Improving Disease Resistance of Maize in the Developing World

Improving disease resistance of maize in the developing world: challenges and opportunities

Santiago Mideros17 February 2011CIMMYT

WFP/Elmer Martinez

OutlineChallenges and Opportunities

◦General

◦Specific Aflatoxins

AFB1

OpportunitiesAg. development is back

Science & Technology◦Genetics, genomics, plant immunity◦Precise phenotype, barcoding, databases

CIMMYT◦Germplasm◦World network◦Mandate

ChallengesClimate Change

◦Food security◦Maize pathology

New or emerging pathogens/races◦Movement of germplasm◦Change on cultural practices

Food quality, health concerns, mycotoxins

Science ImpactPolicy

Climate Change

Uncertainty in predictions

Lack of historical dataFusarium species and

DON

Battisti and Naylor 2009

New and (re)emerging pathogens or racesGray Leaf Spot

◦ Cercospora zeina◦ Cercospora zeae-maydis

Maize fine streak virusMaize streak

(gemini)virusPhaeosphaeria leaf spot

Maize streak virus Shepherd et al (2010)

Policy

Investment on science in developing countries

Aid and technology from developed countries◦ Budgetary concerns

OpportunitiesAg. development is back

Science & Technology◦Genetics, genomics, plant immunity◦Precise phenotype, barcoding, databases

CIMMYT◦Germplasm◦World network◦Mandate

OpportunitiesAg. development is back

Science & Technology◦Genetics, genomics, plant immunity◦Precise phenotype, barcoding, databases

CIMMYT◦Germplasm◦World network◦Mandate

ScienceAssociation Mapping Yan et al, 2011

◦Northern Leaf Blight, ◦Southern Leaf Blight, ◦Gray Leaf SpotWisser, Kolkman, Benson, Nelson, Balint-Kurti (in review)

Glutatione S-transferase

Nested Association MappingSouthern leaf blight (Kump et al, 2011)

32 QTL51 SNP: Receptor like kinases, Glutathione S-

transferase

Northern leaf blight (Poland et al, in review)

21 QTL60 SNP:

◦ Receptor like kinases ◦ Ethylene response factor ◦ Mlo-like

Quantitative disease resistance PTI (Basal Resistance)

Gray leaf spot (Benson et al, in preparation)

12 QTL21 SNP

Science (cont.)Mutant-Assisted Gene Identification and

Characterization (MAGIC)

• Fine mapping genes responsible for resistance in maize

Nature Biotechnology Volume: 28, Pages: 365–369 Year published: (2010) DOI: doi:10.1038/nbt.1613

Technology

OthersCommunication (Internet)

◦Developing partnerships◦Collaboration◦Capacity building

Genomic selectionGenotyping by sequencing

◦Next generation sequencing

OpportunitiesAg. development is back

Science & Technology◦Genetics, genomics, plant immunity◦Precise phenotype, barcoding, databases

CIMMYT◦Germplasm◦World network◦Mandate

Germplasm

Photo by Suketoshi Taba, Yan et al 2011

Multiple Locations

Partners

National agricultural research institutes

Other international organizations

Universities in developing countries

Universities in developed countries

Private companiesNGOs

Sustainable Disease Management

Disease resistanceNo silver bullets

◦Deployment: Pyramids Refuge areas (Bt)

Resistance + management

Multiple disease resistance

Effect of a single QTL. Chung et al, 2010

OutlineChallenges and Opportunities

◦General

◦Specific Aflatoxins

AFB1

Challenges and OpportunitiesA practical example

Challenge:Mycotoxin contamination

Opportunities:Technology and geneticsFood systems

Mycotoxins

AflatoxinsA. flavus and A. parasiticus

aflatoxinsPotent hepatocarcinogenAcute: death; liver damageChronic:

◦ Immune suppression, growth impairment

◦ Hepatocellular carcinomaFinancial burden

AFB1

Other Ear RotsGibberella Ear RotFusarium graminearumDeoxynivalenol = DON = Vomitoxin

