UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
Discovering favourable gene resources for crop improvement
1. Development of Agricultural Science
Discovering Favourable Gene Resources
for Crop Improvement
Ruilian Jing
jingrl@caas.net.cn
The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Science
Chinese Academy of Agricultural Sciences (CAAS)
Specific Topic for Student Abroad • Oct. 20, 2011
3. Feeding the 9 billion people expected to inhabit our
planet by 2050 will be an unprecedented challenge
Special issue 2010
Special issue 2007
Special issue 2003
Special issue 2008
4. “Take one world already being
exhausted by 6 billion people. Find
the ingredients to feed another 2
billion people. Add demand for more
food, more animal feed and more
fuel. Use only the same amount of
water the planet has had since
creation. And don’t forget to
restore the environment that
sustains us. Stir very carefully.”
Margaret Catley-Carlson
2008-2009 Chair of World Economic
Forum Global Agenda Council on
Water Security
World Economic Forum, Davos
January 2009
5. Area-Total yield-Yield per unit of cereal crops
in China during 1952-2008
Area
(10 M ha.)
Total yield
(100 M ton)
Unit yield
(ton·ha-1)
1950’ 1960’-1990’ 1998-
Zhensheng Li
7. To keep pace with food consumer
demand, muti-favourable genes
should be pyramided in crop cultivars.
To discover favourable gene
resources for improving crop plants.
8. The “green revolution
gene” is an allele of gene
which control plant height.
0nly a base pair difference
between wild type and
mutant type.
Finding and utilization of
this one base mutation
resulted in a “Green
Revolution”
Nature, 1999, 400: 256-261
9. Nature allele variation is widely
present in plant germplasm.
Difference of fruit weight of tomato
between wild type and cultivar type
is a few base pair change in the
promoter region of gene fw2.2.
Science, 2000, 289: 85-88
10. Hybrid rice successful utilization in
China due to a cytoplasmic male sterility
gene discovered in wild rice
Wild rice Hybrid rice
22. Germplasm Resources
?
? Gene Resources
?
?
?
?
How can we discover
beneficial genes？
More than 7 million accessions have been collected and
conserved in the germplasm banks in the world. How to
find the favourable genes from the huge number of plant
germplasm resources for plant breeding?
26. An unexpectedly abrupt
decline in the supply of
water for China’s farmers
poses a rising threat to
world food security.
WORLD•WATCH July/August 1998
27. China: Precipitation
About 50% of land area is arid and semi-arid in China, where
6 667 000 ha of rainfed wheat are grown with low and variable yield.
Developing drought-tolerant cultivars is an efficient way to stabilize
wheat production and ensure food security in China and the world.
28. Total drought area
10.5 Mha
8.8 Mha
Average year: 1.7 Mha drought area
Provinces suffered from drought stress
in the early spring 2009
29. Qingtu Lake in Min Qin, from lake to desert in 40 years
Reeds and remaining shells
34. Drought seriously limits crop production in
many areas of the world, especially in China.
More than 70% water is used in the crop
production in China.
Water shortage
Big population
Crop drought-tolerance improvement
is a challenging task for breeders.
Discover and use drought-tolerant
gene resources in the crop breeding
can contribute to improvement for
water-limited environments.
35. Water shortage in agriculture
‘Blue Revolution –
more crop for every
drop’
Norman E. Borlaug
Nobel Peace Prize Laureate 1970
36. 1. Understanding the molecular
mechanisms of water stress responses
Difference in dehydration tolerance and drought
tolerance
• The former is the capability to maintain functions
and minimize damages under dehydration .
In reality, crop plants cannot survive for long under prolonged
dehydration. What we see are a short-term stress responses.
• The later is the ability to grow and yield under less
soil moisture.
This should be the trait of crops in drought-prone areas.
37. How can plant maintain turgidity with
declining soil water availability? The
molecular details about how the metabolic
genes are regulated in responses?
How can plant maintain their membrane
integrity under oxidative stress which is a
secondary stress derived from water
stress?
How are the other physiological functions
maintained or regulated as an integrative
response to water stress?
38. 2. Breeding cultivars to cope with
specific objectives
Drought breeding should be localized with
specific objectives to specific areas, such
as less irrigation, rainfed in semi-arid.
Conventional breeding is time consuming and labor
costly since it is a natural selection under drought
condition. However, large scale gene recombination
can be easily achieved.
39. 2. Breeding cultivars to cope with
specific objectives
Molecular breeding is more efficient but
the available magic drought-resistant
genes are very limited.
Genes for root traits should be tapped.
Drought tolerance is fundamentally related to the
capability to maintain water balance, much less
to the ability to tolerate dehydration.
