Challenges for rice breeding Application of biotechnological tools Dave Mackill Plant Breeding, Genetics & Biochemistry Division International Rice Research Institute Los Baños, Philippines

Crop/soil/water management IRRI MTP Programs Program 1 Program 2 Program 3 Genetic Resources and Gene Discovery Favorable environments Unfavorable environments Genetic improvement Crop/soil/water management

Rice breeding activities Irrigated breeding: Indica varieties New Plant Type Hybrid rice Temperate rice Wide hybridization Adverse soils Molecular breeding Transgenic breeding Rainfed lowland Upland Deepwater/tidal Aerobic rice Favorable environments Unfavorable environments

Important challenges for rice breeding Water limitation Micronutrient density (Fe/Zn, and Golden Rice) Direct seeding (weed competition/anaerobic germination) Abiotic stress (drought, submergence, salinity) Increasing yield potential Grain quality

Water scarcity

Aerobic rice varieties Favorable upland varieties (Apo) Hybrid rice varieties (Magat) Irrigated rice varieties Rainfed lowland varieties Upland X Lowland hybrids

Aerobic rice yields, IRRI, 2001 ds Cultivar Yield DH Magat 4.27 80 IR55423-01 (Apo) 3.54 111 Maravilha 3.04 113 KMP 34 2.98 81 B6144 2.50 116 LSD 0.72 6

Some irrigated breeding lines have superior yields under aerobic conditions

Nutritious rice

Fe content in the hull, brown rice, hull and grain, and different plant parts. (Fe mg/kg) 225 - 448 Brown rice = 10 -17 Paddy = 448 - 908 Hull = 1105 - 2010 247 - 520 174 - 310

Effect of Soil Zn in the micronutrient loading in the grain

Direct seeding

Traits for direct seeding Anaerobic germination tolerance Good seedling vigor Submergence tolerance New Plant Type for higher yield

Anaerobic seeding

Abiotic stress tolerance

Abiotic stress breeding Emphasis on drought, submergence, salinity (some soil difficiencies-P, Zn) Conventional breeding, participatory varietal selection, QTL mapping Functional genomics-identifying candidate genes and allele mining

Proteomics: salt tolerance -2.5 -2 -1.5 -1 -0.5 0.5 1 1.5 2 2.5 CT9993 IR62266 IRL 20 17 28 37 3 14 15 26 40 22 23 4 11 31 36 42 13 6 9 21 24 30 32 34 35 38 39 41 12 25 5 7 10 8 16 18 19 Log2 ((abundance ratio) Cyt TP Rubisco activase Ct FBP aldolase Ct RNA binding protein GSH- DHAR S-like RNase S-Like RNase Cyt Cu-Zn SOD EF-Tu Rubisco Activase NDK1 Ct Cu-Zn SOD Ct Rieske FeS Arabidopsis protein

Higher yield potential

Higher yield potential Original new plant type Japonica type – high yield in temperate areas (China) Susceptible to diseases/poor grain quality Low biomass associated with low tillering

Two varieties released in China

Modified new plant type Single cross with indica parents Improved resistances Long-grain, intermediate amylose Higher yield in tropical environments Retains larger panicle and strong stem

IR72 Improved NPT

Hybrid rice Still higher yield potential Wider crosses show high potential (NPT) Possibility in unfavorable environments (aerobic rice, salinity)

Wild species introgression

C4 rice?

Incorporating biotechnological tools Transgenics Introducing novel genes Modifying rice genes Combining multiple rice genes Marker assisted selection Conventional (linkage mapping) Functional genomics

Major genes or QTLs Major gene traits QTLs Backcrossing recessive genes Pyramiding multiple genes Difficult to measure traits QTLs Limited progress through conventional breeding

Why haven’t breeders taken advantage of QTLs identified in rice? Poor resolution of agronomic QTLs Small effects Interaction with environment and genetic background Expense of genotyping

In what situations would breeders be encouraged to select for QTLs? QTL with relatively large effect Traits difficult to measure QTL effect independent of genetic background QTL being transferred from an exotic source (ABQTL)

Current bottlenecks for rice breeding Many rice varieties are released each year by national programs in Asia. Most of these varieties achieve limited success. A few become widely popular.

