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GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
GRM 2011: Discovery and Development  of Alleles Contributing To  Sorghum Drought Tolerance
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GRM 2011: Discovery and Development of Alleles Contributing To Sorghum Drought Tolerance

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  • 1. Discovery and Developmentof Alleles Contributing ToSorghum Drought ToleranceGCP Project G3008.05PI: Andy Patterson
  • 2. GCP Competitive Project G3008.02:Improving Grain Yield on Acid Soils bythe Identification of Genetics FactorsUnderlying Drought and AluminumTolerance in Maize and SorghumPI: Leon Kochian (USDA-ARS and Cornell University)Co-PI’s on Sorghum & Maize Drought Research: JurandirMagalhaes, Robert Schaffert, Sidney Parentoni, Claudia Guimarães(Embrapa Maize and Sorghum)Root System Architecture and Drought: Randy Clark (USDA-ARSand Cornell University)
  • 3. Development of a Sorghum Genome-Wide Association Platform for Crop TraitsG10-brazilian linesG9-Caudatum from AfricaG7-Guinea from Western AfricaG7-Guinea from Western AfricaG6- Guinea from AsiaG5-Guinea from southern AfricaG4-Dura from Asia andAfricaG3-Caudatum,bicolor from ChinaG11-Kafir from southern AfricaG8-transplanted sorghum from Chad and CameronG1-Guine margaritiferumG2-USA lines• Combined the SP1/EMB/US (IGD) panels: 480 member association panelSP1/EMB (SSR-based) SP1/EMB/US (SNP-based)
  • 4. Genotyping and Phenotyping ofSorghum Association Panel•Initially genotyped with Illumina 1536 SNP chip by MarthaHamblin (IGD-Cornell)•Currently being genotyped by sequencing by Ed Buckler andSharon Mitchell as part of their NSF BREAD grant .-Developed multiplexing approach to sequence multiplesamples in one lane of Illumina High-Seq.-Developed a bioinformatics pipeline for SNP ID-Hope to add 100,000 to 200,000 SNPs to each member ofassociation panel.•Have phenotyped entire panel for Al tolerance – waiting forgenotyping to be completed to conduct GWAS on Al tolerance.•Have phenotyped the IGD part of the panel (converted lines)for P efficiency at Embrapa.•Will soon phenotype panel for P efficiency and rootarchitecture in low P soils in greenhosse at Cornell
  • 5. ALUMINUM TOXICITY IN CROP PLANTS•Al3+ is the major toxic species•Dramatic inhibition of rootgrowth•Root apex is the site of toxicity•Genetic variation in Al tolerancehas led to identification of Altolerance genes/mechanismsAl Sens Al Tol0% Al Saturation20% Al Saturation40% Al SaturationTOL SENS TOL SENSWheatMaize
  • 6. Three experiments (9x9 simple lattice) with threereplications were conducted at two sites (Janauba inMinas Gerais and Teresina in Maranhão) to evaluate243 entries of the IGD sorghum panel. Two controlentries were repeated in each sub-block.Planting Janauba 2010Harvest (No stress)Janauba 2010Phenotyping Sorghum Association (IGD)Panel for Drought Stress in the FieldHarvest (Drought stress)Janauba 2010
  • 7. Figure 1 Figure 2Figure 1 and 2: Genotype SC782 under control andwater stress conditions in Janaúba conducted in 2010.IGD panel phenotyped for grain yield, stay green, plantheight, etc under well watered and drought conditions
  • 8. Drought Tolerance Measured asDegree of Stay Green Trait90% of stay green65% of stay green
  • 9. Mean SquareSource GL YieldExpt. 2 8.978670NSBlock(exp) 51 4.124902**Treat 244 4.891683**Error 296 1.904430CV (%) 22.41Mean yield (t.ha-1) 6.15h2 72%Table 1. Analysis of Variance Summary of ExperimentsConducted under Well Watered Conditions in Janaúba (2009)NS: Not significant, **: Significant at 1% probability by F test, CV (%): Coefficient ofvariation and h2: herdability.
