Nitrogen use efficiency in sorghum
Ismail Dweikat
University of Nebraska
SORGHUM
Sorghum bicolor L.
5th most grown crop in the world
USES
214 Million bu in 2011 (USDA)
Nigeria 13% India 11% Mexico 11%
US 10%  KS TX OK SD NE
 Cereal crop species such as sorghum, wheat, maize and
rice, require large inputs of nitrogenous fertilizers in
order to maximize yield
Nitrogen Fertilizer Recommendations for Grain Sorghum
Expected Yield (Bushels per Acre)
Soil Nitrate-N
40
60
45
20
2% soil organic matter
70
90
110
135
40
60
85
105
155
130
180
150
200
170
220
195
9
ppm
2
4
6
8
10
12
14
80
100
120
140
160
Pounds per N to apply per acre
180
200
30
55
75
100
120
140
165
5
25
50
70
90
115
135
20
40
65
85
110
10
35
55
80
5
30
50
16
18
N accounts for the highest costly input, needs to be reduced to increase the profit
20
 Nitrogen is one of the most important plant nutrients
 N assimilation and remobilization is essential in plant growth and development
44 M MT increase of food production by 2050
Expected increase in N fertilizer 3 Fold
~ 30 – 50% is taken up by the plant
Most N is lost
 Surface run off
 Leaching of nitrates
 Atmospheric NOx NH3
Producer
Environment
contamination
input
Increase NUE
Nitrogen use efficiency:
Objective 1: Identify quantitative trait loci (QTLs) analysis and
marker identification for nitrogen use efficiency (NUE) in
advanced using CK60, China17, and SanChi San
Objective 2: Identify novel candidate genes for NUE using
proteomic and gene expression profiling comparisons of high
and low NUE RILs. Candidate genes will be brought into the
pipeline for transgenic manipulation of NUE
Objective 3: We have transform sorghum using glutamine
synthetase (GS), glutamate synthase (GOGAT), Alanine
aminotransferase(ALA-AT) and maize dof1 transcription factor
genes to enhance NUE . We are in the process of genes
stalking
Table 2. NADP-Malic enzyme activities (JfctS.E.) in leaves of two China and two U.S. derived sorghum lines grown in the greenhouse at
two N levels. Values are calculated on either a protein or leaf area basis
Line
HighN
LowN
Protein
nmol min~' mg~'-
Area
nmol min cm~
Protein
Area
nmol min~' mg~'
nmol min""1 cm""2
China 17
2662±331
16.9±0.05
3338±20
0.50±0.03
San Chi San
CK60
Tx623
Mean
1979±161
927±126
1477±89
1761±177
17.9±0.64
24.8±4.25
25.1±1.37
21.2±1.58
2468±256
1936±146
2547±350
1822±193
3.90±0.14
6.27±0.47
4.81±1.37
3.87±0.50
Table 3. PEPcase enzyme activities (£tS.E.) in leaves of two China and two U.S. derived sorghum lines grown in the greenhouse at two N
levels. Values are calculated on either a protein or leaf area basis
Line
HighN
LowN
Protein
Area
nmol min~' mg~'
nmol min~' cm~
2
Protein
nmol min~' mg~'
Area
nmol min~' cm~2
China 17
29.1 ±8.3
3.65±1.57
41.1±5.6
0.59±0.05
San Chi San
CK60
Tx623
Mean
17.1±1.6
44.4±6.0
59.4±2.8
37.5±4.7
1.50±0.15
11.58±1.53
10.24±0.33
6.74±0.90
28.ldhO.9
I0.8±2.4
7.5±1.2
16.9±2.5
0.14±0.02
0.35±0.07
0.15±0.02
0.31±0.04
The China lines averaged approximately 94 g biomass g−1 N while the U.S. lines averaged 85 g g−1
when grown with N stress. This compared to 77 g g−1 and 76 g g−1,respectively, for these contrasting
groups at normal N .
