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Developing crops with high productivity at high temperature

  1. Developing crops with high productivity at high temperature: A blue sky research initiative BSR Team 29 Nov 2013
  2. Maximum temperature in the SAT Critical Temperature threshold 0 5 10 15 20 25 30 35 40 45 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec MaximumT°C 1983-HQ 1992-HQ 2001-HQ 2012-HQ 1983-ISC 1990-ISC 1998-ISC Headquarter Sahelian Center T°C rarely crosses critical limits
  3. 0 1 2 3 4 5 6 7 8 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec MaximumVPD Sahelian Center Headquarter Vapor pressure deficit (VPD) in the SAT (VPD reflects T°C and Rel. Humidity %) Prevalent high VPD Effect on plant water balance VPD threshold
  4. The basics – Why aquaporins (AQP) ? Transpiration response to VPD Transpiration response to AQP inhibition AQP gene expression AQP in the bigger picture - Drought
  5. Modified from Murata et al., 2000. What are aquaporins?? Membrane transporter for water Passive transport
  6. Terminal drought sensitive Terminal drought tolerant 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.50 1.00 1.50 2.00 2.50 3.00 3.50 VPD (kPa) H77/2 833-2 PRLT-2/89-33 Transpiration(gcm-2h-1) Kholova et al 2010 – J. Exp. Bot Transpiration restriction at high VPD How the story began – Water savings in millet Water saving
  7. Why such a rapid transpiration response?? Rapid response hydraulic signal VPD (kPa)
  8. Where is the source of hydraulic limitation?? ??? We hypothesized roots could be the source of hydraulic limitation
  9. Is the hydraulic restriction in the roots only ??
  10. 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 09:20 09:40 10:00 10:20 10:40 11:00 11:20 11:40 12:00 12:20 12:40 13:00 13:20 Normalizedtranspiration VPD change Low VPD High VPD No difference in slope No hydraulic limitation in the leaves
  11. Apoplastic Pathway (Structural) Symplastic Pathway (AQP) Water pathways in the root cylinder Two pathways have different hydraulic conductance Hypothesis: Aquaporin control plant water loss ? ????
  12. The basics – Why aquaporins ? Transpiration response to VPD Transpiration response to AQP inhibition AQP gene expression AQP in the bigger picture - Drought
  13. Terminal drought sensitive Terminal drought tolerant 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.50 1.00 1.50 2.00 2.50 3.00 3.50 VPD (kPa) H77/2 833-2 PRLT-2/89-33 Transpiration(gcm-2h-1) Kholova et al 2010 – J. Exp. Bot One QTL mapped for low Tr at high VPD Transpiration response to VPD in pearl millet: Growth chamber M322 M394 M214 M321 M592 M443 M356 M738 40cM
  14. 0 0.005 0.01 0.015 0.02 0.025 0.03 1 2 3 4 5 6 7 8Transpiration (gcm-2h-1) VPD (kPa) VPD insensitive VPD sensitive 0 2 4 6 8 10 12 14 16 Xpsmp2237 Xpsmp2072 M13_Xpsmp2066 M13_Xpsmp3056 Xpsmp2206 Xpsmp2059 NoofRecombinants markers within LG2 DT-QTL low Transpiration Rate in high VPD A - from H77 B - from PRLT H - heterozygous Two QTL fine-mapped for low Tr at high VPD
  15. Staygreen ILs (Stg3 – Stg B) are VPD-sensitive 0.0000 0.0020 0.0040 0.0060 0.0080 0.0100 0.0120 9 11 13 15 17 Transpiration(gcm-2h-1) Time of the day (h) stg1 stg3 stg4 stgB R16 B35 Recurrent R16 Stg3 StgB Transpiration response to VPD in Sorghum 1 - Introgression lines
  16. 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.62 1.05 1.58 2.01 2.43 3.05 3.45 Transpiration(gh-1cm-2) VPD (kPa) Transpiration response to VPD in Sorghum 2 - Germplasm Germplasm differences in VPD-sensitivity VPD-Sensitive VPD- Insensitive
  17. BP= 2.58 R2 =0.68BP= 2.51 R2 =0.76 R2 =0.89 R2 =0.83 Transpiration response to VPD in Chickpea
  18. Transpiration response to VPD in Peanut
  19. Mouride IfVPD<2.09,TR=0.0083(VPD)–0.002 IfVPD≥ 2.09,TR=0.0013(VPD)+0.015 R²=0.97 B UC-CB46 TR=0.0119(VPD)-0.0016 R²=0.97 D Transpiration response to VPD in cowpea Tolerant lines are VPD-sensitive (water saving) Tolerant Sensitive Belko et al – 2012 (Plant Biology)
  20. VPD Transpiration(gcm-2h-1) 0.0 2.0 4.0 0.0 1.0 Main types of Tr response to VPD Water Saving Large pattern variation within/across species VPD-sensitivity often link to drought adaptation
  21. Large variation in all species Often discriminate tolerant from sensitive lines Now, systematic screening Exciting results in other crops (rice, maize) In summary…
  22. The basics – Why aquaporins ? Transpiration response to VPD Transpiration response to AQP inhibition AQP gene expression AQP in the bigger picture - Drought
  23. Apoplastic pathway Symplastic Pathway (AQP) Sorting out the proportion of apoplastic and symplastic water transport 1 mM K4[Fe(CN)6] for 3 h Then 1 mM CuSO4.
