Discovery and Development of Alleles Contributing To

Sorghum Drought Tolerance

GCP Project G3008.05 PI: Andy Patterson

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)

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 ChinaG11-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)

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

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

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

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

Drought Tolerance Measured as Degree of Stay Green Trait

90% of stay green 65% of stay green

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.

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)

• 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

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

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.

Exp. 1 – Inbred lines “per se”

Painel Janaúba 2009

Mixed Model Analysis – REML/BLUP (Grain yield - kg/ha )

Components Drought Well-watered

Genetic variance 44999.54** 316252.68**

Error Variance 37938.29 293744.18

Heritability 0.83 0.81

Accuracy 0.91 0.90

Mean (u+g) 255.7 875.7

Yield reduction 70%

Correlation across drought and well-watered conditions = 0.69

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 + 389,64R2 = 0,4879

r = 0,698

-100

400

900

1400

1900

2400

2900

-100 100 300 500 700 900 1100kg

/ha

-W

ell-w

ate

red

co

nd

itio

n

kg/ha - Drought condition

L20

L98-CIM-2-46

L26L3

228-3

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

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

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

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%

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 G

rain

yi

eld

u

nd

er

we

ll-w

ate

red

co

nd

itio

n (

kg/h

a)

Grain yield under drought conditions (kg/ha)

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.

Analysis of Root System Architecture in

Three Dimensions

Clark RT, MacCurdy RB, Jung JJ, Shaff JE, McCouch SR, Aneshansley DJ, Kochian LV. 2011. 3-Dimensional root phenotyping with a novel imaging and software platform. Plant Physiol 156: 455-465.

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

Tradeoffs Between Phosphorus and Water Acquisition

Low P

Sufficient Water

Sufficient P

Low Water

Jonathan Lynch, Penn State University

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

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

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

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)

Dynamic Analysis of 3D Root System Development

D1 D2 D3 D4 D5 D6 D7 D8 D9 D10

D1 D2 D3 D4 D5 D6 D7 D8 D9 D10

D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 0

450

400

350

300

250

200

150

100

50

Len

gth

(cm

)

D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 0

450

400

350

300

250

200

150

100

50

Len

gth

(cm

)

Primary

Embryonic Crown

Post-Embryonic Crown

Lateral

Primary

Embryonic Crown

Post-Embryonic Crown

Lateral

Azucena

IR64

Azucena IR64

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 Clark Janelle Jung

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

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

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

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.

• 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)?

AgriculturalResearch Service

Generation Challenge

Program