MARS and MABB for Drought and Heat Tolerance with Rust Resistance in Wheat

Transcription

1 Genomics for Crop Improvement, Bengaluru Feb 18-20, 2013 MARS and MABB for Drought and Heat Tolerance with Rust Resistance in Wheat GP Singh, Neelu Jain, Vinod, JB Sharma, T Ramya and KV Prabhu Division of Genetics Indian Agricultural Research Institute New Delhi , India head_gen@iari.res.in kvinodprabhu@rediffmail.com To use any of the contents in this presentation please contact the author

2 Water Stress Indicator Map Source: IWMI

3 Abiotic Stresses in Wheat Wheat grown in 30 million hectares and over 85% of wheat is irrigated But nearly 70% of irrigated area does not receive all 6 recommended irrigations Wheat suffers losses due to abiotic stresses such as heat (terminal, early, tillering stages), drought and salinity ranging from 10-40% (yield and reduced quality) Minor genes or QTLs based tolerance is likely to provide abiotic stress tolerance in wheat and very few varieties available for this purpose Options such as MARS, MABB and AM are expected to pick up tolerance imparting QTLs distributed along the complex wheat genome for their deployment in varietal backgrounds

4 Strategies to cope abiotic stresses Plant breeding strategies: 1. Exploitation of alien genetic variation 2. Enhanced input use efficiency under stresses 3. Breeding for earliness 4. Varieties with wide adaptation to ecologies Biotechnological tools: 1. Marker assisted breeding 2. Transgenics/Cisgenics 3. Genomics, proteomics etc. 4. Association genetics/tilling/ecotilling

5 Wheat Breeding Strategies for Drought and Heat Tolerance Development of varieties with to cope with high temperatures during early, mid and terminal stages Varieties suited to change in planting dates to avoid terminal heat stress Varieties with high WUE, suited to low water availability Varieties suited to altered crop rotations Development of varieties for new agricultural areas resulting due to shift in climatic pattern

6 Recurrent Selection Cyclical selection of populations (Selection-Evaluation-Recombination) Systematically increases the frequency of favorable alleles Maintains and reshuffles the genetic variation within a population to permit continual progress from selection Easy to apply in cross-pollinated crops; difficult in selfpollinating crops Marker Assisted Recurrent Selection (MARS): Provides for detection of favourable alleles through markers as well as their recombination

7 Objectives MARS and MABB involving new QTLs and the known QTLs to improve the water-useefficiency and heat tolerance of wheat in India Combine the MABB products possessing drought tolerance with rust resistance

8 Centres and Responsibilities IARI, New Delhi MARS, MABB : Phenotyping, Genotyping JNKVV, Powarkheda MARS: Phenotyping PAU, Ludhiana MARS, MABB : Phenotyping, Genotyping ARI, Pune MARS: Phenotyping NRCPB, New Delhi Genotyping, ICIS (GCP CI India)

9 Traits targeted Morphological traits 1. Days to flag leaf emergence 2. Days to 50% heading 3. Ground cover 4. Grain yield (g/plot) 5. Harvest index 6. Above ground biomass (g/plot) 7. Test weight (g) 8. Grain filling duration Physiological traits 1. Stay green duration(using NDVI) 2. Canopy temperature (CT) using Infrared thermometer 3. Flag leaf area 4. Chlorophyll content 5. Chlorophyll florescence

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11 Digital estimate of per cent ground cover for early vigour evaluation Per cent ground cover : Proportion of the Mean Grey Value to mean value if the image were completely white (255). (Grey value of a completely black image is 0 )

12 VARIABLE AVERAGE MINIMUM MAXIMUM HERITABILITY GERM DH YLD TKW DM CT CTD NDVI SPAD DH DM YLD TKW CT CTD NDVI DM 0.84** YLD -0.22** TKW 0.20** 0.19** 0.20** CT ** -0.36** CTD ** 0.38** ** NDVI 0.39** 0.46** 0.24** ** 0.28** SPAD ** *

13 Indian Council of Agricultural Research Breeding Cross

14 Progressive multi-traits based MARS Xu et al., Mol Breeding (2012)

15 Validation of markers linked to known QTLs More than two hundred microsatellite markers associated with physiological, phenological and agronomic traits were selected. These microsatellite markers associated with specific traits on the parents of our backcross generations to Introgress the QTLs (16 back cross BC1F1 with size generated). Polymorphic markers to target five physiological traits covering 17 chromosomes for identification of known QTls in our backgrounds. These include Canopy temperature QTLs on 15 Chromosomes (1A, 1B, 2A, 2B, 3A, 3B, 4A,4B, 5A, 5B, 6A, 6B, 6D, 7A,7B), NDVI on 3 chrs (2A, 2B and 4A), Chlorophyll on15 chrs (1A,1B,1D, 2A, 2B, 3A, 3B, 4B, 5A, 5B, 6A, 6B, 6D, 7A and 7B), WSC on 17 chrs (1A,1B,1D, 2A, 2B, 2D, 3A, 3B, 4A, 4B, 4D, 5A, 5B, 6B, 6D, 7A and 7B), stay-green on 3chrs (1A,3B and 7D).

