Discovering favourable gene resources for crop improvement

Discovering Favourable Gene Resources for Crop Improvement

Ruilian [email protected]

The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop ScienceChinese Academy of Agricultural Sciences (CAAS)

Development of Agricultural Science

Specific Topic for Student Abroad • Oct. 20, 2011

Why ?Where ?How ?

Phenotyping Genotyping Utilization

Outline

Special issue 2007

Special issue 2010

Special issue 2008

Special issue 2003

Feeding the 9 billion people expected to inhabit our planet by 2050 will be an unprecedented challenge

“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-Carlson2008-2009 Chair of World Economic Forum Global Agenda Council on Water Security

World Economic Forum, DavosJanuary 2009

1950’ 1960’-1990’ 1998-

Area(10 M ha.)

Total yield(100 M ton)

Area-Total yield-Yield per unit of cereal crops in China during 1952-2008

Zhensheng Li

Unit yield(ton·ha-1)

Abiotic & biotic stresses on crop plantsDrought, Waterlogging/SubmergenceHeat, ColdMineral deficiency/Mineral toxicitySalinity ……

Diseases and Insect pests

http://www.plantstress.com

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.

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 “GreenRevolution”

Nature, 1999, 400: 256-261

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

Wild rice Hybrid rice

Hybrid rice successful utilization in China due to a cytoplasmic male sterility

gene discovered in wild rice

Soybean is originated from China. Wild soybean is high diversity.

Salsa(Suaeda heteroptera)

碱蓬(又名盐蒿)

Wild rice

野生稻聚群

Hexaploid Agropyron

六倍体冰草

(Xinjiang)

Psathyrostachys陕西华山新麦草

(Shaanxi)

Investigation and collection of plant

germplasm

National Long-term Genebank

Founded in 1986 -18℃, RH≤50%±7%712 Species; 397,000 accessions

National Medium-term Genebank

0-40C

吉林

内

蒙

新疆

四川

青海

西藏

云南广东

甘

肃

贵州

广西

湖南

江

西福建

浙江

湖北

陕

西河南

安徽

江苏

山东

山

西

河北

辽宁

海南

台湾

上海

宁夏

天津

北京

黑龙江

南海诸岛

15

ⅢⅠ

Ⅱ

27

30

31

31 20

2

8

4518

116

21

16 10

12

17

14

26 2232

923

24

1925

29

重庆

713

28

图例：

资源库

资源圃

Distribution of 32 National Germplasm Nursries

Geographic distribution of crop germplasm in China

Wheat

Rice Soybean

National Germplasm Nursry: Grape, Jujube10 species, 636 accessions

National Germplasm Nursry: perennial grasses147 species, 432 accessions

国家内蒙多年生牧草圃：147个种、432份

CIMMYT

?

?

???

?

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?

Germplasm Resources

Gene Resources

植物功能基因组学研究进展迅速

完成了水稻基因组测序

为分离和发掘新基因奠定了基础

Rice genome sequencing and functional genomics

2002

Forward- vs. reverse-genetics approaches

Forward genetics

Reverse geneticsCandidate sequence

QTL mapping, Association mapping, Positional

cloning, Mutagenesis, etc.

Phenotype GenotypeGenetic engineering,

RNAi, TILLING, Insertionalmutagenesis, etc.

Phenotyping

--- base for discovering genes

(Case: drought tolerance)

WORLD•WATCH July/August 1998

An unexpectedly abrupt decline in the supply of water for China’s farmers poses a rising threat to world food security.

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.

10.5 Mha

8.8 Mha

Provinces suffered from drought stress in the early spring 2009

Total drought area

Average year: 1.7 Mha drought area

Qingtu Lake in Min Qin, from lake to desert in 40 years

Reeds and remaining shells

Abandoned village

The Aral Seain Central Asia, once the 4th largest saline water, has shrunk by 75% in surface area since 1960s

The Chad Lake in central africa, once the 6th largest lake in the world, 90% reduction in size from 1972 to 2006

The Lake Faguibine in Mali, change from 1974 to 2006

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.

‘Blue Revolution –more crop for every drop’

Water shortage in agriculture

Norman E. BorlaugNobel Peace Prize Laureate 1970

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.

1. Understanding the molecular mechanisms of water stress responses

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?

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.

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.

2. Breeding cultivars to cope with specific objectives

Whole-plant responses to drought stressLeft: long-term or acclimation responses; right: short-term responses

(Chaves, et al., 2003)

Sensing, signalling and cell-level responses to

drought stress

ABA-mediated responses

Non-ABA-mediated responses

Other mechanisms

(Chaves, et al., 2003)

Dissecting yield into bite size “physiological markers”

• Ground cover• Plant height• Root depth• Transpiration efficiency• Stem carbohydrates• Spike photosynthesis• ……

YIELD

POTENTIAL

YIELD

POTENTIAL

• Interception of radiation• Canopy cooling• Membrane thermostability• Photoprotection• ……

G-CT-A

G-CT-A

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G-CT-A

Traits

GenesEnvironmentM Reynolds, 2010

Early generation selection methodologies

Visual selection ++ Leaf porometry

Spectral reflectanceCanopy temperature

Factors affecting Canopy Temperature Depression (CTD) in plants

Biological EnvironmentalPartitioning

Metabolism

VascularTransport

Wind

CloudsRadiation

(T C)o

H O2

Evaporation

H O (soil water availability)2

CTD

(M Reynolds, 2001)

The relationship of grain yield to CTD, mean of 2sowings dates, Tlaltizapán, 1992-93, 23 genotypes.

