Presentation in FCSSP, Drought, rice

1. Molecular Breeding for Improving
Drought Tolerance in Rice Mega
Varieties: Progress at IRRI
21FCSSP, Scientific Conference
May 9-14, 2011
B.P. Mallikarjuna Swamy

2. “I challenge the next generation to use
new scientific tools and techniques to
address the problems that plague the
world’s poor.”
Dr. Norman Borlaug
Combination of Breeding
and Biotechnology
hastens the process of
development of
Commercial Products
Marker based technology is successfully being
used in plant breeding to address the complex
problems

3. “Drought” may mean physical water scarcity
constrains growth or development
process affects the normal crop management
practices
Donor Yield Yield 7000
Stress Non-
Yield of cultivar (kg ha-1)
6000
stress
5000
kg ha-1
4000
MTU1001 312 5825
3000
Madhuri line 9 312 4957
Nidhi 356 4963 2000
IR64 278 4685 1000
Mahamaya 318 4344 0
Severe Moderate Control
Swarna 312 5822
stress level
Mahamaya
Sambha Mahsuri
Marker Assisted Breeding is more precise, cost effective and time
saving technology to address the complex problem of drought

4. Drought at which stage?
• Drought can appear at any
stage of the rice crop- seedling,
vegetative, reproductive;
• One at reproductive stage is
highly damaging, highly
prevalent
57 64 69 73 78 85 90 95 Control
Lafitte, unpublished
O’Toole 1982

5. What new now that can make difference?
Earlier At present
Secondary trait based Selection for grain yield itself
selection Combine yield potential with drought
tolerance
Traditional donors Improved donors with good combining
ability
Variable phenotyping Standardized phenotyping
65-85% yield reduction
Secondary traits QTLs Yield QTLs
Advanced tools for MB not in Advanced MB tools available
hand
Advance generations testing Early generations testing under drought
under drought
Less drought occurrence-less Water scarcity realized- efforts enhanced
sincere efforts
Less Funding, commitment Increased funding and commitment

6. Drought molecular Breeding at IRRI:
Strategy
• Use traditional/wild donors in mapping populations
• Identify major drought yield QTLs
• Validation of major effect QTLs
genetic backgrounds
environments
meta analysis
comparative genomics
• Introgression of QTLs in improved drought susceptible varieties
• Physiological and molecular mechanism of drought QTLs
aim is to produce more crop per drop of water

7. Major drought yield QTLs in background of
improved popular varieties
Genetic Additive
Background QTLs Ecosystem effect % mean
Vandna DTY12.1 Upland 47
IR64 DTY1.1 Lowland 32
IR64 DTY9.1 Lowland 27
IR64 DTY10.1 Lowland 22
IR64 DTY2.1 Lowland 13
IR64 DTY4.1 Lowland 14
Swarna DTY1.1 Lowland 25
Swarna DTY2.1 Lowland 19
Swarna DTY3.1 Lowland 25
Swarna DTY8.1 Lowland 16
MTU1010 DTY1.1 Lowland 17

8. DTY1.1:First consensus major QTL
N I H L N M H L
RM431
GY
RM212825 RM315 RM11943
RM431 RM104
Prashant Vikram, Krishna Ghimire, Leni Quiatchon, IRRI

9. How real are DTY? DTY QTLs % of lines
Testing QTLs in a panel of DTY1.1 64
90 tolerant lines DTY2.1 49
DTY3.1 77
Meta-QTL analysis DTY8.1 52
DTY12.1 85
Chr region Mean Initial MQTL MQTL
MQTL
PV CI (cM) (cM) (Mb)
MQTL1.1 1 RG109–RM431 12 7.60 2.40 0.36
MQTL2.1 2 RM452–RM521 12 10.50 5.28 1.24
MQTL2.2 2 RM526–RM497 6 12.00 11.50 2.36
MQTL3.2 3 RM520– M16030 20 10.30 3.40 0.98
MQTL10.2 10 RM596–RM304 16 15.00 23.72 2.60
MQTL12.1 12 RM277–RM260 28 4.20 1.79 0.70
M. Swamy et al. 2011)

