1. Mapping and Transferring QTLs
for drought tolerance in rice
B.P. Mallikarjuna Swamy
November, 19, 2012
Molecular Breeding Course
2012

2. Rice
production
• Rice cultivated on around 150 m ha
• 45% of this area is rainfed
• Average rice productivity in rainfed
area is less than half of that
in irrigated areas
• No possibility to expand the
irrigation facility due to shrinking
water resources
• Needed increased rice production
to meet the growing demand can
only be met through increased
productivity in rainfed ecosystem

3. Drought
Region Rice area (M ha) Drought-prone rice
area (M ha)
Upland Rainfed Upland Rainfed
Lowland Lowland
E. Asia 0.6 2.0 0.6 0.5
S. Asia 7.3 33.2 7.3 8.5
S.E. 2.7 20.8 2.7 4.3
Asia
80% rice area in Sub Saharan Africa is rainfed
57 64 69 73 78 85 90 95 Control
Lafitte, unpublished
O’Toole 1982

4. Varieties currently grown
in
drought prone areas
• Most of the high yielding
varieties grown in rainfed
areas are highly susceptible
to abiotic stresses
• IR64, MTU 1010, Swarna
grown in drought prone area
are high yielding but highly
susceptible to drought

5. What it takes to develop a drought
tolerant variety?
• High yield under normal situation
• Tolerance to drought at reproductive stage
• Tolerance to drought at seedling and vegetative stage
• Tolerant to blast, brown spot, bacterial leaf blight
• Ability to withstand delayed transplanting conditions
• Ability to yield well under low-moderate fertilizer
management
• Ability to be grown under direct seeded situation in case of
unavailability of water for transplanting
• Good grain quality/quality maintenance under drought
• High framers’ preference
• National system support
• Efficient dissemination support

6. Drought Research at IRRI: Strategy
Conventional approaches
• Use improved pre-breeding lines as
donors
• Direct selection for grain yield
• Combine high yield potential with good
yield under drought
• Confirm performance in multi location
testing in target environment-Drought
breeding network
Molecular approaches
• Use traditional/wild donors in mapping populations
• Identify major drought yield QTLs
• Introgress QTLs in improved drought susceptible varieties
• Physiological and molecular mechanism of QTLs drought tolerance

7. Direct selection for grain yield
under drought stress
Population Situation Heritability rg
S NS
IR 55419-04/Way Upland 0.45 0.61 0.31
Rarem
Upland 0.66 0.47 0.21
IR 55419-04/IR Upland 0.49 0.48 0.67
64
Upland 0.52 0.67 0.22
Abhaya/Safri 17 Lowland 0.67 0.41 0.20
Lowland 0.62 0.53 0.36
Lowland 0.59 0.56 0.38
Lowland 0.58 0.68 0.32
6000
Grain yield kgha-1
5000 Selection
4000 Environment Moderate Natural Severe
stress stress stress
Grain yield (kg ha -1)
3000
2000
Drought stress Non stress 1901 1030 a 581 a
1000 Irrigated control
0 Random 1861 1031 a
561 a
Abhaya
Safri 17
IR79907-B-
IR79913-B-
IR64
R2038-2
IR55419-04
Way Rarem
Stress 2150 1250 b
791 b
406
176
LSD0 0 . 05 360 111 131

8. Precise drought phenotyping
30-60% reduction- moderate drought
65-85% reduction- severe drought Genotype
Farmer’s field (UP, India; Oct. 2007)
Yield & stability, adaptation, quality etc.
NARS on-station MET (CRRI Cuttack, India):
Yield, GxE, Crop adaptation, acceptability
IRRI Field: yield & growth processes, traits
IRRI Greenhouse: whole plant
responses & processes
Environment
& Management Platforms e.g. phenopsis INRA-Fr
HTP linkage Gene function-
plant/cellular processes

