Practical application of markers: drought tolerant rice

• G4005.69.01 (CB19a/RF−FS022): Developing and disseminating resilient and productive rice varieties for drought-prone environments in India:2005-2009

• G3007.05: Detecting and fine-mapping QTLs with major effects on rice yield under drought stress for deployment via marker-aided breeding:2006-2010

Arvind Kumar

International Rice Research Institute

Outline • QTLs for grain yield under drought: limitations

• MAB of DTY12.1 to improve drought tolerant cultivar Vandana

• IR64 lines with four DTY QTL: ABQTL

• MAB of DTY1.1, DTY3.1, DTY2.2 QTLs in Swarna sub1

• A QTL with consistent effect in multiple high yielding genetic backgrounds

• Lessons learnt

• Major drought yield QTLs: true and effective

• QTLs x genetic background interaction: a constraint

• QTLs identification in improved genetic background- variety that needs improvement – IR64, Vandana, Swarna, Sambha Mahsuri, MTU1010, Sabitri, TDK 1 sub 1, NSICRc 222, BR11, Saro 5

• Effect of individual QTLs 300-500 kg ha-1, pyramid two-three QTLs to get 1.0 t ha-1 or more yield advantage

QTLs for grain yield under drought: limitations

Improving drought tolerant cultivar Vandana:DTY12.1

• DTY12.1 identified in Vandana/Way Rarem (Bernier et al. 2007)

• Contributed by susceptible parent- Way Rarem

• Mapped to 2.7 Mb (RM28048-RM28166

• Consistent effect in target locations (Bernier et al. 2009)

• Minor QTLs affecting GY and related trait contributed by drought tolerant parent Vandana (Bernier et al. 2007)

Minor QTLs • DTY2.3 – RM1367-RM3212:

(panicle m2) • DTY3.2 –RM7332-RM545:

(biomass)

Fine mapping DTY12.1

• DTY12.1A- 0.8Mb (RM28099-RM511

• DTY12.1B- 0.1 Mb (RM1261-RM28166)

• Both regions show effect in severe, moderate, mild drought stress

• Effect increases with stress severity (Bernier et al. 2009)

• DTY9.1, DTY2.1 and DTY2.2

were also fine mapped

Dixit et al. 2011, TAG under revision

Fine mapping and introgression strategy for DTY12.1

Way Rarem Vandana IR90020:22-283-B-4-B

Genotypes

Upland severe stress Upland non- stress

GY DTF PHT BIO HI GY DTF PHT BIO HI

IR 84984-83-15-481-B 693 64 75 4160 0.17 2525 62 79 9584 0.29

IR 84984-21-19-78-B 478 66 74 3333 0.13 2996 65 89 10769 0.31

IR 90020:22-283-B-1-B 604 66 79 4160 0.14 3039 66 85 11610 0.29

IR 90020:22-283-B-4-B 515 67 77 4133 0.21 2245 68 84 7579 0.27

Way Rarem 0 NF 60 266.7 0.01 1660 87 100 NA NA

Vandana 27 70 79 2080 0.09 2127 68 91 10498 0.34

Apo 0.1 NF 57 226.7 0 2127 80 101 NA NA

Apo

Performance of NILs under severe upland stress

Dixit et al. 2011 Plant Physiology, submitted IRRI, 2011 DS

0

500

1000

1500

2000

2500

Non- stress Mild stress Moderate stress Severe stress

Stress conndition

Perc

en

tag

e a

dvan

tag

e o

ver

Van

dan

a

IR84984-83-15-851-B IR84984-83-15-332-B IR84984-83-15-481-B

IR84984-21-19-48-B IR84984-83-15-330-B

qDTY12.1 NILs advantage over Vandana under

varying stress conditions: Line source: IRRI

DS2011

Way Rarem Swarna Vandana + NIL IR84984-83-15-481-B

Seeding date Feb 1

Stress initiation Feb 5

Harvest date May 15

Days with rainfall >5mm during the

experiment

March 1 -13 60.0 mm

April 29 6.3 mm

May 8 60.0 mm

May 11 38.0 mm

Total 164.3 mm

Swarna +NIL Swarna

Way

Rarem Vandana

Grain type of donor parent (Way Rarem), recipient parent (Vandana), NIL (IR90019:17-156-B) and pre NIL

(IR90019:17-15-B)

Vandana QTL lines are under testing in India (4), Philippines (2)

DTY12.1 interactions with minor QTLs

Eco-

system

qDTY12.1-qDTY2.3

Class mean

++ +- -+ -- Add.