However, a relatively small number of cultivars have been adopted on large areas

It has become increasingly difficult to achieve further improvements Widely grown varieties with favorable features are rare achievements Most newly released varieties, while often showing superiority in breeders’ tests, do not replace the existing varieties

Making incremental improvements in these varieties is a viable breeding strategy These varieties become increasingly prone to diseases and insect pests (maintenance breeding) The varieties often lack tolerance to abiotic stresses, which limits their production to more favorable areas

Resistances to abiotic stresses Highest level of tolerance often in exotic or and/or unproductive cultivars Expensive and difficult to accurately evaluate Improvements would have clear impacts on poorest farmers

Submergence tolerance as an example ST was thought to be a quantitative trait of relatively high heritability based on at least 4 genetic studies up to 1995

Physical map of Sub1 SUB1 CEN NotI NotI NotI NotI NotI NotI 6 Recs 1 Rec? (42kb) 4 Recs (<110kb) 2 Recs 14A11-F15 14A11-481 14A11-L’’ 14A11-270 20P2-F20 RZ698 13L11-L 14A11-L’ 17P5-L RAPD1 SSRA1 14A11-L RAPD1’ RAPD1’’ A303 R71K R50K A209 R1164 NotI NotI NotI NotI NotI NotI 20P2 (150kb) TQR14A11 (99kb) TQB7A1 (109kb) TQR13L11 (75kb) TQH17P54 (69kb) TQH9D24 (69kb) CEN 263 kb, completely sequenced

Traditional backcross BC1 BC2 BC3 BC4 Traditional backcross Percent recurrent parent genome 75.0 87.7 93.3 99.0 Percent recurrent parent genome 85.5 98.0 100 MAB From Ribaut & Hoisington 1998 27

FL1 R FL2 Number of individuals to obtain desired genotype in following BC generation d1 d2 d1 (cM) d2 (cM) From Frisch, Bohn & Melchinger 1999 29

FL1 R FL2 Number of individuals to obtain desired genotype in following BC generation d1 d2 d1 (cM) d2 (cM) From Frisch, Bohn & Melchinger 1999 28

Target QTLs for Abiotic Stress Tolerance Submergence tolerance (Xu and Mackill 1996) Deepwater elongation (Sripongpangkul et al. 2002) Drought (Babu et al. 2003) Al toxicity (Nguyen et al. 2003; Wu et al. 2000) P uptake (Wissuwa et al. 1998) Salt tolerance (Bonilla et al. 2002) Cold tolerance tolerance (Andaya and Mackill 2003) Fe toxicity tolerance (Wan et al 2003)

P uptake 12 Pup1: LOD 16.5 R2 78.8 From Wissuwa & Ismail G124A (30.0) C443 (50.5) S10704 (49.3) P96 (47.9) C449 (72.5) G2140 (63.7) V124 (70.7) S13126 (55.1) S1436 (57.4) S13752 (56.0) C61722 (58.9) C901 C449 W326 C2808 G2140 C443 S10520 G124A S2572 C732 Pup1: LOD 16.5 R2 78.8 From Wissuwa & Ismail

Fine mapping salinity tolerance gene Chromosome 1 58.1 RM23 60.6 AP3206-124201 62.5 AP4253-20757,RM3412 63.9 AP3722-9700 Saltol gene 64.9 RM140, S13927/AluI 65.4 AP3211-28 66.5 CP10135 67.6 AP2869-104052, AP2869-17620, RM8115 67.9 AP3143-072/DraI 73.7 RM113,RM24 LOD 6.7 R2 43.9 From G. Gregorio

Al toxicity Nguyen, Brar

Cold tolerance 4 LOD 8.36, R2 20.8 12 LOD 20.34, R2 40.6 From Andaya & Mackill 2003

Maximizing the value of QTLs 12 1 Allele mining