Developing crops with high productivity at high temperature: A blue sky research initiative

Developing crops with high productivity at high

temperature:

A blue sky research initiative

BSR Team

29 Nov 2013

Maximum temperature in the SAT

Critical Temperature

threshold

0

5

10

15

20

25

30

35

40

45

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Maxim

um

T°C

1983-HQ 1992-HQ

2001-HQ 2012-HQ

1983-ISC 1990-ISC

1998-ISC

Headquarter

Sahelian Center

T°C rarely crosses critical limits

0

1

2

3

4

5

6

7

8

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Maxim

um

VP

D Sahelian

Center

Headquarter

Vapor pressure deficit (VPD) in the SAT (VPD reflects T°C and Rel. Humidity %)

Prevalent high VPD

Effect on plant water balance

VPD threshold

The basics – Why aquaporins (AQP) ?

Transpiration response to VPD

Transpiration response to AQP inhibition

AQP gene expression

AQP in the bigger picture - Drought

Modified from Murata et al., 2000.

What are aquaporins??

Membrane transporter for water Passive transport

Terminal drought sensitive

Terminal drought tolerant

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.50 1.00 1.50 2.00 2.50 3.00 3.50

VPD (kPa)

H77/2 833-2

PRLT-2/89-33

Tra

nsp

irati

on

(g

cm

-2 h

-1)

Kholova et al 2010 – J. Exp. Bot

Transpiration restriction at high VPD

How the story began – Water savings in millet

Water saving

Why such a rapid transpiration response??

Rapid response hydraulic signal

VPD (kPa)

Where is the source of hydraulic limitation??

???

We hypothesized roots could be the source of hydraulic limitation

Is the hydraulic restriction in the roots only ??

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

09:20 09:40 10:00 10:20 10:40 11:00 11:20 11:40 12:00 12:20 12:40 13:00 13:20

Norm

alized

tra

nsp

irati

on

VPD change

Low VPD High VPD

No difference in slope No hydraulic limitation in the leaves

Apoplastic

Pathway

(Structural)

Symplastic

Pathway

(AQP)

Water pathways in the root cylinder

Two pathways have different hydraulic conductance

Hypothesis: Aquaporin control plant water loss ?

????

The basics – Why aquaporins ?



AQP gene expression


Terminal drought sensitive

Terminal drought tolerant

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.50 1.00 1.50 2.00 2.50 3.00 3.50

VPD (kPa)

H77/2 833-2

PRLT-2/89-33

Tra

nsp

irati

on

(g

cm

-2 h

-1)

Kholova et al 2010 – J. Exp. Bot

One QTL mapped for low Tr at high VPD

Transpiration response to VPD in pearl millet: Growth chamber

M322

M394

M214

M321 M592 M443 M356

M738

40 cM

0

0.005

0.01

0.015

0.02

0.025

0.03

1 2 3 4 5 6 7 8Tra

nsp

irati

on

(

g c

m-2

h-1

)

VPD (kPa)

VPD insensitive

VPD sensitive

0

2

4

6

8

10

12

14

16

Xpsmp2237 Xpsmp2072 M13_Xpsmp2066 M13_Xpsmp3056 Xpsmp2206 Xpsmp2059

No o

f R

ecom

bin

an

ts

markers within LG2 DT-QTL

low Transpiration Rate in high VPD

A - from H77

B - from PRLT

H - heterozygous

Two QTL fine-mapped for low Tr at high VPD

Staygreen ILs (Stg3 – Stg B) are VPD-sensitive

0.0000

0.0020

0.0040

0.0060

0.0080

0.0100

0.0120

9 11 13 15 17

Tra

nsp

irati

on

(g

cm

-2 h

-1)

Time of the day (h)

stg1

stg3

stg4

stgB

R16

B35

Recurrent R16

Stg3

StgB

Transpiration response to VPD in Sorghum 1 - Introgression lines

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.62 1.05 1.58 2.01 2.43 3.05 3.45