(Amani, Fischer and Reynolds, 1996)

5500

5000

4500

4000

3500

3000

2500

2000

15005.0 6.0 7.0 8.0 9.0

Canopy temperature depression (oC)

Gra

in y

ield

(kg/

ha)

Selection for canopy temperature: to enrich favourable alleles before yield testing

24.525

25.526

26.527

27.528

28.529

20 21 22 23 24 25 26

Canopy temperature vegetative

Can

opy

tem

p po

st

flow

erin

g

Use of CTD in early generation selection - F4 bulks under drought stress (R. Trethowan)

- Following visual selection, CTD scores used to influence gene frequency

Complementing breeder selection with canopy temperature(Van Ginkel et al., 2008)

0

2

4

6

8

10

12

14

6.3 6.8 7.3 7.8 8.3Yield (t/ha)

Indi

vidu

al n

umbe

r

BREEDERBREEDER+CTD

CIMMYT

Sampling soil coreTo sample roots To measure soil moisture profiles

Models to quantify yield under abiotic stress

Drought yield = Water Uptake x WUE x HI (partitioning)(Passioura, 1977)

WUE: water use efficiencyRUE: radiation use efficiencyHI: harvest index

Irrigated yield =Light Interception x RUE x HI (partitioning)

Water use efficiency (WUE) & Radiation use efficiency (RUE)

Access to water by roots (indicated by cooler canopies)

• Under drought estimates water use• Under hot, irrigated conditions:

estimates CO2 fixation and thus radiation use efficiency

•Transpiration efficiency (drought only)• CID

•Heat tolerant metabolism (growth rate)• Stay green (CHL)• CO2 fixation rate (COND)

Early growth (pre-grainfill)

• Ground cover: measured with spectral indices (NDVI & WI)

• Growth rate (BMA) • Stem carbohydrates (CHO)

Pigments for dissipation of excess light energy, e.g. carotenoids measured using spectral reflectance (RARSc)

Photo-protection

Generic model of stress adaptation under drought & heat

Transpiration EfficiencyWUE of leaf photosynthesis

low 12C/13C discrimination Spike/awn photosynthesis

Physiological breeding: strategic crossing for drought

YLD = WU x WUE x HI (Passioura, 1979)

Partitioning (HI)Partitioning to stem

carbohydrates

Harvest index • Rht alleles

Photo-ProtectionLeaf morphology

• wax/pubescence• posture/rolling

Pigments • chl a:b• carotenoids

Antioxidants

Water Uptake Rapid ground cover

• protects soil moistureAccess to water by roots

• Ψ leaf• cool canopy• (osmotic adjustment)

(Reynolds & Tuberosa, 2008. COPB)

2001

Plant phenotypingmethodology

Drought phenotypingin crops: from theory to practicewww.generationcp.org/drought_phenotyping

2011

Genotyping

--- to discover gene resources

(Case: drought tolerance)

Outline

Linkage mapping

Association mapping

Functional marker mapping

Perspective of MAS

Evaluation of drought tolerance at seedling stage Drought tolerant genotypes

survived in the soil moisture of ~17% relative water content

Drought tolerance evaluation in the field

2009

Henan

Shanxi Henan

DHLs

Linkage mapping

DT QTLs

Hanxuan 10 × Lumai 14

Association mapping

Historical winter wheat collection

DT QTLs

Jinmai 47 ×

Introgression lines (BC3F3-4)Donor 1Donor 2

...

RILs

Elite alleles

Lumai 14Hanxuan 10

Hanxuan 10Drought tolerant cultivar grown under rainfed condition in semi-arid region

Lumai 14High yield potential cultivar grown under irrigated condition

DH Lines

Parents

(Hanxuan 10 × Lumai 14)

Water Regime Treatments for Phenotyping

Traits for QTL Mapping

Agronomic traits (coleoptile length, early vigor, heading date, flowering date, plant height, spike number per plant, kernel perspike, 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)

Treatment: Rainfed/Drought stressControl: Well watered

QTLs for accumulation and remobilization of stem water-soluble carbohydrates

Yang et al., Genetics. 2007, 176: 571-584

K w e (3 3 .3 9 % )K g n (1 5 .5 5 % ~ 2 9 .0 6 % )T s p (1 0 .0 7 % ~ 1 2 .2 5 )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 % )

S le : 7 re p e a ta tio n(1 7 .4 3 % ~ 2 2 .4 4 % )

