noxB-based marker for Alternaria spp.: a new diagnostic marker for specific and early detection in crop plants

Molecular diagnostic assay for pre-harvest detection of Tilletia indica infection in wheat plants

The current study describes a new diagnostic method for the rapid and accurate detection of Tilletia indica, the pathogen accountable for causing Karnal bunt (KB) disease in wheat. This method uses quantitative real-time polymerase chain reaction (qPCR) and a primer set derived from glyceraldehyde 3-phosphate dehydrogenase (GAPDH) gene of T. indica to identify the presence of the pathogen. The qPCR assay using this primer set was found highly sensitive, with a limit of detection (LOD) value of 4 pg of T. indica DNA. This level of sensitivity allows for the detection of the pathogen even in cases of different growth stages of wheat, where no visible symptoms of infection on the wheat plants can be seen by naked eyes. The study also validated the qPCR assay on ten different wheat cultivars. Overall, this study presents a valuable molecular tool for rapid, specific and sensitive detection of KB fungus in wheat host. This method has practical applications in disease management, screening of wheat genotypes against KB and can aid in the development of strategies to mitigate the impact of Karnal bunt disease on wheat production.

Establishment of a recombinase polymerase amplification detection method for Puccinia striiformis f. sp. tritici

Wheat stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is an airborne disease that endangers wheat during its entire growth period. In this study, the Pst134EA_003354 uncharacterized protein (GenBank: XM_047941824.1) of Pst was used as the target sequence, and the primers PS-RPA-F and PS-RPA-R, as well as the probe PS-LF-probe, were designed for recombinase polymerase amplification (RPA) technology. Flow chromatography was combined with the process to establish an RPA detection method for Pst. This method successfully established visual detection within 10 min under a constant temperature of 39 °C, and the detection results were consistent with those of ordinary PCR analysis. However, it only had high specificity for Pst, and the detection limit was 10 fg/μL. In addition, this rapid method successfully detected Pst from wheat leaves during the field incubation period, indicating substantial benefits for applied use. In summary, the RPA detection method established in this study has the favourable characteristics of high efficiency, simple functionality, and rapid and universal practicability, providing a theoretical basis for the early detection and prevention of Pst.

Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests

High-throughput sequencing (HTS), more specifically RNA sequencing of plant tissues, has become an indispensable tool for plant virologists to detect and identify plant viruses. During the data analysis step, plant virologists typically compare the obtained sequences to reference virus databases. In this way, they are neglecting sequences without homologies to viruses, which usually represent the majority of sequencing reads. We hypothesized that traces of other pathogens might be detected in this unused sequence data. In the present study, our goal was to investigate whether total RNA-seq data, as generated for plant virus detection, is also suitable for the detection of other plant pathogens and pests. As proof of concept, we first analyzed RNA-seq datasets of plant materials with confirmed infections by cellular pathogens in order to check whether these non-viral pathogens could be easily detected in the data. Next, we set up a community effort to re-analyze existing Illumina RNA-seq datasets used for virus detection to check for the potential presence of non-viral pathogens or pests. In total, 101 datasets from 15 participants derived from 51 different plant species were re-analyzed, of which 37 were selected for subsequent in-depth analyses. In 29 of the 37 selected samples (78%), we found convincing traces of non-viral plant pathogens or pests. The organisms most frequently detected in this way were fungi (15/37 datasets), followed by insects (13/37) and mites (9/37). The presence of some of the detected pathogens was confirmed by independent (q)PCRs analyses. After communicating the results, 6 out of the 15 participants indicated that they were unaware of the possible presence of these pathogens in their sample(s). All participants indicated that they would broaden the scope of their bioinformatic analyses in future studies and thus check for the presence of non-viral pathogens. In conclusion, we show that it is possible to detect non-viral pathogens or pests from total RNA-seq datasets, in this case primarily fungi, insects, and mites. With this study, we hope to raise awareness among plant virologists that their data might be useful for fellow plant pathologists in other disciplines (mycology, entomology, bacteriology) as well.

