advent of climate smart rice varieties through genomics...

Rice Science for a Better World

Jauhar Ali Plant Breeder, Senior Scientist

PBGB, IRRI ([email protected])

“NGGIBCI ICRISAT Hyderabad”

19th February, 2015

Advent of climate smart rice varieties through genomics-assisted breeding


Why there is a necessity for breeding for resilience?

• Food Security 2008–looming threat-higher yields under ever reducing resources-Quantity & Nutritional Quality

• 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 C’s

• Changing climatic situations-vulnerability-heat-flooding-drought- Multiple Stress Tolerance


Drought stress frequency map in

rainfed rice areas based on rainfall

anomalies from 1960-2002.

Flood frequency map in rice growing areas based on

100 years of UNEP flood risk data. Andy et al (2012) IRRI GSR Report

Fess et al (2011) Crop Breeding for Low Input Agriculture: A Sustainable Response to Feed a Growing World Population. Sustainability 2011, 3(10), 1742-1772


RACE AGAINST TIME


Green Super Rice-“GSR” Rice cultivars that produce higher & more stable yields with lesser inputs (water, fertilizers &pesticides)

High yielding GSR cultivars with “Green” traits: Resistances/ tolerances to: Abiotic stresses: Drought, salinity, alkalinity, iron toxicity, etc. Diseases: Blast, BLB, sheath blight, BLS viruses & false smut Insects: BPH, GLH, stem borer etc Grain quality: Mostly in elite RP background- later in RP-NARES

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

Less inputs, more production & environment sustainability

Low Gelatinization Temperature Varieties means FASTER COOKING TIME Saves on energy required for cooking; Saving fossil fuels at global scale


Highly Adaptable Genotype

◆ High yield, excellent grain quality and wide adaptation

◆ Registration more than 5 provinces in China

◆ Extended areas up to 3 million hectare in China

◆ Found superior to local check for grain yield and adaptable at 21 sites across Asia and Africa

Huang-hua-zhan (HHZ)


Ch. 1

Ch. 2

Ch. 3

Ch. 4

Ch. 5

Ch. 6

Ch. 7

Ch. 8

Ch. 9

Ch. 10

Ch. 11

Chr. 12

Genomic composition of the HHZ genome based

on the sequencing data regarding its pedigree


Two batches of 16 populations with recipient parent as Huang-Hua-Zhan (HHZ) & 16 donors from 9 countries

Batch Pop. Donor Country of origin Gen.(10 DS)

1

HHZ5 OM1723 Vietnam (I) BC1F5

HHZ8 Phalguna India (I) BC1F5

HHZ9 IR50 IRRI (I) BC1F5

HHZ11 IR64 IRRI (I) BC1F5

HHZ12 Teqing China (I) BC1F5

HHZ15 PSB Rc66 Philippines (I) BC1F5

HHZ17 CDR22 India (I) BC1F5

HHZ19 PSB Rc28 Philippines (I) BC1F5

2

HHZ1 Yue-Xiang-Zhan China (I) BC1F4

HHZ2 Khazar Iran (J) BC1F4

HHZ3 OM1706 Vietnam (I) BC1F4

HHZ6 IRAT352 CIAT (upland) BC1F4

HHZ10 Zhong 413 China (I) BC1F4

HHZ14 R644 China (I) BC1F4

HHZ16 IR58025B IRRI (I) BC1F4

HHZ18 Bg304 Sri Lanka (I) BC1F4


Introgression Breeding for QTL

Mapping and pyramiding

Develop first batch of 8 HHZ BC1F2 populations

DT screen SUB screen

3 SUBT plants

311 genotyped/progeny tested for all target traits

Re-sequencing

Random plants

109 DT plants

Yield traits

82 HY plants

ST screen

120 ST plants

153 DT screen 171 SUB screen 212 Yield 211 ST screen

497 ILs

Designed QTL

pyramiding

Phenotyping both in normal, drought, and salinity stress conditions

Linkage and association mapping

Allele mining

Fine mapping

Used for Resequencing & Phenotyping


Phenotyping of 497 ILs

(Irrigated-6 sites, Drought-1site, N stressed-1site, Cold-3 sites)

RCBD- 2 replications Drought stress-draining water at tillering stage 30 d after tpl of 21 d old seedling.

Irrigated condition:5cm standing water-maintained until ILs reached grain filling.

Five representative plants-each plot- measured- PN, TGW, SF, PH, GYP ( by SES). Grain yield under drought condition Drought index %= (upland production - normal paddy yield)/normal paddy yield x100 Grain yield under N stressed condition

N stressed Index:(low N plant yield - yield per plant control)/control plant yield x100 Cold: Spikelet fertility under 3 natural sites

Genotyping:

9 Parental Lines: deep sequencing (ranging 14-40x); Average:22X 1~2X resequencing-BGI-497 ILs; 370,000 SNPs identified from 8 IL

populations with 4613Bins altogether.

