THE IDENTIFICATION OF PLANTS, PATHOGENS, INSECTS AND
NEMATODES THROUGH DNA FINGERPRINTING
Process leader: Dr W. Adriaan Smit (ARC Infruitec-Nietvoorbij)
in collaboration with
Dr Lucienne Mansvelt (ARC Infruitec-Nietvoorbij)
Dr Gerhard Pietersen (ARC PPRI)
Ms Maléne Fouché, Ms Michel Carstens, Ms Melanie Arendse (ARC Infruitec-Nietvoorbij)
1. PLANTS
Cultivar typing has traditionally been based on phenotypic characteristics of mature fruit trees.
This method is subjected to environmental changes and human judgement, and often a decision
on the authenticity of a plant is made with the fruit as single criterion. This process, in the case of
pears, can take up to 4 years. Even then an accurate identification is often impossible. DNA
fingerprinting of plant genomes, however, allows rapid and reliable authenticity of cultivars in
question. Furthermore, it is also a tool for protection of patent rights on newly developed fruit
cultivars.
Unique fingerprints have been developed for 18 apple, 19 pear, 34 peach, 22 plum, 10 apricot, 21
nectarine and 17 table grape 14 wine grape, 6 pistachio, 4 strawberry and 5 persimmon cultivars
and rootstocks.
The cultivars and rootstocks for which unique fingerprints have been developed are listed in
Table 1. They can now be distinguished on a routine basis as a diagnostic service.
2. PATHOGENS / INSECTS / NEMATODES
Molecular detection tools in integrated disease / pest management
The lack of fast, accurate and reliable means for detecting plant pathogens is one of the main
limitations in integrated disease management. It is imperative that organisms be identified
properly so that judicious use of the literature can be made and management strategies can be
designed as quickly as possible. Numerous pathogens are difficult to identify by morphological
characteristics and require extensive, time-consuming work with pure cultures and / or
pathogenicity tests. It is challenging for most plant pathologists to identify isolates routinely from
fungal genera that include a range of plant pathogenic and saprophytic species.
Mechanical trapping devices which capture fungal spores are available to plant pathologists,
however, the usefulness of these tools is limited by the painstaking microscopic sorting and
identification required after trapping. Selective media can help but in most cases they go only as
far as genus selectivity. Baiting methods used for trapping motile stages of certain water moulds
can reduce the range of isolates to be sorted out, but the selectivity of the baits used for the water
moulds is poor. Furthermore, the taxonomy of these fungi is so complex that identifying what
colonised a given bait still remains difficult. Technologies that would enable pathologists to
identify pathogens from plants, traps, baits or in soil samples rapidly and accurately would be
very useful in epidemiological and ecological studies as well as for detecting initial inoculum in
disease forecasting systems.
Monitoring is the corner stone of integrated pest / nematode management. The lack of fast,
accurate and reliable means by which eggs and immature stages of insects can be detected and
identified is one of the main limitations in integrated pest management. The development of the
sophisticated IPM programs currently being implemented for insect management would not have
been possible without the use of different types of traps to monitor the pests. However, standard
procedures to identify insects are time consuming and often require access to specialists in
taxonomy. A technique that could identify eggs and juveniles of different insect species would not
only assist in insect research, but would help to improve integrated pest management strategies.
Although numerous publications describe novel molecular techniques for faster, more accurate
and reliable detection of pathogens, insects and nematodes, there are a few instances where
these new tools are being used in disease and pest management. Recent advances, however,
will accelerate the adoption of molecular technologies into integrated disease and pest
management programs. In order to become more widely used, the new technologies need to
address specific challenges.
A potential limitation of most current, antibody or DNA-based, detection technologies is that only
a single (or a few) species is detected per assay. Although convenient when a large number of
samples must be assessed for the presence of one pathogen / insect / nematode, they are
inefficient when samples must be assessed for several different pathogens / insects / nematodes.
Quarantine testing, the first line of defense in disease / pest management, is only one area that
would benefit greatly from the availability of multi-pathogen / multi insect assays. As free trade
agreements between countries become the norm, rapid testing for possible food contamination
from a wide range of quarantined organisms (nematodes, fungi, viruses, bacteria and immature
stages of insects) will be in high demand. For a wide range of disease / pest management
applications, there is a need for comprehensive diagnostic kits that can detect the presence of
numerous pathogens / insects in a single test. Kits could also be host-based by having the
capability of concurrently testing for all key pathogens of a given host.