USS-I 913 519 332 202 43.5

USS-II 533 428 242 200 16.7

UNS-I 3298 2991 3143 2851 5.2

UNS-II 3032 2533 2861 2703 9.3

Eco-

system

qDTY12.1-qDTY2.3

Add.

Class mean

++ +− −+ −−

LSS 1169 1012 1076 804 8

LMS 1542 1201 1429 1381 12.1

LMiS 2618 2566 2544 2498 1.1

Upland Lowland

Designation Non-Stress Mild Stress Moderate stress Severe Stress IR84996-4-1-B 2457 1859 772 236

IR84996-50-1-B 4242 2319 1428 251

IR84996-50-4-B 2831 1859 1091 172

IR84996-50-6-B 3942 2254 1187 148

IR84996-72-6-B 2304 2229 1115 127

Way Rarem 2126 1224 601 58

Vandana 1976 1535 376 405

APO 2445 1882 1199 130

Trial mean 2379 1606 890 118

p value <0.0001 <0.0001 <0.0001 <0.0001

Way Rarem lines

with QTLDTY2.3

Dixit et al. 2011, Molecular Breeding, submitted

IR64: DTY2.2, DTY4.1, DTY9.1, DTY10.1 introgression

• Aday sel/4*IR64 ABQTL analysis

• 6 mapping populations developed

(IR77298-14-1-2-10, IR771298-5-6-

18) with (IR64, IR77298-14-1-2-13,

IR771298-5-6-11)

Chr MinOf5p MaxOf3p MinOfFisherP size (BP)

2 10,147,149 10,886,276 2.80E-02 739,127

4 12,522,585 13,220,820 3.84E-04 698,235

6 22,708,740 23,455,589 2.95E-02 746,849

9 5,028,455 5,490,310 2.57E-02 461,855

Regions identified by Affy-chip analysis

Hei Leung and Mauleon Ramil, IRRI, unpublished

Population Year Chrom. Marker Interval F R2

Additive

effect

P1 DS09 9 RM566-RM24350 39.4 9.6 201.7

P1 DS10 9 RM566-RM24350 36.7 8.2 89.2

P1 (Combined) DS09&DS10 9 RM566-RM24350 50.9 13 134.4

P2 DS09 9 RM566-RM24350 77.2 19 352.6

P1 DS09 2 RM236-279 28.6 6 166.7

P1 DS10 2 RM236-RM279 19.5 9.3 105.5

P1 (Combined) DS09&DS10 2 RM236-RM279 37.3 9.1 121.8

P4 DS08 2 RM236/RM279-RM555 35 11 112.8

P3 DS10 2 RM236-RM279 108.3 3 147.5

P3 DS10 10

RM258-RM25694 28.7 17 298.1

P4 WS07 4

RM335-RM518 14.7 11 127.1

Major QTLs in IR64 background

Line QTLs DF PH GY GY GS

(%) (NS) (NS) (NS) (S)

