Marker-assisted breeding to improve grain yield under drought

Marker-assisted Breeding to Improve Grain Yield Under Drought

ARVIND KUMAR

Current position: Senior Scientist 1, Plant Breeder Drought, Aerobic Rice

Education & Training:

Ph.D. 2002: Plant Breeding and Genetics, Indira Ghandi Krishi

Vishwavidyalaya (IGKV)-ICGEB, India

M.Sc. 1992: Plant Breeding and Genetics, IGKV, Raipur, India

B.Sc. 1989: Agriculture IGVK, Raipur, India

Work experience:Jan 19, 2010 – present : Senior Scientist I, PBGB, IRRIJan 19, 2007 – Jan 18, 2010: Senior Scientist, PBGB, IRRIJuly 1, 2006 - Jan 18, 2007 : Senior Scientist, IGKV, IndiaOct 30,2004 - Jun 30, 2006 : Post Doc Fellow, IRRIJan 25, 1995 - Oct 29, 2004 : Scientist/Senior Scientist, IGKVNov 4, 1992 - Jan 24, 1995 : Research Associate, IGKV

Research highlights:Varieties developed/

germplasm registered: 21Genes/QTLs identified : 15 (7 genes for gall midge resist.,

8 QTLs for DT)Book Chapters : 19Manuscripts in peer

reviewed journals : 76Thesis Advisor : Post Doctoral: 5; Ph.D.: 7; M.S.: 5

Awards: 1. Young Scientist Award 96-97 from Madhya Pradesh Council of Science & Technology, India

2. Best Scientist Award of IGKV, Raipur for year 2002

Marker Assisted Breeding to Improve Grain Yield Under Drought

Arvind KumarSeptember 06, 2012

Afrida Abu Hassan

GSR

Conclusions from last seminar March 03, 2011• Conventional breeding approaches provide lines with 0.8-1.2 t ha-1 yield

advantage under drought

• Breeding lines released in few countries

• Increased water uptake- not always due to root depth, lateral roots and/or root hairs play important role also

• 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 exists, need to put in more efforts to identify something like sub 1

• Vandana, Way Rarem, IR64 improved for yield under drought. DTY QTLs introgression in Swarna, Swarna sub 1 under progress

• As we move to deliver molecular breeding products in project driven research, efficient testing facility at IRRI required

Varieties released- conventional breeding

Name Designation Days to Maturity

Plant height (cm)

Country, release year, situation

Sahod Ulan 1 IR74371-54-1-1 110 104 Philippines 2009, RL, UP

Hardinath 1 IR80411-B-49-1-1 115 100 Nepal 2009, RL

Sahbhagi dhan IR74371-70-1-1 110 104 India 2010, RL, UP

BRRI dhan 56 IR74371-70-1-1 110 108 Bangladesh 2011 , RL

Sookha dhan 3 IR74371-70-1-1 110 108 Nepal 2011, RL



Katihan 1 IR79913-B-176-B-4 105 90 Philippines 2011, UP

Sahod Ulan 3 IR81412-B-B-82-1 120 107 Philippines 2011, RL

Sahod Ulan 5 IR81023-B-116-1-2 115 130 Philippines 2011 , RL

Sahod Ulan 6 IR72667-16-1-B-B-3 115 100 Philippines 2011, RL

Sahod Ulan 8 IR74963-262-5-1-3-3 125 100 Philippines 2011 , RL

Inpago LIPI Go 1 IR79971-B-191-B-B 110 115 Indonesia 2011 UP

Inpago LIPI Go 2 IR79971-B-227-B-B 113 114 Indonesia 2011 UP

Why MAB for drought tolerance?

1 2 3 4 5 6 7 8 9 10

11

12

13

14

15

16

17

18

19

20

0.000

0.500

1.000

1.500

2.000

2.500

NON STRESS index values of top 20 entries tested from 2005-2007

NON STRESS index values of top 20 entries tested from 2008-2010

1 2 3 4 5 6 7 8 9 10111213141516171819200.000

0.500

1.000

1.500

2.000

2.500

3.000

3.500MOD STRESS index values of top 20 en-tries tested from 2005-2007

MOD STRESS index values of top 20 en-tries tested from 2008-2010

1 2 3 4 5 6 7 8 9 10

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19

20

0.000

0.500

1.000

1.500

2.000

2.500

3.000

3.500SEVERE STRESS index values of top 20 entries tested from 2005-2007

SEVERE STRESS index values of top 20 entries tested from 2008-2010

Why MAB for drought tolerance?• Traditional donors- N22, Aday Sel, Moroberekan, Way Rarem, Dular

are not good combiners

• Increasing GY by crossing two high yielding diverse improved lines did not provide further yield increase under drought

• MAB to provide unique opportunity to bring together large effect regions from different donors and get incremental yield increase under drought

• Consistent QTLs work effectively across stress levels

• MAB with large effect QTLs provide an opportunity to combine drought tolerance with other stresses/traits

• Once QTLs pyramided in improved background, MAB to other background becomes easy

Why rice is a suitable case for MAB for GY under drought?