9. DS, IRRI vs. WS, NARES screening
r=0.57 Reproductive stage drought
Irrigated control
60-85% GY reduction - Severe
Verulkar et al. FCR 117 30-60% GY reduction - moderate
IRRI, DS India, WS

10. Molecular approaches to improve
drought tolerance in rice
• Identification of major QTLs for grain yield
under drought
• QTL X environment and QTL X genetic
background interaction under drought
• Major QTLs in background of mega varieties
• QTLs effective against multiple genetic
backgrounds
• Introgression of major QTLs in popular
varieties IR64, Swarna, Swarna sub 1

11. Approach
• Large mapping populations (400-500) from crosses of
drought tolerant donors with mega varieties
• Phenotyping of mapping populations in dry season in
managed cyclic severe stress that reduces yield by 65-
85% as compared to irrigated yields
• Genotype the population following selective
genotyping/BSA approach, add additional markers in
the region found to possess QTLs
• Validate the effect of QTLs in target environments on a
set of lines with and without QTLs
• Fine map and introgress the QTL in mega varieties for
which identified

12. Molecular Approaches for efficient drought Breeding
1. Identification of QTLs 2. Transfer of QTLs in Mega Varieties
Identification of Major QTLs in the background of Mega
Varieties-IR64, MTU1010, Swarna, Sambha Mahsuri
Mega Varieties ( Swarna,
Drought tolerant donor
(e.g.N22)
X Sambha Mahsuri,MTU1010, QTL Transfer in Mega varieties
IR64) Fine Mapping
Candidate gene analysis
F1
F2 ( take single seed from each Phenotyping in next
F2 F2plant) season with F5 plants for
Grow single F3 plant validation of QTLs.
and harvest
individually
Identification of large
effect QTLs for yield
Phenotyping with single
plant harvest as F4
progeny.
+ Genotyping (Parental survey, BSA
or Selective genotyping, whole
under drought.
genome scan with SSR markers)

13. Efficient, cost effective strategy: BSA for
identifying consistent QTLs
N22 IR64 BH BL N22 IR64 BH BL
QTL identification in multiple
populations simultaneously
RM431
Dhagaddeshi
Dhagaddeshi Identify few markers in BSA
Swarna
Swarna
BH
BH
BL
BL
BSA with adjoining markers
of the identified one
RM11943 RM431 Validation of BSA results
ADVANTAGES of BSA
Consistent Drought Grain Yield QTLs
Cost effective Identified via BSA
Can be applied with expensive marker systems like SNP
qDTY1.1; qDTY2.2; qDTY3.1;
(Becker et al. 2011-Plos One)
qDTY3.2; qDTY4.1; qDTY6.1; qDTY12.1
RNA can be pooled for microarray (Kadam et al. 2012)
Vikram et al. 2012, FCR

14. Why rice is a suitable case for MAB for GY
under drought?
In rice at IRRI
• Many QTLs reported with
– Consistent effect in different environments
– Consistent effect in different genetic backgrounds
– Consistent effect in different ecosystems
– Products developed with increased GY

15. Major effect QTLs for grain yield under drought
Phenotypic
Variety QTL Donor Ecosystem Additive effect variance (R2)
Vandana qDTY12.1 Way Rarem Upland 47 33
IR64 qDTY1.1 N22 Lowland 24 17
qDTY2.2 Adaysel Lowland 14 6
qDTY4.1 Adaysel Lowland 6 11
qDTY9.1 Adaysel Lowland 29 19
qDTY10.1 Adaysel Lowland 18 17
Swarna qDTY1.1 N22 Lowland 29 13
qDTY1.1 Dhagaddeshi Lowland 25 32
qDTY2.1 Apo Lowland 23 7
qDTY3.1 Apo Lowland 30 27
Sabitri qDTY12.1 IR74371-46-1-1 Lowland 25 47
qDTY3.2 IR77298-5-6-18 Lowland 16 19
Samba
Mahsuri qDTY11.1 IR55419-04 Lowland 32 14
TDK1 qDTY3.1 IR55419-04 Lowland 10 7
qDTY6.1 IR55419-04 Lowland 12 9
qDTY6.2 IR55419-04 Lowland 16 10