QTL Mapping: Phenotypic data of ILs obtained from total 10 sites were used for QTL

detection using QTL iCIMapping software v3.2 with default LOD ≥ 2.5 was used to determine the threshold


Re-sequencing data of 9 parents finished by BGI


HHZ vs PSBRC28 HHZ vs PSBRC66

HHZ vs IR64 HHZ vs Teqing

HHZ vs CDR22 HHZ vs OM1723

HHZ vs Phalguna HHZ vs IR50

SNP distributions in parental lines compared with HHZ

Rice Science for a Better World Huang et al. Genome Res., 2009, 19:1068–1076

Genotype determination

Sliding window approach for genotype calling and recombination breakpoint determination

(A)The stripe of blocks represents SNPs along a chromosomal region. Red for HHZ genotype, and blue for

donor one. A sliding window covering 15 SNPs moves from left to right one base at a time. For each window,

the ratio of the number of HHZ to donor SNPs is calculated. (B) Genotype calling based on the highest

expected probabilities: Call homozygous HHZ genotype when the ratio is larger than11:4; call heterozygous

genotype when the ratio is less10:5 and larger than 3:12; call homozygous donor genotype when the ratio less

than 2:13. (C) As the window slides, genotypes are called and recombination breakpoints are determined.


Bin maps of the 8 populations

HHZ5: HHZ/IR64 (55 ILs)

HHZ8: HHZ/Teqing (63 ILs)

HHZ9: HHZ/PSBRC66 (47 ILs)

HHZ11: HHZ/CDR22 (68 ILs)

HHZ12: HHZ/PSBRC28 (65 ILs)

HHZ15: HHZ/OM1723 (75 ILs)

HHZ17: HHZ/Phalguna (56 ILs)

HHZ19: HHZ/IR50 (68 ILs)

3782 bin (50kb-200kb/bin)

497 ILs

1 2 3 4 5 6 7 8 9 10 11 12


Percentage of genome of homozygous HHZ and

donor parent as well as heterozygote for 497 ILs


Performance of 8 IL populations comprising 497 ILs & HHZ

TraitName HHZ HHZ5 HHZ8 HHZ9 HHZ11

Mean Range Mean Range Mean Range Mean Range

2011HN-GY 17.8 19.6±3.6 9.6～26.8 17.1±3.2 0～22.6 17.7±3 11.5～24.5 20.5±3.4 14～30.4

2012HN-GY 20.0 26.4±3 20.2～34.5 26.8±3.4 16.2～32.8 26.3±4.4 15.1～35.1 28.1±3.1 21.1～34.5

2012HZ-GY 18.7 21.9±5.1 9.1～42.4 22.5±3.1 16.1～30.3 20.7±3.2 13.9～27.4 19.8±4.5 7.7～29.1

2012SZ-GY 30.5 37±5.9 17.8～52.3 28.7±5 18.8～40.6 33.2±6.4 21.7～51.7 33.3±6.1 15.1～49.2

2013SZ_GY 20.7 21.4±4.1 11.8～31.9 20.9±3.2 13.3～26.9 23.4±3.9 14～30.6 19.4±3.5 11.8～27.7

2012IR_GY 24.6 27.4±4.5 14.1～37.3 23.2±4.1 15.6～33.9 23.5±4.8 14.7～34 24±4.8 15.6～37.6

NUE13SZ_N_GY 10.8 9.9±1.9 6.3～15 10.2±1.9 6.1～14.2 10.1±2 7～17.4 10.4±2.1 6.3～17.3

2013SZ_I_GY -47.5 -

52.3±12.4 -74.9～-1.6

-

50.7±10.7 -71.6～-18.6

-

55.5±11.6 -73.8～-18.5 -45.1±14 -68.2～-5.5

Drought

2012IR_D_GY 9.4 12.7±3.4 6.4～21.8 13±3.2 6.6～21.3 8.8±2.9 2.3～14.7 11±3.8 1.6～19.3

2012IR_I_GY -0.62 -0.5±0.2 -0.8～-0.2 -0.4±0.2 -0.7～-0.1 -0.6±0.2 -0.9～-0.1 -0.5±0.2 -0.9～0

Cold YX1 0.80 0.80±0.12 0.34～0.95 0.60±0.29 0.11～0.93 0.70±0.22 0.29～0.91 0.80±0.12 0.64～0.98

Cold YX2 0.76 0.50±0.23 0～0.86 0.50±0.25 0.13～0.86 0.60±0.23 0.26～0.92 0.50±0.23 0.15～0.75

Cold XDA 0.56 0.50±0.24 0.15～0.77 0.40±0.25 0.16～0.78 0.50±0.15 0.25～0.75 0.50±0.12 0.11～0.72