In different crops

• Many QTL reported with high-

– QTL x environment interaction

– QTL x genetic background interaction

– No QTL reported to work irrespective of ecosystem

– Many criticism from people working on other crops where large effect QTLs not detected

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

Variety QTL Donor Ecosystem Additive effect Phenotypic variance (R2)

Vandana qDTY12.1 Way Rarem Upland 47 33

IR64 qDTY1.1 N22 Lowland 24 17

qDTY2.2 Adaysel Lowland 14 6




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

MTU1010 qDTY1.1 N22 Lowland 16 13

BR11 qDTY3.1 Apo Lowland 27 25

Major effect QTLs for grain yield under drought

Large effect drought QTLs

• qDTY1.1, qDTY2.3, qDTY3.1, qDTY3.2, qDTY12.1 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

PopulationAdditive effect* Ecosystem Location Reference

CT9993-5-10-1-M/IR62266-42-6-2 20.6 Lowland

Raipur, India

Kumar et al. 2007

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

qDTY1.1 effect across ecosystem, environments & backgrounds

Prashant, IRRI

QTLs Chr Interval R2 Additive effect

Donor Recipient

DTY3.1 3RM520-

RM1603030 25 Apo Swarna

DTY3.1 3RM15935-

RM52020 22 Apo BR11

Apo x Swarna

Apo x BR11

qDTY3.1 : Major and consistent QTL in Swarna and BR11

Swamy, IRRI

Introgression of major effect drought grain yield QTLs DTY3.1 and DTY12.1 Anjali

IR81896-B-195 X Anjali (DS2010)

( DTY3.1)

F1 X Anjali (WS2010)

BC1 X Sub1Swarna (DS2011)

BC2F1 (WS2011)

BC2F2 (DS2012)

Major effect drought grain yield QTLs


Donor

DTY3.1 3 RM520-RM16030 30 25 Apo

DTY 12.1 12 RM28048-RM28166 36 47 Way Rarem

Anjali lLs with DTY12.1 , 12DAS

Anjali lLs with DTY3.1 12DAS

IR 84984-83-15-18-B-B-93 X Anjali (DS2010)

( DTY12.1)

F1 X Anjali (WS2010)

BC1 X Sub1Swarna (DS2011)

BC2F1 (DTY3.1) X BC2F1 (DTY12.1) (WS2011)

BC3F1 BC2F2 (DS2012)

BC3F2 (WS2012)

Fore ground selection




Selection of homozygote for DTY3.1





Fore ground selectionSelection of

homozygote for DTY12.1

Selection of homozygote for DTY3.1 and DTY12.1

Selected homozygotes with DTY3.1, DTY12.1 and theircombinations will be tested under drought DS2013 Swamy, IRRI

Effect of qDTY12.1 in upland and lowland conditions

Ad

dit

ive

effe

ct o

f Q

TL

as

% o

f tr

ial

mea

n

Vandana/ Way Rarem IR74371-46-1-1/ Sabitri

Trial mean grain yield (kgha-1)

Bernier et al. 2007, 2009 Mishra et al. 2012, BMC Genetics (Revision)

Upland Lowland

qDTY2.3, qDTY3.2 were also detected to show effect in Vandana/Way Rarem in upland

Moroberekan: a donor that has eluded Breeders: Moroberekan/ 3* Swarna

• Around 2000 SNP markers surveyed for polymorphism. 191 markers run on a population of 361 BC2F3 derived lines

• Traits measured: grain yield, plant height

and DTF over 2 seasons under lowland stress (severe and moderate) and non- stress conditions in DS 2011 and DS 2012

• 3 QTLs detected for grain yield under stress

• 13 QTLs detected for grain yield under non- stress which showed effect across both seasons

• At present 381 single plant selections from the population being screened in India

• A subset of 100 lines being screened at IRRI under aerobic conditions

S. Dixit, IRRI

Moroberekan X 3* Swarna

361BC2F3 derived lines tolerant to blast for mapping yield QTLs under stress and non- stress

Drought Tolerant

NILs

Drought tolerant

BILs with similar/ superior

grain quality

QTLs for grain yield under

drought stress and non- stress

conditions

BC2F2 population screened for blast tolerance

QTLs for grain yield under drought stress: Moro/3*Swarna

QTL Chr Interval Peak PositionSevere Stress Moderate stress Combined

Add LOD R2 Add LOD R2 Add LOD R2qDTY2.2 2 id2001301-id2003908 id2002229 18.8 60.4 4.7 5.8qDTY2.3 2 id2011110-id2012785 k_9 112.8 33.9 8.8 10.6 10.6 4.1 5.1 19.0 9.7 11.7qDTY3.2 3 id3000757-id3002606 id3000757 5.1 43.4 10.8 12.9 10.6 5.6 7.0 18.8 12.5 14.9qDTY12.2 12 id12000292-id12002057 ud12000118 11.0 55.1 4.0 5.0 25.4 3.9 4.9qDTY12.1 12 id12005302-id12007081 id12005428 61.7 7.2 3.8 4.8qDTY12.3 12 id12007577-ud12001525 id12007988 89.0 31.0 5.2 6.4 12.1 4.1 5.1