Tra

nsp

irati

on

(g

h-1 c

m-2)

VPD (kPa)

Transpiration response to VPD in Sorghum 2 - Germplasm

Germplasm differences in VPD-sensitivity

VPD-Sensitive

VPD- Insensitive

BP= 2.58 R2 =0.68 BP= 2.51 R2 =0.76

R2 =0.89 R2 =0.83

Transpiration response to VPD in Chickpea

Transpiration response to VPD in Peanut

Mouride

If VPD < 2.09, TR = 0.0083 (VPD) – 0.002

If VPD ≥ 2.09, TR = 0.0013 (VPD) + 0.015

R² = 0.97

B UC-CB46

TR = 0.0119 (VPD) - 0.0016

R² = 0.97

D

Transpiration response to VPD in cowpea

Tolerant lines are VPD-sensitive

(water saving)

Tolerant Sensitive

Belko et al – 2012 (Plant Biology)

VPD

Tra

ns

pir

ati

on

(g

cm

-2 h

-1)

0.0 2.0 4.0

0.0

1.0

Main types of Tr response to VPD

Water Saving

Large pattern variation within/across species

VPD-sensitivity often link to drought adaptation

Large variation in all species

Often discriminate tolerant from sensitive lines

Now, systematic screening

Exciting results in other crops (rice, maize)

In summary…




AQP gene expression


Apoplastic

pathway

Symplastic

Pathway

(AQP)

Sorting out the proportion of apoplastic and symplastic water transport

1 mM K4[Fe(CN)6] for 3 h Then 1 mM CuSO4.

Apoplastic pathway inhibition

Apoplastic

pathway

Symplastic

Pathway

(AQP)

Symplastic pathway inhibition

AQP inhibitors: AgNO3 – HgCl2 – H2O2

Follow-up of transpiration before/after inhibition

0.6

0.7

0.8

0.9

1

1.1

1.2N

orm

alized

Tra

nsp

irati

on

Time of the day

VPD-sensitive

VPD - insensitive

Less symplastic inhibition in VPD-sensitive

Pearl millet: Symplastic inhibition

Treatment

M322

M394

M214

M321 M592 M443 M356

M738

40 cM

0.6

0.7

0.8

0.9

1

1.1

1.2

10 30 50 70 90 110 130 150 170 190 210 230 250 270

No

rmalized

tra

nsp

irati

on

Time (minutes)

ICMR1029 1mM

ICMR2042 1mM

H77 1mM

PRLT 1mM

Symplastic inhibition in near-isogenic lines (QTL from VPD-sensitive parent)

NILs behave like QTL donor parent

M322

M394

M214

M321 M592 M443 M356

M738

40 cM

Treatment VPD-sensitive

More apoplastic inhibition in VPD-sensitive

0.00

0.20

0.40

0.60

0.80

1.00

1.20

10:10 10:40 11:10 11:40 12:10 12:40 01:10 01:40 02:10 02:40 03:10

Norm

alized

Tra

nsp

irati

on

Time

Apoplastic

inhibition

Pearl millet: Apoplastic Inhibition

VPD-sensitive

VPD - insensitive

M322

M394

M214

M321 M592 M443 M356

M738

40 cM

0

0.2

0.4

0.6

0.8

1

1.2

Norm

alized

tra

nsp

irati

on

Time

Apoplast & symplast inhibition at low VPD

Apoplastic &

Symplastic inhibition


Apoplastic inhibition

Apoplastic transport predominant

Low VPD small differences/effects

0

0.2

0.4

0.6

0.8

1

1.2

Norm

alized

tran

sp

irati

on

Time(mins)