Trait Name HHZ HHZ12 HHZ15 HHZ17 HHZ19

Mean Range Mean Range Mean Range Mean Range

2011HN-GY 17.8 16.3±3 4.9～21.6 17.5±2.8 9.8～26.1 16.9±2.4 11.6～22.1 18.9±2.8 12.7～27.5

2012HN-GY 20 28.5±2.5 21.6～33.6 27.2±3 21.3～33.5 27.6±3.5 15.7～39.3 28.6±3.2 20.3～36.1

2012HZ-GY 18.7 23.8±3.2 16.3～30.5 25.2±4.9 13.7～34.7 23.9±4.2 9.1～32.8 24.2±4.6 16.1～43.9

2012SZ-GY 30.5 32.3±6.5 8.2～44.6 37±5.6 24.7～46.4 31.6±5.6 22.8～48 30±5.8 16.9～41.2

2013SZ_GY 20.7 22.7±4 14～34.7 23±3.1 16.5～29.3 21.7±2.3 17.1～27 20.1±3.5 9.9～27.9

2012IR_GY 24.6 24.8±4.3 15.4～35.3 22.8±5.4 11.6～33.3 27.7±5 13.3～38.6 20±4.8 10.9～37.2

NUE

2013SZ_N_GY 10.8 11.5±1.9 7.3～15.7 9.6±1.4 6.9～13.2 10.2±2.1 6.4～15.4 10.7±2 6.9～16.7

2013SZ_I_GY -47.5 -

47.9±13.6 -68.1～4.2 -57.6±9.7 -76～-27.3

-

52.5±10.6 -76.3～-22.7

-

45.2±13.5 -68.6～2.1

Drought

2012IR_D_GY 9.4 11.6±2.3 6.3～17.8 11.7±2.5 6～16.2 13.5±2.7 7.4～19.6 12.8±3 7～23.2

2012IR_I_GY -0.62 -0.5±0.1 -0.8～0 -0.5±0.2 -0.7～-0.1 -0.5±0.1 -0.8～0.1 -0.3±0.2 -0.7～0.4

Cold YX1 0.80 0.70±0.1 0.30～0.91 0.80±0.1 0.71～0.99 0.80±0.15 0.63～0.91 0.80±0.15 0.64～0.91

Cold YX2 0.76 0.60±0.2 0.21～0.82 0.60±0.1 0.24～0.95 0.60±0.17 0.44～0.80 0.70±0.16 0.55～0.92

Cold XDA 0.56 0.50±0.2 0.23～0.84 0.60±0.1 0.31～0.94 0.60±0.19 0.32～0.74 0.60±0.12 0.32～0.82

Performance of 8 IL populations comprising 497 ILs & HHZ


High Yield

（6 sites） Drought

(1 site)

Nitrogen

Stressed

(1 site)

Cold tolerance

at booting

(3 sites)

HHZ5 21 1 10 3

HHZ8 5 0 2 1

HHZ9 2 4 2 3

HHZ11 5 6 0 5

HHZ12 10 2 10 14

HHZ15 13 0 0 7

HHZ17 7 2 3 3

HHZ19 3 1 2 0

Total 66 16 29 36

Detection of QTLs for grain yield, drought, nitrogen stressed and cold tolerance at booting stage using 497HHZ ILs from 8 donors in Huanghuazhan

(HHZ) background


Chr Start_point Start_bin End_point End_bin LOD PVE (%) Add. Env Pop.

1 78.5 C1M95 136.5 C1M185 3.5 25.7 -3.0 12IR HHZ11

1 346 C1M437 355 C1M449 2.9 21.4 -1.7 11HN HHZ11

2 294.5 C2M371 307.5 C2M390 2.6 19.8 -1.7 11HN HHZ11

3 17.5 C3M22 18.5 C3M23 2.7 19.8 -2.6 12SZ HHZ8

3 210.5 C3M266 214.5 C3M271 3.5 19.2 -5.7 12SZ HHZ5

3 313.5 C3M399 328.5 C3M420 2.5 14.3 -4.1 12SZ HHZ5

5 69 C5M107 126.5 C5M169 3.1 22.8 -2.9 12SZ HHZ11

6 129 C6M174 178 C6M209 2.6 14.9 -3.6 12SZ HHZ5

7 1.5 C7M1 65 C7M84 3.3 21.3 -1.8 13SZ HHZ12

2.7 15.4 -1.8 13SZ HHZ5

8 40.5 C8M63 69.5 C8M106 2.9 19.1 -2.8 12SZ HHZ12

2.5 15.8 -1.1 11HN HHZ17

9 181.5 C9M226 222.5 C9M285 4.6 27.8 -3.6 12SZ HHZ19

4.5 23.9 -1.9 11HN HHZ5

10 16.5 C10M25 20.5 C10M31 2.9 16.3 -5.2 12SZ HHZ5

11 252.5 C11M292 259.5 C11M304 3.8 23.5 -6.4 12HZ HHZ19

Grain yield QTLs detected using 497 HHZ ILs from 8 donors in HHZ background showed donor allele significantly increased the grain yield


Drought QTLs

Chr Trait Start_point Start_bin End_point End_bin LOD PVE(%) Add Pop.

2 DI 388 C1M472 403.5 C1M482 3.7 23.8 -0.3 HHZ12

2 DY 256.5 C2M314 264.5 C2M326 3.3 18.7 -1.6 HHZ5

5 DY 225.5 C5M304 234 C5M316 3.0 19.5 -5.3 HHZ19

7 DI 1.5 C7M1 10 C7M11 2.6 18.0 -0.2 HHZ17

12 DI 184.5 C12M206 187 C12M210 2.8 18.5 -0.1 HHZ12

DI: Drought Index, DY: yield per plant under drought stress

Drought QTLs detected using 497 HHZ ILs from 8 donors in HHZ background showed donor allele significantly increased the grain yield under drought and drought indices


DT HHZ5-Sal14-Sal2-Y2 APO (check)


QTL mapping for Nitrogen Stressed condition

Chr Start_point Start_bin End-point End_bin LOD PVE(%) Add Pop.