40. Whole-plant responses to drought stress
Left: long-term or acclimation responses; right: short-term responses
(Chaves, et al., 2003)
41. Sensing, signalling and
cell-level responses to
drought stress
ABA-mediated responses
Non-ABA-mediated responses
Other mechanisms
(Chaves, et al., 2003)
43. Early generation selection methodologies
Visual selection ++ Leaf porometry
Canopy temperature Spectral reflectance
44. Factors affecting Canopy Temperature
Depression (CTD) in plants
Radiation
Biological Environmental
Clouds
Partitioning o
(T C)
H2O
CTD
Evaporation
Metabolism
Wind
Vascular
Transport
H2O (soil water availability)
(M Reynolds, 2001)
45. 5500
Grain yield (kg/ha)
5000
4500
4000
3500
3000
2500
2000
1500
5.0 6.0 7.0 8.0 9.0
Canopy temperature depression (oC)
The relationship of grain yield to CTD, mean of 2
sowings dates, Tlaltizapán, 1992-93, 23 genotypes.
(Amani, Fischer and Reynolds, 1996)
46. Selection for canopy temperature: to enrich
favourable alleles before yield testing
47. Use of CTD in early generation selection
- F4 bulks under drought stress (R. Trethowan)
- Following visual selection, CTD scores used to influence gene frequency
29
28.5
C a n o p y te m p p o s t
28
27.5
flo w e rin g
27
26.5
26
25.5
25
24.5
20 21 22 23 24 25 26
Canopy temperature vegetative
48. Complementing breeder selection with
canopy temperature
(Van Ginkel et al., 2008)
14
BREEDER
12 BREEDER+CTD
Individual number
10
8
6
4
2
0
6.3 6.8 7.3 7.8 8.3
Yield (t/ha)
49. Sampling soil core
To sample roots
To measure soil moisture profiles
CIMMYT
50. Models to quantify yield under abiotic stress
Drought yield =
Water Uptake x WUE x HI (partitioning)
(Passioura, 1977)
Irrigated yield =
Light Interception x RUE x HI (partitioning)
WUE: water use efficiency
RUE: radiation use efficiency
HI: harvest index
51. Generic model of stress adaptation under drought & heat
Photo-protection Water use efficiency (WUE) &
Radiation use efficiency (RUE)
Pigments for dissipation
of excess light energy, e.g. •Transpiration efficiency (drought only)
carotenoids measured • CID
using spectral reflectance •Heat tolerant metabolism (growth rate)
(RARSc) • Stay green (CHL)
• CO2 fixation rate (COND)
Early growth (pre-grainfill) Access to water by roots
(indicated by cooler canopies)
• Ground cover: measured with
spectral indices (NDVI & WI) • Under drought estimates water use
• Growth rate (BMA) • Under hot, irrigated conditions:
• Stem carbohydrates (CHO) estimates CO2 fixation and thus
radiation use efficiency
52. Physiological breeding: strategic crossing for drought
YLD = WU x WUE x HI (Passioura, 1979)
Photo-Protection Transpiration Efficiency
Leaf morphology
WUE of leaf photosynthesis
• wax/pubescence
• posture/rolling low 12C/13C discrimination
Pigments Spike/awn photosynthesis
• chl a:b
• carotenoids
Antioxidants
Partitioning (HI) Water Uptake
Partitioning to stem Rapid ground cover
carbohydrates • protects soil moisture
Access to water by roots
Harvest index • Ψ leaf
• Rht alleles • cool canopy
• (osmotic adjustment)
(Reynolds & Tuberosa, 2008. COPB)
60. Parents
Hanxuan 10
Drought tolerant
cultivar grown under
rainfed condition in
semi-arid region
Lumai 14
High yield potential
cultivar grown under
irrigated condition
Hanxuan 10 DH Lines
Lumai 14 (Hanxuan 10 × Lumai 14)
61. Water Regime Treatments for Phenotyping
Treatment: Rainfed/Drought stress
Control: Well watered
Traits for QTL Mapping
Agronomic traits (coleoptile length, early vigor, heading date,
flowering date, plant height, spike number per plant, kernel per
spike, spike length, seed setting, thousand-grain weight, plant