DS11 DS11 DS10 DS11 DS10 DS11

IR 87729-69-B-B-B DTY9.1, DTY2.1, DTY10.1,

DTY4.1

83 91 4312 6308 2011 1943 94.4

IR 87728-491-B-B DTY9.1, DTY2.1, DTY4.1 82 95 - 6232 1041 1879 92.6

IR 87707-186-B-B-B DTY2.1, DTY10.1, DTY4.1 78 99 4550 6103 2068 2632 96.9

IR 87707-446-B-B-B DTY2.1, DTY4.1 80 98 3752 4388 2556 3000 97.0

IR 87707-445-B-B-B DTY2.1, DTY4.1 77 96 5045 5844 2555 3023 96.9

IR 87728-162-B-B DTY9.1, DTY2.1 84 94 - 6115 1147 1636 92.4

IR 87705-83-12-B DTY2.1, DTY10.1 80 95 4796 5526 1916 2270 95.0

IR 87705-80-15-B DTY10.1, DTY4.1 81 89 3850 5516 2074 2151 94.6

IR64 80 96 2987 5435 636 1442

LSD0.05 3 7 1053 690

IR 64 + QTLs lines

IR64 QTLs lines under non-stress and stress

IR64 + QTL line Drought Stress

2011DS, IRRI

Non-Stress

2011 DS, IRRI

+ QTL line IR64

IR64 QTL lines under testing in WS2011 at 14 locations in India under

AICRIP program; Nepal (03), Bangladesh (01), Philippines (01), and will

be under testing in Tanzania and Mozambique in 2011-2012

Swarna sub 1 + drought

• Three drought yield QTLs pyramided in Swarna sub1

• BC4F2 population with three QTLs under test at IRRI

DTY1.1, DTY3.1, DTY2.1 pyramided

Swarna Swarna + DTY

- QTL + QTL - QTL

DTY3.1: Hazaribagh, 2008

Dhagaddeshi x Swarna Dhagaddeshi x IR64Dhagaddeshi x Swarna Dhagaddeshi x IR64

N22 × Swarna 30.20%

N22 × IR64 25.80%

N22 × MTU1010 16.90%

Dhagaddeshi ×

Swarna 24.80%

Dhagaddeshi ×IR64 8.55%

Additive effects in five

populations for grain yield

under drought

DTY1.1: multiple donors - multiple backgrounds

Vikram et al. 2011, BMC Genetics under revision

Meta analysis of DTY QTLs MQTL AIC value Mean phenotypic

variance of the QTLs

Mean initial CI (cM)

Physical length of MQTL

(Mb)

MQTL1.1 146.2 16 7.5 1.14

MQTL2.1 62.7 12 10.5 1.24

MQTL3.1 45.2 13 5.4 0.84

MQTL10.1 61.8 4 13 5.3

MQTL12.1 21.2 28 4.2 0.7

Testing the effect of QTLs on a set of drought tolerant panel lines

0

10

20

30

40

50

60

70

80

90

QTL1.1

QTL1.2

QTL2.1

QTL2.3

QTL3.1

QTL3.2

QTL4.1

QTL4.2

QTL4.3

QTL6.1

QTL8.1

QTL12.1

DTY QTLs

Drou

ght p

anel

line

s (%

)

Swamy et al. 2011, BMC Genomics

Synteny and comparative map of QTLs in

rice and maize

DTY1.1 region in rice – Maize 3, wheat 4B, barley 6H

DTY3.1 region in rice – Maize 1

Swamy et al. 2011, BMC Genomics

Lessons learnt • Combine MAB with accurate drought phenotyping to identify

best lines.

• Initially select larger number of fixed lines with QTLs for insect, disease and quality analysis.

• Some of the QTLs regions contain within them loci with negative effect on GY. Fine mapping and identification of such alleles necessary .

• Some of the DTY QTLs are linked to early flowering and tall height; larger population in BC1, BC2 to break the linkage, select the desired segregants.

• Variety to be improved and donor combination should be suitably decided before initiation of QTL study.

• Know the requirements of the national systems.

BANGLADESH NEPAL INDIA AfricaRice LAOS PHILIPPINES TANZANIA MOZAMBIQUE

2008-BMGF – Varietal Improv.

2011 - BMGF JAPAN BREEDING BMZ

R

A

J

G

A

Z

R

R

S

N R R P

N D U A T

U

A

S

I G A U

C R R I

T N A U

C R U R R S

B

A

U

B

F D A S R C

I I A M

R C C R C

P H i l R i c e

Replicated MET under

managed stress and full irrigation

National testing

Targeted Dissemination

2007 GCP- QTL identification

On farm

testing

Drought Breeding Network: 2005 GCP-RF: Network testing

Initial testing 300-500 lines under

stress & control – OYT-AYT

RDA, Korea

Malaysia

Devgen

2011 GCP: Community

practice, MARS

Donors

Generation Challenge program

Rockefeller Foundation

Bill and Melinda Gates Foundation

Asian Development Bank

Devgen

RDA, Korea

BMZ, Germany

Univ. Kebangsaan Malaysia, Bangi

Partners Bangladesh

BRRI, Gazipur

RRS, Rajshahi

India

AAU, Anand

BAU, Ranchi

BF, Hyderabad

CRRI, Cuttack

CRURRS, Hazaribag

DRR, Hyderabad

ICAR-NEH, Tripura

IGAU, Raipur

JNKVV, Jabalpur

NDUAT, Faizabad

OUAT, Bhubaneshwar

TNAU, Coimbatore

UAS, Bangalore

Nepal

NRRP, Hardinath

RARS, Nepalganj

RARS, Tarharra

Philippines – PhilRice

Laos – NAFRI

Mozambique-IIAM, Chokwe

Tanzania –DASRC, Morogoro

Malaysia – UKM and MARDI

RDA, Korea

Devgen

Thank you very much for your attention