Fusarium Ear RotFusarium verticillioidesFumonisin

Photo: A. Robertson

Aflatoxin child stunting

Regulation & Exposure

1ppb = 1 ng per g or 1mg per metric ton

Country Consumption

(g/p/day)

Max. aflatoxin

(ppb)

Exposure(ng/bw/

day)

Western Europe

33 4 0.3 – 1.3

USA 86 20 0.26

Southern Europe

148 4 0 - 4

Kenya 248 20* 3.4 - 133

Mexico 300 20 14 - 85

Sources:Liu, Y. and Wu, F. 2010. EHP. 118: 818-824

Reddy et al. 2010. Toxin Reviews. 29: 3-26

2010 aflatoxin outbreak, Eastern Province, Kenya

Survey in western Kenya 09

Source of maize N % >10 ppb

% >20 ppb

Gifts from friends or relatives

30 27 7

Purchased 349

11 2

Own-grown 183

5 2

Food aid 7 14 0Total 56

914 3

S. Mutiga; V. Hoffman; and R.J. Nelson unpb

Strategy

Components of resistanceTissue specificComponents of

resistance◦ Latent period (LP)◦ Sporulation

intensity (SP)◦ Infection

frequency (IF)Colonization

◦ qPCR

CML69 Sc212m

Mp339 Tx303

Picture: K. Loeffler

qPCR Development

A. flavus Primers:◦Internal Transcribed Spacer 1 (ITS1),

5.8S rDNA, and ITS2◦Genbank

A. flavus, A. oryzae, A. parasiticus, A. sojae, A. tamarii, Emericella nidulans

A. flavus biomass in maize is strongly correlated with aflatoxin concentration

0

1

2

3

4

Infe

ctio

n

Coe

ffici

ent (

log

IC)

2 3 4 5 6 7 8

Aflatoxin (log ng/g)

Correlation between infection coefficient (IC) and aflatoxin = 0.85 **

Pedigree/Line IC ng/gCML103 0.78 a 1.18 10.03 a 22735Mo17 0.62 ab 0.85 9.39 ab 11982B73 0.51 abc 0.67 9.54 ab 13917B97 0.33 bcd 0.39 9.22 abc 10118MS71 0.28 bcd 0.33 8.21 abcde 3689Oh43 0.27 bcd 0.31 7.84 bcde 2542Oh7B 0.21 cd 0.23 8.16 abcde 3483IBM54 0.11 d 0.12 7.93 bcde 2790NC358 0.11 d 0.11 6.75 defg 854IBM262 0.09 d 0.10 8.75 abcd 6283Ky21 0.08 d 0.08 6.96 defg 1056Tx303 0.06 d 0.06 7.20 cdef 1333Ki3 0.05 d 0.06 7.46 bcde 1739Mp339 0.05 d 0.05 6.79 defg 886M37W 0.02 d 0.02 6.43 efgh 622CML52 0.00 d 0.00 4.55 h 94Mp313E 0.00 d 0.00 4.84 gh 126CML247 0.00 d 0.00 5.15 fgh 172

A. flavus Aflatoxinlog (IC+1) log (ng/g+1)

Mideros et al 2009 Plant Disease 93: 1163

ExperimentsNew York Mississippi

Components of resistance for diverse inbreds: 3 years of studies (P-values)

Component of resistance

Maize Tissue

SilkDeveloping

KernelMature Kernel

In-vitro

Latent Period0.062

4 nsInfection Frequency

0.0018 ns

Sporulation0.006

7 0.0963Colonization (qPCR) - 0.2097

FieldColonization (qPCR)

0.0312 - 0.0301

Aflatoxin - - 0.0006While

significant, not correlated with

aflatoxin

Kernel resistance correlations

Field In-vitro Flint-Garcia's traits

Colonization (qPCR)

Colonizatio

n (qPCR

)

Sporulation Mois

tureProtein Fat Fiber Ash

Carbhdrt

sd wgh

t

%endspr

m

Field Aflatoxin 0.70*** 0.02 0.06 -0.03 -0.45 -0.25 -0.68** -0.57* 0.52* 0.57* 0.12