Brassicaceae Fungi and Chromista Diseases: Molecular Detection and Host–Plant Interaction

Brassicaceae plants cover a large number of species with great economic and nutritional importance around the world. The production of Brassica spp. is limited due to phytopathogenic fungal species causing enormous yield losses. In this scenario, precise and rapid detection and identification of plant-infecting fungi are essential to facilitate the effective management of diseases. DNA-based molecular methods have become popular methods for accurate plant disease diagnostics and have been used to detect Brassicaceae fungal pathogens. Polymerase chain reaction (PCR) assays including nested, multiplex, quantitative post, and isothermal amplification methods represent a powerful weapon for early detection of fungal pathogens and preventively counteract diseases on brassicas with the aim to drastically reduce the fungicides as inputs. It is noteworthy also that Brassicaceae plants can establish a wide variety of relationships with fungi, ranging from harmful interactions with pathogens to beneficial associations with endophytic fungi. Thus, understanding host and pathogen interaction in brassica crops prompts better disease management. The present review reports the main fungal diseases of Brassicaceae, molecular methods used for their detection, review studies on the interaction between fungi and brassicas plants, and the various mechanisms involved including the application of omics technologies.

Identification and fine-mapping of a major QTL (PH1.1) conferring plant height in broomcorn millet (Panicum miliaceum)

The plant height of broomcorn millet (Panicum miliaceum) is a significant agronomic trait that is closely related to its plant architecture, lodging resistance, and final yield. However, the genes underlying the regulation of plant height in broomcorn millet are rarely reported. Here, an F₂ population derived from a cross between a normal variety, "Longmi12," and a dwarf mutant, "Zhang778," was constructed. Genetic analysis for the F₂ and F_2:3 populations revealed that the plant height was controlled by more than one locus. A major quantitative trait locus (QTL), PH1.1, was preliminarily identified in chromosome 1 using bulked segregant analysis sequencing (BSA-seq). PH1.1 was fine-mapped to a 109-kb genomic region with 15 genes using a high-density map. Among them, longmi011482 and longmi011489, containing nonsynonymous variations in their coding regions, and longmi011496, covering multiple insertion/deletion sequences in the promoter regions, may be possible candidate genes for PH1.1. Three diagnostic markers closely linked to PH1.1 were developed to validate the PH1.1 region in broomcorn millet germplasm. These findings laid the foundation for further understanding of the molecular mechanism of plant height regulation in broomcorn millet and are also beneficial to the breeding program for developing new varieties with optimal height.

DNA barcode, multiplex PCR and qPCR assay for diagnosis of pathogens infecting pulse crops to facilitate safe exchange and healthy conservation of germplasm

The DNA barcodes were developed from ITS region for the identification of fungal plant pathogens namely, Alternaria alternata and A. tenuissima both causing leaf spots, Ascochyta rabiei causing Ascochyta blight, Fusarium oxysporum f. sp. ciceris causing wilt, Macrophomina phaseolina causing dry root rot, Rhizoctonia solani causing web blight and wet root rot, Sclerotium (Athelia) rolfsii causing collar rot, Sclerotinia sclerotiorum causing stem rot and Cercospora canescens and Pseudocercospora cruenta both causing leaf spots in pulse crops. Barcode compliance for A. alternata (DBTPQ001-18), A. tenuissima (DBTPQ002-18), A. rabiei (DBTPQ003-18), F. oxysporum f. sp. ciceris (DBTPQ004-18), M. phaseolina (DBTPQ005-18), R. solani (DBTPQ006-18), S. rolfsii (DBTPQ007-18), S. sclerotiorum (DBTPQ008-18), C. canescens (DBTPQ009-18) and P. cruenta (DBTPQ029-20) have been generated based on the Barcode of Life Data System (BOLD) system. In addition to ITS, other genomic regions were also explored and on the basis of sequence variation they were ranked as TEF-α > SSU > LSU > β-tubulin. These genes could be considered for secondary barcode and phylogenetic relatedness. ITS-based markers for the detection of A. alternata (BAA2aF and BAA2aR) and R. solani (BRS17cF and BRS17cR) were developed which provided 400 bp and 220 bp amplicons, respectively. While, for F. oxysporum f. sp. ciceris, COX1-based marker (FOCox1F and FOCox3R) was developed which amplified 150 bp. The markers proved highly specific and sensitive with detection limit of 0.0001 ng of template DNA using qPCR and simultaneously detected these three pathogens. The DNA barcodes and diagnostics developed are suitable for quick and reliable detection of these pathogens during quarantine processing and field diagnostics.