Reverse dot-blot technology has been developed for the detection of fungal pathogens. It not only
eliminates the need for fungal isolation but also detects several fungal species in a single test.
Several currently available techniques can detect single pathogens directly. One of the most
common of these techniques uses a standard dot-blot, in which DNA from different samples is
immobilized on a solid support membrane. The membrane is then hybridized with a speciesspecific probe that can identify the samples containing the organism of interest.
With reverse dot-blot technology, group or species-specific DNAs (oligonucleotides) are bound to
the solid support membrane while the hybridization probe is made from unknown sample DNA.
Part of the system incorporates a grid of oligonucleotides which acts like a check list, against
which several possibilities are checked simultaneously and the pathogens present in a sample
are literally “highlighted”. Precise identity can be determined within 24 hours instead of the
several days to a few weeks for more traditional techniques.
There are wo different agricultural applications of the reverse dot-blot technology: genus based
systems where pathogenic species of fungi can be identified or detected; and host-based
systems where all the key pathogenic fungal species of a host can be identified or detected.
Currently reverse dot-blot has been used to detect fungi directly from roots, fruits, leaves or stems
of different plant species, as well as from spore traps. As more DNA sequences of pathogens
become available, this technique could be expanded to cover all the plant pathogens. A similar
approach was designed to monitor bacteria from the environmental samples. The utility of a
developed method to classify bacteria on the basis of their genomic fingerprint patterns was also
investigated. Such approaches bring us closer to the kind of comprehensive pathogen / insect
testing that could lead to new practical applications in integrated disease / pest management.
The pathogens for which identification protocols have been developed are listed in Tables 2-4.
PCR-based / reverse dot-blot protocols for identification of insects and nematodes species in the
process of development are listed in Table 5.
PCR-based protocols should be developed for all the remaining pathogen, insect and nematode
species (to be incorporated in microchip technology in the future). the development of host-based
reverse dot-blot systems should also be an immediate priority, and should not be limited to the
so-called important diseases and pests (today's framework). Instead it should be extended to
include all pathogens, insects and nematodes - those already present in South Africa, as well as
those threatening the local pome, stone and table grape industries.
Table 1. Deciduous and non-deciduous fruit cultivars / rootstocks for which unique DNA
fingerprints have been generated
Apple
Braebrite
Fiesta
Fuji
Golden Delicious
Golden Del. Emla
Granny Smith
Oregon Spur
Panorama Golden
Royal Gala
Smoothee
Starking
M7
M9
M25
MM106
MM109
MM111
MI793
Pistachio
Ariyeh
Pontikus
Shuffra
Sirora
UCB
Integgerima
Other
Philodendron (Xanadu)
Pear
Beurre Bosc
Beurre Hardy
Bon Chretien
Bon Rouge
Clapp’s Favourite
Comice
Conference
December
Eldorado
Forelle
General Leclerc
Josephine
Onward
Packham’s Triumph
Rosemarie
Starkrimson
Winter Nelis
BP1
BP3
Strawberry
Tioga
Tiobelle
Selekta
Mara des Bois
Persimmon
Matsumoto Wase
Fuyu
Ichikikeu Jiro
Peach
Black
Bokkeveld
Bonnigold
Catherine
Classic
Culemborg
Desert Pearl
Don Elite
Elberta
Excellence
Goudmyn
Kakamas
Keimoes
Keisie
Malherbe
Neethling
Novadonna
Oom Sarel
Oribi
Orion
Rhodes
Sandvliet
San Pedro
Snow White
Summer Giant
Suncrest
Sunsweet
Transvalia
Walgant
Western Cling
Plum
Casselman
Celebration
Eldorado
