The document discusses the use of quantitative PCR (qPCR) as a tool to monitor plant resistance to fungal pathogens, specifically focusing on downy mildew of opium poppy and verticillium wilt of olives. It highlights the significance of crop diseases, various disease control measures, and the advantages of qPCR in quickly detecting pathogen presence and quantifying infection levels in plants and seed lots. Furthermore, it emphasizes the importance of developing resistant varieties and employing robust protocols to ensure the quality of agricultural products.

1. Helping Farmers to Grow Healthier Crops:
Use of qPCR to Monitor Plant Resistance to Fungal
Pathogens and Select Healthy Seed Lots
Helping Farmers to Grow Healthier Crops:
Use of qPCR to Monitor Plant Resistance to Fungal
Pathogens and Select Healthy Seed Lots
Blanca B. Landa del Castillo
blanca.landa@csic.es
Blanca B. Landa del Castillo
blanca.landa@csic.es
Agencia Estatal Consejo Superior de
Investigaciones Científicas
Agencia Estatal Consejo Superior de
Investigaciones Científicas
Instituto de Agricutura Sostenible
Córdoba, España
Instituto de Agricutura Sostenible
Córdoba, España

2. Helping Farmers to Grow Healthier Crops:
Use of qPCR to Monitor Plant Resistance to
Fungal Pathogens and Select Healthy Seed Lots
1. Importance of crop diseases
2. Disease control measures
3. Use of qPCR in selected pathosystems:
• Downy mildew of opium poppy
• Verticillium wilt of olives

3. The relationships among potential, attainable and actual yields
and growth -defining, -limiting and -reducing factors
PRODUCTION LEVEL (kg ha-1)Adapted from Rabbinge, 1993
 diseases
 pests
 weeds
 pollutants
reducing factorsActual
yield-increasing
measures
 CO2
 radiation
 temperature
 crop features
defining factorsPotential
Attainable
 water
 nutrients
limiting factors nitrogen
phosphorus
PRODUCTIONSITUATION
yield-protecting measures

4. Weeds (10%)
Insect pests (11%)
Diseases (12%)
Attained harvest (67%)
Source: Cramer, 1967
1967 (Cramer, 1963) 1988-1990 (Oerke et al., 1994)
Estimated crop losses due to plant diseases
Weeds (13%)
Insect pests (16%)
Diseases (13%)
Attained harvest (58%)
Barley, coffee, cotton, maize, potato, rice, soybean, and wheat 1967-2006
Weeds (9%)
Insect pests (10%)
Diseases (13%)
Attained harvest (68%)
Weeds (13%)
Insect pests (16%)
Diseases (13%)
Attained harvest (58%)
1996-1998 (Oerke & Dehne, 2004) 2001-2003 (Oerke 2006)

5. Region
Crop loss (%)
a Efficacy = (Potential loss – Actual loss) / Potential loss x 100
b Africa, Asia, Eastern Europe, South America, USSR
c Total = Diseases, insect pests, weeds
Stress Potential Real
Western Europe Diseases 18.7
Total C 57.4
North America
and Oceania
Diseases 13.0
Total 56.2
Rest of the
World b
Diseases 18.2
Total 72.6
7.3
22.6
9.9
31.6
14.3
44.4
Efficacy of
control
(%) a
61
61
24
44
21
39
Source : Oerke et al., 1994
Estimated efficacy of disease control measures

6. 1. Importance of crop diseases
Deleterious effects of diseases on crops
 Final plant density established in the field
 Absorption and translocation of water and nutrients
 Absorption of light radiation
 Photosynthesis and assimilate redistribution rate
Reduction of :
There is a need to find or implement new
disease management practices!
 Quality of food (appearance, mycotoxins)

7. Helping Farmers to Grow Healthier Crops:
Use of qPCR to Monitor Plant Resistance to
Fungal Pathogens and Select Healthy Seed Lots
1. Importance of crop diseases
2. Disease control measures
3. Use of qPCR in selected pathosystems:
• Downy mildew of opium poppy
• Verticillium wilt of olives

8. Integrated ControlIntegrated Control
Disease control measures of CropsDisease control measures of Crops
Modification
of cultural
practices
Use of resistant
cultivars
Avoid soils with
inoculum of the
pathogens
Use of certified
seeds/material
(pathogen-free)
Application of
pesticides when
available
Application of
microbial
antagonists

9. 2. Disease control measures
Limitations for the use of resistant cultivars:
 Traditional resistance screening (pathogenicity tests) are very laborious in time
and resources: Needed new high-throughput fast and reliable methods