morphology and grain yield)
Physiological traits (stay-green, chlorophyll fluorescence, leaf
water status, canopy temperature, accumulation and remobilization
of stem water-soluble carbohydrates)
Anatomical structure (number and area of vascular bundles)
64. Integrated mapping of QTLs controlling
drought tolerance in wheat
S le : 7 re p e a ta tio n
F v /F o - W W (1 2 .0 9 % )
(1 7 .4 3 % ~ 2 2 .4 4 % )
R A L V B -D S (1 3 .1 6 % )
H e i (8 .4 9 % ~ 3 1 .0 4 % )
K w e (3 3 .3 9 % )
S le (9 .1 5 % ~ 1 8 .7 3 % )
K g n (1 5 .5 5 % ~ 2 9 .0 6 % )
K w e i (1 4 .0 6 % )
T s p ( 1 0 .0 7 % ~ 1 2 .2 5 )
P y i ( 8 .5 7 % )
H e i ( 9 .3 9 % ~ 2 1 .1 3 % )
P y i (1 0 .6 2 % ~ 1 9 .2 3 % )
S le ( 1 3 .6 2 % )
S s p ( 8 .8 6 % )
N U P - H N 2 (1 4 .0 % )
N U P - L N 1 (6 .0 % ) R P A T V B ( 1 3 .2 3 % )
R D W - H ( 1 1 .0 % ) S le ( 7 .8 % ~ 2 1 .9 7 % )
S p i ( 6 .5 9 ~ 1 0 .3 7 % )
C h lC (1 1 .6 8 % ) K g n ( 2 2 .6 2 % )
N S V B ( 2 1 .3 8 % ) S s p (6 .4 3 % ~ 1 4 .3 8 % )
N T V B ( 2 0 .3 6 % ) S p i (9 .3 7 % )
T s p (8 .0 9 % ~ 3 4 .9 3 % )
S s p (1 0 .8 9 % ~ 3 0 .9 7 % )
N L V B -D S
H e i (9 .3 2 % ~ 2 1 .7 9 )
(1 6 .0 5 % )
F m -D S ( 2 6 .5 8 % )
T s p ( 1 5 .7 1 % ~ 2 4 .5 3 % ) F v -D S (2 2 .9 9 % )
H e i ( 2 4 .5 3 % ~ 4 3 .4 5 % ) R F W (1 0 .3 7 % )
N U P -H (4 .3 % )
65. QTL validation in different populations
DH (Hanxuan 10×Lumai 14) RIL (Opata85×W7984)
67. QTL mapping
Mixed linear model was used to divide genetic
effects into additive main effects (a), epistatic main
effects (aa) and their environment interaction
effects (QE, including ae and aae).
Cao et al, 2001
68. QTLs for plant height during ontogeny in DHLs
Additive QTLs Epistatic QTL pairs
Traits Stages a b c d
Number A AE Number AA AAE
Unconditional S1 12 12 6 7 7 2
plant height S2 11 11 7 18 18 4
S3 12 12 7 19 19 3
S4 10 10 4 22 22 1
S5 10 10 5 20 20 2
Total 55 55 29 86 86 12
Conditional S1|S0 12 12 6 7 7 2
plant height S2|S1 3 3 3 4 4 3
S3|S2 4 4 3 4 2 3
S4|S3 1 1 1 3 1 2
S5|S4 6 5 5 5 3 3
Total 26 26 18 23 17 13
a QTL number with additive main effects;
b QTL number with additive environment interaction effects;
c QTL pair number with additive epistatic effects;
d QTL pair number with epistatic environment interaction effects.
71. 0.5
Component contribution
0.5
Component contribution
0.4
0.4
0.3
0.3
0.2
0.2
0.1
0.1
0
0 S0 S1 S2 S3 S4
S1| S2| S3
|
S4| S5|
S1
S3
S2
S4
S5
h^2(A) h^2(AE) h^2(AA) h^2(AAE)
Contributions of different genetic effects to
plant height during ontogeny in DHLs
72. Rht1
(Cadalen, 1998; QTLs Epi.
Huang, 2006;
Sourdille, 2003;
Liu, 2006; a e ae aa e aae
McCartney, 2005)
S1
S2
Rht12 (Ellis, 2005)
Un. S3
S4
Rht9 (Schnurbusch, 2003; S5
Ellis, 2005)
S1
S2
Con. S3
Rht2
(Cadalen,1998; S4
Huang, 2003, 2006; S5
McCartney, 2005;
Sourdille, 2003)
PH QTL clusters matched up to Rht genes in DHLs
73. Rht8 (Korzun, 1998)
Rht5
（Ellis,
2005）
Rht13
(Ellis 2005)
PH QTL clusters near Rht genes in DHLs
74. (Cadalen et al. 1998)
(Ellis, 2005)
PH QTL clusters on other chromosomes
75. (McCartney ，2005;
Cadalen, 1998;
Sourdille, 2003;
Quarrie, ,2006)
(Schnurbusch, 2003)
PH QTL clusters on other chromosomes
Wu et al., JXB, 2010, 61: 2923-2937
76. Association analysis of candidate PH QTLs
270 historical winter wheat accessions
60 candidate SSR markers in six chromosome regions
Rht8
Rht1
Rht12
Rht9
Rht2 Rht13
Ave. Dis. = 4.7 cM
Wheat, Consensus SSR, 2004
77. Associations of plant height developmental
behavior and the candidate markers
Total of 46 marker-trait associations were detected, among
them 13 associations were highly significant (P<0.001).
