IRRI Rice Seminar Series Current position Education and training

Jauhar Ali

Plant Breeder, Senior Scientist-I, GSR Project Leader & Regional Coordinator (Asia) for Development of Green Super Rice

Ph.D Genetics Indian Agricultural Research Institute, New Delhi, India (1993) M.Sc Genetics Indian Agricultural Research Institute, New Delhi, India (1990) B. Sc Agri (Hons) Punjab Agricultural University, Ludhiana, Punjab, India (1988)

Work experience2011- Onwards Plant Breeder, Senior Scientist-I, Green Super Rice(GSR) Project leader, Regional Coordinator (Asia) for Development of GSR, PBGB, IRRI, Philippines 2009-2011 Scientist, Regional Coordinator (Asia) for Development of GSR, PBGB, IRRI, Philippines 2003-2009 National Coordinator, Hybrid & Molecular Rice Breeding Program of Iran (HMRBPI) & Consultant (IRRI-Iran project), Rice Research institute of Iran, Rasht, Iran 2000 -2003 Project Scientist, Genome Mapping Lab., PBGB, IRRI, Philippines 1995 -2000 Assistant Professor, Dept. of Crop Improvement, AC&RI, Tamil Nadu Agricultural University (TNAU),Trichy, India 1994 -1995 Research Fellow-1, Hybrid Rice (TGMS), PBGB, IRRI, Philippines 1993 -1994 Senior Research Associate, Rockefeller Rice Biotech Program on Anther culture & genetic transformation, IARI, Delhi

Research highlightsPublications: 3 Books and 50 Research Papers & articles Capacity Building: 7 MS, 2 PhD students, 1 OJT, 4 VRF completed; (now 1MS, 2PhD,1 OJT, 1VRF)-trained +723 researchers for seed production Breeding for resilience through development of green super rice materials for varied agro-climatic conditions and ecosystems Breeding for rice grain quality & yield -irrigated conditions-release of Bahar1 hybrid in 2009 &Gohar inbred variety in Iran in 2012 Heterosis breeding for irrigated and abiotic stress conditions through two and three line breeding approaches Breeding products (as team efforts) Bred 40 green super rice materials and nominated 18 entries in the Philippines, 1 aromatic entry and 10 entries in MET stage 2 Nominated 30 GSR inbreds and 24 inbreds in national trials of NARES (Asia) Bred eight TGMS lines (India)-1993, seven hybrids (India & Iran), one salt tolerant variety (India), three varieties (Iran) for irrigated Awards & distinctions: Pt. Jawahar Lal Nehru Award 1994 for outstanding PhD research in crop improvement; Tamil Nadu Young Scientist Fellowship 1997; IARI Junior and Senior Fellowship 1988 to1993; Punjab Agricultural University Merit scholarship holder 1984 to 88

Breeding for Resilience: Green Super Rice

IRRI

Drought tolerance Screening

Jauhar AliPlant Breeder, Senior Scientist GSR Project Leader PBGB, IRRI

Why there is a necessity for breeding for resilience?

Food Security 2008looming threat-higher yields under ever reducing resources Stable sustainable yields using lesser inputs(SSNM)-farmer practice-rainfed complex abiotic stresses-stressed irrigated condition- Lesser inputs-complex conditions Diseases & Insect pest threats-high input environments- Broad spectrum-durable R Caring for environment-pollution of water systems-chemical residues-Reduction of Cs Changing climatic situations-vulnerabilityheat-flooding-drought- Multiple Stress Tol.

Breeding for Resilience-GSRRice cultivars that produce higher and more stable yields with lesser inputs (water, fertilizers and pesticides)High yielding GSR cultivars with Green traits: Resistances/ tolerances to: Abiotic stresses: Drought, salinity, alkalinity, iron toxicity, etc. Diseases: Blast, bacterial blight, sheath blight, viruses, and false smut etc Insects: Brown plant hopper, Green leaf hopper, etc Grain quality Mostly in elite RP background- later in RP-NARES

High resource-use efficiency: Water and nutrients (N P K)

Asia: Cambodia,Indonesia,Laos,Vietnam,Bangladesh,Pakistan,Sri Lanka Africa: Liberia, Mali, Mozambique, Nigeria, Rwanda, Senegal, Tanzania, Uganda China: Guangxi,Guizhou,Suchuan,YunnanGSR Materials given to NARES=Hybrids(193) + Inbreds (152)

TEST SITES: AFRICA & ASIA=15countries

Less inputs, more production & environment sustainability

Development of GSR materials by introgression breeding & designed QTL pyramiding (DQP) strategy initiated at IRRI in 1998RP (3) x donors(205)Li, Z.K. and Xu, J.L. (2007) Advances in Molecular Breeding Toward Drought and Salt Tolerant Crops Springer pp. 531-565.

