helping farmers to grow healthier crops: use of qpcr to monitor plant resistance to fungal pathogens...

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 [email protected]

Blanca B. Landa del [email protected]

Agencia Estatal Consejo Superior de Investigaciones CientíficasAgencia Estatal Consejo Superior de Investigaciones Científicas

Instituto de Agricutura SostenibleCórdoba, EspañaInstituto de Agricutura SostenibleCórdoba, España

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

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 nutrientslimiting factors nitrogen

phosphorus

PRO

DU

CTIO

N S

ITU

ATIO

N

yield-protecting measures

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%)


Barley, coffee, cotton, maize, potato, rice, soybean, and wheat 1967-2006

Weeds (9%)

Insect pests (10%)

Diseases (13%)


Weeds (13%)

Insect pests (16%)

Diseases (13%)


1996-1998 (Oerke & Dehne, 2004) 2001-2003 (Oerke 2006)

RegionCrop loss (%)

a Efficacy = (Potential loss – Actual loss) / Potential loss x 100b Africa, Asia, Eastern Europe, South America, USSRc Total = Diseases, insect pests, weeds

Stress Potential RealWestern Europe Diseases 18.7

Total C 57.4

North America and Oceania

Diseases 13.0Total 56.2

Rest of the World b

Diseases 18.2Total 72.6

7.322.6

9.931.6

14.344.4

Efficacy of control(%) a

6161

2444

2139

Source : Oerke et al., 1994

Estimated efficacy of disease control measures

1. Importance of crop diseasesDeleterious 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)

Integrated ControlIntegrated Control

Disease control measures of CropsDisease control measures of CropsModification

of cultural practices

Use of resistantcultivars

Avoid soils withinoculum of the

pathogens

Use of certifiedseeds/material(pathogen-free)

Application of pesticides when

available

Application of microbial

antagonists

2. Disease control measuresLimitations 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

2. Disease control measuresLimitations 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

Downy Mildew of Opium PoppyTarget 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 importantdisease of P. somniferum causing substantial crop losses world-wide

In Spain during the last decade has become the main yield-limiting factorand epidemics occur throughout all opium poppy–growing areas

Even the new areas were the crops were not previously planted!

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


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?

Efficacy in detecting the pathogen in seed lots & asymptomatic infections?

Use of qPCR to study Downy mildew of P. somniferumWe 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

Relativ

eflu

orescenseun

its

‐d(RFU

)/dt

10 fg10 fg

10 fg 10 fg

10 fg 1 pg 1 pg10 pg

10 fg

10 fg

pg/ul10001001010.10.010.001


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. som

niferi/

DNA Pa

v. som

niferum

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

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. som

niferi/

DNA Pa

v. som

niferum

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 guaranteethe phytosanitary status of seed lots

Symptoms on capsule versus infection?

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

Verticillium wilt of OlivesTarget 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: Intensificationand irrigation

New control methods are needed

Use of qPCR to study Verticillium wilt of OlivesGeographic 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

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

Characteristics of Verticillium wilt that confer difficulty to its management

Long survival in soilMicrosclerotia



Confinement of pathogen growth within the xylem (conidia)



Commercial varietiesSusceptible-TolerantCommercial varietiesSusceptible-TolerantCommercial varietiesSusceptible-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 fungicideavailable

No fungicideavailable

High pathogenicvariability

High pathogenicvariability


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


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 preventthe 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

Use of qPCR to study Verticillium wilt of Olives1) Comparison of real-time protocols for the quantification of V. dahliae

8 real-time PCR protocols (TaqMan, Scorpion, Sybergreen) compared using a backgroundof 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 afterinoculation


Gramaje et al. 2013 Phytopathology 103:1058-1068

Some protocols showed low specificity & cross-amplified Verticillium spp.


Infection of the roots system by Dand ND pathotypes took place soonafter inoculation

The total amount of positiveisolations estimated by the AUICwas significantly higher in stems androots inoculated with D V. dahliaepathotypeGramaje et al. 2013 Phytopathology 103:1058-1068

In the time-course infection bioassay No or slight wilt symptom expression wasobserved in resistant Frantoio plants



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


Jiménez-Díaz et al. (submitted) Plant Pathology

The qPCR protocols was useful for selecting wild olives with resitant ortolerant 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


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.

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

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

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