GRM 2011: Discovery and Development of Alleles Contributing To Sorghum Drought Tolerance
1. Discovery and Development
of Alleles Contributing To
Sorghum Drought Tolerance
GCP Project G3008.05
PI: Andy Patterson
2. GCP Competitive Project G3008.02:
Improving Grain Yield on Acid Soils by
the Identification of Genetics Factors
Underlying Drought and Aluminum
Tolerance in Maize and Sorghum
PI: Leon Kochian (USDA-ARS and Cornell University)
Co-PI’s on Sorghum & Maize Drought Research: Jurandir
Magalhaes, Robert Schaffert, Sidney Parentoni, Claudia Guimarães
(Embrapa Maize and Sorghum)
Root System Architecture and Drought: Randy Clark (USDA-ARS
and Cornell University)
3. Development of a Sorghum Genome-
Wide Association Platform for Crop Traits
G10-brazilian lines
G9-Caudatum from Africa
G7-Guinea from Western AfricaG7-Guinea from Western Africa
G6- Guinea from Asia
G5-Guinea from southern Africa
G4-Dura from Asia andAfrica
G3-Caudatum,bicolor from China
G11-Kafir from southern Africa
G8-transplanted sorghum from Chad and Cameron
G1-Guine margaritiferum
G2-USA lines
• Combined the SP1/EMB/US (IGD) panels: 480 member association panel
SP1/EMB (SSR-based) SP1/EMB/US (SNP-based)
4. Genotyping and Phenotyping of
Sorghum Association Panel
•Initially genotyped with Illumina 1536 SNP chip by Martha
Hamblin (IGD-Cornell)
•Currently being genotyped by sequencing by Ed Buckler and
Sharon Mitchell as part of their NSF BREAD grant .
-Developed multiplexing approach to sequence multiple
samples 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 of
association panel.
•Have phenotyped entire panel for Al tolerance – waiting for
genotyping 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 root
architecture in low P soils in greenhosse at Cornell
5. ALUMINUM TOXICITY IN CROP PLANTS
•Al3+ is the major toxic species
•Dramatic inhibition of root
growth
•Root apex is the site of toxicity
•Genetic variation in Al tolerance
has led to identification of Al
tolerance genes/mechanisms
Al Sens Al Tol
0% Al Saturation
20% Al Saturation
40% Al Saturation
TOL SENS TOL SENS
Wheat
Maize
6. Three experiments (9x9 simple lattice) with three
replications were conducted at two sites (Janauba in
Minas Gerais and Teresina in Maranhão) to evaluate
243 entries of the IGD sorghum panel. Two control
entries were repeated in each sub-block.
Planting Janauba 2010
Harvest (No stress)
Janauba 2010
Phenotyping Sorghum Association (IGD)
Panel for Drought Stress in the Field
Harvest (Drought stress)
Janauba 2010
7. Figure 1 Figure 2
Figure 1 and 2: Genotype SC782 under control and
water stress conditions in Janaúba conducted in 2010.
IGD panel phenotyped for grain yield, stay green, plant
height, etc under well watered and drought conditions
9. Mean Square
Source GL Yield
Expt. 2 8.978670NS
Block(exp) 51 4.124902**
Treat 244 4.891683**
Error 296 1.904430
CV (%) 22.41
Mean yield (t.ha-1) 6.15
h2 72%
Table 1. Analysis of Variance Summary of Experiments
Conducted under Well Watered Conditions in Janaúba (2009)
NS: Not significant, **: Significant at 1% probability by F test, CV (%): Coefficient of
variation and h2: herdability.
10. Mean Square
Source GL Yield
Expt. 2 4.9129710NS
Block(exp) 78 2.8328542**
Treat 244 2.7512407**
Error 566 0.886411
CV (%) 28.58
Mean yield (t.ha-1) 3.29
h2 75%
NS: Not significant, **: Significant at 1% probability by F test, CV (%): Coefficient of
variation and h2: herdability.
Table 1. Analysis of Variance Summary of Experiments
Conducted under Drought Conditions in Janaúba (2010)
11. • Observed significant variability in effect of drought on
grain yield at both sites.
• The reduction of grain yield under drought was 46%
compared to experiments conducted in controlled
conditions in Janaúba and approximately 30% in Teresina -
PI.
• It is noteworthy that irrigation was stopped before
flowering and no further irrigation was provided.
Preliminary Results
12. Recent Activities on Maize Drought Tolerance
at Maize Breeding Program of EMBRAPA
Embrapa-Maize and Sorghum – Sete Lagoas-MG, Brazil
Sidney Parentoni
Lauro Guimarães
Claudia Guimarães
13. Maize Breeding Lines Diversity Panel
•Have assembled a set of 190 maize inbred lines adapted to
tropical conditions.