F1s x RP

BC1F1s x RP

Self and bulk harvest

x

BC3F1s x RP Self and bulk x harvestBC3F2 populations 1, 2, 3, 4, 5, 6,

Selection for target traits and backcrossing BC4F1s x

Bulk BC2F2 populations 1, 2, 3, 4, 5, 6,

BC4F2s

Screening for target traits such as tolerances to drought, salinity, submergence, anaerobic germ., P & Zn def., BPH, etc.Confirmation of the selected traits by replicated phenotyping and genotyping of ILs for gene/QTL identification Crosses made between sister ILs having unlinked desirable genes/ QTLs for target ecosystem

DQP &MAS for pyramiding desirable genes/QTLs and against undesirable donor segments for target ecosystem

Development of GSR materials with improved target traits for wide scale testing in different ecosystems and its release. NILs for individual genes/QTLs for functional genomic studies

Ali et al (2006) FCR 97:66-76

~25 BC2F1s/donor x RP

Development of ILS for different abiotic and biotic stress tolerances at IRRI by 2004

Z.K. Li et al (2005) PMB 59:33-52; Ali et al (2006) FCR 97:66-76

Hidden diversity for abiotic and biotic tolerance in the primary gene pool of rice

Tremendous amounts of hidden diversity-BC progenytransgressive -target traits-regardless of donor performance-severe stress screening Common to identify in BC progeny-extreme phenotypes (tolerances) Selection efficiency highly dependent upon background Selection efficiency-affected by level of stress applied Selection efficiency for different target traits vary in BC generations. More distantly related donors, particularly landraces, tend to give more transgressive segregations for complex phenotypes in the BC progenies. Wide presence and random distribution of stress tolerance genes in primary gene pool of rice good news for rice breeders

Yu et al (2003) TAG 108:131-140; Ali et al (2006) FCR 97:66-76

Donors that gave better results with varying recurrent parental backgroundsS.No. ST ZDT AG SUBT LTG BPHMULTITRAITS

FAVOURABLE DONORS (VARY ACCORDING TO RP)OM1706,OM1723,FR13A,NAN29-2,BABOAMI, KHAZAR TKM9,HEI-HE-AI-HUI(HHAH),JIANGXI-SI-MIAO(JSM), KHAZAR, MADHUKAR, SHWE-THWE-YIN-HYE (STYH), BASMATI385, IKSAN438, YU-QIU-GU, TETEP, NIPPONBARE, CO43, RASI, YUNHUI, BG304,BR24, FR13A GAYABYEO Y134,TKM9,KHAZAR,GAYABYEO,STYH,NAN29-2, BABOAMI,JSM,FR13A,OM1706 CISEDANE,FR13A,IR50,NAN29-2,OM1706,STYH,TAROM MOLAEI,TKM9,Y134 NAN29-2,GAYABYEO JSM,BABOAMI,TKM9,BG300,C418,LEMONT,MADHUKAR,MR167,OM1706,STYH, Y134 BABOAMI, GAYABYEO, SHWE-THWE-YIN-HYE (STYH), NAN29-2, FR13A, OM1706, KHAZAR, JIANGXI-SI-MIAO

Ali et al (2006) FCR 97:66-76

Designed QTL pyramiding experiments at IRRIExperiment set IIR64 x BR24 F1 x IR64 BC2F2 IR64 x Binam F1 x IR64 IR64 x STYH F1 x IR64 BC2F2 IR64 x OM1723 F1 x IR64 BC2F2 IR64 x Type3 F1 x IR64 BC2F2 IR64 x HAN F1 x IR64 BC2F2 IR64 x Zihui100 F1 x IR64 BC2F2

