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Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
Improving Disease Resistance of Maize in the Developing World
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Improving Disease Resistance of Maize in the Developing World

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  • Add picture
  • Climate ChangeFood securityMaize pathologyNew or emerging pathogens/racesMovement of germplasmChange on cultural practicesFood quality, health concerns, mycotoxinsScience  ImpactPolicy
  • Fig. 3. Likelihood (in percent) that future summer average temperatures will exceed the highest summer temperature observed on record (A) for 2050 and (B) for 2090. For example, for places shown in red there is greater than a 90% chance that the summer-averaged temperature will exceed the highest temperature on record (1900–2006) (22).Obvious effect on yieldPlant distributionPlant behaviorMake connection transition to new (re)emerging pathogens
  • Cercosporazeina found independent of Cercosporazeae-maydis in africa. MPP 2010 (11) 1MSVCicadulinambila, but other leafhoppers
  • Add picture
  • Add picture
  • Move GLS upHighlight results Jesse’s SLBMarkers for MAS
  • Move GLS upHighlight results Jesse’s SLBMarkers for MAS
  • Add gls
  • Syntheny,orthologs, pathway; refer to review
  • Number of lines that can be scored is higherThey have done it. Talk about not complete adoption.
  • Maize diversitySI8 Opening the black box of maize genetics diversitySI4 Stress-tolerant maize for enhanced food security and poverty alleviation
  • SI 10 Capacity building of maize institutions and professionalsAdd delivery hereAdd ILRI picture
  • To conclude…
  • Add picture
  • Gibberella:Photo A. Robertson By Alison Robertson and Gary Munkvold, Department of Plant Pathology. Iowa State UniversityFusariumArvydas (Arv) Grybauskas, Extension Plant Pathologist, University of Maryland; arvydas@umd.eduGibberellafujikuroi
  • There is limits of how much to have but it is also related with now much corn is part of the dietEnforcement
  • Extremely pervasivePreharvest-postharvest
  • Show or mention silk in MS
  • The red ones are significant p-values
  • Used 1106 SNP makers from the maize diversity project (Buckler et al.)Two years of data (2007 and 2008) Aflatoxin data and silk IC are from MS. DvK SP and Silk LP and SO are from invitro assays in NYSHOW ON A MAP?
  • RemindGibberella produces DON and is Fusariumgraminearum
  • But we decided to do a more RIGOROUS
  • Mention (A. Charcosset INRA)
  • Weighted least squares strategyRejected the null hypothesis of having the same genetic map among experimentsAdd map names
  • Mention (A. Charcosset INRA)
  • Fix labels
  • Point out to large interval in Chr3= 51MbPoint out this is meta-analysis C
  • Mention (A. Charcosset INRA)
  • Change on color patterns
  • Look for disease resistance ceasing every opportunity that science and technology allow us to face tremendous challenges. Integrate with other priorities with a team of scientitst and social sciences specialists in order to reach to the farmers with the best seed and strategy.Droght
  • Look for disease resistance ceasing every opportunity that science and technology allow us to face tremendous challenges. Integrate with other priorities with a team of scientist and social sciences specialists in order to reach to the farmers with the best seed and strategy.Droght
  • Transcript

    • 1. Improving disease resistance of maize in the developing world: challenges and opportunities Santiago Mideros 17 February 2011 CIMMYTWFP/Elmer Martinez