1 45 C1M56 51 C1M63 3.2 19.5 -5.2 HHZ17

1 100 C1M131 104 C1M139 2.7 16.4 -5.1 HHZ17

4 310.5 C4M342 312 C4M344 2.6 16.5 -8.9 HHZ9

11 3 C11M3 4.5 C11M5 2.8 20.5 -10.7 HHZ8

11 31.5 C11M47 36 C11M54 2.5 18.9 -12.4 HHZ8

QTLs detected for Nitrogen stressed condition using 497 HHZ ILs from 8 donors in HHZ background showed donor allele significantly increased the grain yield under

nitrogen stress and nitrogen stress index


QTL mapping for Cold tolerance at booting

Site Chr Start_point Start_bin End-

point End_bin LOD PVE(%) Add Pop.

XDA 2 259 C2M318 295 C2M372 2.92 27.41 -0.10 HHZ15

YXII 3 82.5 C3M101 88 C3M109 2.57 17.12 -0.05 HHZ17

YXII 3 147.5 C3M199 148.5 C3M201 2.50 20.23 -0.10 HHZ5

XDA 3 312 C3M397 327.5 C3M419 4.01 35.55 -0.09 HHZ15

XDA 7 85 C7M102 3.03 28.27 -0.08 HHZ15

XDA: XUNDIAN ; YXII: Yuxi second batch of sowing

Cold tolerant QTLs detected using 497 HHZ ILs from 8 donors in HHZ background showed donor allele significantly increased the spikelet fertility under cold stress


DT screen SUB screen

SUBT plants

Resequencing or GBS/progeny testing for all target traits

Random plants

DT plants

Yield traits

Group genotypes

for different traits

and their NILs

HY + YC plants

ST screen

ST plants

IL2- HY, YC, NUE IL1- HY, YC, DT, X

F1

F2

New HYVs cultivars

with DT,ST, SUBT -

AYT-MET/NARES

Promising

PLs for yield

Confirm genetic networks for

different target traits and

their genetic relationship

DQP strategy for combining high yield(HY + YC), FITNESS [drought tol.(DT), NUE,

salinity tol.(ST) and submergence tol.(SUBT)] using the promising ILs as parental lines

Designed QTL pyramiding (DQP) for

High Yield(HY) & traits for climate change

Farmers

We are here DS2015

M79 (OM1723) M505 (CDR22)


Target traits

Number of ILs

Produced from

BN

Selected at PYT &

RYT

Nominated to

MET & NCT

Drought tolerance (DT) 613 79 21

High yield under low-input (LI) 370 27 3

Salinity tolerance (SAL) 502 73 18

Submergence tolerance (SUB) 128 13 2

High yield under irrigated (Y) 576 100 27

DT+LI 246 15 2

DT+SAL 326 19 5

DT+SUB 82 6

DT+Y 382 40 11

LI+SAL 274 10 1

LI+SUB 38 0

LI+Y 178 1

SAL+SUB 60 9

SAL+Y 292 42 8

SUB+Y 101 5 1

DT+SAL+SUB 35 3 2

DT+SAL+Y 154 9

DT+SUB+Y 58 3

LI+SAL+SUB 20 0

LI+SAL+Y 117 0

LI+SUB+Y 36 0

SAL+SUB+Y 39 2

total: 845 146 40

IL=Introgression lines; BN=Backcross Nursery;PYT=Preliminary Yield Trial;RYT=Replicated Yield Trial; NCT=National Cooperative Testing

(Philippines); Multi-environment testing (IRRI)

Multiple abiotic stress tolerant ILs developed from 16 donors into HHZ

background and nominated to NCT using GSR breeding scheme. 2

nd G

en

era

tio

n I

RR

I bre

d G

SR li

ne

s

Stood first in MET stage 2 under GRiSP

GSR IR1-8-S6-S3-Y2


Rapid visco analyzer (RVA) pasting properties of

newly developed HHZ Ils suitable for varied

consumers with different taste preferences

-1000

0

1000

2000

3000

4000

5000

6000

0 100 200 300 400 500 600 700 800

Time, sec

Vis

co

sit

y, cP

0

20

40

60

80

100

120

Tem

pera

ture

1 2

3 4

5 6

7 8

9 10

11 12

13 14

15 16

17 18

19 20

21 22

23 24

25 26

27 28

29 30

31 32

33 34

35 36

37 38

39 40

41 42

43 44

45 46

47 48

49 50

Temp(C)

AC=14.5-31.6%; GT=H-I-L; Protein=7.8-11.2


Genomics Assisted Breeding: Key Findings

• Simultaneous Multiple Abiotic and Biotic Stress Screening Selection Scheme employing early generation backcross breeding is an innovative strategy for QTL discovery, omic network dissection & varietal development.

• Several promising ILs developed with multiple abiotic stress tolerances and are being utilized by NARES partners and near to release.