BC2F2

13 BC2F2 populations screened under two types of severe drought, resulting in 221 survived DT BC2F3 introgression lines (ILs), which were genotyped with SSR markersIL1 x IL2 F1X

Experiment set II

IL3 x IL4

IL7 x IL15 F1X

F1X

9 1st round pyramiding F2 populations from crosses between 15 ILs

F2

F2

F2

Screened under severe drought at the reproductive stage, resulting in 455 survived DT F2 plants, which were progeny tested and genotyped with SSR markers(PL1 , PL2, PL3) x (PL4, PL5, PL6, PL7, PL8) F1sX

Experiment set III

14 2nd round pyramiding F2 populations from crosses between 8 1st round PLs

F2s

Screened under severe drought at the reproductive stage and 667 survived DT F3 lines were progeny tested and genotyped with SSR markers

Ch.1RM499 RM462 RM428 RM10287 RM323 RM84 RM220 RM86 RM283 RM522 RM1

Ch.2Bin1.1 Bin1.2 Bin1.3 Bin1.4 Bin1.5 Bin1.6 Bin1.7RM109 RM485 RM154 RM211 RM236 RM279 RM423 RM8 RM53 RM555 RM233A RM174 RM145 RM71 RM327 RM521 RM300 RM324 RM424 RM262 RM561 RM341 RM475

Ch.3Bin2.1 Bin2.2 Bin2.3RM545 RM245 RM517 RM60 RM81B RM22 RM523 RM569 RM231 RM175

Ch.4Bin3.1 Bin3.2 Bin3.3 Bin3.4RM307 RM401 RM537 RM551 RM335 RM518 RM261

Ch.5Bin4.1RM122 RM153

Bin5.1

RM204 RM540 RM469 RM587 RM588 RM190 RM589

Ch.6Bin6.1 Bin6.2

Bin4.2

RM399 RM413 RM13 RM267 RM437

Bin5.2

RM272 RM490 RM575 RM576 RM259 RM243 RM583 RM600 RM572 RM581 RM580 RM23 RM129 RM329 RM446 RM562 RM594

Bin2.4OSR13 RM14963 RM7 RM232 RM251

RM471

Bin4.3 Bin4.4

RM289 RM516 RM169

Bin5.3

RM510 RM204 RM585 RM584 RM557 RM111 RM225 RM314 RM253 RM50 RM549 RM539 RM136 RM19778 RM527

Bin6.3 Bin6.4 Bin6.5

Bin2.5

Bin3.5 Bin3.6

RM142

RM509

Bin5.4RM598 RM163 RM164 RM291

RM3

RM454

RM9 RM5 RM306 RM488 RM237 RM246 RM473A RM11570 RM403 RM128 RM302 RM212 RM319 RM265 RM297 RM315 RM472 RM431 OSR23 RM14

Bin2.6RM282 RM338

RM273 RM252

Bin4.5

RM161 RM188 RM19029 RM233B RM421 RM178 RM26 RM274 RM87 RM480 RM538 RM334

Bin5.5

Bin6.6RM162

Bin3.7

RM241 RM470 RM303 RM317

Bin1.8

Bin4.6

Bin5.6

RM343 RM528 RM30 RM340 RM400 RM439 RM103 RM141 RM176 RM494

Bin6.7 Bin6.8 Bin6.9

RM106 RM263 RM526 RM221 RM525 RM318 RM450 RM497 RM6 RM240 RM530 RM112 RM250 RM166 RM197 RM213 RM48 RM207 RM266 RM535 RM138

Bin2.7 Bin2.8 Bin2.9

Bin1.9 Bin1.10 Bin1.11 Bin1.12 Bin1.13

RM156 RM411 RM487 RM16 RM347

Bin3.8RM348 RM349 RM131 RM280

Bin4.7 Bin4.8

Bin5.7

RM504

RM567

Bin2.10 Bin2.11 Bin2.12

RM203 RM186 RM55 RM168 RM416 RM520 RM293 RM114 RM130 RM565 RM514 RM570

Bin3.9

RM559

Bin3.10

Bin3.11

STYH segments BR24 segments OM1723 segments Binam segments

FGUs identified in cross II-1 FGUs identified in cross II-2 FGUs identified in cross II-3 Cross III-1 Cross III-2 Cross III-3 Cross III-4