16. 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, BMC Genomics

17. 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, BMC Genomics

18. DTY 1.1 :Large effect QTL across the
backgrounds
N22/
N22/ IR64 N22/ Swarna
MTU1010
Population N22/MTU1010 N22/IR64 N22/Swarna
Interval RM315-RM12023 RM11943-RM431 RM11943-RM431
RM315 Chromosome 1 1 1
2.36 Mb
Additive Effect (Kg/ha) 375.8 0 335.92 605.24
RM12023
Population mean ( Kg/ha) 2092.15 1645.05 1589.9
Additive Effect % of Trial mean 17.96 % 20.42% 38.06%
F-value 37.59 41.47 68.76
Chromosome1
Prashanth et al. 2011, BMC Genetics

19. qDTY 1.1 effect across ecosystem,
environments & backgrounds
Additive
Population Ecosystem Location Reference
effect*
CT9993-5-10-1- Raipur,
20.6 Lowland Kumar et al. 2007
M/IR62266-42-6-2 India
Apo/IR64 52.2 Upland IRRI Venuprasad et al. 2011
Apo/IR72 63.6 Upland IRRI Venuprasad et al. 2011
IR64*2/Azucena 36.2 Upland IRRI Venuprasad et al. 2011
Vandana/IR64 25.6 Upland IRRI Venuprasad et al. 2011
Vandana/IR72 63.4 Upland IRRI Venuprasad et al. 2011
N22/IR64 24.3 Lowland IRRI Vikram et al. 2011
N22/MTU1010 16.1 Lowland IRRI Vikram et al. 2011
Dhagaddeshi/Swarna 24.9 Lowland IRRI Ghimire et al. 2012
Dhagaddeshi/IR64 8.3 Lowland IRRI Ghimire et al. 2012
* Maximum additive effect as the % of trial mean
Prashant, IRRI

20. qDTY3.1 : Major effect and consistent QTL in Swarna
and BR11
Additive Recipien
QTLs Chr Interval R2 Donor
effect t
DTY3.1 RM520-
3 30 25 Apo Swarna
RM16030
DTY3.1 RM15935-
3 20-25 22 Apo BR11
RM520
Apo x Swarna
Apo x BR11
Swamy, IRRI

21. First major QTL for grain yield under drought
in rice -DTY12.1
CHR. 12
FINE MAPPED REGION
RM247 3.1 Mbp DTY12.1
RM3472 3.8 Mbp
14.1 RM 28048
16.1 Ind 8
RM3103 7.4 Mbp 15.1 RM 28076
RM7195 9.8 Mbp
15.4 RM 28089
RM28048 14.1 Mbp
3.5 Mbp
15.8 RM 28099 16.7 RM 28130
RM511 17.3 Mbp
0.6 Mbp
RM1261 17.5 Mbp 16.1 Ind 8
16.5 Ind 4 17.3 RM 511
RM28166 17.6 Mbp
16.7 RM 28130 0.3 Mbp
RM3739 24.9 Mbp
17.3 RM 511
17.6 RM 28166
RM235 26.1 Mbp 17.5 RM 1261
RM17 26.9 Mbp 17.6 RM 28166
Identification Fine mapping on For further confirmation
BC2 in BC2 and BC3 21
populations

22. DTY12.1 grain yield under two water regimes
Mild stress Severe stress

23. Large effect drought QTLs
• qDTY 1.1 , qDTY 2.3 , qDTY 3.1 , qDTY 3.2 , qDTY 12.1 shows
effect against-
– Different drought susceptible recipient varieties
– Different environments
– Across both lowland and upland ecosystem
• No guarantee if MAB is not carried by an experienced
drought breeder as many minor modifications are
needed during the process of MAB