Maranville and Madhavan. Plant and soil 202
QTL mapping for nitrogen use efficiency (NUE) traits
Population development:
U.S line Ck60
China lines San Chi San, China 17
•
210 F6 RILs (Ck60 X San Chi San),
•
136 F6 RILs (Ck60 X China 17)
Genetic linkage map
2 week seedlings grown under 0% N
•
Genotyping By Sequencing facility, Cornell University
•
844 SNPs (Ck60 X San Chi San),
•
645 SNPs (Ck60 X China 17)
• Mapping population development
Ck60
China-17
136 F7 RILs
Phenotypic characterization of RILs
•
Mead, NE
•
Alpha lattice incomplete Block Design with 2 reps
Normal-N field (100Kg/ha fertilizer
with soybean rotation)
Low-N (no fertilizer, rotated with oats
in 2011 and Maize in 2012)
Phenotypic characterization of RILs
•
Mead, NE
•
Low N (0% synthetic fertilizer, rotated with oats in 2011 and Maize in 2012)
•
Normal N field (100Kg/ha fertilizer with soybean rotation)
•
Alpha lattice incomplete Block Design with 2 reps
14 x 15 incomplete blocks for Ck60 x San Chi San lines (210),
12 x 13 incomplete blocks for Ck60 x China 17 lines (136) with parents
•
50 seeds per line were used
•
planting date was same in both fields
Phenotypes
•
Measured in 3 randomly selected plants per plot (in two
reps & two locations)
•
Leaf chlorophyll concentration
 at 3 stages- before flowering, during flowering and after
flowering
•
Anthesis date (days)
•
Plant height (cm)
•
Fresh and Dry weights of stover, head (g)
•
Moisture content of stover (MC1) and Head (MC2)
•
Total biomass yield (t/ha)
•
Grain Yield (t/ha)
•
Test weight (g)
•
Grain to stover ratio
Data Analysis
ANOVA : Across two NN environments in Ck60 x San Chi San population (pop1)
Source of
variation
Line
Env
Rep(Env)
Blk(Env*
Rep)
Env*Line
Residual
df
Chl1
Chl2
Chl3
PH
AD
MC1
207
1
2
33.2**
457.68
104.7*
41.9***
851.3**
33.7553
62.8**
9218***
4.64
1985*** 34.5***
26.0***
178435
19309*** 1628
18042*** 34.3**
636***
54
19.5***
15.1**
38.5**
433.8***
4.72
172
325
20.6***
7.78
22.4***
9.03
41.9***
23.95
971***
113.4
18.4***
4.43
MC2
BY
GY
TW
GS
86.32
32.6**
9598
8.49
6792*** 4.35
6.97**
11.3
0.87
22.9*
0.24*
13674** 0.36
208*** 0.58*
15.8***
44.8*
15.3**
1.78
7.16
0.14
16.4***
6.07
69.9***
28.71
21.8*** 4.66***
9.48
1.73
17.7***
5.44
0.17
0.15
Chl-1, Chl-2, Chl-3 (chlorophyll-1, 2, 3), PH (plant height), AD (anthesis date), MC1 (stover moisture content), MC2 (head moisture content), BY
(biomass yield), GY (grain yield), TW (test weight), and GS (grain/stover) df, degrees of freedom; ***p < 0.0001; **p < 0.01; *p < 0.05
ANOVA : Across two LN environments in Ck60 x San Chi San population (pop1)
Source of
variation
df
Chl1
Chl2
Chl3
PH
AD
MC1
MC2
BY
GY
TW
GS
Line
207
24.4**
49.8**
58.8**
1793***
221***
30.0***
195.7***
12.0**
2.51**
37.0***
0.11***
Env
1
2438*
25638**
39857**
984.1
47395***
428.4
70.30
942.5
371**
8075
15.4*
Rep(Env)
Blk(Env*
Rep)
Env*Line
2
140**
115
247**
394.0
49.85
327***
8625***
93.2**
4.38
882***
0.50**
54
14.4
30.8**
32.9*
280*
71.3**
16.1**
85.2*
7.17*
1.38**
19.2**
0.04
172
15.2**
29.5**
35.7**
559***
67.5***
16.3***
102.3***
7.69***
1.6***