Li et al 2012 (unpubl)

RM227 RM85

Bin3.12

Ch.7RM436 RM51 RM481

Ch.8Bin7.1RM408 RM506 RM407

Ch.9Bin8.1RM296 RM285 RM316 RM23818 RM444 RM219 RM524

Bin9.1

Ch.10RM474 RM25022 RM25181 RM222 RM216 RM239 RM311

Ch.11Bin10.1RM181 RM286 RM4B RM26063

Ch.12Bin11.1RM20A RM4A

Bin12.1 Bin12.2

RM125 RM180 RM501 OSR22 RM214 RM418 RM432 RM11 RM346 RM182 RM336 RM10 RM351 RM455 RM505 RM234 RM18

OSR30 RM547

Bin9.2

Bin8.2RM105 RM321

RM19

Bin7.2 Bin7.3

RM544

Bin10.2RM332 RM167

Bin9.3 Bin9.4 Bin9.5RM467 RM184 RM271 RM269 RM258 RM171 RM304

Bin11.2

RM247 RM512 RM179 RM101 RM277 RM511 RM519 RM313 RM309 RM463

Bin12.3

Bin7.4 Bin7.5 Bin7.6

RM25 RM126 RM407 RM44 RM72 RM137 RM331 RM339 RM342A RM515 RM223 RM284 RM210 RM556 RM447 RM256 RM149

Bin8.3

RM409 RM460 RM566 RM434

Bin10.3 Bin10.4 Bin10.5

RM120 RM479 RM202 RM536 RM260 RM287 RM209 RM229 RM457 RM187 RM21 RM473E RM206

Bin11.3

Bin12.4 Bin12.5 Bin12.6 Bin12.7

Bin8.4 Bin8.5 Bin8.6 Bin8.7 Bin8.8

RM257 RM108 RM242 RM278 RM201 RM107 OSR28 RM189 RM215

Bin11.4 Bin11.5 Bin11.6

Bin9.6 Bin9.7 Bin9.8

RM228 RM147 RM333 RM496

Bin10.6 Bin10.7

RM235 RM270

RM17

RM172 RM248

Bin7.7

RM230

RM245 RM205

RM254 RM224 RM144

RM264 RM281

Bin11.7

Genomic correspondences between FGUs identified in 150 ILs of 8 BC2 populations, 200 PLs of three 1st round pyramiding crosses and four 2nd round pyramiding crosses.

Zhang et al 2011 Dissecting genetic networks underlying complex phenotypes: Theoretical framework PLoS one 6(1) e14541

Putative genetic networks identified in 455 DT PLs derived from 9 crosses between DT IR64 ILsA:Drought

B:

DroughtAG2-1 (5) 0.994

I:

Drought

AG1-1 (7) 1.00

AL9-1 (3) 1.000

AG1-2 (7) 0.979

RM347 (3.8) 0.691

RM561 (2.6) 0.618

RM342 (8.5) 0.673

AG2-2 (6) 0.891

RM309 (12.5) 0.927

RM469 (6.1) 0.818

RM575 (1.4) 0.745

RM179 (12.3) 0.727

RM211 (2.2) 0.800

RM350 AG9-5(3) AG9-2(2) (8.4) 0.553 0.915 0.800

AG9-4 (5) 0.500

RM152 (8.1) 0.930

RM215 (9.7) 0.870

RM554 (3.7) 0.700

RM109 (2.1) 0.617

AG1-3 (13) 0.748

AG1-4 (4) 0.688

AG1-5 (5) 0.726

RM418 (7.3) 0.717

RM179 (12.3) 0.607

RM202 (11.3) 0.745

RM463 (12.5) 0.745

RM544 (8.2) 0.727

RM215 (9.8) 0.527

AG9-3(24) 0.870

RM446 (1.6) 0.830

D:

Drought

E:

DroughtRM543 (1.1) 1.000

G:

DroughtAG7-1 (18) 1.00

AG4-1 (6)RM433 (8.7) 0.867 AG5-1 (12) 0.711

RM271 (10.4)