24. Major drought yield QTLs in background of
improved popular varieties: IR64
Genetic Additive effect as
Backgrounds QTLs Ecosystem % of trial mean
IR64 DTY9.1 Lowland 27
IR64 DTY10.1 Lowland 22
IR64 DTY2.1 Lowland 13
IR64 DTY4.1 Lowland 14
IR64 DTY1.1 Lowland 32

25. QTLs in IR64 Back ground
P4, 2007WS
P1, 2009DS P1, 2010DS P3, 2010DS P4, 2008DS
DTY2.2 DTY4.1

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

27. IR64 QTLs lines under non-stress and stress
+ QTL line Non-Stress IR64 + QTL line Drought Stress IR64
2011 DS, IRRI 2011DS, IRRI
IR64 QTL lines under testing in WS2011, WS2012 at 14 locations in India
under AICRIP program; Nepal (03), Bangladesh (01), Philippines (01),

28. IR64 QTLs lines under non-stress and stress
Line QTLs DF(NS) PH(NS) GY(NS) GY(S) GS (%)
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
IR64
IR64 IR64 + QTL line
+ QTL line
IR 87707-445-B IR 87707-182-B IR64
Drought Stress2011DS, IRRI CRURRS, Hazaribag, India 2011 WS
PLOS One ( In review )

29. 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

30. IR64 drought tolerant NILs under upland drought
GY GY
DTF DTF HT HT Kg/ha Kg/ha
ENT DESIGNATION NS S NS S NS S
1 IR 87707-446-B-B-B 77 89 72 69 2844 576
2 IR 87707-445-B-B-B 75 90 IR64 77 64 2800 471
IR64+DTY QTLs
3 IR 87707-182-B-B-B 78 89 69 59 2863 451
4 IR 87707-118-B-B-B 83 93 82 74 1209 102
5 IR 87729-69-B-B-B 80 95 80 56 2073 97
6 IR 87706-215-B-B-B 80 90 61 51 1506 174
7 IR 87705-44-4-B-B 78 95 81 50 1861 113
8 IR 87705-14-11-B-B 78 90 61 61 2180 439
9 IR 87705-83-12-B-B 83 95 69 54 1920 114
10 IR 87728-102-B-B-B 86 95 76 54 1383 64 96
IR
11 IR64 83 90 77 65 1542 54
* 500 Kg yield advantage over IR64 under upland drought

31. Improved drought tolerant IR64 lines under lowland
drought in target environments
Grain yield (kg ha-1)
Rajshahi Nepalganj Raipur Hyderabad 1 Hyderabad 2 Hazaribagh Rewa
Entry NS DS NS DS NS DS NS DS NS DS NS DS NS DS
IR87707-
445-B-B 4167 1525 5990 3472 5084 3956 5672 1684 5672 3800 5690 1604 4100 3731
IR87707-
446-B-B 4521 1933 6302 2847 5771 3614 5634 1813 5634 4057 5711 1229 4911 3899
IR87707-
182-B-B 4312 1508 6510 2778 5646 3419 6047 1383 6047 3604 4453 1500 4513 3509
IR64 3379 980 4297 1597 4083 2662 5699 660 5699 3085 5612 958 3586 2503
LSD 240 156 324 170 434 285 186 939 186 600 475 422 920 909
* 500 to 1500 Kg yield advantage over IR64
under lowland drought
Swamy, 2012