N U P -H N 2 (1 4 .0 % )N U P -L N 1 (6 .0 % )R D W -H (1 1 .0 % )

F v /F o -W W (1 2 .0 9 % )R A L V B -D S (1 3 .1 6 % )H e i (8 .4 9 % ~ 3 1 .0 4 % )S le (9 .1 5 % ~ 1 8 .7 3 % )K w e i (1 4 .0 6 % )P y i (8 .5 7 % )

C h lC (1 1 .6 8 % )N S V B (2 1 .3 8 % )N T V B (2 0 .3 6 % )T sp (8 .0 9 % ~ 3 4 .9 3 % ) S sp (1 0 .8 9 % ~ 3 0 .9 7 % )H e i (9 .3 2 % ~ 2 1 .7 9 )

T s p (1 5 .7 1 % ~ 2 4 .5 3 % )H e i (2 4 .5 3 % ~ 4 3 .4 5 % )

R P A T V B (1 3 .2 3 % )S le (7 .8 % ~ 2 1 .9 7 % )S p i (6 .5 9 ~ 1 0 .3 7 % )

K g n (2 2 .6 2 % )S s p (6 .4 3 % ~ 1 4 .3 8 % )S p i (9 .3 7 % )

N L V B -D S (1 6 .0 5 % )F m -D S (2 6 .5 8 % )F v -D S (2 2 .9 9 % )R F W (1 0 .3 7 % )N U P -H (4 .3 % )


S le : 7 re p e a ta tio n(1 7 .4 3 % ~ 2 2 .4 4 % )

N U P -H N 2 (1 4 .0 % )N U P -L N 1 (6 .0 % )R D W -H (1 1 .0 % )


S le : 7 re p e a ta tio n(1 7 .4 3 % ~ 2 2 .4 4 % )

N U P -H N 2 (1 4 .0 % )N U P -L N 1 (6 .0 % )R D W -H (1 1 .0 % )




T s p (1 5 .7 1 % ~ 2 4 .5 3 % )H e i (2 4 .5 3 % ~ 4 3 .4 5 % )


T s p (1 5 .7 1 % ~ 2 4 .5 3 % )H e i (2 4 .5 3 % ~ 4 3 .4 5 % )

R P A T V B (1 3 .2 3 % )S le (7 .8 % ~ 2 1 .9 7 % )S p i (6 .5 9 ~ 1 0 .3 7 % )

K g n (2 2 .6 2 % )S s p (6 .4 3 % ~ 1 4 .3 8 % )S p i (9 .3 7 % )


R P A T V B (1 3 .2 3 % )S le (7 .8 % ~ 2 1 .9 7 % )S p i (6 .5 9 ~ 1 0 .3 7 % )

K g n (2 2 .6 2 % )S s p (6 .4 3 % ~ 1 4 .3 8 % )S p i (9 .3 7 % )


Integrated mapping of QTLs controlling drought tolerance in wheat

QTL validation in different populations

RIL (Opata85×W7984)DH (Hanxuan 10×Lumai 14)

S0 S1 S2 S3 S4 S5

S1|S0 S5|S4S3|S2S2|S1 S4|S3

Condition PH---net increase effect

in the given period

Unconditional PH---accumulated effect

E1: 2001 Fenyang, ShanxiE2: 2005 Haidian, BeijingE3: 2005 Changping, BeijingE4: 2006 Haidian, BeijingE5: 2006 Changping, BeijingE6: 2001 Fenyang, ShanxiE7: 2005 Haidian, BeijingE8: 2005 Changping, BeijingE9: 2006 Haidian, BeijingE10: 2006 Changping, Beijing

DS

WW

Plant height phenotyping

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

Number Aa AEb Number AAc AAEd

S1 12 12 6 7 7 2S2 11 11 7 18 18 4S3 12 12 7 19 19 3S4 10 10 4 22 22 1S5 10 10 5 20 20 2

Total 55 55 29 86 86 12S1|S0 12 12 6 7 7 2S2|S1 3 3 3 4 4 3S3|S2 4 4 3 4 2 3S4|S3 1 1 1 3 1 2S5|S4 6 5 5 5 3 3Total 26 26 18 23 17 13

Additive QTLs Epistatic QTL pairs

Unconditionalplant height

Conditionalplant height

Traits Stages

QTLs for plant height during ontogeny in DHLs

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.