AG4-2 (4)

RM23 (1.5)

AG4-3 (4)

RM401 (4.1) AG5-4 (2) 0.767 0.733

RM298 (7.1) 0.767

AG5-2 (9) 0.809

RM53 (2.3) 0.833

RM85 AG7-5 RM286 RM44 (3.12) (2) (11.1) (8.3)

AG7-2 (2)

RM469 RM289 (6.1) (5.3)

AG7-7 (2)

RM36 (3.3)

AG7-3 (16)

RM516 (5.3)

RM245 (9.8)

RM18 (7.6)

RM215 RM544 RM272 RM179 RM441 (1.3) (11.2) (9.8) (8.3) (12.3)

AG4-4 (3)

RM220 (1.2)

RM222 (10.1) 0.567

RM270 (12.6) 0.567

RM17 (12.7) 0.500

RM424 (2.5) 0.667

RM244 (10.1) 0.583

RM101 (12.4) 0.766

AG5-3(2) 0.525

RM248 (7.7) 0.500

RM275 RM294B RM224 RM110 RM435 (11.7) (6.6) (1.6) (2.1) (6.1)

AG7-4 (7)

RM13 (5.2)

RM5 (1.7)

RM30 RM465A (6.8) (2.5)

F:

Drought

H:

Drought

AG6-1 (8) 1.000

AG8-1 (26) 1.00

C:

DroughtAG3-1 (4) 1.00

AG6-2 (5) 0.967

RM307 (2.1)

RM446 (1.6)

RM5 (1.7)

RM535 (2.12)

RM331 (8.4)

RM197 (6.1)

RM449 (1.6)

RM481

(7.1)

RM32 (8.3)

RM448 (3.10)

RM51 (7.1) 0.833

AG6-3 (12) 0.894

AG6-4 (2) 0.772RM20 12.1 0.567

RM44 (8.3) 0.633

RM235 (12.6) 0.667

RM14 (1.13)

RM211 RM154 RM317 RM562 (2.2) (2.1) (4.6) (1.6)

AG8-3 AG8-4 (3) (3)

RM589 (6.1)

AG8-5 (2)

RM30 (6.7)

RM547 (8.3)

AG8-2 (2)

RM275 RM335 (3.12) (6.5)

RM143 (3.12)

RG8-6 (2)

AG3-3 (3) 0.736

AG3-2 (4) 0.855

RM302 (1.10) 0.782

RM172 (7.7) 0.727

RM258 (10.4)

RM246 (1.8)

RM169 (5.3)

RM245 (9.8)

Li et al 2012 unpubl.

6.5 6.0 5.5 5.0 4.5 2.5 4.0 1.5 3.5 0.5 3.0 0.0 0.5 1.0 1.0 2.0

Mean yield under the irrigated control (t/ha)

Type II (N=5) C: 5.710.42 VS: 1.360.38 RS: 2.200.45IR64 (CK) C: 4.680.23 VS: 1.490.14 RS: 0.520.38 Type IV (N=7) C: 4.660.48 VS: 1.340.41 RS: 1.860.513.0

Type I (N=17) C: 5.760.53 VS: 2.070.55 RS: 1.790.47 Type III (N=19) C: 5.060.47 VS: 1.980.47 RS: 1.940.52

1.5

2.0

2.5

3.0

Mean yield performances (t/ha) of 48 2nd round PLs (4 types) as compared to IR64 (CK), under the irrigated control (C), drought stresses at the vegetative (VS) and reproductive stages (RS) in the 2007 and 2008 dry-season.Guan et al. 2010 JXB

Highly salinity tolerant

GSR Drought tolerant pyramided lines in IR64 background

Under zero input conditions at IRRI DS2010

IRRI DT Check variety IR74371-70-1-1

GSR-IR83142-B-19-B

Wang et al 2010 Drought induced site specific DNA methylation JXB DOI:10.1093/jxb/erq391

DT PDLs AMMI-Biplot: 6Entry No.15 9 19 18 11 5 10 6 13 12 14 16 20 7 3 8 1 17 4 2