•Are phenotyping these in the field for drought related traits
(grain yield, stay green, plant height, etc) at same field sites as
for sorghum work – Janaúba and Teresina.
•Drought imposed by with holding water for 50 until 80 days
after sowing, then irrigation re-applied.
•Also developed test cross panel by crossing 143 of the
inbreds with L3 and 178 inbreds with l 228.3. L3 and L228-3
represent the two maize heterotic groups.
•The test cross lines also phenotyped at the two sites under
similar conditions.
15. Grain yield of 190 inbred lines (EMBRAPA´s maize panel) evaluated at
drought (x axis) and well-watered (y axis) conditions, in Janaúba, 2009
y = 1,8581x + 389,64
R2 = 0,4879
r = 0,698
-100
400
900
1400
1900
2400
2900
-100 100 300 500 700 900 1100
kg/ha-Well-wateredcondition
kg/ha - Drought condition
L20
L98-CIM-2-46
L26
L3
228-3
16. Maize lines evaluated “per se” under drought
conditions
75 days after sowing
Janáuba-Brazil 2009
Low P
Low P
High P
Tolerant 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
+ 4
checks
Evaluated at Janaúba-MG and Teresina-PI (Brazil) under drought
and well-watered conditions in 2010 - 3 reps
TC Panel
143 inbreds x L3 178 inbreds x 228-3
Drought: without irrigation 45 days after sowing until end of season
Well-watered conditions: irrigation as needed during entire season
300kg/ha 8-28-16
Side dress 100kg/ha of N
18. Maize panel Evaluated in Testcross under
Drought and Well-watered Conditions - 60
days after sowing
Janáuba-Brazil 2010
Low P
Low P
High P
Stress
Irrigated
19. Exp. 2 – TC Panel x testers 2010
Individual analysis for location and water availability
Grain yield (kg/ha)
Components
Janaúba Teresina
Drought W-w Drought W-w
Vg 537104** 1363145** 916694** 1722220**
Ve 990680 1558372 1877842 1243696
h2 0.77 0.84 0.75 0.89
Accuracy 0.87 0.92 0.86 0.94
CVe% 29.2 16.6 39.5 15.7
Means 3400.3 7526.3 3465.8 7110.7
Var. GxE 176807** 701576**
r levels 0.81 0.47
Yield 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 in
Teresina-PI, individual analysis 2010
Grainyieldunderwell-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 genotypes
by 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 of
maize drought tolerance?
• Is LD for these lines greater than in Buckler diversity
panel as lines more related?
•Need professional help in analyzing data from test
crosses.
22. Analysis of Root System
Architecture in
Three Dimensions
Clark RT, MacCurdyRB, Jung JJ, Shaff JE,
McCouchSR, Aneshansley DJ, Kochian LV. 2011.
3-Dimensional root phenotyping with a novel
imaging and software platform. Plant Physiol
156: 455-465.
23. Shallow Intermediate Deep
What is the ideal root architecture for soybean in low phosphorous soils?
[P]
[H+]
P Efficient Soybean Line
Hong Liao, Root Biology Center, S. China Agric Univ., Guangzhou
24. Tradeoffs Between Phosphorus and
Water Acquisition
Low P
Sufficient Water
Sufficient P
Low Water
Jonathan Lynch, Penn State University
25. Gellan Gum Growth System and 3D Imaging Platform
• Plants grown in semi-sterile glass growth cylinders
containing solid gellan gum media replete with
nutrients.
• The camera is synchronized with the turntable via
computer control.
• Captured image sequences consist of 40 images for each
plant; 9° of rotation between images.
• Water tank corrects for optical refraction from the
curved 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 of
conventional 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 visual
and temporal clues.
Rice Root System
27. Trait Root Types Processing Units Description
Length (L) trs, zoi, pr, ecr, pecr, llr, pr+, cr+ a, sa cm
Length along the skeleton of the whole root system, root system component, or
root using a polyline length estimation technique.
Max Width (MaxW) trs, pr+, cr+ a, sa cm
Maximum horizontal width of the whole roots system or root system
component measured every 0.2 degrees of rotation.
Min Width (MinW) trs, pr+, cr+ a, sa cm
Minimum horizontal width of the whole roots system or root system component
measured every 0.2 degrees of rotation.
Max Depth (MaxD) trs, pr+, cr+ a, sa cm
Maximum vertical depth of the whole root systems or root system component
measured 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 cm
Vertical position of the center of mass of the whole root system or root system
component.
Exploitation Volume trs, zoi, pr+, cr+ a, sa cm3
Volume surrounding the root system or root system component at specified
radius minus the root system or root components volume. Adapted from
Berntson, 1994.