  24. Apoplastic pathway inhibition
  25. Apoplastic pathway Symplastic Pathway (AQP) Symplastic pathway inhibition AQP inhibitors: AgNO3 – HgCl2 – H2O2
  26. Follow-up of transpiration before/after inhibition
  27. 0.6 0.7 0.8 0.9 1 1.1 1.2 NormalizedTranspiration Time of the day VPD-sensitive VPD - insensitive Less symplastic inhibition in VPD-sensitive Pearl millet: Symplastic inhibition Treatment M322 M394 M214 M321 M592 M443 M356 M738 40cM
  28. 0.6 0.7 0.8 0.9 1 1.1 1.2 10 30 50 70 90 110 130 150 170 190 210 230 250 270 Normalizedtranspiration Time (minutes) ICMR1029 1mM ICMR2042 1mM H77 1mM PRLT 1mM Symplastic inhibition in near-isogenic lines (QTL from VPD-sensitive parent) NILs behave like QTL donor parent M322 M394 M214 M321 M592 M443 M356 M738 40cM Treatment VPD-sensitive
  29. More apoplastic inhibition in VPD-sensitive 0.00 0.20 0.40 0.60 0.80 1.00 1.20 10:10 10:40 11:10 11:40 12:10 12:40 01:10 01:40 02:10 02:40 03:10 NormalizedTranspiration Time Apoplastic inhibition Pearl millet: Apoplastic Inhibition VPD-sensitive VPD - insensitive M322 M394 M214 M321 M592 M443 M356 M738 40cM
  30. 0 0.2 0.4 0.6 0.8 1 1.2 Normalizedtranspiration Time Apoplast & symplast inhibition at low VPD Apoplastic & Symplastic inhibition Symplastic inhibition Apoplastic inhibition Apoplastic transport predominant Low VPD small differences/effects
  31. 0 0.2 0.4 0.6 0.8 1 1.2 Normalizedtranspiration Time(mins) Apoplast & symplast inhibition at high VPD Symplastic inhibition Apoplastic inhibition Apoplastic transport less predominant High VPD larger differences/effects
  32. Root hydraulic conductance measurement
  33. 0.002 0.0025 0.003 0.0035 0.004 0.0045 0.005 0.0055 0.006 VPD-Sensitive VPD-Insensitive Rootconductivity Root hydraulic conductivity Symplastic transport less predominant In VPD-sensitive Apoplast Symplast (AQP) Control
  34. Apoplast Symplast (AQP) 0.002 0.003 0.004 0.005 0.006 0.007 VPD-Sensitive VPD-Insensitive Rootconductivity Root hydraulic conductivity Apoplastic transport more predominant In VPD-sensitive Control
  35. 0 0.2 0.4 0.6 0.8 1 1.2 10 30 50 70 90 110 130 150 170 190 210 230 250 270 290 310 330 350 370 390 410 NTR Time (mn) Control 100 uM HgCl2 200 uM HgCl2 Before treatment ICC 14799 0 0.2 0.4 0.6 0.8 1 1.2 10 30 50 70 90 110 130 150 170 190 210 230 250 270 290 310 330 350 370 390 410 NTR Time (mn) Control 100 uM HgCl2 200 uM HgCl2 Before treatment ICC 4958 Chickpea: Symplastic Inhibition Less symplastic inhibition in VPD-sensitive VPD - sensitive VPD - insensitive
  36. Apoplastic inhibition of chickpea genotypes 0.00 0.20 0.40 0.60 0.80 1.00 1.20 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 Time (mins) NTR(NormalisedTranspirationRatio) ICC 4958 Control ICC 4958 T reatment ICC 8058 Control ICC 8058 T reatment ICC 867 Control ICC 867 T reatment ICC 14799 Control ICC 14799 T reatment 1mM K4[Fe(CN)6] 0.5mM CuSO4 VPD-sensitive VPD - insensitive Chickpea: Apoplastic Inhibition Less apoplastic inhibition in VPD-sensitive