Five loci were also worked in DHLs.
6.5
6.0
5.5
-Log (P)>3
-Lg(P value)
5.0
4.5
4.0
3.5
3.0
2.5
2.0
m
2
2
1
1
m
2
1
3
4
3
3
2
H
H
H
H
TC
PH
PH
PH
PH
PH
H
PH
H
-P
-P
-P
-P
-P
-P
-D
5-
9-
9-
2-
5-
5-
09
09
09
09
43
49
49
24
24
30
49
49
43
c1
c1
c1
c1
fd
c3
m
m
m
m
m
fd
m
ar
ar
Xc
ar
ar
m
w
w
w
w
w
Xc
w
Xb
Xb
Xb
Xb
Xw
Xg
Xg
Xg
Xg
Xg
Xg
Associations
-Lg (P) value at different associations
80. Phenotypic effects of marker alleles
Xcfd23-4D Xgwm495-4B
A217 A220 A223 A155 A159 A163 A165 A167 A179 A181
10
P la n t h e ig h t a t m a tu r e ( c m )
5
0
-5
-10
-15
-20
PH under drought-stress PH under well-watered
82. Validation of Xwmc349 allelic effect
in ILs with Jinmai 47 background
Average variance
Allele Effect on PH IL No. Range of PH
to receptor
A99 -12.4 24 -19 ~ +14 0
A103 -11.1 6 -9 ~ +6 -2
Xwmc349 allele: A99(-12.4), A101, A103(-11.1), A105(+6.0)
83. Summary
Plant height is a typically quantitative trait
controlled by additive effects and epistatic
effects.
A list of marker-PH association was identified
in the chromosome regions of PH QTLs or
Rht genes detected in DHLs.
Allele effects have to be validated in multi-
genetic backgrounds.
84. Flow chart of suppression subtractive
hybridization (SSH)
Wheat seedling Data analysis
(-0.5MPa PEG-6000)
Test sequences
mRNA preparation
SSH 1, 6, 12, 24, 48h
cDNA synthesis cDNA libraries
Rsa I digestion Transformation
Adaptor ligation Vector ligation
First hybridization Second PCR amplification
Second hybridization First PCR amplification
85. Assessment of contigs from the cDNA libraries
responding to water stress by suppression
subtractive hybridization (SSH)
Known Unknown
cDNA Valid Total Uni- functional contigs
functional
library ESTs contigs contigs
contigs Number %
SSH 1h 1697 938 146 114 792 84.43
SSH 6h 1824 566 265 203 301 53.18
SSH 12h 1833 516 166 133 350 67.83
SSH 24h 1131 786 441 202 345 43.89
SSH 48h 1148 635 414 234 221 34.80
Total 6733 3441 1432 886 2009 58.38
Wheat seedlings were treated with -0.5MPa PEG-6000 for 1, 6, 12, 24, 48h, respectively.
86. Classification of genes that respond to water stress
1h, 6h, 12h, 24h and 48h
G1: Alcohol dehydrogenase
G2: Aldehyde dehydrogenase
SSH 1h G3: Ca2+-binding proteins
G4: Calmondulin binding proteins
1 / 19 G5: Carbohydrate metabolism-related proteins
G6: Cellular structure and organization-related proteins
G7: Cytochrome p450
1 1 G8: Detoxification enzymes
G9: Fatty acid metabolism-related proteins
G10: Ferritin
SSH 48h SSH 6h G11: Membrane proteins
1/26 G12: Osmoprotectant synthesis-related proteins
0 / 19 G13: Plant defence-related proteins
G14: Protease inhibitor
13 / 27 G15: Protection factors of macromolecules
G16: Protein kinases
2 2
G17: Protein phosphatases
G18: Protein synthesis-related proteins
G19: Proteinases
G20: Proteins involved in biosynthesis and metabolism of hormones
G21: Proteins regulated by various hormones
G22: Reproductive development-related proteins
SSH 24h 1 SSH 12h G23: Respiration-related proteins
0/17 1/24 G24: RNA-binding proteins
G25: Secondary metabolism-related proteins
G26: Senescence-related proteins
G27: Transcription factors
Black represents the number of shared/total classification in 5 cDNA libraries;
Red represents the number of classification shared by 2 bordering upon libraries;
Blue represents the number of special/total classification in the library.
