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Division seminar august 1,2012 prashant vikram


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Division seminar august 1,2012 prashant vikram

  1. 1. Major and consistent drought grain yield QTLs for marker assisted breeding in rice Prashant Vikram Visiting Research Fellow PBGB Division, IRRI, Los Baños, Laguna
  2. 2. Outline Introduction qDTY1.1 : A QTL effective in multiple genetic backgrounds  Phenotyping & Genotyping strategies qDTY1.1 : QTL effects qDTY1.1 : Elimination of linkage drag qDTY1.1 : Allelic analysis qDTY1.1 :Candidate gene analysis qDTY3.2 : A loci with interaction effects qDTY12.1 : QTL stability across ecosystems and environments qDTY8.1 : Mapping QTLs with basmati variety Marker Assisted QTL Pyramiding (MAQP) for grain yield under drought stress Conclusions
  3. 3. Global Water Resource & Rice• Estimated water resource: 43750 km3/year• 70% of fresh water resource is consumed in Agriculture• Water resource per inhabitant is least in Asia where 90% world’s rice is grown• Rice is a semi-aquatic plant and 1Kg rice consumes 3000-5000 Kg water• 20% of global calorie intake; 35-60% calories source in Asia alone Water resource Rice Calorie intake
  4. 4. Rice Cultivation and Water regimes Rice Irrigated Rainfed (55%) Rainfed Rainfed upland lowland (9%) (34%) Bouman, 2007Sub-Saharan Africa: ~80% rice area is rainfedSouth Asia: 50% harvested rice area is rainfed (Dawe, 2010) Drought tolerant rice is a felt need Rice field affected by drought in India; June, 2010 (Source, Channel Asia, Times of India)
  5. 5. Drought breeding approaches : Conventional & MolecularDrought is a complex trait & improvement of drought tolerancethrough indirect selection of secondary traits did not yield satisfactoryresultsDirect selection for grain yield under drought is a well proven Indiacriterion and several varieties have been released using this approach inlast 3 years:  Sahbhagi dhan (India);  Sukha dhan-1, Sukha dhan-2 & Sukha dhan-3 (Nepal);  BRRI Dhan-56 (Bangladesh); Bangladesh  Sahod ulan-3, 5, 6, 8 & Katihan-8 (Philippines)Fast track improvement for drought tolerance : MABMarker products in pipeline (Swamy and Kumar, 2011) Nepal MAB: Enhancing efficiency of drought breeding (for grain yield under drought) Philippines
  6. 6. MAB: Drought QTLs identified in rice1. Literature Search: 2. Pub Med Search: Drought: 7072 Drought + rice: 525 Drought +rice +QTLs: 48 Drought +rice +grain yield+ QTLs: 16 8 papers related to GY under drought 3. Gramene Search: Drought + QTLs : 77 Drought + QTLs + rice: 42 Drought +rice + QTLs + grain yield: 0 Vikram et al. 2012 QTLs identified in past: Mostly secondary traits Specific to genetic backgrounds & Seldom used for MAS Consistent drought grain yield QTLs worthy for MAS
  7. 7. Are drought grain yield QTLs real ? qDTY3.2 qDTY6.1 (Vikram et al. 2011) (Venuprasad et al. 2012) qDTY12.1 (Bernier et al. 2007)qDTY1.1 qDTY3.1 (Venuprasad et al.(Vikram et al. 2011) 2009) Drought grain yield QTLs are real ! Several genomic regions harbour consistent QTLs: Across backgrounds Consistent drought grain yield QTLs : Potential candidates for MAB
  8. 8. qDTY1.1: A QTL effective in multiple genetic backgrounds QTL Mapping Strategy Populations: common donor & multiple recipient parents Phenotyping: GY under reproductive stage drought stress Genotyping: WPG & BSA
  9. 9. Development of mapping populationsN22 × IR64 Target varieties F1 F2N22 × SwarnaN22 × MTU1010 Selected single seed of each F2 plantF3:4 plants were phenotyped for grain yield under lowland reproductive stage drought stress. Single F3 plants were grown and harvested individually. Target varieties F1 F2Dhagaddeshi × IR64Dhagaddeshi × Swarna Selected single seed of each F2 plantF3:4 lines of Dhagaddeshi derived populations were Single F3 plants were grown grown for seed increase. and harvested individually. F3:5 & F3:6 lines phenotyped & genotyped for grain yield under drought stress. Populations with common donor and multiple recipients