    • 2. Outline Challenges and Opportunities ◦ General ◦ Specific  Aflatoxins AFB1
    • 3. Opportunities Ag. development is back Science & Technology ◦ Genetics, genomics, plant immunity ◦ Precise phenotype, barcoding, databases CIMMYT ◦ Germplasm ◦ World network ◦ Mandate
    • 4. Challenges Climate Change ◦ Food security ◦ Maize pathology New or emerging pathogens/races ◦ Movement of germplasm ◦ Change on cultural practices Food quality, health concerns, mycotoxins Science  Impact Policy
    • 5. Climate Change  Uncertainty in predictions  Lack of historical data  Fusarium species and DONBattisti and Naylor 2009
    • 6. New and (re)emergingpathogens or races Gray Leaf Spot ◦ Cercospora zeina ◦ Cercospora zeae-maydis Maize fine streak virus Maize streak (gemini)virus Phaeosphaeria leaf spot Maize streak virus Shepherd et al
    • 7. Policy Investment on science in developing countries Aid and technology from developed countries ◦ Budgetary concerns
    • 8. Opportunities Ag. development is back Science & Technology ◦ Genetics, genomics, plant immunity ◦ Precise phenotype, barcoding, databases CIMMYT ◦ Germplasm ◦ World network ◦ Mandate
    • 9. Opportunities Ag. development is back Science & Technology ◦ Genetics, genomics, plant immunity ◦ Precise phenotype, barcoding, databases CIMMYT ◦ Germplasm ◦ World network ◦ Mandate
    • 10. Science Association Mapping  Yan et al, 2011 ◦ Northern Leaf Blight, ◦ Southern Leaf Blight, ◦ Gray Leaf Spot Wisser, Kolkman, Benson, Nelson, Balint-Kurti (in review)  Glutatione S-transferase
    • 11. Nested Association MappingSouthern leaf blight (Kump et al, 2011) 32 QTL 51 SNP: Receptor like kinases, Glutathione S- transferaseNorthern leaf blight (Poland et al, in review) 21 QTL 60 SNP: ◦ Receptor like kinases ◦ Ethylene response factor ◦ Mlo-like Quantitative disease resistance  PTI (Basal Resistance)Gray leaf spot (Benson et al, in preparation) 12 QTL 21 SNP
    • 12. Science (cont.) Mutant-Assisted Gene Identification and Characterization (MAGIC)• Fine mapping genes responsible for resistance in maize
    • 13. Nature Biotechnology Volume: 28, Pages: 365–369 Year published: (2010) DOI:doi:10.1038/nbt.1613
    • 14. Technology
    • 15. Others Communication (Internet) ◦ Developing partnerships ◦ Collaboration ◦ Capacity building Genomic selection Genotyping by sequencing ◦ Next generation sequencing
    • 16. Opportunities Ag. development is back Science & Technology ◦ Genetics, genomics, plant immunity ◦ Precise phenotype, barcoding, databases CIMMYT ◦ Germplasm ◦ World network ◦ Mandate
    • 17. Germplasm Photo by Suketoshi Taba, Yan et al 2011
    • 18. Multiple Locations
    • 19. Partners National agricultural research institutes Other international organizations Universities in developing countries Universities in developed countries Private companies NGOs
    • 20. Sustainable Disease ManagementDisease resistance No silver bullets ◦ Deployment:  Pyramids  Refuge areas (Bt) Resistance + management Multiple disease resistance Effect of a single QTL. Chung et al, 2010
    • 21. Outline Challenges and Opportunities ◦ General ◦ Specific  Aflatoxins AFB1
    • 22. Challenges and OpportunitiesA practical exampleChallenge:Mycotoxin contaminationOpportunities:Technology and geneticsFood systems
    • 23. Mycotoxins AFB1 Aflatoxins A. flavus and A. parasiticus  aflatoxins Potent hepatocarcinogen Acute: death; liver damage Chronic: ◦ Immune suppression, growth impairment ◦ Hepatocellular carcinoma Financial burden