16 Significant QTLs reported and utilized in our populations QTL references Chromosome no. Traits targeted Pinto et al B, 5A, 4A, 1B CT, Chl, NDVI, yield Kumar et al B, 7D, 3B Stay-green trait Mohammadi et al. 2008a and b 2D, 1B, 5B and 7B Yield and GFD under heat Kumar et al D, 3B CT, Chl Olivares et al A Kadam et al B, 3D NDVI Yield under drought and root traits

17 Best possible individual by modeling 1A 1B 1D 2A 2B 2D 3A 3B 3D z 5A 6A 6B 7A 7D 7B Yield from Parent DBW43 Drought tolerance from Parent B HI 1500

18 MARS for Accumulating Favourable Genes x x FAMILY. 1 FAMILY 2 FAMILY. 3 FAMILY. 4 F1 F1 2nd Recombination x

19 SSRs markers linked to QTLs for Drought tolerance which are segregating population DBW43 X HI1500 GWM 484(2D) GWM 644(7B) GWM 156 (5A) GDM 132(6D) GWM 383(3D) GWM 165(4B) GWM 368(4B) GWM273(1B) GWM 582(1B) BARC 147(3B) GWM 566 (3B)

20 Indian Agricultural Research Institute DBW 43 (P1) x HI 1500 (P2) Parental polymorphism F1 Phenotyping in E1, E2 and E3 E4 Genotyping and QTL analysis F4 SELECTION OF LINES FOR INTERCROSSING Ind.1 Ind.2 F1 F1 F2 Ind.3 Ind.4 Ind.5 F2 Ind.6 Ind.7 Ind.8 F1 F1 F2 F2 F2 Selection of homozygous plant

21 Families selected for intercrossing in Rabi 2013 S.No Cross Families selected for intercrossing 1 DBW43/HI1500(Cross 1) 19,26,43,44,76,84,87,98,105,137,143,146,155,156 2 HUI 510/HI 1500 (Cross 2) 68,111,46,7,72,107,101,68 3 Cross 3 51,5,43,113,105,95,49,23,104,84,48 4 Cross 4 8,11,74,97,80,28,44,112,153,118,52,4.

22 Xbarc 186 linked Canopy Temperature Segregation pattern in bulked families HI bp DBW bp

23 Segregation pattern Xbarc 68 linked to Chlorophyll content HI bp DBW bp Here favorable allele is 137 bp

24 WMC 487 linked to 1000 grain weight A1 = HI A2 =DBW and 222bp

25 Segregation pattern of gwm273, marker linked to Canopy temperature, in bulked F4 families DBW 43 x HI 1500

26 Segregation pattern in bulked F4 families -gwm533 linked to stay green duration

27 Hunt for new QTLs segregating in the cross Polymorphic markers among parental genotypes Chromosome 1A,1B,1D 58 No. of Polymorphic markers 2A,2B,2D 60 3A,3B,3D 48 4A,4B,4D 37 5A,5B,5D 46 6A,6B,6D 61 7A,7B,7D 110

28 Identification of new QTLs (WMC 285) in F4 families

29 Families selected for intercrossing in Rabi 2013 in HI 1500/DBW43 Family Early ground cover CT CHL (spad ) Biomass HI Yld g/plot

30 Identification of new QTLs (Cfd 73) in F4 families A1 = HI bp A2 =DBW bp

31 Identification of new QTLs (Xbarc 327) in F4 families A1 = HI1500 A2 =DBW 43

32 NICRA, DIVISION OF GENETICS Development of backcross populations In the last crop season crosses were developed among contrasting parents for heat and drought tolerance F 1 s from twenty three crosses were advanced in the off-season nursey at Lahaul-Spiti F 1 s were backcrossed with the high yielding recurrent parent to generate BC 1 F 1 populations These Bc 1 F 1 s are advanced in the current crop- season to generate BC 2 F 1 populations. DNA samples were drawn from the BC 1 F 1 for foreground selection of the target trait and recovery of the background genome through background selection. A total of 850 microsatellite markers used and approximately hundred polymorphic markers were observed among them

33 Traits targeted for introgression through MABB S.No Backcrosses PopSize BC1F1 Trait targeted Chr no. 1 HD 2733*1/C Yield, CT, Chl 4B,1D, 3B 2 HD 2733*1/HI NDVI, Staygreen,Yield 2B, 7D 3 HD 2733*1/HD NDVI, CT, Yield 1D, 7B, 4A 4 HD 2733*1/HW NDVI, yield 2B, 7D 5 HD 2733*1/NI NDVI, CT, Yield 1D, 7B, 4A 6 HD 2733*1/WH Yield, CT 1B, 7B 7 GW 322*1/HD NDVI, CT 2A, 2B 8 GW 322*1/HD Stay-green, Yield, GFD 7D, 4A, 6D 9 GW 322*1/HI Yield, stay-green, Chl 4A, 7D, 4B content 10 GW 322*1/NI Yield, Chl 4B, 3B 11 GW 322*1/RAJ CT, Yield 1B, 5B, 7B 12 GW 366*1/HD GW 366*1/WH CT, Yield 1B, 5B, 7B 14 GW 366*1/RAJ CT, Yield 1B, 5B, 7B