Uneven distributions of PH QTLs on chromosomes

53109Total921347D

147B657A

8126D466B466A

71315D455B375A

52924D224B154A

51833D4123B133A

10622102D142B382A

1191222221D23751181B1913621A

GenomeHomeologousgroupChrom.GenomeHomeologous

groupChrom.Conditional plant heightUnconditional plant height

Common QTLs for plant height development between unconditional and conditional analysis in DHLs

Stage QTLs Marker interval A AE1 AE2 AE3 AE4 AE5 AE6 AE7 AE8 AE9 AE10

S1|S0 QPh.cgb-2D.1 WMC453.1-WMC18 1.85*** -0.83** 0.35 0.77*

S3|S2 QPh.cgb-2D.1 WMC453.1-WMC18 -0.50*** -0.86* 0.48 -0.74* 0.52 0.39 -0.36 0.74* 0.51 -0.54

S1 QPh.cgb-2D.1 WMC453.1-WMC18 1.85*** -0.83** 0.35 0.77*

S2 QPh.cgb-2D.1 WMC453.1-WMC18 3.89*** -2.44*** 1.87*** -1.06 2.13***

S3 QPh.cgb-2D.1 WMC453.1-WMC18 3.02*** -1.92*** 1.03 -0.64

S4 QPh.cgb-2D.1 WMC453.1-WMC18 4.70*** -0.86 -2.96*** 0.75 0.83 -0.89 1.28 0.85

S5 QPh.cgb-2D.1 WMC453.1-WMC18 2.84*** -0.86 0.49

0

0.1

0.2

0.3

0.4

0.5

Component contribution

S1 S2 S3 S4 S5

Contributions of different genetic effects to plant height during ontogeny in DHLs

h^2(A) h^2(AE) h^2(AA) h^2(AAE)

0

0.1

0.2

0.3

0.4

0.5

Component contribution

S1|S0

S2|S1S3|S2

S4|S3

S5|S4

Rht12

Rht9 (Schnurbusch, 2003; Ellis, 2005)

(Ellis, 2005)

Rht1(Cadalen, 1998;Huang, 2006;Sourdille, 2003;Liu, 2006;McCartney, 2005)

Rht2(Cadalen,1998; Huang, 2003, 2006; McCartney, 2005; Sourdille, 2003)

a e ae aa e aaeS1

S2

S3

S4

S5

S1

S2

S3

S4

S5

Un.

Con.

QTLs Epi.

PH QTL clusters matched up to Rht genes in DHLs

（Ellis, 2005）

Rht5

Rht8 (Korzun, 1998)

(Ellis 2005)

Rht13

PH QTL clusters near Rht genes in DHLs

(Cadalen et al. 1998)

PH QTL clusters on other chromosomes

(Ellis, 2005)

(Schnurbusch, 2003)

(McCartney ，2005;Cadalen, 1998;Sourdille, 2003;Quarrie, ,2006)

PH QTL clusters on other chromosomes

Wu et al., JXB, 2010, 61: 2923-2937

Rht12

Rht9

Association analysis of candidate PH QTLs

270 historical winter wheat accessions 60 candidate SSR markers in six chromosome regions

Rht8Rht1

Rht2 Rht13

Ave. Dis. = 4.7 cMWheat, Consensus SSR, 2004

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

Xcfd43

-PH2

Xcfd43

-DTC2

Xwmc349

-PHm

Xgwm30

2-PH3

Xgwm49

5-PH3

Xgwm49

5-PHm

Xgwm49

5-PH1

Xgwm24

9-PH3

Xgwm24

9-PH4

Xbarc1

09-P

H1Xba

rc109

-PH1

Xbarc1

09-P

H2Xba

rc109

-PH2

Associations

-Lg(

P va

lue)

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.

-Log (P)>3

-Lg (P) value at different associations

Rht8 (Korzun, 1998)

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

23.2 Xgwm261

32.1 Xgwm455

37.1 Xwmc470

40.7 Xgwm484

43.1 Xcfd43

46.7 Xbarc168

48.2 Xgwm102

63.6 Xgwm249

63.7 Xwmc18

65.2 Xcfd17

65.8 Xcfd116

66.7 Xcfd84

67.1 Xwmc144

68.8 Xcfd160

73.1 Xgwm157

81 Xbarc228

82.8 Xwmc41

90.9 Xgwm539

Ht= 0.5806

PH2 PH4 PH4

PH3

PH2 PH3 PH4 DTC2 DTC3

PH1

PH3 PH4

DTC4

DTC4

2D2D PIC

cM

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

28 Xwmc112

32.9 Xcfd23

33.1 Xgwm133

34.5 Xgwm192

42.9 Xwmc331

54 Xwmc399

78.8 Xcfd233

82 Xgwm194

Ht= 0.6489

DTCm

PHm

PH4

PHm

PHm DTCm

PHm PH1 PH3

PH1

4D

4D

PHm PH1 PH2 PH3 PH4

PHm PH1 PH2 PH3 PH4

DTCm DTC1 DTC2 DTC3 DTC4

Plant height under well-watered

Plant height under drought-stress

Drought tolerance coefficient

cM

PIC

Rht2

Cadalen,1998; Huang, 2003, 2006;McCartney, 2005; Sourdille, 2003

Zhang et al., Planta, 2011 (DOI 10.1007/s00425-011-1434-8)

Phenotypic effects of marker alleles

-20

-15

-10

-5

0

5

10A217 A220 A223 A155 A159 A163 A165 A167 A179 A181

Plan

t hei

ght a

t mat

ure

(cm

)