16.4**
0.05***
Residual
324
11.2
18.6
22.1
192.6
36.07
8.99
55.54
4.72
0.83
10.5
0.03
QTL analysis for Ck60 x San Chi San population (pop1)
C1
C3
C4
C5
C6
C7
C8
C9
C10
qChl3-10a
qChl1-3
qMC1-1
qBY-3
qChl1-2
qGY-10a
qGY-9
qChl3-10b
qChl1-10b
qPH-9a
qChl1-10a
qAD-9
qMC2-9
qMC1-8
qGY-8
qBY-7
qTW-3
qMC2-1
qAD-1b
qGY-2
qGY-10b
qPH-6
qBY-8
qTW-4
qAD-2
qPH-3a
qAD-3
qPH-2b
qPH-2a
qTW-1 qGS-1
qAD-1a
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
230
C2
Chl- (chlorophyll 1, 2 and 3), PH (plant height), AD (anthesis date), MC1 (stover
moisture content), MC2 (head moisture content), BY (biomass yield), GY (grain
yield), TW (test weight), and GS (grain/stover)
Data Analysis
ANOVA : Across two NN environments in Ck60 x China17 population (pop2)
Source of
variation
Line
df
Chl1
Chl2
Chl3
PH
AD
MC1
MC2
BY
GY
TW
GS
130
50.9***
41.9***
105.3***
3539
49.6***
34.3**
123.9***
49.4***
6.8***
28.0***
0.08**
Env
1
626.9
4276***
17016***
12913
11333***
347.6
4500
271.6
32.8*
946.9
0.07
Rep(Env)
2
89.1*
9.93
57.8
26255**
55.6*
191.1**
2501***
34.6
2.57
1483***
0.02
Blk(E*R)
44
12.5
12.0*
40.45***
2411***
11.3
14.8
31.7
13.1
2.43*
5.69
0.02
Env*Line
104
15.6**
18.15***
58.2***
3554***
20.5**
21.8**
59.3***
19.6***
3.2***
10.5***
0.048***
Residual
190
9.74
8.06
16.7
780
12.8
12.7
26.7
10.5
1.54
5.2
0.02
Chl-1, Chl-2, Chl-3 (chlorophyll-1, 2, 3), PH (plant height), AD (anthesis date), MC1 (stover moisture content), MC2 (head moisture content), BY
(biomass yield), GY (grain yield), TW (test weight), and GS (grain/stover) df, degrees of freedom; ***p < 0.0001; **p < 0.01; *p < 0.05
ANOVA : Across two LN environments in Ck60 x China17 population (pop2)
Source of
variation
Line
df
Chl1
Chl2
Chl3
PH
AD
MC1
MC2
BY
GY
TW
GS
130
27.2***
45.6**
87.7**
4475***
167.4***
32.1
238.0***
15.0**
1.97**
32.7***
0.05*
Env
1
360.5
16104***
24768**
4740.9
54521***
420.4
264.0
435.9*
163.3***
368.1
6.32*
Rep(Env)
2
87.7*
23.3
131.7*
771.4
48.85
462.1***
670.5**
21.4
0.16
1779***
0.22**
Blk(E*R)
44
16.6*
19.1
18.66
412.3**
36.67
18.7
35.0
5.9
0.69
6.14
0.01
Env*Line
Residual
104
190
12.1
10.7
27.3***
13.9
44.03***
15.13
1000.9*** 46.8*
189.9
31.78
31.6***
13.5
66.2***
34.2
8.87**
5.5
1.17**
0.75
9.48**
5.67
0.039***
0.02
QTL analysis for Ck60 x China17
population
• QTLs for PH, dry biomass (Ritter, 2008)
• days to anthesis (Srinivas et al., 2009)
• EST marker Drenshbm-19 encoding
ETHYLENE INSENSITIVE3-1 (EIL-1)
• Ma3 (Childs et al.,1997)
Putative genes
TOPLESS-related 1 (Sb01g040800)
QTL analysis for Ck60 x San Chi San population
C1
C3
C4
C5
C6
C7
C8
C9
C10
qChl3-10a
qChl1-3
qMC1-1
qBY-3
qChl1-2
qGY-10a
qGY-9
qChl3-10b
qChl1-10b
qPH-9a
qChl1-10a
qAD-9
qMC2-9
qMC1-8
qGY-8
qBY-7
qTW-3
qMC2-1
qAD-1b
qGY-2
qGY-10b
qPH-6
qBY-8
qTW-4
qAD-2
qPH-3a
qAD-3
qPH-2b
qPH-2a
qTW-1 qGS-1
qAD-1a
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
230
C2
Chl-(chlorophyll 1, 2 and 3), PH (plant height), AD (anthesis date), MC1 (stover
moisture content), MC2 (head moisture content), BY (biomass yield), GY (grain
yield), TW (test weight), and GS (grain/stover) .
