A PCR primer-specific to Cylindrocarpon heteronema for detection of the pathogen in apple wood

Brown, Alastair

doi:10.1016/0378-1097(93)90497-p

Cited by 3 publications

(3 citation statements)

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“…Early detection of disease symptoms can be used to schedule pesticide application and pruning of infected tissues or eradication of infected apple trees to reduce the chance of severe outbreaks (Norelli et al, 2000; Delalieux et al, 2007). Current disease identification practices in apple orchards involve scouting by experienced pathologists, shipping of potentially infected samples with visible symptoms to remote laboratories for chemical and PCR tests (Brown et al, 1993; Li et al, 1994; Johnson et al, 2000), and sharing digital images with experts for identification and recommendation. During a busy growing season, the time required for observation, sample collection, shipping, analysis, and identification often results in growers not receiving recommendations until it is too late to take the necessary control measures.…”

Section: Discussionmentioning

confidence: 99%

The Plant Pathology Challenge 2020 data set to classify foliar disease of apples

et al. 2020

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The U.S. apple industry, annually worth $15 billion, experiences millions of dollars in annual losses due to various biotic and abiotic stresses, ongoing stress management, and multi-year impacts from the loss of fruit-bearing trees. Over the growing season, apple orchards are under constant threat from a large number of insects, as well as fungal, bacterial, and viral pathogens, particularly in the northeastern United States (Fig. 1). Depending on the incidence and severity of infection by diseases and insects, impacts range from unappealing cosmetic appearance, low marketability, and poor quality of fruit, to decreased yield or complete loss of fruit or trees, causing huge economic losses (Sutton et al., 2014). Early pest and disease detection are critical for appropriate and timely deployment of disease and pest management programs (Bessin et al., 1998). Disease and pest risk prediction models and management programs are developed based on incidence, severity, and timing of infection, taking into account current and forecasted weather data (

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Section: Discussionmentioning

confidence: 99%

The Plant Pathology Challenge 2020 data set to classify foliar disease of apples

et al. 2020

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“…Amplification of products specific to N. gdigena. PCR primers NS 7 UP (from the 5' end of the N. galligena intron region) and ChIntrev (a reverse primer from the region of the N. galligena-specific primer, ChInt, in the ITSl region of the rDNA; Brown et al, 1993), were used to amplify N. galligenaspecific products which included the SSU rDNA intron region. PCR amplification conditions were : 1 min at 94 O C , 1 min 30 s at 55 "C, 3 min at 72 "C, for 30 cycles (Perkin Elmer 480 thermal cycler).…”

Section: Methodsmentioning

confidence: 99%

Intron polymorphism in small subunit rDNA of Nectria galligena

Crockard¹,

Fulton

Bjourson³

et al. 1998

Microbiology

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PCR amplification of the small subunit (SSU) rDNA gene of 40 isolates of Nectria galligena revealed four length polymorphisms. PCR-RFLP analysis of the SSU rDNA gene divided the isolates into four categories similar, but not identical, to categories identified by Southem-RFLP analysis. Nucleotide sequence analysis revealed that isolates in three of the four SSU rDNA (18s) categories possess an intron of 363 bp, 1185 bp or 1423 bp at the NS 7 priming site. Isolates in the fourth category do not possess an intron. The nucleotide sequences of these introns did not contain the core elements characteristic of typical group I introns, nor did they exhibit a group I intron secondary structure. Homology between the introns indicates a common lineage, all three possibly having come from a larger intron and having been formed by subsequent deletions. PCR primers upstream of the SSU rDNA intron region and from within the internal transcribed spacer 1 region amplify a product specific to N. ga//igena, which will confirm the identity of the pathogen and reveal its 185 category in a single reaction.

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“…The protocol has been used equally successfully, e.g. to detect Cylindrocarpon heteronema (teleomorph Nectria galligena) in symptomless infected apple wood and has superseded the method described in Brown et al (1993). The C. acutatum-specific primer (CaInt2) could be used for the detection of this pathogen on host plants other than strawberry, and to distinguish this ubiquitous and highly variable fungus from the morphologically similar C. gloeosporioides (Sutton, 1992;Sreenivasaprasad et al, 1994).…”

Section: Amplification Of C Acutatum Specific Fragment From Infectedmentioning

confidence: 99%

**PCR‐based detection of Colletotrichum acutatum on strawberry**

et al. 1996

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An oligonucleotide primer (CaInt 2) was synthesized from the variable internal transcribed spacer (ITS) 1 region of ribosomal DNA (rDNA) from Colletotrichum acutatum. PCR with primers CaInt2 and ITS4 (from a conserved sequence of the rDNA) amplified a 490 bp fragment from several isolates of C. acutatum but not from other members of the genus Colletotrichum. Amplification of this fragment was achieved from 100 fg of fungal DNA. These primers amplified a fragment of the same size from DNA extracted from strawberry tissues infected by C. acutatum. Southern hybridization analysis confirmed the 490 bp fragment from C. acutatum DNA and infected strawberry to be identical. The species‐specific primer (CaInt2) developed in this work could be used for the accurate identification of C. acutatum and its detection on other host plants.

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A PCR primer-specific to Cylindrocarpon heteronema for detection of the pathogen in apple wood

Cited by 3 publications

References 0 publications

The Plant Pathology Challenge 2020 data set to classify foliar disease of apples

The Plant Pathology Challenge 2020 data set to classify foliar disease of apples

Intron polymorphism in small subunit rDNA of Nectria galligena

**PCR‐based detection of Colletotrichum acutatum on strawberry**

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