Gaviota
Golden King
Harry Pickstone
Kelsey
Laetitia
Larry Anne
Methley
Red Beaut
Redgold
Reubennel
Santa Rosa
Sapphire
Simka
Songold
Sun Breeze
Suplum Six
Wickson
Marianna
Maridon
Nectarine
Alpine
Armking
August Glo
August Red
Crimson Giant
Donnarine
Fantasia
Fiesta Red
Flamekist
Flavour Top
Margret’s Pride
Mayglo
Nectar
Nectared
Olympia
Red Jewel
September Red
Sunlite
Unico
Zaigina
Zeeglo
Table grape
Barlinka
Bonheur
La Rochelle
Sonita
Eclipse
Redglobe
Flame Seedless
Lady Anne
Sunred
Regent
Sundance
Muscat Seedless
Sultana H3
Waltham Cross
Majestic
Dauphine
White Gem
Apricot
Bebeco
Bulide
Grandir
Ladisun
Malan Royal
Palsteyn
Olive
Agoromanakolea
Coratina
Haas
Hojiblanco
Kalamata
Manzanilla
Mission
Wine grape
Bukettraube
Chenin Blanc
Pearl of Csaba
Alphonse Lavallée
Chardonnay
Cinsaut Noir
Cape Riesling
Gewürztraminer
Malbec
Merlot
Queen
Woltemade
Piet Cillie
Oblonga
Tinta Barocca
Table 2. Stem canker and root rot fungi for which PCR-based / reverse dot-blot identification
protocols have been developed
Fungal Pathogen
Identification method
Funding
Pome and stone fruit
Botryosphaeria dothidia
PCR-based
ARC / UP / DFPT
Botryosphaeria obtusa
PCR-based
ARC / UP / DFPT
Fusicoccum luteum
PCR-based
ARC / UP / DFPT
Leucostoma cincta
PCR-based
ARC / DFPT
Leucostoma persoonii
PCR-based
ARC / DFPT
Diaporthe ambigua
PCR-based
ARC / DFPT
Nectria galligena
PCR-based
ARC / DFPT
Table grapes
Phytophthora cinnamomi
Reverse dot-blot
ARC / Winetech
Phomopsis viticola
PCR-based
US / Winetech
Various other fungal species
Reverse dot-blot (to be completed) ARC / Winetech
Table 3. Plant associated bacteria for which Rep-PCR genomic fingerprinting or other identification
protocols have been developed
Bacterial Pathogen
Marker system
Product
Funding
Pome and stone fruit
Xanthomonas
arboricola pv pruni
- bacterial spot
Fingerprint
ERIC
ARC
REP
ARC
BOX
ARC
PCR band
SCAR
ARC
Pseudomonas
syringae pv syringae /
pv morsprunorum
- bacterial canker
PCR band
SCAR
ARC / US
Table grapes
Xylophilus ampelinus
- bacterial blight
PCR band
SCAR (ITS)
ARC / DFPT
Table 4. Plant viruses for which PCR-based / other identification protocols have been developed
Viral Pathogen
Identification method
Funding
Pome and stone fruit
Apple stem grooving virus
(ASGV)
PCR-based
ARC / SAPO
Apple chlorotic leafspot virus
ACLSV
PCR-based
ARC / SAPO
Table grapes
Grapevine leafroll associated
virus - type 7 (GLRaV-7)
Immuno-electron microscopy
ARC / Winetech
Grapevine leafroll associated
virus - type 6 (GLRaV-6)
Immuno-electron microscopy
ARC / Winetech
Grapevine leafroll associated
virus - type 5 (GLRaV-5)
Immuno-electron microscopy
ARC / Winetech
Grapevine leafroll associated
virus - type 4 (GLRaV-4)
Immuno-electron microscopy
ARC / Winetech
Grapevine leafroll associated
virus - type 3 (GLRaV-3)
ELISA
ARC / Winetech
Immuno-electron microscopy
ARC / Winetech
PCR-based
ARC / Winetech
Grapevine leafroll associated
virus - type 2 (GLRaV-2)
ELISA
ARC / Winetech
Immuno-electron microscopy
ARC / Winetech
Grapevine leafroll associated
virus - type 1 (GLRaV-1)
ELISA
ARC / Winetech
Immuno-electron microscopy
ARC / Winetech
Grapevine virus A (GVA)
Immuno-electron microscopy
ARC / Winetech
PCR-based (to be completed)
ARC / Winetech
Grapevine virus B (GVB)
PCR-based (to be completed)
ARC / Winetech
Grapevine fleck virus
Immuno-electron microscopy
ARC / Winetech
Grapevine fanleaf virus
(GFLV)
ELISA
Dept. of Agriculture / SAPO
Table 5. Insects and nematodes for which PCR-based / reverse dot-blot identification protocols are
in the process of development
Insects / Nematodes
Identification method
Funding
Ceratitis capitata / Ceratitis
rosa / Ceratitis cosyra fruit fly species
Reverse dot-blot
ARC (terminated)
Woolly Apple Aphid
PCR-based
US / Winetech
Nematode species (various)
Reverse dot-blot
ARC / Winetech