87. Putative key classifications of differential
expressed genes from 648 Uni-genes
Protein Protein kinase Ca2+-binding
phosphatase 4.01% protein
2.16% 0.62%
Transcription Calmondulin
factor binding protein
0.46%
6.17%
Detoxification
enzyme
3.40%
Plant defence-
Others related protein
65.74% 8.33%
Membrane protein
9.11%
Pang et al., Acta Agronomica Sinica. 2007, 33:333-336
88. Case 1: TaPP2Ac (protein phosphatase 2Ac)
TaPP2Ac
identified from cDNA
libraries at 6h and
12h, plays important
roles in cellular
growth and signalling,
ubiquitously
expressed in plants.
90. PP2Ac Function
CTR 1, a negative regulator of the ethylene response pathway in
Arabidopsis, encodes a member of the Raf family of protein kinase.
(Kieber et al., Cell, 1993, 72: 427-441)
92. Overexpression of transgenic TaPP2Ac-1
tobacco under water stress condition
Before water stress Water stress 12 d
WT GFP TaPP2Ac WT GFP TaPP2Ac
Water stress 18 d Water stress 24 d
WT GFP TaPP2Ac WT GFP TaPP2Ac
93. Transgenic TaPP2Ac-1 tobacco plants enhance
drought tolerance under water deficit
Time of drought stress (d) Physiological trait
RWC: relative water content; MSI: membrane stability index;
WRA: water retention ability; WUE: water use efficiency
94. DT of transgenic TaPP2Ac-1 Arabidopsis
Salt tolerance
WT: wild type
&: transgenic line
P: GFP
Xu et al., Annals of Botany. 2007, 99:439-450
95. Chromosome location of TaPP2Ac-1 by the wild relative
species and nulli-tetrasomics lines of Chinese Spring
(A) TaPP2Ac-1-1 with PCR specific primer on A genome;
(B) TaPP2Ac-1-3 with PCR specific primer on D genome;
(C) TaPP2Ac-1-2 with PCR specific primer on S genome;
(D) TaPP2Ac-1-2 with PCR-RFLP (TaqI) on S genome.
M: DNA marker; H: Hanxuan 10; L: Lumai 14; O: Opata 85; W: W7984;
AB: Triticun durum DS107(AABB); A: T. urartu UR203(AA); B: Ae.speltoides 2046(SS);
D: T.tauschii Y2009(DD); CS: Chinese Spring; N4AT4B, N4AT4D, N4BT4D and N4DT4B:
nulli-tetrasomics lines of CS.
96. 4D
M: DNA marker
O: Opata85
W: W7984
Schematic illustration of PCR-RFLP product of
specific-sequence of D genome between two
parents of RIL population
EcoR V Hind III Noc I
ABD
ABD
ABD
AB
AB
AB
D
D
D
A
A
A
S
S
S
Three copies of TaPP2Ac was identified in
hexaploid wheat by Southern Blotting
Map of TaPP2Ac-1 on chromosome 4DL
97. Case 2: TaABC1L mapping in RILs
Genetic mapping of TaABC1L gene based
on CAPS marker and AS-PCR marker
Wang et al., JXB, 2011, 62:1299-1311
98. Case 3: TaSnRK2.7 Cloning, location and functional
analysis of a gene involved in abiotic-stressed responses
Minimal ABA signaling pathway Structure prediction
a. In the absence of ABA, the phosphatase PP2C is free to 10-33: Protein kinases ATP-binding
inhibit autophosphorylation of a family of SnRK2 kinases. region signature
b. ABA enables the PYR/PYL/RCAR family of proteins to bind to 119-131: Serine/Threonine protein kinases
and sequester PP2C. This relieves inhibition on SnRK2, which active-site signature
becomes auto-activated and can subsequently phosphorylate
and activate downstream transcription factors (ABFs) to initiate
transcription at ABA-responsive promoter elements (ABREs).
(Sheard and Zheng, 2009. Nature 462, 575-576)
99. Southern blotting
One copy of TaSnRK2.7 might exist in each of
the three genomes of common wheat.
Chromosome location
Phylogenetic tree of TaSnRK2.7 and of TaSnRK2.7-A copy
SnRK2s from other plant species
Phosphorus utilization efficiency
TaSnRK2.7 was clustered in subclass I, Accumulation efficiency of stem
bootstrap values are in percentages. water-soluble carbohydrates
Zhang et al., Gene, 2011, 478:28-34
100. TaSnRK2.7 was expressed strongly in seedling
roots, weakly in booting spindles, and marginally
in seedling leaves and heading spikes.