    • 24. Other Ear Rots Gibberella Ear Rot Fusarium Ear Rot Fusarium graminearum Fusarium verticillioides Deoxynivalenol = DON = Vomitoxin FumonisinPhoto: A. Robertson
    • 25. Aflatoxin  child stunting
    • 26. Regulation & ExposureCountry Consumptio Max. aflatoxin Exposure n (ppb) (ng/bw/day) (g/p/day)Western 33 4 0.3 – 1.3Europe USA 86 20 0.26Southern 148 4 0-4 Europe Kenya 248 20* 3.4 - 133Mexico 300 20 14 - 85 Sources: Liu, Y. and Wu, F. 2010. EHP. 118: 818-824 Reddy et al. 2010. Toxin Reviews. 29: 3-26 1ppb = 1 ng per g or 1mg per metric ton
    • 27. 2010 aflatoxinoutbreak, Eastern Province, Kenya
    • 28. Survey in western Kenya 09 Source of maize N % >10 % >20 ppb ppbGifts from friends or 30 27 7 relatives Purchased 34 11 2 9 Own-grown 18 5 2 3 Food aid S. Mutiga; V.14 7 0 Hoffman; and R.J. Nelson unpb Total 56 14 3 9
    • 29. Strategy Components of Resistance Map disease resistance
    • 30. CML69 Sc212mComponents ofresistance Tissue specific Mp339 Tx303 Components of resistance ◦ Latent period (LP) Picture: K. Loeffler ◦ Sporulation intensity (SP) ◦ Infection frequency (IF) Colonization ◦ qPCR
    • 31. 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
    • 32. A. flavus biomass in maize is strongly correlated with aflatoxin concentration A. flavus AflatoxinPedigree/Line log (IC+1) IC log (ng/g+1) ng/g 4CML103 0.78 a 1.18 10.03 a 22735Mo17 0.62 ab 0.85 9.39 ab 11982 3 Coefficient (log IC)B73 0.51 abc 0.67 9.54 ab 13917B97 0.33 bcd 0.39 9.22 abc 10118 InfectionMS71 0.28 bcd 0.33 8.21 abcde 3689 2Oh43 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 2790 1NC358 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 1056 0 2 3 4 5 6 7 8Tx303 0.06 d 0.06 7.20 cdef 1333 Aflatoxin (log ng/g)Ki3 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 622 Correlation between infectionCML52 0.00 d 0.00 4.55 h 94 coefficient (IC) and aflatoxinMp313E 0.00 d 0.00 4.84 gh 126CML247 0.00 d 0.00 5.15 fgh 172 = 0.85 ** Mideros et al 2009 Plant Disease 93: 1163
    • 33. Experiments New York Mississippi
    • 34. Components of resistance fordiverse inbreds: 3 years of studies (P-values) Maize Tissue Component of resistance Developing Mature Silk Kernel Kernel 0.062 Latent Period 4 ns Infection 0.001 Frequency 8 ns In-vitro 0.006 Sporulation 7 0.0963 Colonization (qPCR) - 0.2097 Colonization 0.031 Field (qPCR) 2 - 0.0301 While significant, Aflatoxin - - 0.0006 not correlated with aflatoxin
    • 35. Kernel resistance correlations Field In-vitro Flint-Garcias traits Colonization Colonization Sporulation %endsprm Moisture Carbhdrt sd wght Protein (qPCR) (qPCR) Fiber Ash Fat Aflatoxin 0.70*** 0.02 0.06 -0.03 -0.45 -0.25 -0.68** -0.57* 0.52* 0.57* 0.12Field Colonization -0.16 -0.01 -0.02 -0.21 -0.17 -0.47 -0.50 0.27 0.46 0.09 Colonization 0.00 0.33 -0.38 0.03 -0.07 0.03 0.23 0.14 -0.05In-vitro Sporulation -0.53* 0.39 0.27 0.03 0.26 -0.38 -0.41 0.15
    • 36. Strategy Dissect the trait into multiple components Map disease resistance
    • 37. Model selection QTL mapping (B73 xCML322) Trait Year Marker Position p-value 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 ** B73 Aflatoxin, MS 2009 m1096 10.07 1.0E-07 ** CML322 Aflatoxin, MS 2009 m216 2.03 9.3E-05 * CML322 Aflatoxin, MS 2009 m746 6.06 2.7E-03 CML322 Sporulation SP 25 Latent Period LP QTL Infection Freq IF
    • 38. QTL studiesPlant Disease Germplasm SourceAspergillus 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. 2005Fusarium 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 Robertson-Hoyt et al. 2006 FR1064 NC300 x B104 Robertson-Hoyt et al. 2006