10. 2. Disease control measures
Limitations for the use of resistant cultivars:
Advances in biotechnology and molecular biology (qPCR or dPCR)
may help to solve those conditioning factors and contribute to a
more efficient use of those control measures
Limitations for the use of healthy seed stocks:
 Environmental conditions may modify the disease response of the plant
(Symptoms appearance): Importance of detecting asymptomatic infections
 Conditioned by the diversity of the pathogen population (races & pathotypes) or
the development of new virulent strains of the pathogen: Need to be adaptable
 Traditional resistance screening (pathogenicity tests) are very laborious in time
and resources: Needed new high-throughput fast and reliable methods
 Pathogens that are obligate biotrophs or are present at very low concentrations
 Sources of resistance are scarce and complete resistance may be not available to
all races/pathotypes: Use of tolerant varieties

11. Helping Farmers to Grow Healthier Crops:
Use of qPCR to Monitor Plant Resistance to
Fungal Pathogens and Select Healthy Seed Lots
1. Importance of crop diseases
2. Disease control measures
3. Use of qPCR in selected pathosystems:
• Downy mildew of opium poppy
• Verticillium wilt of olives

12. Downy Mildew of Opium Poppy
Target pathogen:
Peronospora somniferi
(formerly P. arborescens)
 Papaver somniferum is the only source of pharmaceutical codeine,
morphine, and thebaine, key drugs for alleviation of chronic pain
 Downy mildew caused by Peronospora spp. is one of the most important
disease of P. somniferum causing substantial crop losses world-wide
 In Spain during the last decade has become the main yield-limiting factor
and epidemics occur throughout all opium poppy–growing areas
Even the new areas were the crops were not previously planted!

13. Use of qPCR to study Downy mildew of P. somniferum
Disease symptoms:
Chlorosis Dwarfing Necrosis and death Damage to capsule and peduncule
Obligate biothroph
Thousands of
sporangia
Easy disemination
Long lasting oospores
Landa et al. 2007 Phytopathology; Montes-Borrego et al. 2009 Phytopathology & Plant Pathology; Montes-Borrego et al. 2011 Plant disease

14. Use of qPCR to study Downy mildew of P. somniferum
 Avoid monoculture (oospores
kept in plant debris and soil)
 Use of pathogen-free seed
lots (obligate biothroph)
 Develop resistant varieties
Early, specific, sensitive and
accurate in planta detection
and quantification of
Peronospora somniferi
Early, specific, sensitive and
accurate in planta detection
and quantification of
Peronospora somniferi
Objective: To develop a robust & highly sensitive qPCR protocol that can
guarantee the quality of seed lots & screening of germplasm resitance
Focus on disease management:
SEEDS?
Plant debris?

15. Efficacy in detecting the pathogen in seed lots & asymptomatic infections?
Use of qPCR to study Downy mildew of P. somniferum
 We developed a reliable, quick, and accurate qPCR assay
based on the MIQE guidelines (ITS rDNA region)
 The protocol was highly reproducible (different
technicians, labs, equipment, plant material, etc.)
 Allowed accurate quantification of pathogen DNA up to
10 fg in different plant DNA backgrounds without losing
specificity and efficiency (D.Lim. similar to nested-PCR)
ITS1 ITS25.8S
P3 (594 bp)
P6 (456 bp)
Consensus sequence (≈ 730 bp)
0
300
600
70 72 74 76 78 80 82 84 86 88 90 92 94
-400
0
400
800
200
600
2000
2400
2800
3200
0 10 20 30
Temperature (ºC)Cycle number
Relativefluorescenseunits
‐d(RFU)/dt
10 fg10 fg
10 fg 10 fg
10 fg 1 pg 1 pg10 pg
10 fg
10 fg
pg/ul
1000
100
10
1
0.1
0.01
0.001

16. Use of qPCR to study Downy mildew of P. somniferum
0.0
0.5
1.0
1.5
2.0
0.00
0.05
0.10
0.15
0.00
0.05
0.10
0.15
Simple-PCR: (-)
Nested-PCR: (±)
Simple-PCR: (±)
Nested-PCR: (+)
Simple-PCR: (+)
Nested-PCR: (+)
7522-1 7522-2 7522-3 919-1 927-1 927-2 927-3 931-2 919-3 9147-2 9151-3 923-1 916-3 916-1 922-3 922-1 9151-1 9151-2 9149-3 919-2 922-2 9147-1 925-2 925-1 9147-3 916-2 931-3 923-1 923-2 923-3 925-3 9149-1 9149-2