The expression levels of
TaSnRK2.7 increased
significantly under salt,
PEG and cold stress
conditions, but might be
not activated by ABA.
Expression patterns of TaSnRK2.7 in various tissues (A)
and in response to various treatments (B)
101. Subcellular localization
TaSnRK2.7-GFP was present in the
cell membrane, cytoplasm and nucleus
Stress tolerance assays
of TaSnRK2.7
over-expressing
transgenic Arabidopsis
Zhang et al., JXB, 2011,
62:975-988
102. Drought tolerant
Drought sensitive
Phylogenetic tree representing TaSnRK2.7 haplotype
relationship among 50 wheat accessions
Zhang et al., Gene, 2011, 478:28-34
103. Case 4: Ta6-SFT Cloning, location and functional
analysis of a gene involved in fructan synthesis
6-SFT 1-FFT
levan neoseries 6G-kestotriose inulin neoseries
β(2-1) β(2-1)
6G-FFT
6-SFT 6-SFT 1-SST 1-FFT
levan 6-kestotriose SUCROSE 1-kestotriose inulin
β(2-1) β(2-1)
6-SFT
6-SFT 1-FFT
mixed-type levan bifurcose mixed-type levan
β(2-1) and β(2-6) 6-SFT β(2-1) and β(2-6)
FEH
1-FFT
levan
β(2-6)
Model for fructan synthesis
The fructan class of water soluble carbohydrates has been assigned a possible
role in conferring tolerance to drought. 6-SFT is capable of producing 6-kestose
as well as elongating 6-kestose and 1-kestose and producing both levan and
branched fructan.(Vijn et al., Plant Physiology, 1999, 120, 351-359)
104. Specific primer design based on the
polymorphism in the sequencing of gene 6-SFT
10 20 30 40 50
6-SFT-A1 TACCAAACTCTCTTAGAGTTCACGAGCGGCGCTGCGATGGGGTCACACGGCAAGCCACC
6-SFT-A2 TACCAAACTCTCTTAGAGTTCACGAGGGGCGCTGCGATGGGGTCACACGGCAAGCCACC
6-SFT-D1 TACCAAACTCTCTTAGAGTTCACGAGCGGCGCTGCGATGGGGTCACACGGCAAGCCACC
550 560 570 580 590
6-SFT-A1 ACGGGATCTCTCTCT--AGGCATAATCAAAA----TTGCTTAACTCACACCAA
6-SFT-A2 ACGGGATCTCTCTCTCTAGACATAATCAAAAGGGATTGTTTAACTCACACCAA
6-SFT-D1 ACGGGATCTCTCTCT--AGACATAATCAAAA----TTGCTTAACTCGCACCAA
6-SFT-A2 specific primer
3380 3390 3400 3410 3420 3430
6-SFT-A1 TGTCACTGTGAACTACAGTATATTACTTTGTTGGGCGTAGAATCGATATAGTTTGGGTGGGTGG
6-SFT-A2 TGTCATAGTGAACT-----ATATTACTTTGTTGGGCGTAGAATCAATATAGTTTGAGTGGGTGG
6-SFT-D1 TGTCACAGTGAACTA-----TATTACTTTGTTGGGTGTAGGATCGATATAGTTTGGGTGGGTGG
6-SFT-A1 specific primer
6-SFT-D1 specific primer
Three copies for 6-SFT were detected in wheat. Two copies were located
on genome A, one on genome D.
105. Single nucleotide mutation in 6-SFT-A1
No. Site Location Type Change Amino acid change
1 116 exon1 SNP C/T
2 333 intron1 SNP C/G
3 541 intron2 SNP G/C
4 563 intron2 SNP T/A
5 1053 intron2 SNP A/G
6 1609 exon3 SNP A/G
7 1727 exon3 SNP A/G Asn /Asp
8 1781 exon3 SNP A/G Thr/Ala
9 1783 exon3 SNP A/G
10 1831 exon3 SNP T/C
11 2140 intron3 SNP G/C
12 2157 intron3 SNP G/T
13 2311 intron3 SNP C/T
14 2358 intron3 Indel T/0
Among 30 hexaploid cultivars, 14 polymorphism sites in 6-SFT-A1 gene
nucleotide sequences were identified, which included 13 SNPs and 1 InDel.
106. 6-SFT-A1 mapping
1781 bp G/A
3269 bp
MluⅠdigest
Wu et al.