S. Dixit, IRRI

IR64 drought tolerant NILs under upland drought

IR64 IR64+DTY QTLs

IR 64

ENT DESIGNATIONDTFNS

DTFS

HTNS

HTS

GYKg/ha

NS

GYKg/ha

S

1 IR 87707-446-B-B-B 77 89 72 69 2844 576

2 IR 87707-445-B-B-B 75 90 77 64 2800 471

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 96

11 IR64 83 90 77 65 1542 54

* 500 Kg yield advantage over IR64 under upland drought

Has this been an easy job?Year Lowland Upland

Population No. Populations No.2003 RIL 5 2004 RIL 2 2005 RIL 4 RIL 4

BIL 1 2006 RIL 3 RIL 8

BIL 1 2007 RIL 4

BIL 2 BIL 62008 RIL 8 RIL, BIL 1, 12009 RIL 5

BIL 9 BIL 22010 RIL 9

BIL 3 BIL 22011 RIL 3

BIL 11 2012 RIL 6 RIL 1

BIL 11 BIL 4Total 87 29

No second example of such a massive effort to identify QTLsThe efforts resolved many misgivings about drought yield QTLs

Efficient, cost effective strategy: BSA for identifying consistent QTLs

Identify few markers in BSA

BSA with adjoining markers of the identified one

Validation of BSA results

RM431

N22 IR64 BH BL N22 IR64 BH BL

RM11943 RM431

Dh

agad

des

hi

Sw

arn

a

BH

BL

Dh

agad

des

hi

Sw

arn

a

BH

BL

QTL identification in multiple populations simultaneously

ADVANTAGES of BSA

Cost effective

Can be applied with expensive marker systems like SNP (Becker et al. 2011-Plos One)

RNA can be pooled for microarray (Kadam et al. 2012)

Consistent Drought Grain Yield QTLs Identified via BSA

qDTY1.1; qDTY2.2; qDTY3.1; qDTY3.2; qDTY4.1; qDTY6.1; qDTY12.1

Vikram et al. 2012, FCR

What is within DTY QTLs?

• Regions that increase yield under drought

• Regions that increases yield under irrigated situation

• Regions that increases yield under dry direct seeded aerobic situation (DS flooded?)

• Regions that increases plant height

• Regions that decreases days to flowering

• Regions that might have a negative effect on GY

N22 × Swarna BC3F1

FGSelected 21 F1s

X

FG

~ 3000 BC3F2 217 dwarf plants

2 Plants segregating for qDTY1.1

~ 180 BC3F3+QTL &

recombinantsRatooned, split planted

XFG

Single plants with QTL

FG

Selection for Swarna plant type

Selfing of recombinants

X

Screened for GY under droughtScreened plants with

Swarna grain type

Background genotyping

Plants with clear background Phenotypically and genotypically

Being Screened at IRRI under ROS

Being Screened in India under ROS

Breaking linkage

Generating QTL lines

FIELD SCREENING AT MULTIPLE LOCATIONS

Phenotypic selection

Background selection

Drought screening

Elimination of linkage drag

qDTY1.1 was linked with plant height; Linkage needed to be broken prior to application of the QTL

Vikram, Prashant

MAB for drought tolerance

• Identify two to three major QTLs with high effect in the background of popular high yielding varieties.

• Introgression and pyramiding of identified QTLs for-

• Maintenance breeding – improve popular high yielding varieties- Vandana, IR64, Swarna, Sabitri, TDK 1 keeping the other traits intact

• Forward breeding- From segregating BC2F2 population select lines with high yield irrespective of background clearance, and traits different from the recipient variety

• Develop near isogenic lines in improved background with different QTL combinations for basic as well as applied research

Marker assisted Breeding Strategy for high grain yield under drought Mega varieties

Swarna, IR64,

MTU1010, TDK, Vandana

Sabitri, Sambha Mahsuri

F2

F3

F3:4

F3:5 (300-400)

Lines with QTLs and combinations identified from the mapping populations and Intercrossed/back crossed to recipient parents

qDTY1.1, qDTY2.1, qDTY3.1,qDTY12.1, qDTY6.1, qDTY11.1

Pyramiding of 3 major QTLs

BC1F1(500)/ BC2F1 ( 1000) / BC3F1(1500-2000) lines with all the QTLs Selected

Lines with single QTLs

lines with different QTL combinations

Screening under managed drought stress and non-stress (IRRI)

Best lines evaluated in target environments of the respective variety

Best lines released for cultivation by Farmers

Selection of BC3F2 (4000-5000)

homozygous lines and background genotyping (To break DTF and HT linkages)

Selection of QTL lines based on DTF and HT

Multi-location evaluation

xN22, Dhagad Desi,

Apo, Dular, Adaysel

Kalis Aus, Aus 226, Wayrarem

Drought tolerant land races

BC1F1

BC2F1

BC2F2

BC2F3

BC2F4 (300 -400 )

Advanced Back Cross mapping population

Recombinant Inbred mapping Population

qDTY2.2, qDTY4.1qDTY9.1, qDTY10.1

Saro5, IR64

MTU1010, Nerica lines xAdaysel,

IRGC81994,

IRGC105775

Mega varieties Land races & wild species

F1

F1

QTLs identified for high grain under drought using BSA/ WG

Consistent and major effect QTLs selected for MAS in each recipient background

Lines with two QTLs Lines with all the QTLs

Selected best lines evaluated for grain quality and Other parametersPhenotyping

Fore ground and back ground genotyping

High yielding Forward Breeding Lines

IR 64 introgression lines with DTY QTLs: AB QTL approach

+ QTL - QTLIR64 IR64+DTY QTLs

Parents- 2007

Similar to IR64 grain quality traits of introgressed lines

Introgressions under drought- 2010

DTY introgressed line

Product - 2011

IR 64

IR64 QTLs lines under non-stress and stress

IR64+ QTL line Drought Stress2011DS, IRRI

Non-Stress2011 DS, IRRI

+ QTL line IR64

IR64 QTL lines under testing in WS2011, WS2012 at 14 locations in India under AICRIP program; Nepal (03), Bangladesh (01), Philippines (01),