PH under drought-stress PH under well-watered

Xcfd23-4D Xgwm495-4B

- 2.4+ 6.7- 2.1+ 6.0鲁215953 Lu 215953-2.1510冀麦32 Jimai 32+ 0.4157晋麦44 Jinmai44+ 3.2153晋麦16 Jinmai 16+ 14.6151Xwmc396

- 3.3+ 10.4- 3.2+ 9.9丹麦1号 Danmai 1+ 9.9103矮孟牛Ⅳ型(8057) Aimengniu- 3.299Xgwm212

- 18.30- 21.40西安8号 Xian 8- 31.7122豫麦13 Yumai 13- 24.1120陕229 Shan 229- 24.7118太原566 Taiyuan 566- 5.2108Xgwm95

0+29.60+21.9科遗29 Keyi 29+ 12.8199燕大1817 Yanda 817+ 32.8195冀麦32 Jimai 32+ 20.1193Xgwm126

-11.00-11.5衡5229 Heng 5229 0- 5.0256衡95观26 Heng 95 Guan 26 - 11.5254鲁麦1号 Lumai 1- 3.3238鲁麦14 Lumai 14- 17.6228中麦9号 Zhongmai 9- 13.9222西安8号 Xian 8- 17.8220Xgwm285

0+34.50华北187 Huabei 187 +26.0+ 29.2162:174庆丰1号 Qingfeng 1+ 17.6160:172

科遗29 Keyi 29+ 17.8160:174中苏68 Zhongsu68+ 37.5160Xbarc168

Negative effectPositive effectNegative effectPositive effect

Percentage of effect (%)Average effectTypical accessionEffectAlleleLocus

Allele effect on plant height of associated locus in drought environment

Wei et al., Acta Agron Sin, 2010, 36:895-904

Validation of Xwmc349 allelic effect in ILs with Jinmai 47 background

-2-9 ~ +66-11.1A103

0-19 ~ +1424-12.4A99

Average variance to receptor

Range of PHIL No.Effect on PHAllele

Xwmc349 allele: A99(-12.4), A101, A103(-11.1), A105(+6.0)

Summary

Plant height is a typically quantitative trait controlled by additive effects and epistaticeffects.

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.

Flow chart of suppression subtractive hybridization (SSH)

Vector ligation

cDNA synthesis

Rsa I digestion

Adaptor ligation

Second hybridization

First hybridization

First PCR amplification

Second PCR amplification

Test sequences

Data analysis

Transformation

mRNA preparationSSH 1, 6, 12, 24, 48h

cDNA libraries

Wheat seedling(-0.5MPa PEG-6000)

Assessment of contigs from the cDNA libraries responding to water stress by suppression

subtractive hybridization (SSH)

221 34.802344146351148SSH 48h

792 84.431141469381697SSH 1h301 53.182032655661824SSH 6h

345 43.892024417861131SSH 24h

2009 58.38886143234416733Total

166

Known functional

contigs

350 67.83

Unknown functional contigs

Number %

1335161833SSH 12h

Uni-contigs

Total contigs

Valid ESTs

cDNAlibrary

Wheat seedlings were treated with -0.5MPa PEG-6000 for 1, 6, 12, 24, 48h, respectively.

Classification of genes that respond to water stress1h, 6h, 12h, 24h and 48h

G1: Alcohol dehydrogenaseG2: Aldehyde dehydrogenaseG3: Ca2+-binding proteins G4: Calmondulin binding proteins G5: Carbohydrate metabolism-related proteins G6: Cellular structure and organization-related proteins G7: Cytochrome p450 G8: Detoxification enzymes G9: Fatty acid metabolism-related proteinsG10: FerritinG11: Membrane proteins G12: Osmoprotectant synthesis-related proteins G13: Plant defence-related proteins G14: Protease inhibitor G15: Protection factors of macromolecules G16: Protein kinasesG17: Protein phosphatasesG18: Protein synthesis-related proteins G19: ProteinasesG20: Proteins involved in biosynthesis and metabolism of hormones G21: Proteins regulated by various hormones G22: Reproductive development-related proteins G23: Respiration-related proteins G24: RNA-binding proteinsG25: Secondary metabolism-related proteins G26: Senescence-related proteins G27: Transcription factors

SSH 1h1 / 19

SSH 6h 0 / 19

SSH 12h 1/24

SSH 24h0/17

SSH 48h1/26

13 / 27

1 1

2

1

2

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.

Putative key classifications of differential expressed genes from 648 Uni-genes

Others65.74%

Transcriptionfactor6.17%

Calmondulinbinding protein0.46%

Ca2+-bindingprotein0.62%

Proteinphosphatase2.16%

Detoxificationenzyme3.40%

Plant defence-related protein8.33%

Membrane protein9.11%

Protein kinase4.01%

Pang et al., Acta Agronomica Sinica. 2007, 33:333-336

TaPP2Acidentified from cDNA

libraries at 6h and 12h, plays important

roles in cellular

growth and signalling,

ubiquitously expressed in plants.