10. 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
M. Swamy et al. 2011

11. Marker Assisted Breeding Protocol

12. Protocol for pyramiding major effect QTLs
Generation No. of seeds/Plants Genotyping Cross
Selection of - Fore ground selection Make crosses between
parents QTL1.1 – M1, M2, M3 ( DA1) plants with QTL1.1 and
QTL1.2 – M4, M5, M6, M7, M8, M9 (DA2) QTL1.2
F1 (Two QTLs) 50 confirm F1 Make crosses between
•QTL1.1 - M1, M2, M3 ( DA1) plants having QTL1.1 and
• QTL1.2 – M4, M5, M6, M7, M8, M9 (DA2) QTL1.2 with plants having
•Select plants with QTL QTL 1.3
F1 (Three QTLs) 100 confirm F1 Cross F1 plants with three
•QTL1.1 - M1, M2, M3 ( DA1) QTLs to recipient parent
•QTL1.2 – M4, M5, M6, M7, M8, M9 (DA2) (RP)
•QTL1.3 - M10, M11, M12, M13, M14 (DA3)
•Select plants with all the QTLs (QTL1.1, QTL1.2, QTL1.3)
BC1F1 500 confirm BC1F1 Cross BC1F1 with three
•QTL1.1 - M1, M2, M3 ( DA1) QTLs to RP
•QTL1.2 – M4, M5, M6, M7,M8,M9 (DA2)
•QTL1.3 - M10, M11, M12, M13, M14 (DA3)
•Select plants with all the three QTLs
•Back ground selection using 100 SSR markers uniformly distributed on all the
chromosomes in selected plants
BC2F1 1000 confirm BC2F1 Self the selected plants
•QTL1.1 - M1, M2, M3 ( DA1)
•QTL1.2 – M4, M5, M6, M7, M8, M9 (DA2)
•QTL1.3 - M10, M11, M12, M13, M14 (DA3)
•Select plants with all the three QTLs
•Back ground selection for segregating SSR markers in selected plants
BC2F2 2000 confirm F2 Select the plants with
•QTL1.1 - M1, M2, M3 ( DA1) all the three QTLs , RP
flanking and more recipient
•QTL1.2 – M4, M5, M6, M7, M8, M9 (DA2)
background
•QTL1.3 - M10, M11, M12, M13, M14 (DA3) Advance the lines
•Select plants with all the three QTLs in homozygous condition
•Back ground selection for segregating SSR markers in selected plants
•Check for QTL flanking markers (RA)
•Select the plants with QTLs in homozygous condition, flanks with recipient

13. Improved IR64 introgression lines
Line GS
QTLs GY Drought GY Control (%)
DS09 DS10 DS09 WS10
IR 87729-69-B-B-B DTY9.1, DTY2.1, DTY10.1,
DTY4.1 2006 2011 6936 4627 94.4
IR 87728-102-B-B DTY9.1, DTY10.1,DTY4.1 2440 1160 6059 5462 92.9
IR 87707-186-B-B-B DTY2.1, DTY10.1,DTY4.1 3200 2068 6289 6737 96.9
IR 87707-446-B-B-B DTY2.1, DTY4.1 3624 2556 6005 6076 97.0
IR 87707-445-B-B-B DTY2.1, DTY4.1 3639 2555 8006 5565 96.9
IR 87707-118-B-B-B DTY2.1, DTY4.1 3264 2273 6096 4617 95.8
IR 87705-21-13-B DTY2.1 2223 4785 6231 95.8
IR 87705-6-8-B DTY4.1 2152 5399 5576 95.5
IR 87728-395-B-B DTY9.1 1122 5500 5457 93.4
IR 87705-36-3-B DTY10.1 2062 5052 7211 95.3
IR64 567 636 4151 5811
M. Swamy, IRRI

14. Quality traits of IR64 introgression
lines
LINES QTLs DTF PH AC GT MP CS
IR 87729-69-B-B-B DTY9.1, DTY2.1, DTY10.1,
DTY4.1 86 98 20.7 I 1 1
IR 87728-102-B-B DTY9.1, DTY10.1,DTY4.1 86 101 20.1 I 1 1
IR 87707-186-B-B-B DTY2.1, DTY10.1,DTY4.1 82 107 21.6 I 2 1
IR 87707-446-B-B-B DTY2.1, DTY4.1 81 106 22.2 I 1 1
IR 87707-445-B-B-B DTY2.1, DTY4.1 83 111 22.3 I 1 1
IR 87707-118-B-B-B DTY2.1, DTY4.1 83 108 20.7 I 1 1
IR 87705-21-13-B DTY2.1 82 86 21 I 2 1
IR 87705-6-8-B DTY4.1 80 85 21 I/L 2 1
IR 87728-395-B-B DTY9.1 86 100 20.2 I 1 2
IR 87705-36-3-B DTY10.1 87 84 20.3 I 1 1
IR64 82 105 21.8 I/L 1 1
M. Swamy, IRRI