  • 10. Mean SquareSource GL YieldExpt. 2 4.9129710NSBlock(exp) 78 2.8328542**Treat 244 2.7512407**Error 566 0.886411CV (%) 28.58Mean yield (t.ha-1) 3.29h2 75%NS: Not significant, **: Significant at 1% probability by F test, CV (%): Coefficient ofvariation and h2: herdability.Table 1. Analysis of Variance Summary of ExperimentsConducted under Drought Conditions in Janaúba (2010)
  • 11. • Observed significant variability in effect of drought ongrain yield at both sites.• The reduction of grain yield under drought was 46%compared to experiments conducted in controlledconditions in Janaúba and approximately 30% in Teresina -PI.• It is noteworthy that irrigation was stopped beforeflowering and no further irrigation was provided.Preliminary Results
  • 12. Recent Activities on Maize Drought Toleranceat Maize Breeding Program of EMBRAPAEmbrapa-Maize and Sorghum – Sete Lagoas-MG, BrazilSidney ParentoniLauro GuimarãesClaudia Guimarães
  • 13. Maize Breeding Lines Diversity Panel•Have assembled a set of 190 maize inbred lines adapted totropical conditions.•Are phenotyping these in the field for drought related traits(grain yield, stay green, plant height, etc) at same field sites asfor sorghum work – Janaúba and Teresina.•Drought imposed by with holding water for 50 until 80 daysafter sowing, then irrigation re-applied.•Also developed test cross panel by crossing 143 of theinbreds with L3 and 178 inbreds with l 228.3. L3 and L228-3represent the two maize heterotic groups.•The test cross lines also phenotyped at the two sites undersimilar conditions.
  • 14. Exp. 1 – Inbred lines “per se”Painel Janaúba 2009Mixed Model Analysis – REML/BLUP (Grain yield - kg/ha )Components Drought Well-wateredGenetic variance 44999.54** 316252.68**Error Variance 37938.29 293744.18Heritability 0.83 0.81Accuracy 0.91 0.90Mean (u+g) 255.7 875.7Yield reduction 70%Correlation across drought and well-watered conditions = 0.69
  • 15. Grain yield of 190 inbred lines (EMBRAPA´s maize panel) evaluated atdrought (x axis) and well-watered (y axis) conditions, in Janaúba, 2009y = 1,8581x + 389,64R2 = 0,4879r = 0,698-1004009001400190024002900-100 100 300 500 700 900 1100kg/ha-Well-wateredconditionkg/ha - Drought conditionL20L98-CIM-2-46L26L3228-3
  • 16. Maize lines evaluated “per se” under droughtconditions75 days after sowingJanáuba-Brazil 2009Low PLow PHigh PTolerant and sensitive lines under drought stress condition
  • 17. Trial 2 - Testcross Evaluation- 2010 Trial-1: 64 TC Trial-2: 64 TC Trial-3: 15 TC Trial-4: 81 TC Trial-5: 82 TC Trial-6: 15 TC+ 4checksEvaluated at Janaúba-MG and Teresina-PI (Brazil) under droughtand well-watered conditions in 2010 - 3 repsTC Panel143 inbreds x L3 178 inbreds x 228-3Drought: without irrigation 45 days after sowing until end of seasonWell-watered conditions: irrigation as needed during entire season300kg/ha 8-28-16Side dress 100kg/ha of N
  • 18. Maize panel Evaluated in Testcross underDrought and Well-watered Conditions - 60days after sowingJanáuba-Brazil 2010Low PLow PHigh PStressIrrigated
  • 19. Exp. 2 – TC Panel x testers 2010Individual analysis for location and water availabilityGrain yield (kg/ha)ComponentsJanaúba TeresinaDrought W-w Drought W-wVg 537104** 1363145** 916694** 1722220**Ve 990680 1558372 1877842 1243696h2 0.77 0.84 0.75 0.89Accuracy 0.87 0.92 0.86 0.94CVe% 29.2 16.6 39.5 15.7Means 3400.3 7526.3 3465.8 7110.7Var. GxE 176807** 701576**r levels 0.81 0.47Yield reduction = 55% Yield reduction = 51%
  • 20. Grain yield of testcrosses (EMBRAPA´s maize panel x 2 testers)evaluated under drought (x axis) and well-watered (y axis) conditions inTeresina-PI, individual analysis 2010Grainyieldunderwell-wateredcondition(kg/ha)Grain yield under drought conditions (kg/ha)
  • 21. Genotyping Maize Inbred Line Panel• Initially genotyped with 1536 SNP chip• Approx 100 of the inbred lines have been genotypesby GBS in Buckler lab. The rest will be done soon.About 70,000 markers per line right now.• Will we have enough markers to do GWAS analysis ofmaize drought tolerance?• Is LD for these lines greater than in Buckler diversitypanel as lines more related?•Need professional help in analyzing data from testcrosses.
  • 22. Analysis of Root SystemArchitecture inThree DimensionsClark RT, MacCurdyRB, Jung JJ, Shaff JE,McCouchSR, Aneshansley DJ, Kochian LV. 2011.3-Dimensional root phenotyping with a novelimaging and software platform. Plant Physiol156: 455-465.