Validation of QTLs across two populations
C9
Chromosome-6
C5 C6
C7
C6
C8
C7
C4
C5
Chromosome-3
C3
2
C4
C3
C2
qPH-2a
qChl3-10a
qPH-9a
qGY-8
qGY-9
qGY-10a
qChl3-10b
qChl1-10b
qGY-10b
qAD-9
qMC1-8
qGY-9
qGY-8
qChl1-2
qBY-3
qChl1
qChl1-2
qChl1-3
qTW-3 qBY-3
qMC1-8 qBY-7
qBY-7
qTW-3
qGY-2
qGY-2
qMC2-9
qGY-10a
qPH-9a
qChl3-10b
qChl1-10a
qChl1-10b
qChl3-10a
qAD-2
qMC2-9
qChl1-10a
qAD-9
qGY-10b
qPH-6
qTW-4
qPH-2b
qAD-3
qAD-3
qPH-3a
qPH-3a
qTW-4
qPH-6
qBY-8
qBY-8
Genes
DW2 (Srinivas 2009)
Ma1 (Paterson 1995)
qPH-2b qAD-2
qPH-2a
C10 yield, seed
QTLs for grain
C10
weight and plant height
(Srinivas et al. 2009)
C9
C8
PopII
PopI
PopII
PopI
Validation of QTLs across populations
qChl3-10a
qBY-3
qMC1-1
qChl1-3
qChl1-2
qGY-10a
qChl3-10b
qChl1-10b
qGY-10b
qPH-9a
qChl1-10a
qAD-9
qGY-9
qGY-8
qMC1-8
qBY-7
qGY-10a
qChl3-10b
qMC2-9
qGY-10b
qPH-9a
qChl1-10a
qAD-9
qGY-9
qGY-8
qMC2-1
qAD-1b
qMC1-8
qGY-2
qMC2-9
qTW-3
qChl1-10b
qChl3-10a
qPH-6
qBY-8
qTW-4
qAD-3
qPH-2b
qPH-2a
qAD-1a
qBY-8
qTW-1 qGS-1
qAD-2
qPH-3a
Grain yield and Plant
height QTLs Dw3 gene
(Srinivas et al.,2009)
qPH-6
qBY-7
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
230
C10
C8
C9
Chromosome-8
C7
C6
C5
C10 C4
C3
C7
C8
C9
C1
C2
Chromosome-7
C6
C5
PopII
PopI
PopII
PopI
PopI
C5 C6
C7
C8
PopII
C9
C10
Chromosome-9
QTLs for PH, flowering time (Lin et al. 1995)
qGY-10a
qChl3-10b
qChl1-10b
qGY-10b
qGY-9
qGY-8
qMC1-8
qBY-7
qPH-9a
qChl1-10a
qAD-9
qMC2-9
qChl3-10a
qBY-8
qPH-6
Trait
Chl1
Chl2
Chl3
PH
AD
BY
GY
R2 (%)
37.80
50.80
37.30
44.80
14.70
33.80
17.50
Conclusions
• Five genomic regions consistently detected across
environments
• Candidate genes
• Marker assisted selection
Objective 3: Identification of differentially
expressed exons (DEGs) for NUE in known
low-N tolerant and sensitive genotypes of
sorghum
Phenotypic performance
Genotype
Plant Height
Biomass Yield
Grain Yield
NN
LN
NN
LN
NN
LN
RIL-1
113
95
4.05
3.00
1.25
0.90
RIL-2
132
83
9.00
3.05
3.05
1.35
RIL-3
149
77
7.50
3.20
1.60
1.12
RIL-4
147
98
7.55
3.45
3.15
1.71
RIL-5
122
109
8.10
3.65
2.45
0.88
CK60
115
91
6.60
3.10
2.90
1.13
BTx623
140
126
8.15
3.99
2.84
1.16
KS78
132
76
10.10
5.90
4.14
2.19
SanChiSan
157
137
16.50
7.60
6.40
4.97
China-17
170
157