  37. Apoplast Symplast (AQP) Apoplast Symplast (AQP) More water via apoplast in VPD-sensitive Limited water via symplast in VPD-sensitive Insensitive Sensitive
  38. VPD sensitive have apoplastic water transport They have limited “tuning” via the symplast More effort to be put on hydraulic measurement Many more materials to test In summary…
  39. The basics – Why aquaporins ? Transpiration response to VPD Transpiration response to AQP inhibition AQP gene expression AQP in the bigger picture - Drought
  40. VPD-insensitive VPD-sensitive Any difference in aquaporin expression In sorghum contrasting for VPD response?? 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.62 1.05 1.58 2.01 2.43 3.05 3.45 Transpiration(gpl-1cm-2) VPD (kPa)
  41. • 14 PIPs in the Sorghum genome (4 PIP1, 10 PIP2) • Comparable to maize and rice • RTqPCR primers designed • Putative reference genes AQP gene expression in sorghum • 3 conditions (low VPD am, low VPD pm / High VPD pm) • RNA then cDNA, ref genes • TRqPCR From Hanna Anderberg
  42. 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.62 1.05 1.58 2.01 2.43 3.05 3.45 Transpiration (gpl-1cm-2) VPD (kPa) Morning (low VPD) VPD-insensitive VPD-sensitive
  43. 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.62 1.05 1.58 2.01 2.43 3.05 3.45 Transpiration (gpl-1cm-2) VPD (kPa) VPD-insensitive VPD-sensitive Afternoon (low VPD)
  44. 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 0.018 0.62 1.05 1.58 2.01 2.43 3.05 3.45 Transpiration (gpl-1cm-2) VPD (kPa) Afternoon (high VPD) VPD-insensitive VPD-sensitive
  45. 0 2 4 6 8 10 12 14 16 18 Low TE High TE HighVPD/LowVPD PIP1;1 PIP1;2 PIP1;3 PIP1;4 PIP2;1 PIP2;2 PIP2;4 PIP2;5 PIP2;6 PIP2;7 PIP2;8 PIP2;9 PIP2;10 PIP relative expression (High VPD/Low VPD) VPD – insensitive line increases expression of PIP2 PIP2;6 PIP2;9 PIP2;7 VPD-Insensitive VPD-Sensitive
  46. Phylogenetic relationships of AQPs across cereals
  47. Tentative annotation based on rice Tentative annotation based on sorghum Tentative annotation based on maize PIP1;1 Pip1;3/4 pip1.1 PIP1;2 Pip1;3/4 Pip1;3/4 PIP1;3 pip1.5 pip1.5 PIP1;4 pip1.6 pip1.6 PIP2;10 pip2.7 pip2.7 PIP2;10 pip2.2 pip2.1 PIP2;2 hypothetical protein PIP2;2 PIP2;3 pip PIP2;4 pip2.3 pip2.4 PIP2;5 pip2.5 pip2.5 PIP2;6 pip2.6 pip2.5 PIP2;7 pip 95%PIP2;1 PIP2;8 pip2.6 pip2.6 PIP2;9 pip2.6 pip2.3 Tentative annotation in rice, sorghum, maize
  48. VPD insensitive High VPDLow VPD VPD sensitive VPD insensitive VPD sensitive 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 VPD-sensitive_LVPD VPD-insensitive_LVPD VPD-sensitive_HVPD VPD_insensitive_Hvpd bandintensity More AQP protein in VPD–insensitive line AQP protein measurement with maize PIP2;6 antibodies
  49. Total RNA Ist Strand cDNA Degenerate primer designing using other closely related species as a source M -Ve 1 2 3 4 5 6 7 8 9 PCR amplifications of Aqp genes from cDNA. Cloning of PgAqp genes into pCR8/GW/TOPO vectorPlasmid DNA isolated for positive Aqp clones Sequencing and analysis Cloning of Aquaporin genes in pearl millet (homology based cloning strategy) .