A rapid colorimetric LAMP assay for detection of Rhizoctonia solani AG-1 IA causing sheath blight of rice

Rhizoctonia solani is one of the most devastating pathogens. R. solani AG-1 IA causes sheath blight in rice, maize, and other Gramineous plants. Accurate identification is essential for the effective management of this pathogen. In the present study, a set of four primers were designed viz. RSPG1, RSPG2, RSPG4, and RSPG5 for polygalacturonase (PG) gene, an important virulence factor in phytopathogenic fungi. All four primer sets showed specific amplification of 300 bp (RSPG1F/R), 375 bp (RSPG2F/R), 500 bp (RSPG4F/R) and 336 bp (RSPG5F/R) amplicons. q-PCR detection using each primer sets could detect up to 10 pg of DNA. We also designed six primers (RS_pg_F3_1/RS_pg_B3_1, RS_pg_FIP_1.1/RS-pg_BIP_1.1, and RS_pg_LF_1/RS_pg_LB_1) for PG gene. Further, a colorimetric LAMP assay developed yielded visual confirmation of the pathogen within 45 min of sample collection when coupled with rapid high throughput template preparation method (rHTTP) from infected samples. The sensitivity of the LAMP assay was as low as 1.65 fg/µl of template DNA and could effectively detect R. solani AG-1 IA from diseased plant tissues and soil samples. The LAMP assay was highly specific for R. solani as it did not show any amplification with other AG groups of R. solani and closely related fungal and bacterial outgroups. This study will help in designing an effective point of care diagnostic method for early monitoring of R. solani and thereby planning timely preventive measures against the pathogen.

Molecular Diagnostic Assay for Rapid Detection of Flag Smut Fungus (Urocystis agropyri) in Wheat Plants and Field Soil

Flag smut incited by Urocystis agropyri has the potential to cause substantial reduction in yield and quality of wheat production. An early and precise diagnosis is a key component in the successful management of flag smut of wheat. Therefore, a simple molecular assay for the rapid detection of U. agropyri was developed for the first time. To detect U. agropyri, species specific primers were developed by comparing the partial sequences of internal transcribed spacer (ITS) DNA region of U. agropyri with related and unrelated phytopathogenic fungi. The clear amplicons of 503 and 548 bp were obtained with the two sets of designed primers (UA-17F/UA-519R and UA-15F/UA-562R) from the genomic DNA of 50 geographic distinct isolates of U. agropyri. However, no amplicon was obtained from the DNA of other 21 related and unrelated phytopathogenic fungi which showed the specificity of the primers for the U. agropyri. PCR reaction was also set up to confirm the presence of U. agropyri spores in six different wheat varieties along with eleven distinct regional soil samples as template DNA. The presence of U. agropyri in all the soil samples collected from an infected field and plant tissue of diseased plants collected at two different stages (20 and 40 days post sowing) and the absence in the soils and plants of healthy plots indicated 100% reliability for detection of U. agropyri. This simple and rapid test can be employed for the detection of U. agropyri from enormous wheat and soil samples in very short time with less man power. Thus, the reported molecular assay is very specific for U. agropyri and requires less time and man power over conventional diagnosis which is often confused by coinciding morphological features of closely related fungal pathogens, and therefore, it can be used for quarantine surveillance of flag smut.