• Genomics assisted breeding helped in identification of superior materials for Designed QTL pyramiding (DQP) & Genomics assisted recurrent selection scheme (GARSS) (dominant male sterility facilitated)

• Pyramiding of non-allelic QTLs (or DNA segments) improving trait tolerances from different donors into common adaptable recipient parent could be utilized for developing superior climate smart varieties in rice as per design and needs


Lines Climate Change Traits present

Target Environments

Target Locations

Released

IR83140-B-11-B DT+ST+NUE Rainfed Lowlands +Coastal saline+ Irrigated

INDO+VNM +BGL+PHL+S& E India

2014 (PHL)

GSR IR1-8-S6-S3-Y2

DT+ST+SU + NUE Irrigated+ Rainfed lowlands+ +coastal saline

PHL+INDO+ VNM+BDL+S& E India

2014(PHL)

GSR IR1-12-D10-S1-D1 (Aromatic)

DT+ST+ NUE+ Low GT (fast cooking time)+Premium quality under stress

Irrigated+ Rainfed lowlands+ +coastal saline

PHL+INDO+ VNM+BDL+S& E India

2014(PHL)

GSR IR1-1-Y4-Y1

ST+ SU+ DT+ NUE Coastal saline +Rainfed Lowlands+ irrigated

PHL+INDO+ VNM+BDL S& E India

2014(PHL)

Promising Green Super Rice materials

DT=drought tolerance; ST=salinity tolerance; SU=Submergence; GT=gelatinization temp.: NUE=nutrient use efficiency

Third generation IRRI GSR bred materials will be available in 2015 with more combinations of complex traits


GSR cultivars

Overall Mean Grain Yield (t/ha)

(Wet Seasons 2012 &13)

% Yield advantage over

average of checks Total sites

studied

GSR IR1-1-Y4-Y1(GSR1) 4.22 15.1 26

GSR IR1-5-S14-S2-Y2(GSR 5) 4.00 8.9 50

GSR IR1-5-S8-D3-SU1(GSR5A) 3.93 7.1 36

GSR IR1-8-S6-S3-Y2(GSR8) 4.34 18.3 50

GSR IR1-12-D10-S1-D1(GSR12) 3.66 -0.4 50

All national checks average (21 checks used in 13WS + 25 Checks used 12WS)

3.67 0.0 39

Performance of GSR varieties under rainfed Conditions of Philippines during WS12,13

Dept. of Agriculture(Regions 1,3,4,4B,5,6,7,10,11,12)

Checks were all the national released best varieties for each ecology and farmer’s variety in the all sites with abiotic stressed (salinity, submergence, drought, favorable and unfavorable rainfed) conditions Plot size= >500-1000sqm; In WS2014=60 sites expanded with +20m pesos/year

Obien et al 2013


Candijay (RVII) Apolinar Asa

Bohol,WS2013 Climate Smart GSR cultivar

GSR IR1-8-S6-S3-Y2

6.Drought:(18DAT-Flowering)

4. Submergence:4 days

5.Recovery

3.Salinity:4 DAT

2. Nursery:15d TPL

1. Land

7.Flowering

8.Harvest: 1.2t/ha

Obien et al 2013

91-24-14 kg NPK/ha

Potential for a second crop despite salinity, flooding and drought combined

Saline area: flooded and drought (Candijay, Bohol)

Entry Name WS Yield (t/ha) DS Yield (t/ha)

GSR 1 0.49 6.16

GSR 5 1.06 2.90

GSR 5A No harvest 5.51

GSR 8 1.20 7.23

GSR 11 No harvest 4.85

GSR 12combined 1.34 7.11

Farmer’s adverse 0.21 n.a.

Farmer’s good 1.20 n.a.

Multi-trait lines means less risk if other climate-induced stresses hit an already stressed area, i.e. saline area hit by floods and/or flooded areas hit by drought, etc.


GSR

GSR IR1-8-S6-S3-Y2

High yielding under irrigated with moderate multiple abiotic stress tolerance GSR line with good cooking quality suitable for coastal rainfed and irrigated lowlands.

Ready for Deployment; seeds sent to NARES Nominated to NCT Philippines –Release in 2014

GSR NUE Trial IRRI DS2012


March 2, 2015 © 2012 Bill & Melinda Gates

Foundation | 32

GSR IR1-Y4-Y1-Y1 GSR IR1-Y4-Y1-Y1 IR64 sub1

IR42 Swarna sub1 GSR IR1-8-S14-S3-Y2

GSR IR1-11-D10-S1-SU1 Huanghuangzhan IR42

GSR IR1-14-S1-Y-SU1-L1 GSR IR1-18-D4-Y1-SU1-L2 GSR IR1-14-S1-Y1-SU1-L1

GSR IR1-8-Y1-D3-SU1 GSR IR1-8-S14-S1-SU1 Huanghuangzhan

IR 83105-B-B-5 IR64 sub1 GSR IR1-11-D10-S1-SU1

IR64 sub1 GSR IR1-10-D12-L1-L1 GSR IR1-8-S14-S1-SU1

GSR IR1-18-D4-Y1-SU1-L1 GSR IR1-S14-S1-Y1-SU1-L1 GSR IR1-8-S6-S3-Y2

GSR IR1-3-S13-Y2-D1 GSR IR1-8-S6-S3-Y2 GSR IR1-5-S14-S2-Y2

Swarna sub1 GSR IR1-5-S14-S2-Y2 Swarna sub1

GSR IR1-18-D4-Y1-SU1-L2 GSR IR1-1-Y6-Y1-SU1-L1 GSR IR1-1-Y4-Y1-Y1

Multi-Stress tolerant GSR at IRRI


Promising GSR lines identified with multiple abiotic stress tolerances at IRRI Philippines