Case 1: TaPP2Ac (protein phosphatase 2Ac)

Structural subunit A; Variable subunit B (B’, B’’, B’’’); Catalytic subunit C

PP2A structure

CTR 1, a negative regulator of the ethylene response pathway inArabidopsis, encodes a member of the Raf family of protein kinase.

(Kieber et al., Cell, 1993, 72: 427-441)

PP2Ac Function

Expression of TaPP2Ac-1

Overexpression of transgenic TaPP2Ac-1 tobacco under water stress condition

Water stress 12 d

WT GFP TaPP2Ac

Before water stress

WT GFP TaPP2Ac

WT GFP TaPP2Ac

Water stress 18 d Water stress 24 d

WT GFP TaPP2Ac

Transgenic TaPP2Ac-1 tobacco plants enhance drought tolerance under water deficit

RWC: relative water content; MSI: membrane stability index;WRA: water retention ability; WUE: water use efficiency

Time of drought stress (d) Physiological trait

Xu et al., Annals of Botany. 2007, 99:439-450

Salt tolerance

WT: wild type &: transgenic lineP: GFP

DT of transgenic TaPP2Ac-1 Arabidopsis

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.

Map of TaPP2Ac-1 on chromosome 4DL

Three copies of TaPP2Ac was identified in hexaploid wheat by Southern Blotting

4D

Schematic illustration of PCR-RFLP product of specific-sequence of D genome between two

parents of RIL population

M: DNA markerO: Opata85 W: W7984

ABD

AB SA D ABD

AB SA D

Hind III Noc I

ABD

AB SA D

EcoR V

Genetic mapping of TaABC1L gene based on CAPS marker and AS-PCR marker

Case 2: TaABC1L mapping in RILs

Wang et al., JXB, 2011, 62:1299-1311

Case 3: TaSnRK2.7 Cloning, location and functionalanalysis of a gene involved in abiotic-stressed responses

a. In the absence of ABA, the phosphatase PP2C is free to inhibit autophosphorylation of a family of SnRK2 kinases. b. ABA enables the PYR/PYL/RCAR family of proteins to bind to and sequester PP2C. This relieves inhibition on SnRK2, which becomes auto-activated and can subsequently phosphorylateand activate downstream transcription factors (ABFs) to initiate transcription at ABA-responsive promoter elements (ABREs).

Minimal ABA signaling pathway Structure prediction

10-33: Protein kinases ATP-bindingregion signature

119-131: Serine/Threonine protein kinasesactive-site signature

(Sheard and Zheng, 2009. Nature 462, 575-576)

TaSnRK2.7 was clustered in subclass I, bootstrap values are in percentages.

Phylogenetic tree of TaSnRK2.7 and SnRK2s from other plant species

Southern blottingOne copy of TaSnRK2.7 might exist in each of

the three genomes of common wheat.

Chromosome location of TaSnRK2.7-A copyPhosphorus utilization efficiencyAccumulation efficiency of stem water-soluble carbohydrates

Zhang et al., Gene, 2011, 478:28-34

Expression patterns of TaSnRK2.7 in various tissues (A) and in response to various treatments (B)

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 benot activated by ABA.

Subcellular localization

Stress tolerance assaysof TaSnRK2.7

over-expressing transgenic Arabidopsis

TaSnRK2.7-GFP was present in thecell membrane, cytoplasm and nucleus

Zhang et al., JXB, 2011, 62:975-988

Drought tolerant

Drought sensitive

Phylogenetic tree representing TaSnRK2.7 haplotyperelationship among 50 wheat accessions

Zhang et al., Gene, 2011, 478:28-34

Model for fructan synthesis

levan neoseriesβ(2-1)

6G-kestotriose inulin neoseriesβ(2-1)

levanβ(2-1)

6-kestotriose SUCROSE 1-kestotriose inulinβ(2-1)

mixed-type levanβ(2-1) and β(2-6)

bifurcose mixed-type levanβ(2-1) and β(2-6)

levanβ(2-6)

1-SST6-SFT

6-SFT

6G-FFT

6-SFT

6-SFT

6-SFT1-FFT

1-FFT

FEH

1-FFT

1-FFT6-SFT

Case 4: Ta6-SFT Cloning, location and functional analysis of a gene involved in 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)

10 20 30 40 50

T A C C A A A C T C T C T T A G A G T T C A C G A G C G G C G C T G C G A T G G G G T C A C A C G G C A A G C C A C C

T A C C A A A C T C T C T T A G A G T T C A C G A G G G G C G C T G C G A T G G G G T C A C A C G G C A A G C C A C C

T A C C A A A C T C T C T T A G A G T T C A C G A G C G G C G C T G C G A T G G G G T C A C A C G G C A A G C C A C C

3380 3390 3400 3410 3420 3430

T G T C A C T G T G A A C T A C A G T A T A T T A C T T T G T T G G G C G T A G A A T C G A T A T A G T T T G G G T G G G T G G