Locations -2011DS

BRAC-Gaz, VAAS-Gia, VAAS-Duo, ICRR-Jak, ICRR-Teg, & IRRI-Los BanosGSR LinesIR 83142-B-57-B IR 83141-B-17-B IR 83142-B-7-B-B IR 83142-B-79-B IR 83142-B-19-B IR 83140-B-11-B IR 83141-B-18-B IR 83140-B-28-B IR 83142-B-21-B IR 83142-B-20-B IR 83142-B-49-B IR 83142-B-60-B IR 83142-B-8-B-B IR 83140-B-32-B Best Check IR 83140-B-36-B 2nd Best Check IR 83142-B-61-B IR 74371-70-1-1 Apo

Mean LSD (t/ha) Group5.46 5.17 5.13 5.12 5.06 5.05 5.02 4.94 4.86 4.79 4.78 4.75 4.74 4.74 4.67 4.32 4.29 4.27 3.57 3.53 a b bc bc bcd bcde bcdef bcdefg cdefg defg efg fg g g g h h h i i

10amBrGa PC %

17% adv.0.5

1 60.9 2 24.7 1 17 10dsIRig

2 12 10 13 19 186

2nd Best Check40.0

8

10dsIcJa 16 7 14 9 5

PC 2

Best Check3-0.5

10suVaGi 11 IR 83142-B-19-B 10suVaDu 15

IR 83142-B-57-B20

IR 83140-B-11-B Environments

Mean LSD (t/ha) Group IL breeding + Designed QTL Pyramiding IRRI-Los Banos 6.55 a Possible role of Epigenetics VAAS-Gia 6.53 a 10dsIcTe VAAS-Duo 6.06 b Selection for grain yield, higher BRAC-Gaz 0.5 4.29 c spikelet fertility, deeper and thicker 0.0 -0.5 1.0 3.18 d roots esp. under reproductive stage ICRR-Jak PC 1 DT stress ICRR-Teg 2.08 e Why such yield advantages?-1.0

Promising GSR Drought + Salinity tolerant materials tested under Iloilo during WS2010GSR entry No of panicles Plant height (cm) Maturity (days) Yield (kg/ha) % increase over FL478 SES score 4WAT SES score Maturity

IR83140-B-11-B IR83140-B-28-B

16 13

84 86

116 114

1140 876

103.6 56.4

4 4

5 5

IR83140-B-32-B FL478NSIC 222

15 1119

85 7083

114 111112

657 560147

17.3 0.0-73.8

4 54

5 -

First two nominated for NCT Philippines WS2011

High protein 11%, AC 21%, GT-I, suitable for direct wet and dry, transplanting, drought, salinity, cold germination BLB, Blast tolerant

IR83140-B-11-B

PVS Purvakarta2.5ha trial area Indonesia 8.2011

Grain yield t/ha

Site specific nutrient management (SSNM)

Untung et al (2012) unpubl.

Summary of GSR data received from NARES in AsiaNo. of lines HYBRIDS INBREDS Batch 1 Batch 2 Batch 2 Batch 3 Batch 4 Batch 1 Batch 2 Batch 3 IRRI-GSR 24 80 42 37 9 22 31 9 47 IRLL, HY IRLL, HY RFLL, DT IRLL, DT, RFLL, (I & RFLL, I, RFLL (I & DT, SubT, HT, Nuse, J) DT, T-BL, J), DT, T- ST, HY T-BB, BL, GQ BL, BB, BPH, SB TBB, HT, WT, ST, GQ 15 14 5 10 8 4 21 17 5 12 11 3 16 14 5 39 21 7 31 18 6 10 8 4 Total 301 -

Line composition

Total no. of experiment reported No. of location Year/Season No. of data sets received from NARES No. of replicated data No. of data sets usable for GxE Analysis 5 Best Entries 1 2 3 4 5 Mean yield across location (t/ha) Average advantage over the best check Yield advantage of the best entry ANOVA: Pr(>F) ENV REP(ENV) GEN ENV:GEN

154 111 39 116 76 58

-

12 53

10 54

10 1010

12 1010 HuF1-9 HuF1-17

13 43

23 2314

27 1914 ZH1 TME80518

9

IIyou3203 HanF1-40 CXY2 CXY2 CXY727 ZXY673 XYR24 7.13 8.3% 13.3% 8.808E-09 0.0008013