  10. 10. Phenotyping: Larger populations required 1. Distribution of genotypes for grain yield under stress in N22 x IR64 population 2. Distribution of genotypes for grain yield under stress in N22 x Swarna population3. Distribution of genotypes for grain yield under stress in N22 x MTU1010 population Populations were large enough to show normal distribution
  11. 11. QTL identification for grain yield under drought: Population size 300-350 population size is good enough for identification of drought grain yield QTLs Vikram et al. 2012 (FCR)
  12. 12. Phenotyping: Screening for grain yield under drought Drought stress experiment • All mapping populations planted in two replications 5m single row plot in two consecutive Dry seasons • Water stress was given 50 days after sowing • Grain Yield and yield related trait data were recorded • Days to 50% flowering • Plant height • Biomass • Grain yield • HI Non Stress/ Irrigated experiment •Same trial was repeated under non stress condition •Under non stress a 5cm water maintained till maturity Lines must be under stress at least 2 weeks before flowering
  13. 13. Phenotyping: Characterization for grain yield under drought Stress Depleting water level under drought stress Water table goes below 80 KPa Mild stress: ≤ 30% yield reduction Moderate stress: 31-65 % yield reduction Rainfall relative to meat trial flowering Severe stress: 65-85 % yield reduction DS2010 RAINFALL mm DS2011 RAINFALL mm Rainless days during flowering Water table Rainfall March 1-10 March 21-31 March 11-20 January 1-10 January 21-31 January 11-20 February 1-10 February 21-28 February 11-20 Flowering DS2010 DS2011 FLOWERING RANGE
  14. 14. Genotyping: Whole population genotyping Vs BSA BSA Powerful and cost effective approach Applicable to multiple populations simultaneously Useful in identifying major and consistent QTLs
  15. 15. Bulk Segregant Strategy for high grain yield under drought Vikram et al. 2012 (FCR)
  16. 16. BSA: genotype multiple populations simultaneously BSA RM212 Identify few markers BSA with adjoining markers RM431 of the identified one. Validation of BSA results RM315 BSA can be validated through genotyping of phenotypic tails withDHAGADDESHI DHAGADDESHI BULK HIGH BULK HIGH BULK LOW BULK LOW BULK HIGH BSA markers (Kanagaraj et al. 2010) SWARNA BULK LOW SWARNA SWARNA N22 RM11943 RM431 RM231
  17. 17. BSA: QTL EffectsSelective genotyping lead to an upward estimation of QTL effectsBSA doesn’t lead to an upward estimation of QTL effects Vikram et al. 2012 (FCR)
  18. 18. Drought grain yield QTLs in N22 populations N22 * N22 N22 * qDTY2.3 qDTY1.1 N22 x IR64N22 x Swarna qDTY3.2N22 x IR64N22 x MTU1010 N22 x Swarna
  19. 19. QTL qDTY1.1 on tail end of chromosome 1 qDTY1.1 located at the distal end of chromosome 1 RM212 RM3825 RM315 RM11943 RM431 RM12023 RM12091 RM12146 RM12233
  20. 20. qDTY1.1 effect in different populationsN22/ MTU1010 N22/ IR64 N22/ Swarna Dhagaddeshi/ Swarna Dhagaddeshi/ IR64 RM12233 RM12233 RM12233 RM12146 RM315 RM315 RM212 RM104 RM431 RM315 Population Additive effect Phenotypic variance N22 × Swarna 29.30% 13.40% N22 × IR64 24.30% 16.90% N22 × MTU1010 16.10% 12.60% Dhagaddeshi × Swarna 24.90% 32.00% Dhagaddeshi × IR64 8.30% 9.30% Vikram et al. 2011 (BMC Genetics); Ghimire et al. 2012 (FCR)
  21. 21. QTL identification: Contrasting parents Vs Target varietyqDTY3.2 effect undermoderate stress only Vikram et al. 2011 (BMC Genetics)qDTY2.3 effect undersevere stress onlyDays to floweringloci from MTU1010 •QTL effect depends on contrast of the parents Additive effect •Large effect QTL in one background may not work in other Swarna > IR64 > MTU1010 •Target variety should be used in QTL identification and MAB Drought tolerance