Apoplast & symplast inhibition at high VPD


Apoplastic inhibition

Apoplastic transport less predominant

High VPD larger differences/effects

Root hydraulic conductance measurement

0.002

0.0025

0.003

0.0035

0.004

0.0045

0.005

0.0055

0.006

VPD-Sensitive VPD-Insensitive

Ro

ot

co

nd

ucti

vit

y

Root hydraulic conductivity

Symplastic transport less predominant In VPD-sensitive

Apoplast

Symplast

(AQP)

Control

Apoplast

Symplast

(AQP)

0.002

0.003

0.004

0.005

0.006

0.007

VPD-Sensitive VPD-Insensitive

Ro

ot

co

nd

ucti

vit

y

Root hydraulic conductivity

Apoplastic transport more predominant In VPD-sensitive

Control

0

0.2

0.4

0.6

0.8

1

1.2

10

30

50

70

90

110

130

150

170

190

210

230

250

270

290

310

330

350

370

390

410

NT

R

Time (mn)

Control

100 uM HgCl2

200 uM HgCl2

Before treatment

ICC 14799

0

0.2

0.4

0.6

0.8

1

1.2

10

30

50

70

90

110

130

150

170

190

210

230

250

270

290

310

330

350

370

390

410

NT

R

Time (mn)

Control

100 uM HgCl2

200 uM HgCl2

Before treatment

ICC 4958

Chickpea: Symplastic Inhibition

Less symplastic inhibition in VPD-sensitive

VPD - sensitive

VPD - insensitive

Apoplastic inhibition of chickpea genotypes

0.00

0.20

0.40

0.60

0.80

1.00

1.20

0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300Time (mins)

NT

R (

No

rm

ali

sed

Tran

sp

irati

on

Rati

o)

ICC 4958 Control ICC 4958 T reatment




1mM K4[Fe(CN)6] 0.5mM CuSO4

VPD-sensitive

VPD - insensitive

Chickpea: Apoplastic Inhibition

Less apoplastic inhibition in VPD-sensitive

Apoplast

Symplast

(AQP)

Apoplast

Symplast

(AQP)

More water via apoplast in VPD-sensitive Limited water via symplast in VPD-sensitive

Insensitive

Sensitive

VPD sensitive have apoplastic water transport

They have limited “tuning” via the symplast

More effort to be put on hydraulic measurement

Many more materials to test

In summary…




AQP gene expression


VPD-insensitive

VPD-sensitive

Any difference in aquaporin expression In sorghum contrasting for VPD response??

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.62 1.05 1.58 2.01 2.43 3.05 3.45

Tra

nsp

irati

on

(g

pl-

1 c

m-2)

VPD (kPa)

• 14 PIPs in the Sorghum genome (4 PIP1, 10 PIP2) • Comparable to maize and rice

• RTqPCR primers designed • Putative reference genes

AQP gene expression in sorghum

• 3 conditions (low VPD am, low VPD pm / High

VPD pm) • RNA then cDNA, ref

genes

• TRqPCR From Hanna Anderberg

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.62 1.05 1.58 2.01 2.43 3.05 3.45

Tra

nsp

irati

on

(g

pl-

1 c

m-2)

VPD (kPa)

Morning (low VPD)

VPD-insensitive

VPD-sensitive

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.62 1.05 1.58 2.01 2.43 3.05 3.45

Tra

nsp

irati

on

(g

pl-

1 c

m-2)

VPD (kPa)

VPD-insensitive

VPD-sensitive

Afternoon (low VPD)

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.62 1.05 1.58 2.01 2.43 3.05 3.45

Tra

nsp

irati

on

(g

pl-

1 c

m-2)

VPD (kPa)

Afternoon (high VPD)

VPD-insensitive

VPD-sensitive

0

2

4

6

8

10

12

14

16

18

Low TE High TE

Hig

h V

PD

/Lo

w V

PD

PIP1;1

PIP1;2

PIP1;3

PIP1;4

PIP2;1

PIP2;2

PIP2;4

PIP2;5

PIP2;6

PIP2;7

PIP2;8

PIP2;9

PIP2;10

PIP relative expression (High VPD/Low VPD)

