Quantitative polymerase chain reaction (Q-PCR) and fluorescent in situ hybridization (FISH) detection of soilborne pathogen Sclerotium rolfsii

Milner, Holli; Ji, Pingsheng; Sabula, Michael; Wu, Tiehang

doi:10.1016/j.apsoil.2019.01.002

Cited by 19 publications

(5 citation statements)

References 40 publications

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“…Southern blight in tomato is caused by a soil-borne pathogen, Sclerotium rolfsii . Soil smears in a DNA isolation with 0.06 pg µl −1 of S. rolfsii was effectively detected by FISH technique that used an oligonucleotide probe labeled with cyanine dyes Cy3 and Cy5 ( Milner et al., 2019 ). Reproducibility, sensitivity, specificity, accuracy, and speed are the best features of FISH ( Bozorg-Ghalati et al., 2019 ).…”

Section: Molecular Tools For Detection Of Fungimentioning

confidence: 99%

Recent Advances in Molecular Diagnostics of Fungal Plant Pathogens: A Mini Review

Hariharan¹,

Prasannath²

2021

Front. Cell. Infect. Microbiol.

106

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Phytopathogenic fungal species can cause enormous losses in quantity and quality of crop yields and this is a major economic issue in the global agricultural sector. Precise and rapid detection and identification of plant infecting fungi are essential to facilitate effective management of disease. DNA-based methods have become popular methods for accurate plant disease diagnostics. Recent developments in standard and variant polymerase chain reaction (PCR) assays including nested, multiplex, quantitative, bio and magnetic-capture hybridization PCR techniques, post and isothermal amplification methods, DNA and RNA based probe development, and next-generation sequencing provide novel tools in molecular diagnostics in fungal detection and differentiation fields. These molecular based detection techniques are effective in detecting symptomatic and asymptomatic diseases of both culturable and unculturable fungal pathogens in sole and co-infections. Even though the molecular diagnostic approaches have expanded substantially in the recent past, there is a long way to go in the development and application of molecular diagnostics in plant diseases. Molecular techniques used in plant disease diagnostics need to be more reliable, faster, and easier than conventional methods. Now the challenges are with scientists to develop practical techniques to be used for molecular diagnostics of plant diseases. Recent advancement in the improvement and application of molecular methods for diagnosing the widespread and emerging plant pathogenic fungi are discussed in this review.

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Section: Molecular Tools For Detection Of Fungimentioning

confidence: 99%

Recent Advances in Molecular Diagnostics of Fungal Plant Pathogens: A Mini Review

Hariharan¹,

Prasannath²

2021

Front. Cell. Infect. Microbiol.

106

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“…Several methods have introduced by several researchers for the processing of fish images (Hanafiah et al, 2015;Fern andez-Alvarez et al, 2019;Han et al, 2019;Malik et al, 2017;Preena et al, 2019;Ivanova et al, 2018;Elsheshtawy et al, 2019;Carraro et al, 2018;Jovanovi c et al, 2018;Hutchins et al, 2018;Dong et al, 2019;Fazio, 2019;Tran et al, 2019;Milner et al, 2019). In this section, some of the works have discussed.…”

Section: Related Workmentioning

confidence: 99%

A fuzzy approach to identify fish red spot disease

Bhoi

Panda

Jena

et al. 2020

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PurposeFish are considered as one of the important aquatic animals in the planet. They play a vital role in the nutrient cycle. They can be considered as one of the healthy food for human beings. They can also act as a solution for some of the human health problems. If fish are affected by several diseases, they in turn provide an adverse effect on human health. Therefore, it is very much essential to protect fish from being affected by any diseases.Design/methodology/approachThis paper is mainly focused on the identification of the red spot diseased area in fish. In this work, a fuzzy rule based method (FRBAM) and triangular membership function (TMFN) is used to identify the red spot disease (RSD) in the fish by analyzing several red spot diseased fish (RSDF) images. The canny edge detector is used for intermediate processing of RSDF images.FindingsThe proposed method is able to identify the red pixels over the fish by marking the affected area with red color by using a standard RGB model.Originality/valueThe proposed method follows FRBAM and TMFN in order to detect the RSD and canny edge detector for processing of RSDF images. Finally, it is tested using ten different image sizes and the results show its better performance in terms of detection of RSD affected regions of fish and execution time.

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“…Zhu et al (2022) established a real-time fluorescence quantitative PCR detection system and applied it to detect Ciboria shiraiana and C. carunculoides in the collected mulberry fruit sclerotinia samples, which provided a basis for the prediction and early control of the disease [5]. This technique is also widely used in the detection of soil-borne pathogenic fungi [6][7][8][9], helping to identify the occurrence, epidemiology, and timely control of soil-borne diseases. Thomas et al (2022) developed a rapid and sensitive diagnostic tool to detect and quantify Fusarium sambucinum in plant tissues by using a modified random amplified polymorphic DNA PCR assay [10].…”

Section: Introductionmentioning

confidence: 99%

Measuring Pathogenic Soil Fungi That Cause Sclerotinia Rot of Panax ginseng Using Real-Time Fluorescence Quantitative PCR

et al. 2023

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Sclerotinia ginseng is the primary pathogenic fungus responsible for Sclerotinia rot of ginseng, which significantly reduces plant yield and quality. The density of sclerotia in the soil is closely associated with rot incidence and severity. Whole genome sequencing was conducted to obtain fungal frame maps. The specific primers, q2001F/q2001R, were screened out by pan-genomic analysis using the NCBI database. Recombinant plasmids containing amplicons obtained with this primer set were used as standard plasmids to construct a real-time fluorescence quantitative PCR system. The relationships between the cycle threshold (Ct) values and the soil sclerotium densities were determined by real-time PCR. Real-time PCR had a detection limit of 1.5 × 10−2 g·kg−1 soil for Sclerotinia rot causing fungal mycelium, and the relationship between the density of S. ginseng mycelium n (g·g−1 soil) and the Ct value was n = 10(40.048 − Ct)/6.9541. The detection limit of real-time PCR for measuring soil sclerotia was 3.8 × 10−5 g·g−1 soil, suggesting a sensitivity 100 times that of conventional PCR. The relationship between the sclerotium density n (g·g−1 soil) and the Ct value was n = 10(18.351 − Ct)/7.0914. Compared with the conventional PCR method, the fluorescent quantitative PCR method could detect the population of Sclerotinia spp. in soil more efficiently, accurately, and sensitively.

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Quantitative polymerase chain reaction (Q-PCR) and fluorescent in situ hybridization (FISH) detection of soilborne pathogen Sclerotium rolfsii

Cited by 19 publications

References 40 publications

Recent Advances in Molecular Diagnostics of Fungal Plant Pathogens: A Mini Review

Recent Advances in Molecular Diagnostics of Fungal Plant Pathogens: A Mini Review

A fuzzy approach to identify fish red spot disease

Measuring Pathogenic Soil Fungi That Cause Sclerotinia Rot of Panax ginseng Using Real-Time Fluorescence Quantitative PCR

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