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 performance at IRRI

Swamy and Helal, IRRI

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

Improved drought tolerant IR64 lines under lowland drought in target environments

* 500 to 1500 Kg yield advantage over IR64 under lowland drought

Swamy, 2012

IR64 drought tolerant NILs under upland drought: IRRI

IR64 IR64+DTY QTLs

IR 64

ENTNO DESIGNATION

DTFNS

DTFS

HTNS

HTS

GYKg/ha

NS

GYKg/ha

S

1 IR 87707-446-B-B-B 77 89 72 69 2844 576

2 IR 87707-445-B-B-B 75 90 77 64 2800 471

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 96

11 IR64 83 90 77 65 1542 54

* 500 Kg yield advantage over IR64 under upland drought

IR64IR 87707-445-B-B-B IR 87707-182-B-B-B

CRURRS, Hazaribag, India 2011 WS

Performance of IR64 QTL lines under drought

Similar RVA and cooking quality traits for IR64 & IR64 NILsENTRY Peak 1 Trough 1 Breakdown Final Visc Setback Peak Time Pasting Temp Retro

IR 87706-215-B-B-B 2932 1356 1576 2840 -92 5.6 78.4 1484IR 87705-14-11-B 2845 1405 1440 2750 -95 5.67 78.25 1345IR 87705-83-12-B 2793 1348 1445 2633 -160 5.67 78.3 1285IR 87707-445-B-B-B 2689 1521 1168 2868 179 5.87 79 1347IR 87728-102-B-B 2627 1311 1316 2620 -7 5.67 79.05 1309IR 87707-446-B-B-B 2828 1561 1267 2938 110 5.87 79.1 1377IR 87705-444-B 2778 1433 1345 2798 20 5.73 78.4 1365IR 87729-69-B-B-B 2681 1288 1393 2631 -50 5.67 78.4 1343IR 87707-182-B-B-B 2646 1404 1242 2793 147 5.73 78.25 1389IR64 2799 1462 1337 2825 26 5.8 79.85 1363

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0

-500

0

500

1000

1500

2000

2500

3000

3500

IR 64

ir87729-69-b-b-b

ir87728-102-b-b

ir 87707-446-b-b-b

ir 87707-182-b-b-b

ir87707-445-b-b-b

ir87705-444-b

ir 87705-83-12-b

ir87705-14-11-b

IR87706-215-b-b-b

Aday sel

S. Dixit, IRRI

LINEStress Non stress Grain type

GY (Severe)

GY (Moderate)

GY (Combined) GYC DTFC

HTC % Swarna Similarity to Swarna Class

IR 91648-B-85-B 2032 3141 2613 5118 86 98 90 Yes MediumIR 91648-B-285-B 1403 2566 1979 6496 88 96 90 No Medium

IR 91648-B-319-B 819 3389 2124 4418 91 93 91 No MediumIR 91648-B-73-B 1372 3438 2398 5474 91 95 92 Yes Medium

IR 91648-B-192-B 689 3025 1832 4569 86 93 93 Yes Medium

IR 91648-B-240-B 1775 3017 2336 4499 81 83 95 Yes MediumSWARNA 86 2326 1211 4282 99 91

MOROBEREKAN 88 717 384 1701 95 120

NILs Moro/3* Swarna: AB QTL, SNP, maintenance breeding: 2009-2012

NILs Moro/3* Swarna: AB QTL, SNP, Forward breeding

LINE

Stress Non stress%

Swarna

Grain type

GY (Severe)

GY (Moderate)

GY (Combined) GY DTF HT Similarity to

Swarna Class

IR91648-B-89-B 1743 3169 2448 6811 90 94 35 No Long IR 91648-B-101-B 947 2956 1967 5171 87 90 44 No Medium

IR 91648-B-55-B 1845 2168 2013 5514 89 93 45 No LongIR 91648-B-139-B 999 2481 1755 4447 85 89 85 No MediumIR 91648-B-105-B 762 3218 1956 5461 88 95 85 No MediumIR 91648-B-131-B 1090 2536 1799 5267 89 98 86 No MediumIR 91648-B-146-B 1635 2542 2060 4304 86 95 87 No MediumIR 91648-B-151-B 566 3068 1814 5698 87 98 87 Yes MediumIR 91648-B-74-B 934 3497 2219 4643 89 99 87 No MediumIR 91648-B-54-B 1352 2856 2125 5410 87 94 87 Yes Medium

IR 91648-B-210-B 1240 2387 1864 4409 94 97 88 Yes MediumIR 91648-B-95-B 1887 2729 2315 4467 82 91 89 No Medium

IR 91648-B-347-B 749 3098 1945 5040 91 97 89 No MediumSWARNA 86 2326 1211 4282 99 91