GSR/Checks

Grain Yield (t/ha)

IRRIGATED

(IG)

LOW-INPUT

(LI)

DROUGHT

(DT)

SALINE

(SAL)

SUBMERGENCE

(SUB) Mean

Rainfed

(IG+DT+SUB+L

I)

Irrigated

(IG +LI)

Saline

(IG+SAL+D

T)

GSR IR1- 3-S13-Y2-D1 13.32 8.16 0.13 5.93 8.01 7.11 7.40 10.74 6.46

GSR IR1- 18-D4-Y1-SU1-L2 12.61 6.16 0.23 5.52 10.19 6.94 7.30 9.38 6.12

GSR IR1- 8-S6-S3-Y2 9.84 7.17 0.27 8.28 6.78 6.47 6.01 8.50 6.13

GSR IR1- 8-S14-S3-Y2 10.98 3.98 0.06 5.47 11.64 6.42 6.66 7.48 5.50

Huanghuazhan 10.05 6.45 0.44 6.02 8.48 6.29 6.36 8.25 5.50

GSR IR1- 5-S14-S2-Y2 9.48 4.93 0.67 6.50 9.64 6.24 6.18 7.20 5.55

GSR IR1- 10-D12-L1-L1 11.56 5.66 0.79 4.30 8.29 6.12 6.57 8.61 5.55

GSR IR1- 1-Y4-Y1-Y1 9.43 5.22 0.78 7.21 5.06 5.54 5.12 7.32 5.81

Swarna-Sub 1 (Check) 10.54 4.58 0.33 0.16 7.11 4.54 5.64 7.56 3.68

IR64-Sub1 (Tolerant Check) 8.98 3.74 0.38 3.56 3.83 4.10 4.23 6.36 4.30

IR 42 ( Susceptible Check) 11.71 3.33 0.00 2.80 0.00 3.57 3.76 7.52 4.84

NSIC Rc222( Irrigated Check) 10.78 5.22 0.70 1.85 not planted 4.64 5.57 8.00 4.44

Rice Science for a Better World IR42 (dead)

IRRI bred GSR lines with multiple stress tolerances WS2014 Submergence tank


Performance of 10 IRRI bred GSR cultivars released for cultivation in the Philippines

New Designation DA code/

NSIC

MAT

days

Grain Yield (t/ha) @14% MC % Yield

advantage

over NSIC222

IG- 4 S

Low-input

(4 S)

DT-LL (4 S)

ST-

Infanta 6dSm-1 12DS

Zn def

Bae Laguna 12DS

Victoria Laguna

HY 12DS

Mean Yield

GSR IR1-8-S6-S3-Y2 GSR8 105 6.5 3.3 3.5 5.1 4.3 7.4 5.0 18.2

IR 83142-B-19-B GSR2 100 6.2 3.8 3.4 - - - 4.5 5

GSR IR1-12-D10-S1-D1 GSR12 115 6.4 3.7 3.6 5.1 4.1 6.0 4.8 13.4

GSR IR1-5-S8-D3-SU1 GSR5A 110 5.7 3.3 3.4 5.1 - - 4.4 2.4

IR 83140-B-11-B GSR11 110 6.2 3.3 3.3 5.1 - - 4.5 6.1

GSR IR1-1-Y4-Y1 GSR1 110 6.0 4.5 5.4 5.6 - - 5.5 26.8

GSR IR1-5-S14-S2-Y2 GSR5 115 6.1 3.0 3.6 5.4 3.5 6.3 4.6 8.8

IR 83140-B-28-B NSIC390 105 6 2.9 3.6 4.7 - - 4.3 1.2

IR 84675-58-4-1-B-B NSIC392 110 5.6 3.4 3.5 4.3 - - 4.2 -1.7

IR 83140-B-36-B NSIC29 110 6.0 3.4 4.4 - - - 4.6 8.7

PSB Rc82 -low Input

check - 115 6.0 3.8 3.2 - 4.1 - 4.3 0.2

NSIC Rc222 IG-Check - 116 5.9 3.6 2.6 - 4.0 5.2 4.3 0

NSIC Rc184-Saline check - 4.8 4.8

MAT=Maturity; IG=irrigated; DT-LL=Drought lowland; ST=Salinity; S=Seasons; IRRI sub tank WS12: Submergence scores of GSR 8=4.2; GSR 5A=5; GSR1=3; IRRI 119=2.8;IRRI 149=4.1


2010 WS Weed Tolerant Rice (WTR) crossed with 16 donors

2010 DS 16 Backcross Populations (BC1F1)were created

2011 DS 16 BC1F2 bulk populations were created

2011 WS Irrigated (IG) 1

st Round of Screening

Low Input (LI) Rainfed (RF) 242 237 251

2012 DS

Irrigated (IG) 2

nd Round of Screening (730 ILs)


Salinity (S) Submergence (SU)

Anaerobic Germination (AG)

394 220

80

Tungro (T) 51

Upland (Ul) 112

2012 WS Irrigated (IG) 3rd Round of Screening (1151 ILs)


2013 DS Out of 2242 ILs only 617 ILs used for Preliminary Yield Trials (PYT) at 3 conditions

2013 WS Physiological Yield

Potential Trials 22 lines

2014 DS

DQP Crosses 9 RP’s

5 DP’s

Replicated Yield Trials

64 lines

Demo

4 lines

MET 0

20 lines

2014 WS Replicated Yield Trials

64 lines

Demo

4 lines

2015 DS

Replicated Yield Trials

32 lines

Demo

4 lines

Sequenced by tGBS 576 lines

MET 1 9 Ils

>15%

NCYT 2 ILs

Rice Science for a Better World Rice Science for a Better World

BLUP means (t/ha) of GSR entries in the 2014DS MET Stage 0.

