biological significance of pathogen abundance was further examined using correlation analysis, logistic regression, receiver operating characteristic (ROC) analysis, and generalized linear mixed-effects models (GLMMs). The 0736 assay showed high amplification efficiency, excellent linearity, and reproducible quantification throughout the validated dynamic range. Quantitative performance was comparable between the two assays, whereas the 0736 assay achieved substantially greater analytical specificity against the bacterial panel examined. ROC analysis also produced a higher area under the curve for the 0736 assay, although the difference between assays was not statistically significant. Pathogen abundance increased with disease severity but overlapped considerably among adjacent symptom classes, indicating that bacterial abundance alone could not fully distinguish disease status. Logistic regression identified quantitative reference values associated with symptom transition and diagnostic classification, while mixed-effects modelling confirmed that the relationship between pathogen abundance and disease status remained significant after accounting for cultivar-related variation. Together, these results show that genome-guided target selection can improve analytical specificity without compromising quantitative performance. They also provide a quantitative basis for interpreting qPCR-derived pathogen abundance in sugarcane leaf scald. Because the proposed reference values were derived from the populations and sampling conditions included in this study, independent validation across additional cultivars, environments, and pathogen populations will be required before routine diagnostic or regulatory use.
Cuilin Huang, Xiao Yang, Meilin Li et al.· Plant Disease· 0 citations