32. Introgression of major effect drought grain yield QTLs
DTY3.1 and DTY12.1 Anjali
IR81896-B-195 X Anjali (DS2010) Fore ground selection Major effect drought grain yield QTLs
( DTY3.1) Additive
QTLs Chr Interval R2 Donor
F1 X Anjali (WS2010) Fore ground selection effect
DTY3.1 3 RM520-RM16030 30 25 Apo
BC1 X Sub1Swarna (DS2011) Fore ground selection DTY 12.1 12
RM28048-
36 47 Way Rarem
RM28166
Fore ground selection
BC2F1 (WS2011)
Selection of
BC2F2 (DS2012) homozygote for DTY3.1
IR 84984-83-15-18-B-B-93 X Anjali (DS2010) Fore ground selection
( DTY12.1)
F1 X Anjali (WS2010) Fore ground selection
BC1 X Sub1Swarna (DS2011) Fore ground selection Anjali lLs with DTY12.1 , 12DAS
Fore ground selection
BC2F1 (DTY3.1) X BC2F1 (DTY12.1) (WS2011)
Fore ground selection
Selection of
homozygote for DTY12.1
BC3F1 BC2F2 (DS2012)
Selection of homozygote
for DTY3.1 and DTY12.1
Selected homozygotes with DTY3.1, DTY12.1 and their Anjali lLs with DTY3.1 12DAS
BC3F2 (WS2012)
combinations will be tested under drought DS2013 Swamy, IRRI

33. Improving Swarna and Swarna
Sub for drought tolerance
• Pyramid four drought yield
QTLs- DTY 1.1 , DTY 3.1 , DTY 2.1
and DTY 8.1 to improve yield of Swarna
Swarna by 1.2-1.5 t/ha
• Pyramid three drought yield
QTLs – DTY 1.1 , DTY 3.1 , DTY 2.1 to
improve yield of Swarna sub1
by 1.0-1.2 t/ha
Swarna sub1+ DTY
QTLs

34. Pyramiding of major effect drought grain yield QTLs
DTY1.1, DTY2.1 and DTY3.1 in Swarna Sub1:MAB
Pyramiding two QTLs Major effect drought grain yield QTLs in Swarna
Fore ground selection Additive
IR81896-B-195 X Swarna(WS2009) QTLs Chr Interval R2 Donor
Background selection effect
(DTY2.1and DTY3.1)
DTY1.1 RM11943-
1 14 30 N22
RM12091
Fore ground selection
BC2 X Sub1Swarna(DS2010) Background selection DTY2.1 2 RM327-RM262 16 12.5 Apo
DTY3.1 3 RM520-RM16030 30 25 Apo
Fore ground selection
BC3 X Sub1Swarna (WS2010) Background selection
Fore ground selection
BC4F1 (DS2011) Background selection
Select homozygote's
BC4F2 (WS2011) Background selection
Drought screening
Pyramiding3 three QTLs
BC4F (DS2012)
BC3 (DTY2.1 and DTY3.1) X BC3(DTY1.1) (WS2010)
BC4F1(DS2011) Fore ground selection
Swarna sub1 Swarna sub 1 Swarna sub1
lLs with DTY lLs with DTY
Select homozygote's QTLs
QTLs
BC4F2 (WS2011)
Drought screening
Swamy, IRRI, 2012

35. Pyramiding of major effect drought grain yield QTLs
DTY1.1, DTY2.1 and DTY3.1 in SwarnaSub1
Background recovery of Swarna ILs
BC4F3 Swarna lLs (Two QTLs + Sub1)
Submergence
screening
1 day after draining
BC4F3 Swarna lLs (Three QTLs + Sub1) 6 days after draining
Swarna

36. Performance of Swarna Sub1 three QTL lines: MAB
Designation DTF HT GY S QTLs ART5
IR96321-558-206 4919 DTY1.1 DTY3.1 DTY2.1 s1
IR96321-1080-91 90 103 4479 DTY1.1 DTY3.1 DTY2.1 s
IR96321-327-107 4202 DTY1.1 DTY3.1 DTY2.1 h
IR96321-327-210 90 93 4022 DTY1.1 DTY3.1 DTY2.1 s
IR96321-1099-154 3948 DTY1.1 DTY3.1 DTY2.1 h
IR96321-1080-278 86 121 3939 DTY1.1 DTY3.1 DTY2.1 s
IR96321-967-412 86 139 3918 DTY1.1 DTY3.1 DTY2.1 h
IR96321-967-105 82 136 3909 DTY1.1 DTY3.1 DTY2.1 s1
IR96321-1099-44 90 94 3891 DTY1.1 DTY3.1 DTY2.1 s1
IR96321-967-57 82 138 3885 DTY1.1 DTY3.1 DTY2.1 s
IR96321-558-209 3876 DTY1.1 DTY3.1 DTY2.1 s1
IR96321-1393-58 90 89 3855 DTY1.1 DTY3.1 DTY2.1 s
IR96321-678-240 89 90 3845 DTY1.1 DTY3.1 DTY2.1 s
IR96321-315-374 3836 DTY1.1 DTY3.1 DTY2.1 s1
Apo 76 115 2078