  22. 22. Co-variate analysis for DTF and Plant height Co-variate adjustment of DTF and plant height qDTY1.1: Significant for grain yield under drought after the co-variate adjustment Single-marker analysis after covariance adjustment for DTF under drought stress Mean grain yield of N22 Mean grain yield of IR64, Swarna, Population Marker p-value homozygote (kg/ha) MTU1010 homozygote (kg/ha) RM431 1273 761 <0.001 N22/IR64 RM11943 1239 878 <0.001 RM431 1517 926 <0.01 N22/Swarna RM11943 1484 927 <0.01 RM431 1543 1149 <0.01 N22/MTU1010 RM11943 1531 1199 <0.01 Single-marker interval analysis after covariance adjustment for PH under drought stress Mean grain yield of N22 Mean grain yield of IR64/, Population p-value homozygote Swarna/, MTU1010 homozygote N22/Swarna 1448 1267 <0.01 N22/IR64 1330 1073 <0.01 N22/MTU1010 1470 1381 NS Vikram et al. 2011 (BMC Genetics)
  23. 23. Elimination of linkage drag: N22/SwarnaN22 × Swarna FG X FG 217 dwarf 2 Plants segregating for BC3F1 Selected 21 F1s ~3000 BC3F2 qDTY1.1 plants X FG X Ratooned and Screened under ROS in WS2011 Full & partial QTL ~180 BC3F3 split planted lines Selected recombinants X Single plant selected and Screened in DS2012 Full QTL lines genotyped for foreground Plants selected for Swarna plant type and grain type Background genotyping Six introgressed Markers run on regions identified N22/Swarna RIL population Plants with clear background Phenotypically and genotypically No effect on GY under RS Being screened at IRRI Being screened at Hazaribagh, under ROS India under ROS Dwarf qDTY1.1 lines in Swarna background
  24. 24. Background genotyping of dwarf qDTY1.1 lines (~ 90% background clear; gaps need to be filled)
  25. 25. 115 Days after sowing STRESS Swarna BIL NON STRESS Swarna BIL April, 16,2012 Dwarf qDTY1.1 lines in Swarna backgroundNon stress: they had similar flowering time as Swarna
  26. 26. Elimination of linkage drag: N22/IR64 & N22/MTU1010 N22/IR64 & N22/MTU1010 RILs •segregating for qDTY1.1 , F5, F6 and •<130 cm under non stress, F7 planted •Better yield under drought stress All these plants are grown under rainfed situation 800 semi-dwarf (~400 from both population) plants tagged and genotyped. RILs with qDTY1.1 and height comparable to IR64/ MTU1010 identified
  27. 27. qDTY1.1: Allelic study•qDTY1.1 tolerant allele contributed by traditional donors: (1) N22 (2) Apo (3)Dhagaddeshi RM431 in random varieties qDTY1.1 was significant in more than 50% of drought QTL panel lines (Swamy et al. 2011) RM431 in random varieties 0.06 N22 landraces Dhagaddeshi N22 & Dhagaddeshi are Samba Mahsuri closer phylogenetically Sw arna Apo Variety MTU1010 IR 64 Basmat i 334
  28. 28. Closeness of N22 & Dhagaddeshi 67 %Marker loci where drought-tolerant varieties Dhagaddeshi and N22 have similar alleles, different from the alleles in susceptible varieties Swarna and IR64
  29. 29. Basmati370NuadhusanuNuakalajeeraNaveenVasumatiDehulaSelumpikitIR55419Suskhasamrat Drought tolerantIR74371SadabaharApo genotypes in oneSambamahsuriBhoj clusterBhuvanAshokaSwarnaMahamayaLalitagiriSatabdiVanprabhaDularJayaSaitaLalatKshitijKakroSaket4IR36KalingaIIIRatnaSahabhagiRajniPadminiDandiMehardhalaheera Drought QTL allelesHeeraUdayagiri Conserved in landracessattariMahsuriGanteswariSamantakhandagiriLalnakanda41SukhawanRajeshwariIR64IR83614Basmati334AbhishekShravaniChicken SoniSafri17TharaIR76569BrowngoraDurgabhogBirsagoraSathiKalakeri Drought tolerantVandanaIR70844 cultivarsRaskadamLalsarN22AnjaliVirendraAnnadaASD17
  30. 30. Candidate gene analysis for qDTY1.1SNPs among N22, IR64 and Swarna, qDTY1.1 region were compared.Based on available reports differentially expressed genes in qDTY1.1region between N22 and IR64 were annotated.