‰ DNA P. somniferi/
DNA Pav. somniferum
 Use of the real-time qPCR protocol allowed detecting P. somniferi DNA in
100% of commercial seed stocks and 97.0% of seed samples analyzed: It
confirmed the hypothesis of being the main cause of pathogen spread
 Allowed to quantify as low as 1.2 pg of patogen DNA per µg of seed DNA
 The quantity of P. somniferi DNA vas very variabe (ranged from 0.4 ppm
to 1275 ppm) in commercial seed lot samples that produced, respectively,
null, weak, or positive amplifications in simple-PCR assays, and a weak,
positive, or positive amplification, respectively, in nested-PCR assays.
 In highly infested seed stocks (#923), P. somniferi comprised as much as
1275 ppm in plant DNA: ~ 0.256 mg of pathogen DNA/kilogram of seed
0.13 to 74 ppm 0.4 to 91 ppm 50 to 1275 ppm

17. 10
-4
10
-3
10
-2
10
-1
10
0
10
1
10
2
01234
Use of qPCR to study Downy mildew of P. somniferum
‰ DNA P. somniferi/
DNA Pav. somniferum
 Real-time qPCR assays of seeds harvested from 30
individual poppy capsules from the field (11 were
asymptomatic, 6 affected with mild DM symptoms, and
13 had evident pathogen sporulation):
 70.0% (21/30) of all samples assayed
 36.4% (4/11) of asymptomatic capsules
 In those seeds the pathogen DNA concentration was:
 0.3 to 7 ppm in asymptomatic capsules
 6 to 61 ppm in capsules with mild symptoms
 12 to 253 ppm in highly infested capsules
Severity of symptoms+ ‐
The qPCR protocol developed is a cost-viable
technology that allow to verify seed lot
infection yearly to producers and guarantee
the phytosanitary status of seed lots
Symptoms on capsule versus infection?

18. Use of qPCR to study Downy mildew of P. somniferum
 Use of the real-time qPCR protocol allowed detection of P. somniferi DNA in 68.2%
of stem samples from asymptomatic opium poppy plants of a ‘resistant’ variety
 Amount of P. somniferi DNA in DNA samples extracted from stems of asymptomatic
plants was highly variable, ranging from 0.110 ppm to 5,557 ppm (5.6‰) of P.
somniferi target DNA/ng of Papaver somniferum DNA
 The protocoll allowed to demonstrate that some potential resistant plants were
systemically infected: Consequently show tolerance to the pathogen not resistance
 The capsules formed in those plants harbor infested/infected seeds!!
This qPCR protocol is currently being used in breeding programs to DM
Suceptible Resistant

19. Verticillium wilt of Olives
Target pathogen:
Verticillium dahliae
 Currently considered the main soilborne fungal disease threatening olive
production worldwide
 Increasing concern in olive production due to the rapid spread and increased
severity associated with recent changes in cropping practices: Intensification
and irrigation
 New control methods are needed

20. Use of qPCR to study Verticillium wilt of Olives
Geographic distribution of Verticillium wilt of olives in the Mediterranean Basin
Italy
(1946)
California (1950)
Greece
(1963) Turkey
(1972) Syria
(1993)
France
(1975)
Spain
(1980)
Morocco
(1995)
Algeria
(1990)
Recently reported: Israel, Malta, Rhodes and Tunisia

21. Use of qPCR to study Verticillium wilt of Olives
Apoplexy (acute form)
 Late winter to early spring: Death of
twigs and branches, necrotic leaves
remain attached to affected branches
 Spring: necrosis & mummification of
inflorescences, leaf chlorosis and
necrosis, necrosis of twigs
Slow decline (chronic form)
Non-defoliating syndrome: Defoliating syndrome:
 Symptoms develop from late fall to early
winter
 Early drop of still-green, infected leaves
 Complete defoliation of branches
 Death of the tree (Highly virulent)
 Needs less inoculum to cause severe
disease as compared to non-defoliating

22. Characteristics of Verticillium wilt that confer difficulty to its management
Long survival in soil
Microsclerotia
Long survival in soil
Microsclerotia
Long survival in soil
Microsclerotia
Confinement of pathogen growth within the
xylem (conidia)
Confinement of pathogen growth within the
xylem (conidia)
Confinement of pathogen growth within the
xylem (conidia)
Commercial varieties
Susceptible-Tolerant
Commercial varieties
Susceptible-Tolerant
Commercial varieties
Susceptible-Tolerant
Several means of dispersal: leaves,
soil, irrigation water etc.
Several means of dispersal: leaves,
soil, irrigation water etc.
Broad host range
(cultivated and not)
Broad host range
(cultivated and not)
No fungicide
available
No fungicide
available
High pathogenic
variability
High pathogenic
variability
Use of qPCR to study Verticillium wilt of Olives