37. Effect of DTY12.1 at pre flowering and reproductive stage under severe upland stress
and grain types of improved Vandana NILs
Vegetative stage Reproductive stage
-DTY12.1 +DTY12.1 -DTY12.1 +DTY12.1

38. 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

39. Performance of Vandana NILs at IRRI and in India
Upland severe stress Upland non- stress
Designation GY DTF PHT BIO HI GY DTF PHT
IR84984-83-15-481-B 693 64 75 4160 0.17 2525 62 79
IR90020:22-283-B-1-B 604 66 79 4160 0.14 3039 66 85
IR90020:22-283-B-4-B 515 67 77 4133 0.21 2245 68 84
Way Rarem 0 NF 60 2667 0.01 1660 87 100
Vandana 27 70 79 2080 0.09 2127 68 91
Apo 0.1 NF 57 2267 0 2127 80 101
PHT
Designation DTF GY- C GY-D DTF GY-D
IR84984-83-15-481-B 78 116 5670 2343 61 1687
IR90019:22-283-B 78 107 5208 2410 60 1580
VANDANA 81 105 4348 1799 60 1327
WAY RAREM 90 115 4649 868 90 100
IR84894-83-15-481-B Vandana
S. Dixit, IRRI; NP Mandal, CRURRS

40. Genomic regions for MARS in IR55419-04 x Samba Mahsuri
Marker Aided Introgression
Additive
Chr Interval Trait
Effect Donor
1 RM212-RM486 700 Yield -NS IR55419-04
DTY11.1
11 Kid2746 – Kid 287 117 Yield -S IR55419-04
Kid3806 –RM520 Yield -S IR55419-04
3 and 6 350
Kid1613-Kid3434
1 RM212- RM486 10 Height -NS IR55419-04
2 RM525-RM221 -3 Height -NS IR55419-04
3 RM16-RM520 - Blast IR55419-04
Marker Aided Exclusion
Additive
Chr Interval Trait
Effect Donor
Kid8590 – Kid 9045
5&6 10 Height- NS IR55419-04
Kid8590 – Kid 9045 Line *RM212 *RM486 *RM525 *RM221 *RM16 *K_id3 *K_id3 *K_id3 *RM520 *K_id6 *K_6
10 IR55419-04 x Samba Mahsuri (MARS)
3 RM175- Kid6808 -149 Yield-S IR55419-04 1 1 2 2 2 1 1 1 1 1 1
30 1 1 3 3 1 1 1 1 2 3 .
31 1 3 1 1 1 1 1 1 2 1 1
80 2 2 2 2 2 1 3 3 3 1 1
82 2 3 3 2 2 1 1 1 1 1 1
84 1 2 1 2 2 1 1 1 1 1 1 FRS
102
109
1
1
1
1
3
2
3
2
1
2
3
1
1
1
1
3
2
3
2
1
1
1
SRS
123 3 3 1 1 1 3 3 1 2 2 1
199 1 3 1 1 1 2 2 3 3 . 3
201 1 1 1 1 1 . 2 1 2 . 1
Interactions for plant height under non-stress