Colonization -0.16 -0.01 -0.02 -0.21 -0.17 -0.47 -0.50 0.27 0.46 0.09

In-vitro Colonization 0.00 0.33 -0.38 0.03 -0.07 0.03 0.23 0.14 -0.05

Sporulation -0.53* 0.39 0.27 0.03 0.26 -0.38 -0.41 0.15

Strategy

Model selection QTL mapping (B73 x CML322)

Sporulation SPLatent Period LPInfection Freq IF

Trait Year Marker Position source

DvK Sporulation 2007 m758 6.07 1.8E-03 B73

DvK Sporulation 2008 m758 6.07 3.7E-05 * B73

DvK Sporulation 2008 m838 7.06 7.8E-05 * B73

DvK Sporulation 2008 m209 2.03 1.0E-04 * CML322

Aflatoxin, MS 2008 m500 4.08 4.4E-06 ** CML322

Aflatoxin, MS 2008 m746 6.06 7.0E-05 * CML322

Aflatoxin, MS 2008 m35 1.03 2.2E-04 * CML322

Silk LP, NY 2008 m316 3.04 2.1E-10 ** CML322

Silk LP, NY 2008 m421 3.09 7.1E-10 ** B73

Silk LP, NY 2008 m540 4.10 2.6E-08 ** CML322

Silk LP, NY 2008 m154 1.11 2.7E-07 ** CML322

Silk LP, NY 2008 m706 6.03 1.0E-06 ** B73

Silk LP, NY 2008 m849 8.01 2.6E-06 ** B73

Silk LP, NY 2008 m168 1.11 1.3E-04 * B73

Silk LP, NY 2008 m857 8.03 1.6E-04 * CML322

Silk SP, NY 2008 m911 8.06 2.1E-08 ** CML322

Silk SP, NY 2008 m766 7.01 3.7E-08 ** B73

Silk SP, NY 2008 m428 3.09 1.0E-06 ** CML322

Silk SP, NY 2008 m763 7.01 4.9E-04 * CML322

Silk IC, MS 2008 m774 7.02 4.4E-05 ** B73

Silk IC, MS 2008 m775 7.02 5.0E-06 ** CML322

Aflatoxin, MS 2009 m821 7.04 1.0E-07 ** B73Aflatoxin, MS 2009 m1096 10.07 1.0E-07 ** CML322Aflatoxin, MS 2009 m216 2.03 9.3E-05 * CML322Aflatoxin, MS 2009 m746 6.06 2.7E-03 CML322

p-value

25 QTL

QTL studiesPlant

DiseaseGermplas

mSource

Aspergillus Ear Rot

Mp313E x Va35

Wilcox et al. (unpublished)

Mp313E x B73 Brooks et al. 2005

Mp717 x Nc300

Warburton et al. 2009

Mp715 x T173 Warburton et al. 2010

CML322 x B73 Mideros et al. (unpublished)