METNO FIXED NAME Location

Across Across

Rank Muñoz San Mateo Los Baños Ubay

MT5434 NSIC Rc132H (Mestizo 6 -hybrid) 8.35 7.56 7.85 6.71 7.61 1

MT6230 GSR IR2-1-R5-N1-Y3 8.17 7.38 7.67 6.53 7.44 3 MT6220 GSR IR2-19-Y14-L2-L2 8.16 7.37 7.66 6.52 7.42 4

MT6219 GSR IR2-8-Y14-SU3-R2 8.11 7.32 7.61 6.47 7.38 5

MT6212 GSR IR2-11-R9-Y1-L2 8.02 7.23 7.52 6.38 7.28 6

MT6253 GSR IR1-6-D10-Y1-D1-L2 7.93 7.14 7.43 6.30 7.20 8

MT6229 GSR IR2-1-Y16-S1-R2 NA 7.13 7.43 6.29 7.19 9

MT6227 GSR IR2-5-L10-Y1-Y2 7.89 7.10 7.39 6.25 7.16 11 MT5433 IRRI 156 (NSIC Rc238) 6.95 6.16 6.45 5.31 6.22 225

MT4902 IRRI 123 (PSB Rc82) 6.84 6.05 6.34 5.20 6.11 244

MT4901 IRRI 104 (PSB Rc10) 6.66 5.87 6.16 5.02 5.93 274


Selection Strategy Favors Genetic Gain & Resilience

Conventional breeding (8-10y)

GSR breeding strategy (4-5y)


Victoria, Laguna

Bay, Laguna

Infanta, Quezon

Irrigated

Zinc-deficient

FM-PVS 3-5 entries

FM-PVS 3-5 entries

RM-PVS 8 entries

2011, 2012, 2013 DS

2011 WS, 2012 DS

2012 DS

Saline prone (6-10 dSm)


Performance of GSR varieties with increased plasticity especially for rainfed trials

S.No.

Designation

Grain yields (t/ha) per location in India Average

% Adv

over

IR64

check

Ori

ssa

Mug

ad

Bih

ar

And

aman

Ass

am

Man

ipur

Hyd

erab

ad

Har

dina

th

(t/ha)