13.80
7.25
5.48
3.90
RIL-6
124
93
13.00
11.35
6.17
4.55
RIL-7
152
122
13.20
9.60
3.95
0.95
RIL-8
161
125
13.40
9.40
3.35
2.62
RIL-9
185
168
17.70
15.10
6.15
5.18
RIL-10
163
137
18.40
16.45
7.74
6.65
Low NUE RILs
Sensitive
Sorghum Inbreds
Tolerant
High NUE RILs
Seedlings growth under (0%) N conditions
Differentially Expressed Genes
1) Ck60
2) Tx623
7) Low bulk
vs
3) San Chi San
4) China17
5) KS-78
6)High bulk
Candidate genes in the QTL regions
• QTLs for PH, dry biomass (Ritter, 2008)
• days to anthesis (Srinivas et al., 2009)
• EST marker Drenshbm-19 encoding
ETHYLENE INSENSITIVE3-1 (EIL-1)
• Ma3 (Childs et al.,1997)
Putative DEGs
Gene
3/1
4/1
5/1
6/1
Annotation
Sb01g041180
5.3
3.3
2.7
2.7
HSP21
Sb01g048100
4.4
4.2
3.4
3.2
lysm domain GPI-anchored
protein
Sb01g044810
-3.7
-3.0
-0.6
-1.8
MADS-box family gene
Characterization and identification of lead events based on
greenhouse phenotype studies for use in down-stream field
evaluations.
The modulation of nitrogen metabolism requires the understanding
of the function and the means of regulation of the different enzymes
involved in the process of nitrogen (N) uptake, assimilation and
remobilization in order to develop plants with enhanced efficiency
in nitrogen utilization.
Glutamine synthetase (GS) is a key enzyme in N metabolism.
GS together with glutamate synthase (GOGAT) are the main route
for ammonium
Alanine aminotransferase (ALa-AT) has been shown to allow the
maintenance of the carbon-nitrogen balance in plants through the
translocation of pyruvate or alanine
Dof1 (DNA binding with one finger), which regulates C-skeleton
production, including PEPC. These C-skeletons can then be utilized
in N metabolism.
SORGHUM
WHEAT
TX430
CBO37
Agrobacterium-mediated transformation
NTL4/Chry5
C58C1/pMP90
SORGHUM
EVENTS
WHEAT
EVENTS
pPTN1037
13
8
pPTN1034
21
13
pPTN1031
11
33
pPTN1040
30
15
pPTN1033
19
48
pPTN1036
21
11
Molecular characterization of transgenic sorghum and wheat
7.7 -6.2 -5.5 --
3—
2—
1.5—
1—
Southern blot, reprobe, Northern Blot
pPTN1033 sorghum. DNA digested
with Sst I.
Probe: pUC 57-OsGSI digested with
Xho I and Eco RI (666 bp)
Southern Blot, Northern blot, RNA.
pPTN1031 DNA digested with Eco RI.