Gibberella Ear Rot

CO387 x CG62 Ali et al. 2005

Fusarium Ear Rot 3 x 18 Perez-Brito et al. 2001

5 x 18 Perez-Brito et al. 2001

87-1 x Zone3 Ding et al. 2008

GE440 x FR1064

Robertson-Hoyt et al. 2006

NC300 x B104 Robertson-Hoyt et al. 2006

9.029.03

9.04

9.06

9.07

9.08

9

9.01

bnlg1209

9.05

umc1191umc1033

phi027

umc2121

umc1789

bnlg128

umc1277

umc1654

bnlg1191

umc1688

umc1867umc1291

10.00

bnlg1451

10.01

bnlg640

10.02

umc124610.03

umc1053umc1506

10.04

umc1477

10.05

umc1084

10.07

bnlg1450

10.08bnlg1185

10

umc1898

phi062

10.06 umc1061

5.00

5.02

5.04

5.03

5.01

5.09

5

5.06

bnlg1046

umc1761

mmc0081

umc2019mmc0481

bnlg1306

umc1153

bnlg603

5.05

5.07

5.08 umc2136bnlg2291

umc1667

umc10084.00

umc16824.01

nc004

4.03

nc005

bnlg1137

4.05

bnlg2162

4.06

umc1051

4.07

umc1173

4.08

umc1631

umc2011

4

umc17574.02

4.04

sts001

bnlg1126

4.09

4.10

2.06

2.07

2.08

2.00

2.01

2.03

2.04

2

umc1065

umc1079

phi109642

umc11852.02

umc1783

umc1637

umc1526

2.05

bnlg371

bnlg371

umc12921.00

umc17271.01

umc1166bnlg14291.02umc1070

phi001

1.03

umc1590bnlg1057

1.06

umc1035

1

umc1065

umc2047

1.09

umc14211.11

umc1630

umc11181.12

bnlg1596

bnlg400

1.07

1.08

1.10

bnlg15981.04

1.05

umc2170

bnlg1759

phi0756.00 bnlg238

6.01

umc1006

6.03

umc10146.04

bnlg1702

6.05

6

bnlg1165

6.02

umc1463

6.06

umc1248

6.07

phi0896.08umc2059

6.09 umc1127

bnlg1154

umc1498

umc1632

umc21053.00umc1746

3.02

umc1970

3.03 bnlg1144

3.04

bnlg1325

3.05

phi036

3.06

phi029

3.07

bnlg1063

3.08

bnlg1350

3.09

bnlg197

3.10

bnlg1182

3

umc1361

umc2048

umc1062

umc1642

3.01

umc1066

7.00

bnlg1200

7.01

bnlg1070

7.02

umc10017.04

umc1029

7

phi2604857.05

umc1407

phi1167.06umc1799

umc2222

umc1978

phi1147.03

umc11398.00

bnlg1194

8.01

bnlg1352

8.02

bnlg1863

8.03

bnlg666

8.04

umc11498.05

bnlg240

dupssr148.09

8

bnlg1828

8.07

bnlg1350

umc19978.06

8.08

Mp313EaMp313EbMp717Mp715Oh516Tex6B73CML322

Collaboration with M. Warburton

QTL Meta-analysis

Consensus Genetic Map

Projection of QTL and CI

Position of metaQTL

Veyrieras et al. 2007 BMC Bioinformatics 8Truntzler et al. 2010 TAG 114

Consensus Genetic Map

Consensus

Mp313E x B73

Genetic 2008B73 x

CML322

QTL Meta-analysis

Consensus Genetic Map

Projection of QTL and CI

Position of metaQTL

Goffinet et al. 2000 Genetics 155Veyrieras et al. 2007 BMC Bioinformatics 8Truntzler et al. 2010 TAG 114

1 2 43 5

6 10

97 8Aspergillus Ear Rot

AflatoxinFusarium Ear Rot

FumonisinEar rot (w)Ear rot

Gibberella Ear RotSilk disease severityKernel disease severity

QTL Meta-analysisConsensus Genetic Map

Projection of QTL and CI

Position of metaQTL

Goffinet et al. 2000 Genetics 155Veyrieras et al. 2007 BMC Bioinformatics 8Truntzler et al. 2010 TAG 114

1.012.5 Mb

1.0623.2 Mb

Sustainable Disease Management

Disease resistanceResistance +

managementEffect of a single QTL Chung et al, 2010Pre-

harvest resistance

Drought tolerance

Better varieties

Yield

Field managem

ent

Biological control

Post-harvest

management

•Resistance•Storage•Testing•Detoxification

Lower aflatoxi

ns

Acknowledgments Rebecca Nelson Tiffany Jamann Paola Zuluaga Margaret Smith Jaci Benson Bill Holdsworth Jose Luis Zambrano

R. Nelson Labo Chia-Lin Chungo Jesse Polando Samuel Mutigao Judy Kolkmano Wenzhe Lio Chris Mancusoo Nelson Chepkwonyo Ariel Fialkoo Oliver Otto Sara Heinzo Lin-Si Hsieho Kristen Kennedy o Kerri Lyons o Joy Longfellowo Ellie Walsh

Marilyn Warburton Gary Windham Paul Williams

o Gregory Flinto Ladonna Owenso Mike Alpeo Victoria Scott