  50. Phylogentic relationships between pearl millet, maize and rice Aquaporin proteins
  51. 0.25 0.5 1 2 4 8 16 L R L R L R L R 1122 1086 1152 1078 PIP1.1 PIP1.2 PIP2.1 PIP2.3 PIP2.6 TIP1.1 TIP2.2 Relativeexpression Genotype and Stress conditions VPD - Insensitive VPD - Sensitive PIP relative expression (Low VPD) High AQP expression in VPD-insensitive line
  52. 0.25 0.5 1 2 4 8 16 L R L R L R L R 1122 1086 1152 1078 PIP1.1 PIP1.2 PIP2.1 PIP2.3 PIP2.6 TIP1.1 TIP2.2 Genotype and Stress conditions PIP relative expression (High VPD/Low VPD) Relativeexpression VPD - Insensitive VPD - Sensitive Even Higher AQP expression in VPD-insensitive line under high VPD
  53. Increase in AQP expression in VPD-insensitive under high VPD Transcript abundance & protein agree Up regulation in both leaves and roots On-going work in other species Comparative genomics In Summary…
  54. The basics – Why aquaporins ? Transpiration response to VPD Transpiration response to AQP inhibition AQP gene expression AQP in the bigger picture - Drought
  55. 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.62 1.05 1.58 2.01 2.43 3.05 3.45 Transpiration(gpl-1cm-2) VPD (kPa) Why are VPD-sensitive sorghum so interesting? VPD-insensitive VPD-sensitive
  56. VPD-sensitive have high transpiration efficiency 2.0 3.0 4.0 5.0 6.0 7.0 152 Germplasm tested TE 10 lowest TE are VPD-Insensitive 10 highest TE are VPD-sensitive High TE lines limit transpiration at high VPD
  57. 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 TE 0 0.005 0.01 0.015 0.02 0.025 0.03 1 2 3 4 5 6 7 8 Transpiration (gcm-2h-1) VPD (kPa) Same result in sorghum and pearl millet What about pearl millet? Low TE (VPD-Insensitive) High TE (VPD-Sensitive)
  58. grain yield gain (low TR) -300 -200 -100 0 100 200 300 400 0 500 1000 1500 2000 2500 3000 3500 original yield (kg/ha) yieldgain(kg/ha) 1 postflowering 2 flowering 3 postflowering-relieved 4 no stress 5 preflowering Original yield (kg ha-1) 0 Yield increase (kg/ha) with transpiration sensitivity to high VPD: Rabi sorghum Yieldincrease
  59. -1 0 +33 Crop modelling used to predict trait effects 15-30% yield increase at high latitudes % yield increase with transpiration sensitivity to high VPD: Peanut
  60. Lysimetric evaluation Transpiration in pots 0.000 0.004 0.008 0.012 0.016 0.020 0.62 1.05 1.58 2.01 2.43 3.05 3.45 Transpiration (gcm-2h-1) VPD Low TE High TE 0 1 2 3 4 5 6 7 Low TE High TE TE grain yield gain (low TR) -300 -200 -100 0 100 200 300 400 0 500 1000 1500 2000 2500 3000 3500 original yield (kg/ha) yieldgain(kg/ha) 1 postflowering 2 flowering 3 postflowering-relieved 4 no stress 5 preflowering Original yield (kg ha-1) 0 AQP gene expression Modeling of Tr restriction effect on yield
  61. The VPD response lead to higher TE It is itself related to differences in AQP gene expression Major yield increase possible across crops Breeding (donors identified) Harness genetics – Phenotyping (new platform) In Summary…
  62. Thank you Collaborators: F. Chaumont (Univ. Louvain) H. Anderberg (Lund Univ.)Donors: ICRISAT ACIAR DFID B&MGF Technicians / Data analyst: Srikanth Malayee Rekha Badham Students: M Tharanya S Sakthi T Rajini S Medina K Aparna Colleagues: J Kholova / P Suddhakar Reddy / G Barzana / JM Devi/ KK Sharma / T Shah / P Bhatnagar / Hima Bindhu / RK Varshney / R Srivastava / SP Deshpande
  63. Lysimetric evaluation Transpiration in pots 0.000 0.004 0.008 0.012 0.016 0.020 0.62 1.05 1.58 2.01 2.43 3.05 3.45 Transpiration (gcm-2h-1) VPD Low TE High TE 0 1 2 3 4 5 6 7 Low TE High TE TE grain yield gain (low TR) -300 -200 -100 0 100 200 300 400 0 500 1000 1500 2000 2500 3000 3500 original yield (kg/ha) yieldgain(kg/ha) 1 postflowering 2 flowering 3 postflowering-relieved 4 no stress 5 preflowering Original yield (kg ha-1) 0 AQP gene expression Modeling of Tr restriction effect on yield
  64. Xpsmp2237 Xpsmp2072 17.1 cM Xpsmp2066 12.0 cM Xpsmp3056 19.1 cM Xpsmp2206 14.2 cM Xpsmp2059 2.5 cM Grain Yld Flowering time Grain Yld Allele effect Xibmsp44 Xibmsp4 Xibmsp7 Xibmsp60 Xibmsp34 Xibmsp14 Xibmsp24 Xibmsp31 Xibmsp11 Xibmsp62 Xibmsp27 Xibmsp9 Xibmsp12 Xibmsp15 Xibmsp23 PRLT 2/89-33 H 77/833-2 Increased decreased decreased Increased Flowering time Increased decreased decreased Increased Stay green decreased Increased Increased decreased Tr rate Increased decreased Tr rate decreased Increased Stay green Candidate genes Zn finger CCCH-type, serine/threonine protein kinase, MADS-box, acetyl CoA carboxylase Stay green
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