T G T C A T A G T G A A C T - - - - - A T A T T A C T T T G T T G G G C G T A G A A T C A A T A T A G T T T G A G T G G G T G G

T G T C A C A G T G A A C T A - - - - - T A T T A C T T T G T T G G G T G T A G G A T C G A T A T A G T T T G G G T G G G T G G

550 560 570 580 590

A C G G G A T C T C T C T C T - - A G G C A T A A T C A A A A - - - - T T G C T T A A C T C A C A C C A A

A C G G G A T C T C T C T C T C T A G A C A T A A T C A A A A G G G A T T G T T T A A C T C A C A C C A A

A C G G G A T C T C T C T C T - - A G A C A T A A T C A A A A - - - - T T G C T T A A C T C G C A C C A A

6-SFT-A16-SFT-A26-SFT-D1

6-SFT-A2 specific primer

6-SFT-A1 specific primer

6-SFT-D1 specific primer



Specific primer design based on the polymorphism in the sequencing of gene 6-SFT

Three copies for 6-SFT were detected in wheat. Two copies were located on genome A, one on genome D.

T/0Indelintron3235814C/TSNPintron3231113

21572140183117831781172716091053563541333116

Site

G/TSNPintron312G/CSNPintron311T/CSNPexon310A/GSNPexon39

Thr/AlaA/GSNPexon38Asn /AspA/GSNPexon37

A/GSNPexon36A/GSNPintron25T/ASNPintron24G/CSNPintron23C/GSNPintron12C/TSNPexon11

Amino acid change ChangeType LocationNo.

Single nucleotide mutation in 6-SFT-A1

Among 30 hexaploid cultivars, 14 polymorphism sites in 6-SFT-A1 gene nucleotide sequences were identified, which included 13 SNPs and 1 InDel.

MluⅠdigest

M G A G G G G G G G G Y N

2000 bp3000 bp

1200 bp

Linkage map of 6-SFT-A1 on 4A (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).

3269 bp

1781 bp G/A

Wu et al. 2010, 2011

Yue et al., Scientia Agricultura Sinica. 2011, 44:2216-2224

6-SFT-A1 mapping

Segregation 6-SFT-A1 of in RILs(Yanzhan 1×Neixiang 188)

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.

Phylogenetic tree representing the haplotyperelationship of 6-SFT-A1

Hapl Ⅰ

Hapl Ⅲ

Hapl Ⅱ

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

Well-watered (CK) Drought stress (T)

CK T

3.930.033785.0±5.482.6±6.4Plant height

11.020.000127.0±4.224.9±3.6Peduncle lengthWell-watered

5.600.005888.1±14.379.2±13.2Plant height

7.630.00458.0±1.47.4±1.0Peduncle lengthRain-fed

R2(%)P-ValueHap IIIHap ITraitEnvironment

Agronomic traits associated with 6-SFT-A1 in a historical population with 154 accessions

Single nucleotide polymorphism in 6-SFT-A2

GAGG/ASNPExon 4295113CGGG/CSNPExon 4291812TCCC/TSNPExon 42546110C00/CIndelIntron 3205610T0TT/0IndelIntron 320539AGGG/ASNPExon 318708TCCC/TSNPExon 315917TCAA/TSNPExon 312376AAGG/ASNPExon 312075ACCC/ASNPIntron 28584CACT/ASNPIntron 28073TCTT/CSNPIntron 27302AGGG/ASNPIntron 26001

Hapl IIIHapl IIHapl IChangeTypeLocationSiteNo.

2660bp

1870bp G/A 2951bp G/A

G G G A G G G G G G G A

+ - + -

Hapl Ⅰ + +Hapl Ⅱ + -Hapl Ⅲ - +

Msg I DigestMbo II Digest

Molecular marker design for 6-SFT-A2

4A

Linkage map of 6-SFT-A2 on chromosome 4A

(Hanxuan 10×Lumai 14)

HaplⅠ

HaplⅡ

Hapl Ⅲ

Phylogenetic tree representing the haplotype relationship of 6-SFT-A2

Hapl I (Hanxuan 10) Hapl III (Lumai 14)

0

5

10

15

20

25

30

35

40

45

50

2001 2005 2006H 2006S 2009H 2009S 2010H 2010S

TGW

(g)

*

**

*

**

** * ****

2006DS 2009DS 2010DS 2010WW2009WW2006WW20052001

Thousand grain weights of DHLs with two 6-SFT-A2 haplotypes

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.

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

TGW of three haplotypes of 6-SFT-A2 in a historic population

Hapl III of 6-SFT-A2 is associated with higher thousand grain weight in the historic population consisted of 154 accessions.