Probe: pUC 57-HV-ALA-AT digested with
Xho I (504bp)
S/N Blot pPTN1040 sorghum plants.
Probe: pUC 57-HV-ALA-AT digested with Xho I (504bp)
(+ control)
TX 430 (- control)
ZG 123 3-4a T1-6
ZG 123 3-4a T1-3
ZG 127 3-3a T1-4
ZG 127 3-3a T1-2
ZG 120 4-8a T1-6
ZG 120 4-8a T1-2
ZG 120 1-2a T1-5
ZG 120 1-2a T1-3
NPTII ELISA
Southern/Northern blots
MW
1.
2.
SELECTION OF LEAD EVENTS
PCR
SPECIFIC ENZYME ACTIVITY
GS
FeCl
G
S
3
Glutamine synthetase activity in sorghum
pPTN1033 UBI4 + OsGS1
540nm
20.00
18.00
16.00
14.00
12.00
10.00
8.00
6.00
4.00
WQ18 8-1-1 (T1-7 T2-1) T3
WQ18 3-2-1 (T1-5 T2-5) T3
WQ18 3-1-1 (T1-1 T2-1) T3
PP4 24-1b (T0) T1
0.00
TX430
2.00
PP1 2-6a (T0) T1
G
S
Glutamine
GS activity
µmol ΥGHA/min/mg protein
Acyl phosphate
intermediate
Glutamate
ϒ Glutamyl
hydroxamate
Hydroxylamine
Glutamine
0.350
0.300
0.250
0.200
0.150
0.100
0.050
0.000
Ala AT activity
µmol NADH/min/mg protein
TX430
ZG159 1-2b (T1-7) T2
ZG158 2-3a (T1-4) T2
ZG158 2-2a (T1-7 T2-2) T3
ZG158 1-1a (T1-8) T2
ZG151 4-5a (T1-5) T2
2-oxoglutarate
ZG151 4-1a (T1-7) T2
ZG151 3-12a (T1-6) T2
ZG151 3-10a (T1-4) T2
Alanine aminotrasferase activity in sorghum
pPTN1031 UBI4 + HvAlaAT
ZG151 2-15a (T1-6) T2
Pyruvate
ZG151 1-24a (T1-7 T2-1) T3
TX430
Glutamate
ZG127 3-3a (T1-2) T2
ZG120 4-8a (T1-6) T2
ZG120 4-4b (T1-5) T2
ZG120 2-2a (T1-4 T2-1) T3
ZG120 4-17b (T1-1 T2-1) T3
ZG120 1-2a (T1-3) T2
WQ20 2-1-1 (T1-3) T2
Ala AT activity
µmol NADH/min/mg protein
ALA
AT
Alanine
NADH
LDH
NAD+
Lactate
Alanine aminotrasferase activity in sorghum
pPTN1040 OsANT1 + HvAlaAT
0.25
0.2
0.15
0.1
0.05
0
Example of the
pyramiding scheme
for the NUE
putative genes
Conclusions and future work
 A set of transgenic events have been developed in sorghum overexpressing
enzymes involved in N/C metabolism.
 Lead events from this set are currently under selection based on number of inserts,
levels of expression and enzyme activities.
 Moreover, an appropriate N regime has been determined to phenotype the selected
lead events for NUE. The N regime selected was 5% N (0.75mM N) .
 Furthermore, a set of gene stacks have been developed and its characterization is
under progress. NUE evaluation for remaining events will be started.
 Down-stream field evaluations of selected events and gene stacks for different
levels of nitrogen conditions.
Ethanol plants turning toward grain sorghum
The future is bright
Dorchester Co-op workers remove a pile of grain sorghum in this 2000 file photo,
Lincoln Journal Star March 4, 2013
Acknowledgment
NE Grain Sorghum Board
NSCP
DOE
John Rajewski
Malli Geli
Tom Clemente
Pamela Peña