MOROBEREKAN 88 717 384 1701 95 120

S. Dixit, IRRI

QTLs for grain yield under non- stress

QTL Chr Markers Peak PositionNon stress 2011 Non stress 2012 CombinedAdd LOD R2 Add LOD R2 Add LOD R2

qDTY2.1 2 id2004861- id2007213 id2006621 54.8 37.7 9.3 11.2 33.5 6.3 7.8 35.7 10.6 12.8qDTY3.3 3 id3010094-ud3001370 id3010740 95.1 32.4 7.8 9.5 26.8 7.2 8.8 29.8 10.2 12.2qDTY4.2 4 id4001205- ud4000437 id4001882 63.4 22.3 7.4 9.0 15.8 5.0 6.2 19.2 8.3 10.1qDTY4.3 4 id4003690-id4005389 id4004461 137.4 32.0 6.1 7.5 26.7 7.4 9.1 29.5 8.2 10.0qDTY6.3 6 id6006336- id6007759 id6007312 44.6 28.2 9.9 11.9 20.2 8.9 10.8 24.5 13.0 15.4qDTY6.2 6 id6010515- id6012967 id6011613 72.6 22.6 10.1 12.1 16.0 6.7 8.3 19.5 10.7 12.8qDTY8.2 8 id8001604- id8002632 id8002098 30.1 12.1 12.2 14.4 5.9 5.7 7.1 9.2 12.3 14.6qDTY8.3 8 id8006885- id8007977 id8006997 100.1 43.7 7.4 9.0 32.2 4.5 5.6 38.3 8.0 9.8qDTY9.2 9 id9002357- id9003188 id9002721 37.7 35.9 7.8 9.5 30.7 5.4 6.8 33.4 8.8 10.8qDTY9.3 9 id9004727- id9007259 id9004727 65.7 25.7 13.1 15.4 16.5 5.2 6.5 21.4 12.3 14.6qDTY11.2 11 id11009197- id11011285 id11009456 102.9 30.6 10.4 12.5 26.0 6.7 8.3 28.4 11.8 14.1qDTY12.3 12 id12006515- id12007988 id12007081 85.0 29.9 5.2 6.5 19.5 4.5 5.6 25.0 6.6 8.2S. Dixit, IRRI

High yielding BILs with QTLs affecting yield under non- stress

Line QTLsGrain Yield

Combined

DTF

HT

% SwarnaDS2011 DS2012

IR91648-B-7-BqDTY2.1, qDTY3.3, qDTY4.2, qDTY4.3, qDTY6.3, qDTY6.2,

qDTY8.2, qDTY8.3, qDTY9.2, qDTY9.3, qDTY11.2, qDTY12.3 9458 7690 8577 81 120 72


qDTY8.2, qDTY8.3, qDTY9.2, qDTY9.3, qDTY11.2, qDTY12.3 7161 6434 6792 81 118 71


qDTY12.3 7009 6085 6553 83 103 47IR91648-B-22-B qDTY6.3, qDTY6.2, qDTY8.2, qDTY8.3, qDTY9.3, 7909 5518 6714 85 116 34IR91648-B-32-B qDTY8.2 7230 4840 6034 92 118 67

IR91648-B-150-B qDTY9.3 6237 4826 5529 93 94 67IR91648-B-57-B qDTY6.2 6025 5114 5566 82 102 34


qDTY8.3, qDTY9.3, qDTY11.2, qDTY12.3 6323 5341 5835 85 104 40

IR91648-B-76-B qDTY3.3, qDTY6.3, qDTY8.3, qDTY9.3, qDTY11.2, qDTY12.3 6395 4613 5511 85 100 53


qDTY8.2, qDTY8.3, qDTY9.3, qDTY11.2, qDTY12.3 7020 6592 6811 90 94 35IR91648-B-251-B qDTY8.2, qDTY9.3, 7321 4349 5845 92 119 67

MOROBEREKAN 2234 1171 1701 95 120SWARNA 4552 4012 4282 99 91

-B -B - B -B

Development of Vandana NILs with qDTY12.1: MAB

Way Rarem Vandana

Apo IR90020:22-283-B-4-B

Dixit et al. 2012, TAG

Designation

Upland severe stress Upland non- stress

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

Performance of Vandana NILs at IRRI and in India

Designation

DTF PHT

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

IR81896-B-195 X Swarna(WS2009)

(DTY2.1and DTY3.1)

BC2 X Sub1Swarna(DS2010)

BC3 X Sub1Swarna (WS2010)

BC4F1 (DS2011)

BC4F2 (WS2011)

BC4F3 (DS2012)

Fore ground selection Background selection

Fore ground selectionBackground selection


Select homozygote's Background selection

Pyramiding of major effect drought grain yield QTLs DTY1.1, DTY2.1 and DTY3.1 in Swarna Sub1:MAB

BC3 (DTY2.1 and DTY3.1) X BC3(DTY1.1) (WS2010)

BC4F1(DS2011)

BC4F2 (WS2011)

BC4F3 (DS2012)

Pyramiding three QTLs

Pyramiding two QTLs


Drought screening

Select homozygote's

Drought screening

Swarna sub 1Swarna sub1 lLs with DTY QTLs


Donor

DTY1.1 1 RM11943-RM12091 14 30 N22

DTY2.1 2 RM327-RM262 16 12.5 Apo

DTY3.1 3 RM520-RM16030 30 25 Apo

Major effect drought grain yield QTLs in Swarna


Swarna sub1 lLs with DTY QTLs

Swamy, IRRI, 2012

Designation DTF HT GYS

GYNS QTLs

Sub1

IR 94391-131-358-19 88 103 5237 7421 DTY3.1 DTY2.1 h

IR 94391-131-245-2 88 89 4839 7101 DTY3.1 DTY2.1 .