1 GSR IR1- 11-Y10-D3-Y3 5.4 9.4 1.8 1.1 5.5 3.1 3.8 3.1 4.1 41.4

2 GSR IR1- 11-D7-S1-S1 4.3 6.4 1.9 1.8 5.5 3.5 3.6 3.9 3.9 34.5

3 GSR IR1- 12-S2-Y3-Y1 2.8 9.3 1.9 1.7 5.9 3 2.8 4.1 3.9 34.5

5 GSR IR1- 12-S8-Y1-S1 5.8 5.1 2.4 1 5.6 2.3 3.2 3.1 3.6 24.1

6 GSR IR1- 5-D1-D1 3.6 5.4 1.9 2.1 5.3 2.9 4.4 3 3.6 24.1

7 GSR IR1- 5-S8-D2-S1 2.9 6.2 2.2 2.3 6 2.1 4.2 3.2 3.6 24.1

8 GSR IR1- 5-Y4-S1-Y1 3.9 5.8 1.8 2.8 5.8 2.2 3.8 2.8 3.6 24.1

9 GSR IR1- 5-D7-Y3-S1 3 5.8 1.4 1.6 6.2 3.1 3.3 3.9 3.5 20.7

10 GSR IR1- 5-S10-D3-Y2 4.8 4.1 3.3 2.7 4.3 2 4.4 2.6 3.5 20.7

11 GSR IR1- 5-S14-S2-Y2 4.3 5.7 1.9 1.6 4.8 2.9 3.4 3.1 3.5 20.7

12 HUANGHUAZHAN 3.3 5.2 2.1 1.4 4.5 1.2 3.5 2.7 3 3.4

13 IR 64 2.2 3.1 2.1 1.8 4.9 2.9 3.9 2.6 2.9 0

14 IRRI 123 1 2.6 1.5 1.4 3.5 2.6 3 2.6 2.3 -20.7

15 Local check (tol-early) 4.1 6.2 2.6 1.2 2.9 3 3.1 1.7 -

16 Local check (tol-medium) 5 6.7 1.1 1.3 5 3.5 3.8 3.1 -

17 Local check (sensitive) 4.8 5.4 1.5 1.3 3 2.5 4 3 -

18 Local check (quality) 5.1 7.6 1.9 1.2 6.9 2.9 3.6 3.4 -

Rice Science for a Better World Rice Science for a Better World

Seeds released, produced, and nominated to NCYT

Country Released Seeds Produced (t) Near to release

Nominated

to NCYT Inbreds Hybrids Inbreds Hybrids Inbreds Hybrids

South Asia

Pakistan 0 9 - 3,440 2 0 2

Sri Lanka 1 0 - 0 1 0 1

Bangladesh 1 3 - 4,340 3 0 2

India 0 0 - 0 0 0 13

SE Asia

Philippines 11 0 18,800 0 4 0 25

Vietnam 1 1 1,430 564 1 0 2

Indonesia 1 4 - 1,250 0 1 4

Lao PDR 5 CSB 0 26 0 2 0 2

Cambodia 2 3 - 1,650 0 0 0

ES Africa

Tanzania 0 2 - 316 2 0 5

Uganda 1 0 30 0 0 0 0

Rwanda 1 0 5 0 0 0 2

Mozambique 0 0 300 0 3 0 15

19+5 CSB

22 20,591 11,600 19 1 73

*CSB=Community seed bank –Mother –baby trial –PVS approaches in the upland areas (Hua564, SACG4 Zhongzu14,Wanxian763)

Area Covered is 0.7mha with GSR varieties


An additional ton of rice in the rain-fed and irrigated lowlands will change the livelihoods of millions of resource poor farmers from the clutches of poverty and sustained income source to prosper….

THANKS

GSR IR1-12-D10-S1-D1 –Aromatic & High Yielding

Suitable for Direct seeding & Irrigated conditions, good cooking quality (AC24%,GT-L, Protein 9.4%) + Drought and Salinity tolerant


CAAS-IRRI-BMGF

Dr Zhikang Li Director GSR project

Dr David Bergvinson, Dr June Yao, Senior Program Officers(BMGF)

GSR National Coordinators (Asia & Africa)

Drs Tuat, Untung, Helaluddin, Somphet, Nimal, Rehman, Arif, Babu, Bhadana, Bayuh, Lamo, Kessy, Innocent, Langa, Philippines team: DA: Obien, Lito, PhilRice: Thelma,

Dr W.Xu (Boshima-SS,IDO) & Dr Sirajul Islam(BRAC)

GSR-CAAS team: Drs Z. Li, Gao, Xu, Wang, Fu, Yu, & Chi many unknown

IRRI GSR: Drs Alexis (ESA GSR Coordinator), Rosemary, Nollie, Glenn, Choi, Redona, Pede Andy, Krishna, Wang, Tao

GSR-GML group Jastin (field), Neil(seed movement & Out Station Research), Bart (Data & Stat); Corine(PVS), Lolit (seed);

VRF:Meng, GSR PhD:Umair, Varun, Zilhas, Jiefeng, Pang, Seyed; MS:Nina, Adrian

GSR Project Adm.: Pauline (Seed Tracking); Secretarial Assistance: Badett

“Cooperation & Collaboration makes the world a smaller place”

Acknowledgements & Thanks:


Grain Yield QTLs- HHZ ILs

Studied over Six Locations 2012 and 2013 spring season at Hainan, 2012 Summer, 2013 Spring and Summer in Shenzhen, 2012 DS irrigated normal condition at IRRI 497 HHZ ILs with 2 replication each for yield and yield-related traits Yield QTLs under different environments and identifying major QTL pyramiding, Mining from the donor alleles that improved Huanghuazhan for increased yields

497 HHZ ILs Hainan(2013) 497HHZ ILs Shenzen(2012) IRRI (2012DS)


Drought QTLs

2012 DS at the International Rice Research Institute(IRRI), 497 HHZ ILs planted under Upland drought and Irrigated normal conditions Water stress was given after 30 d onwards of transplanting 21 d old seedlings in the field until harvest. Rainfall during this entire stressed period was < 85mm (2012). Drought index %=(upland production - normal paddy yield)/normal paddy yield x100

497ILs screening- upland DT (12DS IRRI)


QTLs for Nitrogen Stressed Conditions

Control Low N Control Low N

2013 DS in Shenzhen Dapeng , SIBI with 497 HHZ ILs -nitrogen stress treatment, with 2 reps. Low nitrogen dose (Basal fertilizer and FYM at nursery )before transplanting and after transplanting during the entire growth period no N fertilizer applied but P & K fertilizers were applied as per recommended based on SSNM Control: Farm Yard Manure=3000kg; Compound (15:15:15) (NPK)-slow release= 450kg; 100 kg/ha of Urea as Top dressing at Tiller stage and 50kg Urea at booting stage. N stress : No N Fertilizers, Basal dose for P & K as control. Biomass and grain yield related traits were recorded under the control and nitrogen stress conditions Nitrogen Stress Index%=(low N plant yield - yield per plant control)/control plant yield x100


Cold Tolerance Evaluation at Booting stage

Cold tolerant ILs Cold susceptible ILs Cold injury at heading

Natural sites: Yuxi (ann.ave. temp=19.3 ℃) suitable indica cold resistant screening Two batches: regular planting and 10 days delayed planting each with 2 reps. Xundian= (ann.ave. temp=14.5℃) rainy, suitable for cold resistant screening , One regular planting date with 2 replications Field management: standard practice as per the local conditions Parameters: survival rate was observed at seedling stage, withered leaves, frequency of seed setting, grain yield at maturity was used to identify cold tolerant introgression lines

advent of climate smart rice varieties through genomics...

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