15. IR 64 introgression lines with DTY QTLs
+ QTL - QTL
IR64 IR64+DTY QTLs
Parents- 2007 Introgressions under drought- 2010
DTY IR 64
introgressed line
Similar to IR64 grain quality traits of Product - 2011
introgressed lines

16. Line 1 Line 2

17. + QTL IR64

18. Introgression of DTY3.1 and DTY2.1 in Swarna
IR81896-B-195 X Swarna Fore ground selection for QTLs
Background selection
(BC1 line with QTLs)
BC2 X Swarna Fore ground selection with segregating markers
Background
selection for QTLs and Sub1 locus
Fore ground selection for QTLs and Sub1 locus
BC3 X Swarna Background selection with segregating markers
Fore ground selection for QTLs and Sub1 locus
BC4F 1
Background selection with segregating markers
Selected plants selfed
Select homozygote's for QTLs and Sub1 locus
Background selection with segregating markers
BC4F2
Selected BC4F3 plants will be phenotyped under drought

19. DTY3.1, DTY2.1 in Swarna, Swarna sub1
Swarna lLs
(DTY +Sub1)
Swarna
M. Swamy, IRRI

20. DTY1.1, DTY3.1, DTY2.1 in Swarna, Swarna sub1
BC4F1 Swarna lines (three QTLs +Sub1)
*2 in 1 rice for drought and submergence prone areas

21. Development of improved Vandana with DTY12.1
Grain yield (Kgha-1)
%
Lines Generation DTF PHT
USS UMS UNS BG
A
IR 84984-83-15-110-B BC2F2:4 299 1514 4855 54 124 92.4
IR 84984-83-15-481-B BC2F2:4 175 1300 4196 55 120 94.1
IR 84984-83-15-862-B BC2F2:4 238 1114 4018 58 121 94.1
Vandana 72 825 3556 54 120
Way Rarem 11 212 1610 81 122
B IR 90019:17-156-B BC3F2:3 522 1487 4712 61 106 98.3
IR 90019:17-159-B BC3F2:3 461 1930 5236 62 103 97.5
IR 90019:17-15-B BC3F2:3 565 2341 4534 65 107 98.3
IR 90020:22-265-B BC3F2:3 446 2090 4233 60 115 96.6
IR 90020:22-283-B BC3F2:3 415 1224 5950 58 100 94.9
Vandana 179 1049 4061 56 104
Way Rarem 0.1 500 2878 81 103
Dixit, Shalabh, IRRI

22. Differences in grain type of donor parent (Way Rarem), Recipient parent (Vandana), NIL (IR90019:17-
156-B) and pre NIL (IR90019:17-15-B)

24. Partners
Bangladesh Philippines – PhilRice
BRRI, Gazipur Laos – NAFRI
RRS, Rajshahi Mozambique-IIAM, Chokwe
Tanzania –DASRC, Morogoro
India
Malaysia – UKM and MARDI
AAU, Anand RDA, Korea
BAU, Ranchi
BF, Hyderabad
CRRI, Cuttack
CRURRS, Hazaribag
DRR, Hyderabad
ICAR-NEH, Tripura Donors
IGAU, Raipur Rockefeller Foundation
JNKVV, Jabalpur Bill and Melinda Gates Foundation
NDUAT, Faizabad
OUAT, Bhubaneshwar Generation Challenge program
TNAU, Coimbatore Asian Development Bank
UAS, Bangalore
Devgen
Nepal RDA, Korea
BMZ, Germany
NRRP, Hardinath
RARS, Nepalganj Univ. Kebangsaan Malaysia, Bangi
RARS, Tarharra MARDI, Malaysia

25. Everything can wait
but not agriculture
Thanks