IR 94391-131-722-2 88 94 4450 10675 DTY3.1 s1

IR 94391-131-455-19 88 101 3994 8500 DTY3.1 DTY2.1 s1

IR 94391-131-165-2 88 84 3975 6947 DTY3.1 DTY2.1 s1

IR 94391-131-605-20 88 89 3896 7586 DTY3.1 DTY2.1 .

IR 94391-131-344-1 88 93 3887 7374 DTY3.1 DTY2.1 s1

IR 94391-131-42-2 85 84 3823 7365 DTY3.1 s1

IR 94391-131-713-1 88 89 3784 6840 DTY3.1 s

IR 94391-131-605-17 88 90 3731 6115 DTY3.1 DTY2.1 .

IR 94391-131-120-2 88 83 3716 6582 DTY3.1 DTY2.1 h

IR 94391-131-74-9 85 87 3714 6479 DTY3.1 DTY2.1 h

IR 94391-131-358-16 88 106 3695 7907 DTY3.1 DTY2.1 h

IR 94391-131-161-13 88 86 3686 6683 DTY3.1 DTY2.1 s

Swarna Sub1 92 90 2558 5207

Swarna 92 90 2120 4435

Performance of Swarna Sub1 two QTL:MAB

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

Swarna 96 92 1896

2012 Designation DTF-NS HTAVE-NS GY-NS GY-S

IR94313:16-22-2-3-2 75 103 3841 5777

IR94313:2-1-1-5-1 75 91 4699 5465

IR88286-136-B-B-B-2-1 81 110 4404 5428

IR94391-564-1-3 75 102 3429 5392

IR94391-707-1-1 75 100 4238 5343

IR94314-20-11-2 78 93 5186 5188

IR94313:1-9-2-1-1 78 107 5767 5059

IR94391-755-1-2 78 85 4098 5018

IR94313:16-37-1-3-4 78 111 3863 4989

IR94313:2-1-1-4-2 75 93 4634 4909

IR94314-20-9-3 81 80 5458 4868

IR94313:1-9-2-8-1 81 118 3895 4865

IR94313:18-4-1-5-2 81 82 4473 4863

IR94391-587-1-3 75 93 3662 4849

Apo 78 111 6284 4263

Swarna Sub1 87 87 4789 1695

Swarna 91 88 4475 1895

Performance of Swarna ILs – early: under drought

Designation DTF-NS HTAVE-NS GY-NS GY -S

IR94313:8-1-5-5-2 81 89 6511 5817

IR94313:19-36-1-7-1 90 95 6464 5557

IR94313:16-32-1-9-3 81 99 6559 5354

IR94313:8-1-3-9-3 85 95 5967 5335

IR94313:8-1-1-6-1 85 97 7321 5271

IR94313:16-32-3-2-1 81 93 6478 5210

IR94313:19-36-3-6-2 90 102 10047 5093

IR94313:12-32-1-2-1 85 93 6783 5048

IR94313:19-7-1-4-1 90 90 6544 5029

IR88286-582-1-B-B-4-3 92 113 10821 4913

IR94313:8-1-1-4-1 85 98 5055 4898

IR94313:16-32-1-2-3 81 97 4234 4897

IR94391-303-1-1 85 101 10808 4877

Swarna 95 92 4867 3048

Swarnasub1 93 95 5530 3205

Apo 78 110 5574 3386

Performance of Swarna ILs – medium: under drought

*1500 -2000 Kg yield advantage over Swarna and Swarna Sub1 Swamy, IRRI

F1 (145) F1 (142)

F1 (53)

X

F1 (18) X

F1 (10) X MRQ74

BC1F2 (5000)

Foreground genotyping for qDTY2.2

Foreground genotyping for qDTY12.1

Foreground genotyping for qDTY3.1Foreground genotyping for qDTY2.2 & qDTY12.1

BC1F1 (10)

BC1F3

Field Screening (Dry season 2013)

MRQ74

X

IR77298-14-1-2-10 (qDTY2.2)

MRQ74

X

IR84984-83-15-18-B (qDTY12.1)

MRQ74

X

IR81896-B-B-195 (qDTY3.1)

X

X

Foreground genotyping for qDTY2.2, qDTY 3.1 & qDTY12.1,

Foreground genotyping for qDTY2.2, qDTY 3.1 & qDTY12.1, Recombinant & Full background genotyping

Foreground genotyping for qDTY2.2, qDTY 3.1 & qDTY12.1, (homozygous condition), Recombinant & Full background genotyping, Selecting lines with different +qDTY combinations and -qDTY

Foreground genotyping for qDTY2.2, qDTY 3.1 & qDTY12.1, Recombinant & Full background genotyping

Currently at this stage

Wet Season 2012

MAB to improve GY under drought of MRQ74, MR219

878 (Total) 35 (foreground genotyping) 10 (PH, background genotyping)

743 (Total) 21(foreground genotyping) 10 (PH, background genotyping)

388 (Total) 18 (foreground genotyping)

Forward breeding

Nora, IRRI- UKM, Malaysia

Pyramiding qDTY3.2 and qDTY12.1 in Sabitri

IR74371-46-1-1 IR77298-5-6-18SabitriX SabitriX

BC1F5X BC1F5qDTY12.1 mapped

and effect tested

qDTY3.2 mapped and effect tested

F1Plants segregating for qDTY12.1 and qDTY3.2

identified, background genotypedX Sabitri

BC1F1

Plants segregating for qDTY12.1 and qDTY3.2 with clearest background to be identified and back crossed to Sabitri