23. Main control measures focused on:
 Use of pathogen-free plant material
 Resistant/Tolerant varieties
 Resistant/Tolerant rootstocks
Main control measures focused on:
 Use of pathogen-free plant material
 Resistant/Tolerant varieties
 Resistant/Tolerant rootstocks
Use of qPCR to study Verticillium wilt of Olives
Early, specific, and
accurate in planta
detection and
quantification of
Verticillium dahliae
Early, specific, and
accurate in planta
detection and
quantification of
Verticillium dahliae
Help to prevent
the spread of
Verticillium wilt in
olive
Objective: To develop a robust & highly sensitive qPCR protocol that can
guarantee the quality of olive in nursery & screening of olive resitance

24. Use of qPCR to study Verticillium wilt of Olives
1) Comparison of real-time protocols for the quantification of V. dahliae
 8 real-time PCR protocols (TaqMan, Scorpion, Sybergreen) compared using a background
of DNAs extracted from olive roots, stems & leaves
 77 fungal isolates representing 9 Verticillium spp. (Inderbitzin et al. 2011 PLoS ONE)
 Score system: R2, AE, DL and total specificity
2) Olive-V. dahliae time-course infection bioassay with a resistant cultivar
• Inoculation of Frantoio olive with two V. dahliae isolates D pathotype and ND pathotype
• Assessment of symptom severity at 35 and 122 days after inoculation
• Isolation of V. dahliae from roots and stems of inoculated plants
Index of colonization (IC).
• In planta real-time PCR quantification of D and ND V. dahliae
0, 6, and 24 h and 2, 3, 7, 10,
15, 21, and 35 days after
inoculation

25. Use of qPCR to study Verticillium wilt of Olives
Gramaje et al. 2013 Phytopathology 103:1058-1068
 Some protocols showed low specificity & cross-amplified Verticillium spp.

26. Use of qPCR to study Verticillium wilt of Olives
Gramaje et al. 2013 Phytopathology 103:1058-1068

27. Use of qPCR to study Verticillium wilt of Olives
 Infection of the roots system by D
and ND pathotypes took place soon
after inoculation
 The total amount of positive
isolations estimated by the AUIC
was significantly higher in stems and
roots inoculated with D V. dahliae
pathotypeGramaje et al. 2013 Phytopathology 103:1058-1068
 In the time-course infection bioassay No or slight wilt symptom expression was
observed in resistant Frantoio plants

28. Use of qPCR to study Verticillium wilt of Olives
Gramaje et al. 2013 Phytopathology 103:1058-1068
 Presence of V. dahliae in upper tissues of symptomless plants
 The qPCR protocols was proven useful for certification schemes of pathogen-
free planting material and breeding programs for resistance screening to VW

29. Use of qPCR to study Verticillium wilt of Olives
Jiménez-Díaz et al. (submitted) Plant Pathology
 The qPCR protocols was useful for selecting wild olives with resitant or
tolerant reaction to VW
 Those wild olives are being tested as rootstocks for commercial varieties
Resistance of wild olives after inoculation with V. dahliae Defoliating pathotype
Check
OutVert
Inoculated
StopVert OutVert Picual
Inoculated

30. Use of qPCR to study Verticillium wilt of Olives
Jiménez-Díaz et al. (submitted) Plant Pathology
Reaction of ‘Picual’ olive grafted onto cv. ‘Frantoio’ or a resistant clon of acebuche
(wild olive) to double inoculation with defoliating V. dahliae
of wild olives after inoculation with V. dahliae Defoliating pathotype
Control Inoculado Control InoculatedInoculatedControlControl Inoculated
Picual/Acebuche (27%) Picual/Frantoio (87%) Picual selfrooted (100)
Incubated 4 months at 25ºC after root-dip inoculation with 107 conidia of V. dahliae.

31. Those qPCR protocols have allowed us to:
 Clearly differentiate susceptible from resistant plant
reactions to the pathogens
 Show differences in the degree of virulence between
pathotypes of the pathogen
 Quantify the pathogen in asymptomatic plant tissues
at early stages of the infection process
 Provide farmers with certify pathogen-free seed
stocks or plants for field sowings
The use of qPCR protocols can be of great value for
farmers, plant breeders and for epidemiological studies
in growth chambers, greenhouses and field-scale plots

32. ACKNOWLEDGEMENTSACKNOWLEDGEMENTS
AGR-136 Sanidad Vegetal
M. Montes-Borrego, D. Gramaje
J. A. Navas-Cortés, R.M. Jiménez-Díaz
AGR-136 Sanidad Vegetal
M. Montes-Borrego, D. Gramaje
J. A. Navas-Cortés, R.M. Jiménez-Díaz FUNDING & COLABORATORS