41. Intogression of DTY QTLs in Korean parents (RDA)
Back ground Stage QTLs
Hanareumbyeo BC1 DTY1.1 and DTY2.2
Jinmybyeo BC1 DTY1.1 and DTY2.2
Gayabyeo BC1 DTY1.1 and DTY2.2
Sagnambatbyeo BC1 DTY1.1 and DTY3.1
BC2 – confirmed for foreground markers
and will be backcrossed
Introgression of QTLs in Smbha Mahsuri
• QTLs – DTY2.2 and DTY4.1
• Generation - BC2F2
• Foreground selection and selection of homozygote's
• Background selection

42. MAB to improve MRQ74, MR219
MRQ74 MRQ74
MRQ74
X X
X
IR84984-83-15-18-B IR81896-B-B-195
IR77298-14-1-2-10
(qDTY12.1) (qDTY3.1)
(qDTY2.2)
Foreground genotyping for qDTY12.1
Foreground genotyping for qDTY2.2
F1 (145) X F1 (142)
Foreground genotyping for qDTY2.2 & qDTY12.1 Foreground genotyping for qDTY3.1
388 (Total) 18 (foreground F1 (18) X F1 (53)
genotyping)
Foreground genotyping for qDTY2.2, qDTY 3.1 & qDTY12.1,
743 (Total) 21(foreground genotyping) 10 (PH, background genotyping) F1 (10) X
MRQ74
Foreground genotyping for qDTY2.2, qDTY 3.1 & qDTY12.1,
Recombinant & Full background genotyping
878 (Total) 35 (foreground genotyping) 10 (PH, background genotyping) BC1F1 (10)
Foreground genotyping for qDTY2.2, qDTY 3.1 & qDTY12.1,
X Recombinant & Full background genotyping
BC1F2 (5000)
Wet Season 2012
Foreground genotyping for qDTY2.2, qDTY 3.1 & qDTY12.1, (homozygous condition),
X Recombinant & Full background genotyping,
Selecting lines with different +qDTY combinations and -qDTY
Forward breeding BC1F3
Currently at this stage
Field Screening (Dry season 2013)
Nora, and Swamy
IRRI- UKM, Malaysia

43. Pyramiding qDTY3.2 and qDTY12.1 in Sabitri
IR74371-46-1-1 X Sabitri IR77298-5-6-18 X Sabitri
qDTY3.2 mapped
qDTY12.1 mapped
BC1F5 [5] X BC1F5 [5] and effect tested
and effect tested
Plants segregating for qDTY12.1 and
Plants segregating for qDTY12.1 and qDTY3.2
identified, background genotyped
F1 [300] X Sabitri qDTY3.2 with clearest background to be
identified and back crossed to Sabitri
Plants segregating for qDTY12.1
and qDTY3.2 with clearest
BC1F1 [1000] background identified
and selfed
Plants with qDTY12.1 and qDTY3.2
with clearest background to be
F2 [1000]
Plants with qDTY12.1 and qDTY3.2
identified and seeds multiplied BC1F2 [1000] with clearest background to be
identified
F3 [1000] BC1F3
Seed multiplication
and drought screening
Seed multiplication
and drought screening Shalabh and
Prashant, IRRI

44. Fine mapping DTY2.1, DTY2.2, DTY9.1 and DTY12.1
Original QTL Fine mapped region(s)
Length Length
QTL Flanking markers (Mb) QTL Flanking marker (Mb)
DTY2.1 RM521-RM262 10.8 DTY2.1 A SS RM521-RM3549 0.3
DTY2.1 B MS RM3549-RM6374 4.5
DTY2.2 OSR17-RM12868 7.9 DTY2.2 SS RM279-RM492 4.9
DTY9.1 RM464-RM24421 8.2 DTY9.1A MS RM321-RM24325 2.6
DTY9.1B SS RM24350-RM24390 0.9
DTY12.1 RM28048-RM28166 2.7 DTY12.1AMiS RM28099-RM511 0.8
DTY12.1B SS RM28130-RM1261 0.5
DTY12.1C MS RM1261-RM28166 0.1
Shalabh Dixit, IRRI