[5] [5]

[300]

[1000]Plants segregating for qDTY12.1 and qDTY3.2 with clearest background identified and selfed

BC1F2

Plants with qDTY12.1 and qDTY3.2 with clearest background to be identified

BC1F3

[1000]

F2 [1000]

F3 [1000]Seed multiplication and drought screening

Plants with qDTY12.1 and qDTY3.2 with clearest background to be identified and seeds multiplied

Seed multiplication and drought screening

Shalabh and Prashant, IRRI

Wild species derived mapping population development

SL No Female Parentage Male Parent

1 MTU 1010/IRGC 81994 MTU1010

2 MTU 1010/IRGC 105757 MTU1010

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





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





Mapping strategy

Development of Advanced Back Cross mapping population (BC2F2)

Genotyping BC2F2 population

Phenotyping BC2F3 and BC2F4 populations

Identification novel major effect QTLs

Introgression of QTLs in the recipient backgrounds

Swamy, IRRI

What we still do not know

• How the different combinations of QTLs work together in different genetic backgrounds

• In case of IR64, two QTL combinations with qDTY2.2 and qDTY4.1 were the best yielders

• The identified QTLs have shown effect under drought in lowland and upland situations as well as for yield under normal situation, indicating their possible role in improving yield in puddled irrigated situation, dry direct seeded aerobic and dry direct seeded flooded situation (better water uptake, nutrient uptake ?)

• Need to know the involved trait?

Line QTL Combinations Background

IR87729-69-B-B-B qDTY9.1, qDTY2.2, qDTY10.1, qDTY4.1 IR64

IR87728-491-B-B qDTY9.1, qDTY2.2, qDTY4.1 IR64

IR87707-186-B-B-B qDTY2.2, qDTY10.1, qDTY4.1 IR64

IR87707-359-B-B-B qDTY2.2, qDTY10.1, qDTY4.1 IR64

IR87707-446-B-B-B qDTY2.2, qDTY4.1 IR64

IR87707-445-B-B-B qDTY2.2, qDTY4.1 IR64

IR87728-162-B-B qDTY9.1, qDTY2.2 IR64

IR87705-83-12-B qDTY2.2, qDTY10.1 IR64

IR87705-80-15-B qDTY10.1, qDTY4.1 IR64

IR87705-72-12-B qDTY2.2 IR64

IR87705-6-8-B qDTY4.1 IR64

IR87728-395-B-B qDTY9.1 IR64

IR99261:12-13 qDTY12.1 IR64 IR99619:342-1 qDTY2.2 IR64

IR96301:140-10 qDTY1.2 (S) IR64 IR99619:143-7 qDTY1.1+ qDTY1.2 IR64 IR 96296-35-11 qDTY12.1+qDTY2.3 (P) IR64 IR99261:33-17 qDTY12.1+qDTY3.2 (P) IR64 IR99261:78-25 qDTY12.1 (P)+qDTY3.2 (P) IR64

IR 96296-113-16 qDTY12.1 +qDTY3.2 (S)+qDTY2.3 IR64 IR99619:333-8 qDTY1.1+ qDTY1.2 +qDTY2.2 IR64

IR 96296-112-10 qDTY12.1 +qDTY3.2 (S)+qDTY2.3(S) IR64

NILs for different QTLs in IR64 background

BPM. Swamy, IRRI

NILs for different QTLs in IR64 background

Line QTL Combinations Background F1 Plants (S) qDTY1.1 IR64 Sub1F1 Plants (S) qDTY2.2 IR64 Sub1F1 Plants (S) qDTY2.3 IR64 Sub1 F1 Plants (S) qDTY3.2 IR64 Sub1 F1 Plants (S) qDTY12.1 IR64 Sub1F1 Plants (S) qDTY2.3+qDTY2.3 IR64 Sub1F1 Plants (S) qDTY2.2 +qDTY12.1 IR64 Sub1F1 Plants (S) qDTY1.2+qDTY12.1 IR64 Sub1F1 Plants (S) qDTY1.1+qDTY12.1 IR64 Sub1F1 Plants (S) qDTY2.2 +qDTY2.3+qDTY12.1 IR64 Sub1F1 Plants (S) qDTY1.1+ qDTY1.2 +qDTY2.2 IR64 Sub1F1 Plants (S) qDTY1.1+ qDTY1.2 +qDTY2.3 IR64 Sub1F1 Plants (S) qDTY1.1+ qDTY1.2 +qDTY12.1 IR64 Sub1F1 Plants (S) qDTY1.1+ qDTY1.2 +qDTY12.1+qDTY2.2 IR64 Sub1F1 Plants (S) qDTY1.1+ qDTY1.2 +qDTY2.2+qDTY2.3 IR64 Sub1F1 Plants (S) qDTY1.1+ qDTY1.2 +qDTY12.1+qDTY2.3 IR64 Sub1F1 Plants (S) qDTY2.2 +qDTY2.3+qDTY3.2+qDTY12.1 IR64 Sub1

F1 Plants (S) qDTY1.1+ qDTY1.2 +qDTY2.2+qDTY2.3+qDTY12.1 IR64 Sub1(S): Segregating (P): Partial introgression