Single nucleotide polymorphism in 6-SFT-D

CAGAⅢ

TGACⅡ

CGACⅠ

2850 bp2243 bp841 bp475 bpHaplotype

475 841 2243 2850

CA

AG

GA

C T

C C C C C T C T C T C T C T C C C C C C T C T C

HaplⅡ

HaplⅠ

Hapl Ⅲ

Phylogenetic tree representing the haplotype relationship of 6-SFT-D

HaplⅠ of 6-SFT-D is a favourable haplotypefor TGW in a historical population

Year Haplotype TGW (g) P-Value R2（%）

Ⅰ 40.4 ± 4.6 2009

Ⅱ 38.3 ± 5.7

0.0351 2.46

Ⅰ 34.5 ± 7.4 2010

Ⅱ 31.7 ± 6.7

0.0385 1.94

0

5

10

15

20

25

30

35

40

45

50

TGW(g)

Ⅰ

Ⅱ

**

2009 2010

2008H

25

30

35

40

45

50

I+I I+II II+I II+II III+I III+II

2008S

25

30

35

40

45


2009S

30

32

34

36

38

40

42

44

46


2010S

25

30

35

40

45

50


2009H

25

30

35

40

45

50


2010H

25

30

35

40

45

50


38.37 39.31 36.58 40.39 III+II40.60 39.55 37.18 39.46 III+I38.49 38.58 35.36 35.55 II+II39.65 37.89 34.63 37.30 II+I37.96 34.80 35.01 36.77 I+II40.01 38.64 37.34 38.50 I+I

2009W2009D2008W2008DHaplotype*

Hapl Ⅲ of 6-SFT-A2 and HaplⅠ of 6-SFT-D are favourablehyplotypes for increasing grain weight, their combination is optimum for improving grain weight in wheat.

* Combines of three haplotypes of 6-SFT-A2 and two haplotypes of 6-SFT-D.

TGW in genotypes with different haplotypecombinations of 6-SFT-A2 and 6-SFT-D

CK

Cut spike

0.3% KI(200 mL/m2)

Early grain filling stage Middle grain filling stage

Relationship between TGW and water soluble carbohydrate in stem

Analysis of thousand grain weight (TGW)

Env. Treatment Range (g) Mean±SDReduction (CK – KI)

Max (g) Min (g) Mean±SD

Well-watered CK 27.50-49.76 39.42±5.0629.40 4.62 16.14±5.53

KI 11.13-38.46 23.28±5.23Rain-fed CK 26.63-48.13 36.95±4.60

24.87 1.23 7.82±5.82KI 14.78-43.58 29.13±6.16

Well-watered: ×100% = 59.32%

Rain-fed: × 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.

control

KI

TGWTGW

control

KI

TGWTGW

QTLs for stem WSC in DH population

QTLs for TGW in DH population

TraitAdditive Epistatic Total

(%)Number R2(%) Number R2(%)Peduncle 21 31.93 9 4.87 36.80

Second section 17 40.97 10 8.60 49.57Lower section 20 37.73 15 11.51 49.24

StageAdditive Epistatic Total

(%)Number R2(%) Number R2(%)2 4 6.99 6 4.02 11.013 4 5.13 5 3.82 8.954 4 13.03 1 3.08 16.115 7 22.69 5 6.48 29.17

WSC QTL58 additive, 34 pairs epistatic QTL; contribution rate 36.80% (peduncle), 49.57% (second section), 49.24% (lower section)

TGW QTL20 additive, 17 pairs epistatic QTL; contribution rate 66.36%

22 common intervals of WSC QTL and TGW QTL.(1A: WMC59; 1B: WMC156, CWM65, A1133-370, WMC269.2; 1D:

WMC222; 2B: WMC441; 2D: WMC453.1, Xgwm539, A4233-175,

WMC41; 3A: Xgwm391; 4A: A3446-205; 5A: Xgwm156, Xgwm595; 5B:

Xgwm67, Xgwm213, Xgwm499, WMC380; 6A: CWM487; 7A: A3446-

280, A2454-280)

QTL for WSC and TGW on chromosome 4A

Lower section, WSCadditive QTL, stage 5

Lower section, WSCepistatic QTL, stage 3


Second section, WSCepistatic QTL, stage 1


TGW epistatic QTL, stage 4

TGW additive QTL, stage 2, 3, 4

TGW epistatic QTL, stage 5

Linkage map of 6-SFT-A2 on 4A (Hanxuan 10×Lumai 14)

H10 L14

Su et al., 2009Plant Science

Yang et al., 2007Genetics

6-SFT-A2 mapping

4A

4A

TGW epistaticQTL, stage 5

TGW

4A

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.

In the Future

To integrate the QTLs and functional markers mapped in multi-population

To identify beneficial alleles in germplasmresources by association mapping of candidate genes/QTLs

To introgress DT into elite wheat backgrounds by molecular marker assisted recurrent selection

Acknowledgements

Yuchen DONGJizeng JIAXueyong ZHANGXiuying KONGChenyang HAO

Collabrators

Financial SupportNational High Tech ProgramNational Key Program for Basic Research

Thank you!

“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

果聚糖的作用

Bolouri-Moghaddam, et al., 2010, FEBS J., 277, 2022-2037

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.

Education

Discovering favourable gene resources for crop improvement