45. IR84984-21-19-62-B-B
2010WS ROS Expt 2b QTL 12.1
IR84984-83-15-481-B-B
Vandana
Physiology DTY12.1
38
Way Rarem
37
36 -QTL
Canopy temp (C)
Bernier et al. (2009) : 7% greater 35
34
water uptake in +QTL lines under 33
drought in lysimeters
+QTL
32
31
No difference in root depth 30
28 31 36 42 56 70
days after sow ing
+QTL lines had lower canopy
temperatures during drought
stress in the field
+QTL lines had greater root
branching (larger proportion of
fine (lateral) roots) than -QTL
lines under drought
83-15-481-B-B (+QTL) 21-19-60-B-B (-QTL)
Hypothesis: greater root branching induced by drought stress in +QTL lines
improves water uptake from drying soil Amelia Henry, IRRI

46. Physiology Aday Sel x IR64 NILs
-QTL +QTL
-QTL
IR64 14-1-2-13 5-6-18
5-6-11
In severe drought, +QTL lines
showed lower canopy temperature
and greater stomatal conductance.
• No differences in root length or depth
were detected +QTL Aday Sel
14-1-2-10
+QTL lines showed lower root hydraulic conductance, and also smaller root
and xylem vessel diameter
14-1-2-10 (+ QTL) 14-1-2-13 (- QTL)
Hypothesis: smaller xylem vessels in +QTL lines result in reduced xylem vessel
cavitation under severe stress Amelia Henry, IRRI

47. Wild species derived mapping population development
SL No Female Parentage Male Parent
Rice varieties
Diversity 1 MTU 1010/IRGC 81994 MTU1010
based on
SSR 2 MTU 1010/IRGC 105757 MTU1010
markers
3 MTU 1010/IRGC 106109 MTU1010
4 MTU 1010/IRGC 106283 MTU1010
5 MTU 1010/IRGC 106285 MTU1010
6 Saro 5/IRGC 81994 Saro 5
7 Saro 5/IRGC 105757 Saro 5
Wild accessions
8 Saro 5/IRGC 106109 Saro 5
9 Saro 5/IRGC 106283 Saro 5
10 Saro 5/IRGC 106285 Saro 5
11 NericaL-14/IRGC 105757 NericaL-14
12 Nerica-L-14/IRGC 106277 NericaL-14
13 Nerica-L-14/IRGC 106285 NericaL-14
14 Nerica-L-31/IRGC 104639 Nerica-L-31
15 Nerica-L-31/IRGC 106277 Nerica-L-31
16 Nerica-L-5/IRGC 106109 Nerica-L-5
17 Nerica-L-7/IRGC 106283 Nerica-L-7
18 Nerica-L-8/IRGC 106285 Nerica-L-8

48. qDTY3.1 : Major effect and consistent QTL in Swarna and BR11
Additive Recipien
QTLs Chr Interval R2
effect
Donor
t • QTL validation
DTY3.1 RM520-
3 30 25 Apo Swarna
RM16030
• Fine mapping
DTY3.1 RM15935-
3 20-25 22 Apo BR11
RM520
• Physiogical
characterization
• Insilico candidate
Apo x Swarna Apo x BR11 gene identification
•Transciptome
analysis to identify
differentially
expressed genes
• Validation of genes
by RT and QRT PCR

49. Conclusions
• Major drought yield QTLs are true and effective
• Effect of individual QTLs 300-500 kg ha -1 ,
requires pyramiding of three QTLs to get 1.2 ton
or more yield advantage
• Major QTLs with effect in the multiple improved
genetic background exist
• Vandna, Way Rarem, IR64 improved for yield
under drought
• DTY QTLs introgression in Swarna, Swarna sub
1 have been successfully tested
• Introgression, molecular and physiological

50. 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