    • 39. 5 1 2 3 4 5.00 1.00 umc1292 2.00 phi109642 3.00 umc2105 4.00 umc1008 5.01 umc1746 5.02 umc1761 2.01 umc1727 2.02 umc1185 1.01 umc1079 3.01 umc1970 4.01 umc1682 bnlg371 5.03 bnlg1046 umc1166 1.02 bnlg1429 umc1065 3.02 bnlg603 umc1070 2.03 5.04 bnlg371 4.02 umc1757 bnlg1144 3.03 mmc0081 bnlg1325 5.05 1.03 umc2019 5.06 mmc0481 phi001 4.03 bnlg1126 1.04 bnlg1598 2.04 umc1783 4.04 nc004 phi036 3.04 phi029 2.05 1.05 4.05 nc005 5.07 bnlg1306 2.06 3.05 sts001 umc1590 1.06 4.06 bnlg1057 bnlg2291 5.08 umc2136 2.07 umc1637 umc1035 1.07 bnlg1596 4.07 bnlg1137 3.06 bnlg1063 1.08 umc2047 umc1667 3.07 bnlg1350 1.09 bnlg197 4.08 5.09 umc1153 bnlg400 bnlg2162 2.08 umc1526 3.08 1.10 umc1051 umc1361 umc1173 umc1421 umc1062 1.11 3.09 4.09 umc1631 bnlg1182 umc1630 3.10 umc2048 1.12 umc1118 4.10 umc2011 umc1065 6 10 phi075 7 6.00 bnlg238 9 8 10.00 umc1498 umc1291 10.01 7.00 umc1642 9.01 umc1867 6.01 bnlg1165 8.00 9.02 umc1632 phi027 8.01 umc1139 9.03 6.02 bnlg1451 umc1688Mp313Ea 6.03 umc1006 bnlg1194 umc1033 10.02 phi062 umc1191Mp313Eb 6.04 umc1014 7.01 8.02 8.03 9.04 bnlg1209 umc2121 10.03 10.04 bnlg640 umc1246 bnlg1352 umc1053Mp717 6.05 bnlg1154 8.04 bnlg1863 9.05 umc1654 10.05 umc1506 umc1898 umc1066 bnlg1702 bnlg666Mp715 umc1477 bnlg1200 8.05 umc1149 6.06 umc2170 7.02 umc1978 bnlg240 9.06 umc1789 bnlg1350 10.06 umc1061Oh516 umc1463 7.03 7.04 phi114 bnlg1070 8.06 umc1997 bnlg1191Tex6 umc1001 8.07 bnlg1759 umc1029 9.07 bnlg128 umc1084 6.07 bnlg1828 bnlg1450 umc1248 7.05 phi260485B73 umc2222 8.08 10.07 6.08 phi089 umc1407 umc2059 8.09 9.08 umc1277 7.06 phi116 dupssr14 bnlg1185CML322 6.09 umc1127 umc1799 Collaboration with M. Warburton 10.08
    • 40. QTL Meta-analysisConsensus Genetic Map Projection of QTL and CI Select number of QTL in chromosome Position of metaQTL Veyrieras et al. 2007 BMC Bioinformatics 8 Truntzler et al. 2010 TAG 114
    • 41. Consensus GeneticMap Mp313E x B73 Genetic 2008Consensus B73 x CML322
    • 42. QTL Meta-analysisConsensus Genetic Map Projection of QTL and CI Select number of QTL in chromosome Position of metaQTL Goffinet et al. 2000 Genetics 155 Veyrieras et al. 2007 BMC Bioinformatics 8 Truntzler et al. 2010 TAG 114
    • 43. 1 2 3 4 56 7 8 9 10 Aspergillus Ear Rot Aflatoxin Fusarium Ear Rot Fumonisin Ear rot (w) Ear rot Gibberella Ear Rot Silk disease severity Kernel disease severity
    • 44. QTL Meta-analysisConsensus Genetic Map Projection of QTL and CI Select number of QTL in chromosome Position of metaQTL Goffinet et al. 2000 Genetics 155 Veyrieras et al. 2007 BMC Bioinformatics 8 Truntzler et al. 2010 TAG 114
    • 45. 1.012.5 Mb 1.0623.2 Mb
    • 46. Sustainable Disease Management Disease resistance  Resistance + management Effect of a single QTL Chung et al, 2010 Pre-harvest resistance Post- Field Lower Drought Better harvest manageme aflatoxintolerance varieties manageme nt s nt Yield •Resistance Biological •Storage control •Testing •Detoxification
    • 47. Acknowledgments R. Nelson Lab o Chia-Lin Chung Rebecca Nelson o Jesse Poland Tiffany Jamann o Samuel Mutiga o Judy Kolkman Paola Zuluaga o Wenzhe Li Margaret Smith o Chris Mancuso Jaci Benson o Nelson Chepkwony Bill Holdsworth o Ariel Fialko Jose Luis Zambrano o Oliver Ott o Sara Heinz  Marilyn Warburton o Lin-Si Hsieh  Gary Windham o Kristen Kennedy  Paul Williams o Kerri Lyons o Gregory Flint o Joy Longfellow o Ellie Walsh o Ladonna Owens o Mike Alpe o Victoria Scott

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