34 HD2733 X HD2888 F1 X HD 2733 BC1F1 (population size 454) Foreground selection for QTL for yield under drought on 3DS L cfd55 13 = HD2733(259bp) 14=HD2888(270bp) Plants positive for both cfd55 & cfd79 selected (plant No. 3 and 22) cfd79 L Kadam et al Funct Integr Genomics (2012) 13 = HD2733(300& 248 bp) 14=HD2888(306& 256bp)

35 HD2733 X C306 F1 X HD 2733 BC1F1 (population size 645) HD2733 C 306 HD2733 C 306 Kadam et al Funct Integr Genomics (2012) Kadam et al Funct Integr Genomics (2012) xbarc20 gwm 368

36 HD 2733 (Recurrent parent) X HI 1500 (Donor parent ) F1 X HD 2733 BC1F1 (population size 782) Foreground selection :QTL for Stay green under drought on 7D L gwm 111 Lane 13 = HD 2733 Lane 14=HI 1500 gwm 437 L Kumar et. al Euphytica (2010)

37 No. of SSR markers employed for background selection through MABB for rust resistant NIL 1A : 6 2A : 7 3A : 8 4A : 9 5A : 7 6A : 6 7A : 5 1B : 9 2B : 7 3B : 8 4B : 7 5B : 8 6B : 8 7B : 10 1D : 6 2D : 8 3D : 7 4D : 7 5D : 12 6D : 5 7D :

38 MABB for Rust Resistance in HD 2733 Recipient parent HD2733 Donor Parents HD2687+Lr19 HD2687+Lr24 HD2687+Yr15 HD2189+Lr34 HD2851+Sr26 HD2851+Yr10

39 HD2733 (MABB) HD2733 HD2687+Lr19 HD2733 HD2687+ Lr24 HD2733 HD2687 Yr15 F1 HD2733 F1 HD2733 F1 HD2733 BC1 HD2733 BC1 HD2733 BC1 HD2733 BC2 HD2733 BC2 HD2733 BC2 HD2733 BC3 BC2F2 BC2F1 BC3 BC2F2 BC2F1 BC3 BC2F2 NIL for Lr19 NIL for Lr24 Double cross F 1 NIL for Yr15

40 Off season, IARI (2012) BC 2 F 2 generation of each cross containing rust resistance genes Lr19, Lr 24 and Yr15 in the background of HD2733 was raised at wellington in off season. Foreground selection was conducted and gene positive plants (Both homozygous and heterozygous) were identified Foreground selection in BC2F2 for identifying plants homozygous for Lr19 P2 P P2 P1 P1 P P1: HD2733, P2: HD2687+Lr19 : Plants homozygous for Lr19

41 Foreground selection in BC2F2 for identifying plants GENE +VE for Lr24 P3 P P1: HD2733, P3: HD2687+Lr24 Foreground selection in BC2F2 for identifying plants homozygous for Yr-15 P4 P P2 P2 P1 P1 P1: HD2733, P4: HD2687+Yr15 : Plants homozygous for Yr15

42 Background selection for recurrent parent HD2733 in BC 2 F 2 homozygous plants P1 P P1 P P1 P P1: HD2733 P2: HD2687+ Lr19 P3: HD2687+Lr24 P4: HD2687+Yr15 Homozygous

43 Percent genome recovery of HD2733 Maximum genetic background of 94.82% was recovered in BC 2 F 2 of HD2733/ HD2687+Lr19/2/HD2733 Maximum genetic background of 95.12% was recovered in BC 2 F 2 of HD2733/HD2687+Lr24/2/HD2733 Maximum genetic background of 96.25% was recovered in BC 2 F 2 of HD2733/HD2687+Yr15/2/HD2733 Reconstitution of HD 2733 with drought and heat tolerance + Rust resistance Evaluation of BC2F3 at all four locations for drought and heat Intercross NILs: HD 2733 lines(dht) X HD2733 (RR) Selection in F2-F4

44 Our Team This was a presentation on behalf of our Wheat Networks on abiotic stress tolerance and rust resistance breeding GP Singh, Neelu Jain, Vinod, JB Sharma, T Ramya, SC Mishra, PC Mishra, NK Singh, TR Sharma, Praveen Chhuneja, VS Sohu, GS Mavi, Biswajit Mondal, Neha Rai, Shweta Umar, Dnyaneshwar Kadam, Jyothi Jha, Anupam Singh, C Pandey, Niharika, KV Prabhu*

45 GCP and DBT Thank you