  31. 31. SNPs in qDTY1.1 region: a region specific to N22 N22 Swarna IR64 1 TBGI065107 40298480 C T T 1 TBGI065108 40298598 T C C 1 TBGI065127 40329203 A G G 1 TBGI065129 40329319 C T T 1 TBGI065130 40329422 G A A 1 TBGI065133 40330056 G T T 1 TBGI065139 40332364 T G G A 90 Kb block specific to N22 1 TBGI065142 40332797 G A A in qDTY1.1 region 1 TBGI065146 40333650 A C C 1 TBGI065154 40334497 C T T 1 TBGI065155 40334597 C T T 1 TBGI065156 40334719 T C C 1 TBGI065158 40334855 G T T 1 TBGI065161 40335346 T C C 1 TBGI065169 40373741 G C C SNP ID Position
  32. 32. Differentially expressed genes between N22 & IR64 in qDTY1.1 : Candidate genes RM212 1. LOC_Os01g65690 2. LOC_Os01g65780 3. LOC_Os01g66010 RM315 4. LOC_Os01g66290 RM11943 5. LOC_Os01g66860(4,5-DOPA dioxygenase extradiol, RM431 glycosyl transferase, amino acid transporters, RM104 MADS-box family gene, RM529 serine/threonine protein kinase) RM2182 RM2227 (Lenka et al. 2011) RM2289 Vikram et al. 2011 (BMC Genetics)
  33. 33. qDTY1.1 peak marker RM431: A marker from Gene containing zing finger RM431 Peak marker in most studies Meta-QTL analysis
  34. 34. qDTY3.2 : A loci with interaction effectsqDTY3.2: First identified in N22 x Swarna population for grain yield under drought(Vikram et al. 2012-BMC Genetics)Located on the proximal end (top) of the chromosome 3This QTL showed significant interaction with qDTY1.1 in N22 × Swarna as well as N22× IR64 populationsqDTY3.2 : interaction with qDTY12.1 (Dixit et al. 2012- Mol. breed)qDTY3.2 : Significant effect for GY under drought in IR77298-5-6-18/Sabitri population. Additive interaction of qDTY1.1 & qDTY3.2 : advantage for MAB
  35. 35. qDTY3.2 – qDTY1.1 interaction qDTY3.2 qDTY3.2 qDTY1.1 qDTY1.1N22/IR64 RIL population N22/Swarna RIL population
  36. 36. qDTY12.1: QTL stability across ecosystems and environmentsIR74371-46-1-1/ Sabitri BIL populationSabitri is popular variety of Nepal  Screened under lowland drought stress at IRRI and Nepal  Genotyped through BSAqDTY12.1 was found consistent at both locations
  37. 37. Phenotyping at IRRI Duration WATER TABLE DATA OF DS2011 DS2011, IRRIWater table (cm)Rainfall (mm) RAINFALL DATA OF DS2011flowering (days) Days to 50% FLOWERING RANGE
  38. 38. Phenotyping at Nepal Duration WATER TABLE DATA OF DS2011 WS2011, NepalWater table (cm) RAINFALL DATA OF DS2011Rainfall (mm)flowering (days)Days to 50% FLOWERING RANGE
  39. 39. qDTY12.1: QTL across ecosystems, environments & backgrounds Peak marker : RM28166 Additive effect: 47.7% Phenotypic variance: 24.6% qDTY12.1 (18.15Mb) (15.41Mb) RM28199 RM28089 •Ecosystem: lowland and upland drought stress •Environments: IRRI and Nepal •Backgrounds –Vandana and Sabitri Mishra et al. Unpublished
  40. 40. qDTY12.1: Interaction effect analysis V/W•qDTY12.1 showed significant interaction with two other loci W Yield advantage qDTY12.1 Under drought(qDTY2.3 and qDTY3.2) Dixit et al. 2012 (Mol. Breed)•No interaction was observed in lowland drought stress in +IR74371-46-1-1/ Sabitri population V V/W Enhanced qDTY2.3 yield advantagePopulation qDTY12.1 qDTY2.3 qDTY3.2 qDTY3.2 Under drought Interaction Ecosystem QTL (29-41%) V-W W V V √ Upland I-S I I/S I/S × Lowland IR74371-46-1-1 (I) is derivative of Wayrarem (W)•Under upland qDTY12.1 W allele interacts with qDTY2.3 & I/S I Yield advantageqDTY3.2 allele of Vandana (V) qDTY12.1 Under drought•Under lowland I/W allele of qDTY12.1 is effective alone +•Vandana is drought tolerant upland adapted variety S I/S No additional•Sabitri is drought susceptible lowland adapted variety qDTY2.3 yield advantage qDTY3.2 Under drought qDTY12.1 effect vary with backgrounds and ecosystems Use of target variety in QTL study