  • 23. Shallow Intermediate DeepWhat is the ideal root architecture for soybean in low phosphorous soils?[P][H+]P Efficient Soybean LineHong Liao, Root Biology Center, S. China Agric Univ., Guangzhou
  • 24. Tradeoffs Between Phosphorus andWater AcquisitionLow PSufficient WaterSufficient PLow WaterJonathan Lynch, Penn State University
  • 25. Gellan Gum Growth System and 3D Imaging Platform• Plants grown in semi-sterile glass growth cylinderscontaining solid gellan gum media replete withnutrients.• The camera is synchronized with the turntable viacomputer control.• Captured image sequences consist of 40 images for eachplant; 9° of rotation between images.• Water tank corrects for optical refraction from thecurved surface of the glass cylinders.• Approximately 4 minutes to image one root system.Randy Clark
  • 26. RootReader3D Reconstruction and Analysis Software• RootReader3D generates 3D root models from image sequences and facilitates the quantification ofconventional and novel RSA and developmental traits.• Measured traits include: length, volume, width, angle, distribution, root scavenging volume,emergence times, gravitropic and circumnutation responses, etc.• Automated analysis of whole root system traits.• Interactive isolation, classification and analysis of specific root system components based on visualand temporal clues.Rice Root System
  • 27. Trait Root Types Processing Units DescriptionLength (L) trs, zoi, pr, ecr, pecr, llr, pr+, cr+ a, sa cmLength along the skeleton of the whole root system, root system component, orroot using a polyline length estimation technique.Max Width (MaxW) trs, pr+, cr+ a, sa cmMaximum horizontal width of the whole roots system or root systemcomponent measured every 0.2 degrees of rotation.Min Width (MinW) trs, pr+, cr+ a, sa cmMinimum horizontal width of the whole roots system or root system componentmeasured every 0.2 degrees of rotation.Max Depth (MaxD) trs, pr+, cr+ a, sa cmMaximum vertical depth of the whole root systems or root system componentmeasured in relation to upper most slice containing a root system voxel.MinW/MaxW Ratio trs, pr+, cr+ a, sa cm/cm Ratio of minimum width to maximum width.MaxW/MaxD Ratio trs, pr+, cr+ a, sa cm/cm Ratio of maximum width to maximum depth.Centroid trs, pr+, cr+ a, sa cmVertical position of the center of mass of the whole root system or root systemcomponent.Exploitation Volume trs, zoi, pr+, cr+ a, sa cm3Volume surrounding the root system or root system component at specifiedradius minus the root system or root components volume. Adapted fromBerntson, 1994.Exploitation Index trs, zoi, pr+, cr+ a, sa cm3/cmRatio of the exploitation volume to the root system to root system length.Adapted from Berntson, 1994.Median Number of Roots (MedR) trs, zoi, pr+, cr+ a, sa #Median number of roots from root counts taken from all horizontal cross-sectional slice through the entire root system or root system component.Adapted from Iyer-Pascuzzi, et al, 2010.Maximum Number of Roots (MaxR) trs, zoi, pr+, cr+ a, sa #Number of roots at the 84th percentile of a sorted list (smallest to largest) ofroot counts from all horizontal cross-sections through the entire root system orroot system component. Adapted from Iyer-Pascuzzi, et al, 2010.MaxR/MedR Ratio (Bushiness) trs, zoi, pr+, cr+ a, sa #/#Ratio maximum number of roots to median number of roots. Adapted fromIyer-Pascuzzi, et al, 2010.Surface Area (SA) trs, zoi, pr+, cr+ a, sa cm2 Summed surface area of the whole root system or root system componentvoxels that are 6-connected with a background voxel.Current Traits Measured with RootReader3D Software
  • 28. Trait Root Types Processing Units DescriptionSA/V Ratio trs, zoi, pr+, cr+ a, sa cm2/cm3Ratio of surface area to volume.SA/L Ratio trs, zoi, pr+, cr+ a, sa cm2/cm Ratio of surface area to length.Volume Distribution trs a cm3/cm3Ratio of the volume of root system contained above one third depth of the rootsystem to the volume of root system contained below one third depth of theroot system.Convex Hull Volume (CHV) trs a cm3Volume of the convex hull that encompasses the whole root system. The convexhull is found by summing the convex hulls of all horizontal cross-sectional slicethrough the root system, where the convex hull is the smallest convex set ofvoxels that contains all other root voxels in the slice. Adapted from Iyer-Pascuzzi, et al, 2010.V/CHV (Solidity) trs a cm3/cm3Ratio of volume to convex hull volume. Adapted from Iyer-Pascuzzi, et al, 2010.Emergence Time pr, ecr, pecr, llr sa daysAverage root emergence time for a given root type in relation to the plantingdate.Initiation Angle pr, ecr, pecr, llr sa degreesAverage horizontal root initiation angle for a given root type. Measured inrelation to gellan gum surface