S. Dixit, IRRI

Line Combinations Background

IR 96321-678-508 qDTY1.1, qDTY3.1, qDTY2.1 Swarna Sub1

IR96321-558-209 qDTY1.1, qDTY3.1, qDTY2.1 Swarna Sub1

IR 96321-678-271 qDTY1.1, qDTY3.1 Swarna Sub1

IR96321-315-60 qDTY1.1, qDTY3.1 Swarna Sub1




IR964391-131-358-19 qDTY3.1, qDTY2.1 Swarna Sub1

IR 96321-647-73 qDTY1.1 Swarna Sub1

IR96321-678-240 qDTY1.1 Swarna Sub1


IR 964391-131-242-2 qDTY2.1 Swarna Sub1


IR964391-131-624-1 qDTY3.1 Swarna Sub1

NILs for QTLs in Swarna and Swarna Sub 1 background

Line QTL combination Background

IR 91659:41-59-1 qDTY1.1 + qDTY3.2 Swarna













BPM. Swamy, IRRI P. Vikram, IRRI

NILs for DTYQTL

Developed NILs shall help to-

• Understand physiological and molecular mechanism involved with each QTL

• Know the combinations of QTLs highly likely to provide higher grain yield under drought

• Facilitate MAB in different background without any undesirable linkage drag

• Characterize individual QTLs/QTL combinations for their effect in different severity of stresses

• Characterize different regions for severity of stress they are prone to.

Breeding for drought tolerance in rice – An over view

2005-2008

2009 - 2013

2014 beyond

2000-2004

• Selections based on secondary yield traits

• QTL mapping for physiological and secondary traits under drought

• MAS for QTLs of secondary traits

• Managed field drought screening standardized • Selection for GY under drought • qDTY12.1 identified• Questions on consistency of large effect QTLs• MAS for large effect QTLs initiated

• Additional large effect QTLs identified• QTL pyramiding in popular rice mega varieties• Fine mapping QTLs and candidate gene analysis• MAS products successfully developed and tested in TPE• Identification of novel QTLs from land races and wild species • Marker aided recurrent selection (MARS) initiated

• MARS and GWS fully implemented for better genetic gain• Wild species derived QTLs used in MAS• QTLs pyramided and tested in hybrid parental backgrounds• Genetic stocks developed, characterized, best combination of QTLs• SNP chip developed, drought QTLs combined with other traits

Construction of the chip with consistent DTY-QTLs

Application in Marker Assisted Breeding

DTY1.1 × RDTY3.1 × RDTY3.2 × RDTY6.1 × RDTY12.1 × R

DTY-QTL donors

Recipient background

F2

X

Large number of F2s genotyped in few days

Lines with QTL homozygote selected

Drought screening at multiple locationsCombining QTLsGeneration advancement,

genotyping , Seed multiplication

1.5 year 1 year 1 year

qDTY1.1

qDTY3.1

qDTY3.2

qDTY6.1

qDTY12.1

MAB Product

Fast track MAB using SNP platforms

DTY2.3 × R

Why we did not clone the drought genes?• Many initial challenges- QTLs real?, effect of individual QTL? led us

to focus on identification and effect confirmation of more than one QTL

• First priority product development

• Initial involvement with with gene cloning, we would have limited ourselves to qDTY12.1

• There are better people available to do this

• Collaborating within and outside IRRI on three qDTY1.1,qDTY3.1 and qDTY12.1

Conclusions

• At least six QTLs- qDTY1.1, qDTY2.2 qDTY2.3, qDTY3.1, qDTY3.2, qDTY6.1 and qDTY12.1 have shown effect in more than one genetic backgrounds and across both lowland and upland ecosystem.

• Their use in MAB have successfully shown yield increase of Vandana, IR64, Swarna, Swarna sub1 under drought.

• There are indications that these QTLs provide yield increase under normal situation, aerobic situation and can be useful to increase yield under dry direct seeded flooded situation.

• We do not know the best QTL combination for different backgrounds. Understanding the physiological and molecular mechanism of individual QTLs on NILs will help us to streamline this and make MAB easy.

• Developing SNP chip for these QTLs/QTLs combinations can help to make MAB quick, easy and help to integrate these QTLs into market segmentation breeding program of IRRI to combine with other traits.

Donors Rockefeller FoundationBill and Melinda Gates FoundationGeneration Challenge program Asian Development BankDBT, IndiaDevgenRDA, KoreaGIZ, GermanyUniv. Kebangsaan Malaysia, BangiMARDI, Malaysia

PartnersBangladesh

BRRI, GazipurRRS, Rajshahi

India

BAU, SabourBAU, RanchiBF, Hyderabad CRRI, CuttackCRURRS, HazaribagDRR, Hyderabad ICAR-NEH, TripuraICAR, PatnaIGAU, RaipurJNKVV, JabalpurNDUAT, FaizabadOUAT, BhubaneshwarTNAU, CoimbatoreUAS, Bangalore

Nepal

NRRP, HardinathRARS, NepalganjRARS, Tarharra

Philippines – PhilRiceLaos – NAFRIMozambique-IIAM, ChokweTanzania –DASRC, MorogoroMalaysia – UKM and MARDIRDA, Korea

Thank you very much for your kind attention and time

Documents

Marker-assisted breeding to improve grain yield under drought