  41. 41. qDTY8.1: Mapping QTLs with basmati variety Basmati334:traditional Basmati cultivar of Punjab (India and Pakistan)• F3:5 Basmati334/ Swarna population was screened for yield under drought stress in Dry Season 2010.• qDTY8.1 was identified as significant loci for yield under drought through BSA. Additive effect -160.53 Population mean 621.12 AE (%) -25.84 % Marker interval RM210-RM447
  42. 42. Marker Assisted QTL Pyramiding (MAQP) for grain yield under drought stress N22/ Swarna Swarna Apo/ Swarna Basmati334/ Swarna IR74371-46-1-1/ Sabitri Sabitri IR77298-5-6-18/ Sabitri
  43. 43. Marker assisted Pyramiding: MABC followed by intercrossing F2 F3 F4 Vikram et al. 2012
  44. 44. Marker assisted Pyramiding in Swarna background Basmati334-Swarna F4 X Apo-Swarna BC3F1 WS 2008 qDTY8.1 qDTY3.1 F1 X N22 x Swarna F4 WS 2009 qDTY1.1qDTY1.1 + qDTY3.1 +qDTY8.1 F1 DS 2010 F1 plants with 3 QTLs X Swarna WS 2010 F1 plants individual QTLs X Swarna F1s with qDTY3.1 X F1s with qDTY1.1+qDTY8.1 DS 2011 Four F1 plants selected with qDTY1.1+qDTY3.1+qDTY8.1 WS 2011 X Four F2 families with qDTY1.1+qDTY3.1+qDTY8.1 planted DS 2012 T RE QT L S RE H E L INE ADY FOR PH NOT IC SCRE NING E YP E
  45. 45. Marker assisted Pyramiding in Sabitri background IR74371-46-1-1/Sabitri X IR77298-5-6-18/Sabitri WS 2011BC1F5 BC1F5 qDTY12.1 qDTY3.2 F1 F2 qDTY12.1 + qDTY3.2 DS 2012 1000F2 Genotyping of F2 contd….
  46. 46. CONCLUSIONS……• A large effect QTL on chromosome 1 was identified in multiple populations simultaneously through WPG/BSA.• Bulked segregant Analysis is a powerful and cost-effective strategy in identifying drought grain yield QTLs• QTL effects depend on ecosystems, environments and backgrounds. Target varieties should be used in QTL studies.• DTY-QTLs showed interactions with other regions. Additive interactions are useful for MAB.• qDTY1.1 linked with plant height. Linkage broken for product development.• qDTY1.1 positive alleles are likely to be conserved in landraces• qDTY1.1 harbors candidate genes –AA transporters, PK & ZFP.• qDTY12.1 was consistent across-ecosystems, environments & backgrounds.• Marker Assisted QTL Pyramiding (MAQP) is a preferred strategy for improving rice varieties for rainfed environments.
  47. 47. Acknowledgements Funding Agencies Team Leader •Generation Challenge program (GCP) • Dr. Arvind Kumar •Bill and Melinda Gates Foundation (STRASA) PDF /VRF Collaborating IRRI scientists • Dr. BPM Swamy • Dr. Amelia Henry • Dr. Ajay Kohli • Dr. Shalabh Dixit Collaborators (NARS)Assistant Scientists • Dr. N. K. Singh, NRCPB, IARI, India• Jennylyn Trinidad • Dr.N.P.Mandal, Hazaribagh, India• Paul C. Maturan • Dr.P.Swain, CRRI, Cuttack, India• MT Sta. Cruz • Dr.O.N.Singh, CRRI, Cuttack, IndiaResearchers • Krishna Kumar Mishra, Nepal• Ruth E Carpio • Ram Baran Yadaw, Nepal• Guevarra JocelynTechnicians• Teody, Loui, Orly