VPD – insensitive line increases expression of PIP2

PIP2;6

PIP2;9

PIP2;7

VPD-Insensitive VPD-Sensitive

Phylogenetic relationships of AQPs across cereals

Tentative annotation based on rice

Tentative annotation based on sorghum

Tentative annotation based on maize

PIP1;1 Pip1;3/4 pip1.1 PIP1;2 Pip1;3/4 Pip1;3/4 PIP1;3 pip1.5 pip1.5 PIP1;4 pip1.6 pip1.6

PIP2;10 pip2.7 pip2.7 PIP2;10 pip2.2 pip2.1

PIP2;2 hypothetical protein PIP2;2

PIP2;3 pip PIP2;4 pip2.3 pip2.4 PIP2;5 pip2.5 pip2.5 PIP2;6 pip2.6 pip2.5 PIP2;7 pip 95%PIP2;1 PIP2;8 pip2.6 pip2.6 PIP2;9 pip2.6 pip2.3

Tentative annotation in rice, sorghum, maize

VPD

insensitive

High VPD Low VPD

VPD

sensitive VPD

insensitive

VPD

sensitive

0.00.10.20.30.40.50.60.7

VPD-sensitive_LVPD VPD-insensitive_LVPD VPD-sensitive_HVPD VPD_insensitive_Hvpd

ban

d i

nte

nsi

ty

More AQP protein in VPD–insensitive line

AQP protein measurement with maize PIP2;6 antibodies

Total RNA Ist S trand cDNA

Degenerate primer

designing using

other closely related

species as a source

M -Ve 1 2 3 4 5 6 7 8 9

PCR amplifications of Aqp genes from cDNA.

Cloning of PgAqp genes into pCR8/GW/TOPO vector Plasmid DNA isolated for positive Aqp clones

Sequencing

and analysis

Cloning of Aquaporin genes in pearl millet (homology based cloning strategy) .

Phylogentic relationships between pearl millet, maize

and rice Aquaporin proteins

0.25

0.5

1

2

4

8

16

L R L R L R L R

1122 1086 1152 1078

PIP1.1 PIP1.2 PIP2.1 PIP2.3 PIP2.6 TIP1.1 TIP2.2R

ela

tive e

xp

ressio

n

Genotype and Stress conditions

VPD - Insensitive VPD - Sensitive

PIP relative expression (Low VPD)

High AQP expression in VPD-insensitive line

0.25

0.5

1

2

4

8

16

L R L R L R L R

1122 1086 1152 1078

PIP1.1 PIP1.2 PIP2.1 PIP2.3 PIP2.6 TIP1.1 TIP2.2

Genotype and Stress conditions

PIP relative expression (High VPD/Low VPD) R

ela

tive e

xp

ressio

n

VPD - Insensitive VPD - Sensitive

Even Higher AQP expression in VPD-insensitive line under high VPD

Increase in AQP expression in VPD-insensitive under high VPD

Transcript abundance & protein agree

Up regulation in both leaves and roots

On-going work in other species

Comparative genomics

In Summary…




AQP gene expression


0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.62 1.05 1.58 2.01 2.43 3.05 3.45

Tran

spir

ati

on

(g

pl-1

cm

-2)

VPD (kPa)

Why are VPD-sensitive sorghum so interesting?

VPD-insensitive

VPD-sensitive

VPD-sensitive have high transpiration efficiency

2.0

3.0

4.0

5.0

6.0

7.0

152 Germplasm tested

TE

10 lowest TE are VPD-Insensitive

10 highest TE are VPD-sensitive

High TE lines limit transpiration at high VPD

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

TE

0

0.005

0.01

0.015

0.02

0.025

0.03

1 2 3 4 5 6 7 8

Tra

nsp

irati

on

(g

cm

-2 h

-1)

VPD (kPa)

Same result in sorghum and pearl millet

What about pearl millet?