Exploitation Index trs, zoi, pr+, cr+ a, sa cm3
/cm
Ratio 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) of
root counts from all horizontal cross-sections through the entire root system or
root 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 from
Iyer-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 component
voxels that are 6-connected with a background voxel.
Current Traits Measured with RootReader3D Software
28. Trait Root Types Processing Units Description
SA/V Ratio trs, zoi, pr+, cr+ a, sa cm2
/cm3
Ratio 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
/cm3
Ratio of the volume of root system contained above one third depth of the root
system to the volume of root system contained below one third depth of the
root system.
Convex Hull Volume (CHV) trs a cm3
Volume of the convex hull that encompasses the whole root system. The convex
hull is found by summing the convex hulls of all horizontal cross-sectional slice
through the root system, where the convex hull is the smallest convex set of
voxels that contains all other root voxels in the slice. Adapted from Iyer-
Pascuzzi, et al, 2010.
V/CHV (Solidity) trs a cm3
/cm3
Ratio of volume to convex hull volume. Adapted from Iyer-Pascuzzi, et al, 2010.
Emergence Time pr, ecr, pecr, llr sa days
Average root emergence time for a given root type in relation to the planting
date.
Initiation Angle pr, ecr, pecr, llr sa degrees
Average horizontal root initiation angle for a given root type. Measured in
relation to gellan gum surface or horizontal.
Gravitropic Response pr, ecr, pecr, llr sa degrees/cm
Difference in the horizontal root angle divided by the length of the root or root
section.
Circumnutation pr, ecr, pecr, llr sa degrees/cm
Difference in the root turn angle divided by the length of the root or root
section.
Narrowness Index trs, pr+, cr+ a, sa cm/cm
Average ratio of minimum width to maximum width for each horizontal cross-
sectional slice through the whole root system. Slices that only contain the
primary root and its connected laterals are excluded.
Volume (V)
Count
trs, zoi, pr+, cr+
pr, ecr, pecr, llr
a, sa
sa
cm3
#
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 system
skeleton and is the number of skeleton voxels that have only one 26-connected
neighbor 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)
31. Exploring Rice Root
Architecture in 3 Dimensions
Using a Diverse Set of Oryza
sativa and Oryza rufipogon
Accessions
Randy Clark – Oryza sativa
Janelle Jung – Oryza rufipogon
Randy ClarkJanelle Jung
32. Primary Objectives
•To survey the range of variation in seedling 3-D root morphology observed
within the rice diversity panel using the gellan gum culture system
•To quantify and characterize seedling root growth and root system
architecture traits in a diverse set of 400 O. s. and 100 O. r. accessions using
RootReader 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, or
that are correlated with enhanced yield or stress tolerance
•To run association mapping analyses using the 950K SNP platform to
identify QTL controlling these root architecture traits in O. sativa & O.
rufipogon
Research Overview
33. NSF-TV Rice Diversity Panel
• 100 O. rufipogon accessions
Chosen for
• Genetic diversity
• Country of origin – natural range
• Vegetative trait variation – tiller angle and
stolon presence
• Reproductive trait variation – yield,
heading date, panicle and seed traits Geographic origin of O. r. panel accessions
Rice Diversity Panel -- 500 accessions – Association
Mapping
• 400 O. sativa accessions
Chosen for
• Genetic and geographic diversity
• Genomic and agricultural significance
34. 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/week
3 reps (individuals) per accession
1 rep at a time (30 accessions per batch)
O.s.: 28 unique, 2 internal controls
O.r.: 27 unique, 3 internal controls (1 O.r., 2 O.s.)
Time course: Imaging at 3, 6, 9, 12 days past planting
35. GWAS of Rice 3D Root Architecture Traits
• Have completed phenotyping rice for 3-D RSA traits under
control conditions in gel-based media. Phenotyped the
McCouch’s NSF-TV rice diversity panel (500 lines) and also
bi-parental mapping population (168 lines).
• That involved phenotyping approximately 2000 individual
plants in gellan gum cylinders.
• Roots imaged at 3, 6, 9, & 12 days after
planting to include dynamic
growth parameters.
•Randy is in Taiwan for the summer
where he as nearly completes 3D
reconstructions and quantification
of his 20 RSA traits.
•GWAS analysis will be completed
in Fall with 950k SNP chip.
36. •Will begin to phenotyping sorghum (and then maize) for 2-D and 3-D
RSA, including our sorghum association panel, and the Embrapa maize
breeding panel.
•Need to begin determining physiological relevance of specific RSA
traits – looking at their role in nutrient (P and N), and water acquisition.
•The gel-based system is not optimal for some stresses such as P
deficiency and drought – thus we are developing a sand-based culture
system where we control water potential or P availability for subsequent
analysis of 2D RSA and shoot/root biomass under stress (P efficiency and
drought 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)?
Agricultural
Research Service
Generation Challenge
Program