or horizontal.Gravitropic Response pr, ecr, pecr, llr sa degrees/cmDifference in the horizontal root angle divided by the length of the root or rootsection.Circumnutation pr, ecr, pecr, llr sa degrees/cmDifference in the root turn angle divided by the length of the root or rootsection.Narrowness Index trs, pr+, cr+ a, sa cm/cmAverage ratio of minimum width to maximum width for each horizontal cross-sectional slice through the whole root system. Slices that only contain theprimary root and its connected laterals are excluded.Volume (V)Counttrs, zoi, pr+, cr+pr, ecr, pecr, llra, sasacm3#Volume of the whole root system or root system component.Number of roots of a particular type.Tip Count trs a #Number of root tips in the whole root system. Measured from root systemskeleton and is the number of skeleton voxels that have only one 26-connectedneighbor voxel.L/V (Specific Root Length, SRL) trs, zoi, pr+, cr+ a, sa cm/cm3 Ratio of length to volume of the whole root system or root system component.Adapted from Eissenstat, 1991 and Iyer-Pascuzzi, et al, 2010.Current Traits Measured with RootReader3D Software (con’t)
  • 29. Dynamic Analysis of 3D Root System DevelopmentD1 D2 D3 D4 D5 D6 D7 D8 D9 D10D1 D2 D3 D4 D5 D6 D7 D8 D9 D10D1 D2 D3 D4 D5 D6 D7 D8 D9 D10045040035030025020015010050Length(cm)D1 D2 D3 D4 D5 D6 D7 D8 D9 D10045040035030025020015010050Length(cm)PrimaryEmbryonic CrownPost-Embryonic CrownLateralPrimaryEmbryonic CrownPost-Embryonic CrownLateralAzucenaIR64Azucena IR64
  • 30. Exploring Rice RootArchitecture in 3 DimensionsUsing a Diverse Set of Oryzasativa and Oryza rufipogonAccessionsRandy Clark – Oryza sativaJanelle Jung – Oryza rufipogonRandy ClarkJanelle Jung
  • 31. Primary Objectives•To survey the range of variation in seedling 3-D root morphology observedwithin the rice diversity panel using the gellan gum culture system•To quantify and characterize seedling root growth and root systemarchitecture traits in a diverse set of 400 O. s. and 100 O. r. accessions usingRootReader 3D platform.•To develop a standard ontology of rice root system architecture (RSA) traits•To identify seedling root architecture traits that distinguish O. r. and O. s, orthat are correlated with enhanced yield or stress tolerance•To run association mapping analyses using the 950K SNP platform toidentify QTL controlling these root architecture traits in O. sativa & O.rufipogonResearch Overview
  • 32. NSF-TV Rice Diversity Panel• 100 O. rufipogon accessionsChosen for• Genetic diversity• Country of origin – natural range• Vegetative trait variation – tiller angle andstolon presence• Reproductive trait variation – yield,heading date, panicle and seed traits Geographic origin of O. r. panel accessionsRice Diversity Panel -- 500 accessions – AssociationMapping• 400 O. sativa accessionsChosen for• Genetic and geographic diversity• Genomic and agricultural significance
  • 33. Experimental Design• 400 O. sativa accessions (NSF-TV) (15-18 weeks)• 100 O. rufipogon accessions (NSF-TV) (4-6 weeks)• 168 IR64 x Azucena SSD lines (6-8 weeks)30 plants/batch, 3 batches/week3 reps (individuals) per accession1 rep at a time (30 accessions per batch)O.s.: 28 unique, 2 internal controlsO.r.: 27 unique, 3 internal controls (1 O.r., 2 O.s.)Time course: Imaging at 3, 6, 9, 12 days past planting
  • 34. GWAS of Rice 3D Root Architecture Traits• Have completed phenotyping rice for 3-D RSA traits undercontrol conditions in gel-based media. Phenotyped theMcCouch’s NSF-TV rice diversity panel (500 lines) and alsobi-parental mapping population (168 lines).• That involved phenotyping approximately 2000 individualplants in gellan gum cylinders.• Roots imaged at 3, 6, 9, & 12 days afterplanting to include dynamicgrowth parameters.•Randy is in Taiwan for the summerwhere he as nearly completes 3Dreconstructions and quantificationof his 20 RSA traits.•GWAS analysis will be completedin Fall with 950k SNP chip.
  • 35. •Will begin to phenotyping sorghum (and then maize) for 2-D and 3-DRSA, including our sorghum association panel, and the Embrapa maizebreeding panel.•Need to begin determining physiological relevance of specific RSAtraits – looking at their role in nutrient (P and N), and water acquisition.•The gel-based system is not optimal for some stresses such as Pdeficiency and drought – thus we are developing a sand-based culturesystem where we control water potential or P availability for subsequentanalysis of 2D RSA and shoot/root biomass under stress (P efficiency anddrought tolerance). Then need to move onto to soil-based studies.•Need to look at correlation of RSA traits between 2-D and 3-D analysis.WHAT’S NEXT (con’t)?AgriculturalResearch ServiceGeneration ChallengeProgram

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