Low TE (VPD-Insensitive)

High TE (VPD-Sensitive)

grain yield gain (low TR)

-300

-200

-100

0

100

200

300

400

0 500 1000 1500 2000 2500 3000 3500

original yield (kg/ha)

yie

ld g

ain

(kg

/ha)

1 postflowering

2 flowering

3 postflowering-relieved

4 no stress

5 prefloweringOriginal yield (kg ha-1)

0

Yield increase (kg/ha) with transpiration sensitivity to high VPD: Rabi sorghum

Yie

ld i

ncrease

-1 0 +33

Crop modelling used to predict trait effects

15-30% yield increase at high latitudes

% yield increase with transpiration sensitivity to high VPD: Peanut

Lysimetric evaluation

Transpiration in pots

0.000

0.004

0.008

0.012

0.016

0.020

0.62 1.05 1.58 2.01 2.43 3.05 3.45

Tra

nsp

ira

tio

n

(g

cm

-2 h

-1)

VPD

Low TE

High TE

0

1

2

3

4

5

6

7

Low TE High TE

TE


-300

-200

-100

0

100

200

300

400

0 500 1000 1500 2000 2500 3000 3500


yie

ld g

ain

(kg

/ha)

1 postflowering

2 flowering


4 no stress

5 preflowering

Original yield (kg ha-1)

0

AQP gene expression

Modeling of Tr restriction effect on yield

The VPD response lead to higher TE

It is itself related to differences in AQP gene expression

Major yield increase possible across crops

Breeding (donors identified)

Harness genetics – Phenotyping (new platform)

In Summary…

Thank you

Collaborators: F. Chaumont (Univ. Louvain) H. Anderberg (Lund Univ.)

Donors: ICRISAT ACIAR DFID B&MGF

Technicians / Data analyst: Srikanth Malayee Rekha Badham

Students: M Tharanya S Sakthi T Rajini S Medina K Aparna

Colleagues: J Kholova / P Suddhakar Reddy / G Barzana / JM Devi/ KK Sharma / T Shah / P Bhatnagar / Hima Bindhu / RK Varshney / R Srivastava / SP Deshpande

Special thanks to: ICRISAT MG/RC Gov. Board

Lysimetric evaluation

Transpiration in pots

0.000

0.004

0.008

0.012

0.016

0.020

0.62 1.05 1.58 2.01 2.43 3.05 3.45

Tra

nsp

ira

tio

n

(g

cm

-2 h

-1)

VPD

Low TE

High TE

0

1

2

3

4

5

6

7

Low TE High TE

TE


-300

-200

-100

0

100

200

300

400

0 500 1000 1500 2000 2500 3000 3500


yie

ld g

ain

(kg

/ha)

1 postflowering

2 flowering


4 no stress

5 preflowering

Original yield (kg ha-1)

0

AQP gene expression

Modeling of Tr restriction effect on yield

Xpsmp2237

Xpsmp2072

17.1 cM

Xpsmp2066

12.0 cM

Xpsmp3056

19.1 cM

Xpsmp2206

14.2 cM

Xpsmp2059

2.5 cM

Grain Yld Flowering time

Grain Yld

Allele effect

Xibmsp44

Xibmsp4

Xibmsp7

Xibmsp60 Xibmsp34

Xibmsp14 Xibmsp24

Xibmsp31 Xibmsp11

Xibmsp62 Xibmsp27 Xibmsp9 Xibmsp12

Xibmsp15

Xibmsp23

PRLT 2/89-33 H 77/833-2

Increased decreased

decreased Increased

Flowering time

Increased decreased

decreased Increased

Stay green decreased Increased

Increased decreased

Tr rate Increased decreased

Tr rate decreased Increased

Stay green

Candidate genes

Zn finger CCCH-type, serine/threonine protein kinase, MADS-box, acetyl CoA carboxylase

Stay green

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Developing crops with high productivity at high temperature: A blue sky research initiative