M G A G G G G G G G G Y N 2010, 2011
3000 bp
2000 bp
1200 bp
Segregation 6-SFT-A1 of in RILs Linkage map of 6-SFT-A1 on 4A
(Yanzhan 1×Neixiang 188) (Yanzhan 1×Neixiang 188)
The CAPS marker was developed based on the SNP at 1781 bp. 6-SFT-A1
was mapped on chromosome 4A. QTLs for plant height, 1000-grain weight
were located in 6-SFT-A1 region (Wu et al., 2010, JXB; 2011, PLoS ONE).
Yue et al., Scientia Agricultura Sinica. 2011, 44:2216-2224
107. Phylogenetic tree representing the haplotype
relationship of 6-SFT-A1
Hapl Ⅰ
Hapl Ⅱ
Hapl Ⅲ
Three haplotypes were identified using the 34 wheat germplasm. Haplotype I
was mainly detected among wheat accessions showing mid-drought resistance
and drought susceptiple. Haplotype III was found in the most of high-resistant
and resistant wheat germplasm.
108. The high correlation between seedling biomass under
drought stress and the molecular marker was
identified, which was designed based on the specific
SNP/InDel in Haplotype III of 6-SFT-A1
CK T
Well-watered (CK) Drought stress (T)
109. Agronomic traits associated with 6-SFT-A1 in
a historical population with 154 accessions
Environment Trait Hap I Hap III P-Value R2(%)
Rain-fed Peduncle length 7.4±1.0 8.0±1.4 0.0045 7.63
Plant height 79.2±13.2 88.1±14.3 0.0058 5.60
Well-watered Peduncle length 24.9±3.6 27.0±4.2 0.0001 11.02
Plant height 82.6±6.4 85.0±5.4 0.0337 3.93
110. Single nucleotide polymorphism in 6-SFT-A2
No. Site Location Type Change Hapl I Hapl II Hapl III
1 600 Intron 2 SNP G/A G G A
2 730 Intron 2 SNP T/C T C T
3 807 Intron 2 SNP T/A C A C
4 858 Intron 2 SNP C/A C C A
5 1207 Exon 3 SNP G/A G A A
6 1237 Exon 3 SNP A/T A C T
7 1591 Exon 3 SNP C/T C C T
8 1870 Exon 3 SNP G/A G G A
9 2053 Intron 3 Indel T/0 T 0 T
10 2056 Intron 3 Indel 0/C 0 C 0
11 2546 Exon 4 SNP C/T C C T
12 2918 Exon 4 SNP G/C G G C
13 2951 Exon 4 SNP G/A G A G
111. Molecular marker design for 6-SFT-A2
4A
1870bp G/A 2951bp G/A
2660b
Mbo II Digest p Msg I Digest
G G G A G G G G G G G A
+ - + -
Hapl Ⅰ + +
Hapl Ⅱ + - Linkage map of 6-SFT-A2
Hapl Ⅲ - + on chromosome 4A
(Hanxuan 10×Lumai 14)
113. Thousand grain weights of DHLs with
two 6-SFT-A2 haplotypes
50
**
*
**
**
**
45
**
40 * *
35
30
TGW(g)
25
20
15
10
5
0
2001
2001 2005
2005 2006H
2006DS 2006S
2006WW 2009H
2009DS 2009S
2009WW 2010H
2010DS 2010S
2010WW
Hapl I (Hanxuan 10) Hapl III (Lumai 14)
Thousand grain weight (TGW) of doubled haploid lines (DHLs) with
Hapl III of 6-SFT-A2 is significant higher than that of Hapl I under
different water regimes in five years.
114. TGW of three haplotypes of 6-SFT-A2 in
a historic population
Year Haplotype TGW (g) P-Value R2 (%)
Ⅰ 34.8±4.8 0.0397* 4.79
2008 Ⅱ 33.0±5.6
Ⅲ 35.6±4.9
Ⅰ 38.1±5.3 0.0310* 5.12
2009 Ⅱ 37.0±5.7
Ⅲ 39.7±5.5
Hapl III of 6-SFT-A2 is associated with higher thousand grain
weight in the historic population consisted of 154 accessions.
115. Single nucleotide polymorphism in 6-SFT-D
C A G C
A G A T
475 841 2243 2850
Haplotype 475 bp 841 bp 2243 bp 2850 bp
Ⅰ C A G C
Ⅱ C A G T
Ⅲ A G A C
C C C C C T C T C T C T C T C C C C C C T C T C
119. TGW in genotypes with different haplotype
combinations of 6-SFT-A2 and 6-SFT-D
Haplotype* 2008D 2008W 2009D 2009W
I+I 38.50 37.34 38.64 40.01
I+II 36.77 35.01 34.80 37.96
II+I 37.30 34.63 37.89 39.65
II+II 35.55 35.36 38.58 38.49
III+I 39.46 37.18 39.55 40.60
III+II 40.39 36.58 39.31 38.37
* Combines of three haplotypes of 6-SFT-A2 and two haplotypes of 6-SFT-D.
Hapl Ⅲ of 6-SFT-A2 and HaplⅠ of 6-SFT-D are favourable
hyplotypes for increasing grain weight, their combination
is optimum for improving grain weight in wheat.
120. Relationship between TGW and
water soluble carbohydrate in stem
CK
Cut spike
0.3% KI
(200 mL/m2)
Early grain filling stage Middle grain filling stage
121. Analysis of thousand grain weight (TGW)
Reduction (CK – KI)
Env. Treatment Range (g) Mean±SD
Max (g) Min (g) Mean±SD
Well-watered CK 27.50-49.76 39.42±5.06
29.40 4.62 16.14±5.53
KI 11.13-38.46 23.28±5.23
Rain-fed CK 26.63-48.13 36.95±4.60
24.87 1.23 7.82±5.82
KI 14.78-43.58 29.13±6.16
TGWKI
Well-watered: ×100% = 59.32%
TGWcontrol
TGWKI
Rain-fed: TGWcontrol × 100% = 79.13%
Stem-reserved WSC significantly contributes to TGW. The
contribution under the drought stress condition is higher
significantly than that under well-watered condition.
122. WSC QTL for stem WSC in DH population
QTLs
58 additive, 34 pairs Additive QTL; contribution rate 36.80%
epistatic Epistatic Total
Trait
(peduncle), 49.57% (secondR2(%) Number (lower section)
Number section), 49.24% R2(%) (%)
Peduncle 21 31.93 9 4.87 36.80
TGW QTL
Second section 17 40.97 10 8.60 49.57
Lower section
20 additive, 17 pairs 20
epistatic37.73
QTL; contribution 11.51 66.36%
15 rate 49.24
QTLs for TGW in DH population
22 common intervals of WSC QTL and TGW QTL.
Additive Epistatic Total
(1A:Stage
WMC59; 1B: WMC156, CWM65, A1133-370, WMC269.2; 1D:
Number R2(%) Number R2(%) (%)
WMC222; 2B: WMC441; 2D: WMC453.1, Xgwm539, A4233-175,
2 4 6.99 6 4.02 11.01
WMC41; 3A: Xgwm391; 4A: A3446-205; 5A: Xgwm156, Xgwm595; 5B:
3 4 5.13 5 3.82 8.95
4 4 13.03 1 3.08 16.11
Xgwm67, Xgwm213, Xgwm499, WMC380; 6A: CWM487; 7A: A3446-
280, A2454-280) 7
5 22.69 5 6.48 29.17
124. 6-SFT-A2 mapping
4A 4A
4A
H10 L14
TGW
TGW epistatic
QTL, stage 5
Linkage map of 6-SFT-A2 on 4A Su et al., 2009 Yang et al., 2007
(Hanxuan 10×Lumai 14) Plant Science Genetics
125. Summary
A number of QTLs and QTL clusters for drought
tolerance have been identified by linkage
mapping.
A few of functional markers have been developed.
Some useful alleles of target genes/QTLs were
tested in common wheat collections.
Few markers were corresponding in diversity
genetic backgrounds.
126. In the Future
To integrate the QTLs and functional markers
mapped in multi-population
To identify beneficial alleles in germplasm
resources by association mapping of
candidate genes/QTLs
To introgress DT into elite wheat backgrounds
by molecular marker assisted recurrent
selection
127. Acknowledgements
Collabrators
Yuchen DONG
Jizeng JIA
Xueyong ZHANG
Xiuying KONG
Chenyang HAO
Financial Support
National High Tech Program
National Key Program for Basic Research
129. “There’s no single gene that’s going to be the
panacea to our drought problem. We’re trying
to cherry-pick the various mechanisms and
recombine them into one elite cultivar.”
--- Dr. Ryan Whitford, a scientist with the
ACPFG’s Drought Focus Group, 2011
130. 果聚糖的作用
Water soluble carbohydrate (WSC) in wheat stem is mainly composed of
fructans, sucrose, glucose and fructose, with fructans being the major
component at the late stage of the WSC accumulation phase.
At the stage of maximum WSC content, fructans represented 85% of the
WSC in wheat stem internodes.
Fructan’s high water solubility: osmotic adjustment.
Fructan as a source of hexose sugars: allow continued leaf expansion
during periods of drought.
Direct protective effects of fructan: membrane stabilization.
Bolouri-Moghaddam, et al., 2010, FEBS J., 277, 2022-2037
