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Phenotypic and genetic dissection of water stress adaptations in pearl millet (Pennisetum glaucum) using QTL co-localization approach
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Phenotypic and genetic dissection of water stress adaptations in pearl millet (Pennisetum glaucum) using QTL co-localization approach

  1. Feb 2017 Phenotypic and genetic dissection of water stress adaptations in pearl millet (Pennisetum glaucum) using QTL co-localization approach Murugesan Tharanya1 ,2 , Jana Kholova1 , Kaliamoorthy Sivasakthi1 ,2 , Deepmala Seghal3 , Charles Tom Hash4 , Basker Raj1 , Rekha Baddam1 , Thiyagarajan Thirunalasundari2 , Rattan Yadav3 , Vincent Vadez1 * 1 International Crops Research Institute for the Semi–Arid Tropics (ICRISAT), Crop Physiology Laboratory, Patancheru 502324, Telangana, India. 2 Bharathidasan University, Tiruchirappalli 620 024, Tamilnadu, India. 3 Institute of Biological, Environmental and Rural Sciences (IBERS), Aberystwyth University, AberystwythSY23 3EB, UK. 4 International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), ICRISAT Sahelian Center, Pearl Millet Breeding, BP 1204, Niamey, Niger. About ICRISAT: www.icrisat.org ICRISAT’s scientific information: http://EXPLOREit.icrisat.org Introduction Crop yield is a consequence of several plant biological functions and its interactions with environment. Here we focus on some of basic plant functions related to i) water-use ii) canopy development and iii) agronomic traits and investigate on the relationship of these traits for crop production in different water-stress scenarios using the QTL co-localization approach. Figure 1. APSIM generic template model developed by Graeme L. Hammer Figure 2. Different phenotypic environments: a) Pot culture, b) High throughput phenotyping platform (LeasyScan), c) Lysimeter and d) Field Figure 3. Range of variation obtained – Transpiration rate (Tr), 3dimensional leaf area (3DLA), transpiration (T) and grain yield (GY) from various phenotyping environments. Figure 5 Selective principal component analysis (PCA) done for a) Grain yield (GY) from field under well-watered (WW) conditions and traits (canopy development and water-use related) from LeasyScan under WW b) GY from field under WW and traits (water-use and biomass related) from pot culture under WW c) GY from field under severe stress (SS) and traits (water- use and yield related) from Lysimeter under SS d) early water extraction from Lysimeter (SS) and canopy development related traits from LeasyScan (SS). CS represents canopy structure; RDW represents root dry weight; T represents transpiration and DAS represents days after sowing. APSIM Generic Crop Template from Graeme L. Hammer Grain Yield Grain Number Grain Size D Biomass Radiation Transpiration Efficiency Transpiration Radiation use efficiency Radiation intercept (Rint) Vapour pressure deficit Leaf hydraulic conductance (kl) Leaf area indexSpecific leaf nitrogen Roots Extinction Coefficient (k) “building blocks” =CAUSE of GxE Yield = CONSEQUENCE Of Genotype x Environment (GxE) Fig. 1 Nitrogen content Leaf number Objectives i) Mapping of QTLs underlying traits related to i) water use ii) canopy development and iii) agronomy which have been assessed at various phenotyping systems. ii) Infer the associations between the investigated traits and its importance for crop production through QTL co-localization approach and principal component analysis (PCA). Materials and Methods A fine mapping population (FMP) population (162 lines) based on the cross between ICMR01004 x ICMR01029 segregating within LG02 for terminal water stress adaptation (Yadav et al., 2010). Genotypic data included of 17 polymorphic markers on LG02 (gene-based markers, RFLP, SNP, Seghal et al., 2012) Phenotyping was done at different levels of plant organization using four different environments • Pot culture (water-use related traits) • High throughput phenotyping platform: LeasyScan (canopy development related traits) • Lysimeter (water-use, agronomy-related traits) • Precision field (agronomy-related traits) a) Pot culture b) High throughput phenotyping system: LeasyScan c) Lysimeter d) Field Conclusion • The phenotyping facilities at ICRISAT are highly relevant to identify the traits underlying agronomic performance of crops in environments with various in-season water availability and so support the crop-improvement program. • The gained knowledge provides the power to combine the alleles from LG02 and construct the plant ideotype for specific regions according to the prevailing conditions. Selected reference Vadez et al (2015). J. Exp. Bot. (2015) 66 (18): 5581-5593. Kholova et al (2012). Mol Breed. 30, 1337-1353. 0 200 400 600 800 1000 1200 1400 1600 1800 1036 1071 1067 1040 1018 1082 1069 1151 1094 1139 1092 1116 1009 1162 1052 1061 1078 1101 Transpirationat64DAS(gweek-1) High Resolution Cross (HRC) 0.010 0.011 0.012 0.013 0.014 0.015 0.016 0.017 0.018 0.019 1002 1024 1006 1093 1100 1141 1059 1134 1016 1037 1042 1146 1107 1081 1077 1136 1157 Transpirationrate(gcm-2hr-1) High Resolution Cross (HRC) 400 500 600 700 800 900 1000 1100 1100 1049 1132 1093 1015 1128 1009 1099 1149 1021 1008 1050 1153 1133 1019 1148 1146 1031 3Dleafarea(cm2) High resolution cross (HRC) 9 11 13 15 17 19 21 23 1032 1116 1124 1020 1101 1027 1109 1130 1096 1108 1040 1041 1031 1131 1033 1051 1113 1037 Grainyield(gplant-1) High Resolution Cross (HRC) POT CULTURE LeasyScan Lysimeter Field LSD = 154**LSD = 0.0005** LSD = 532* LSD = 4.1** Fig. 3 Figure 4. Colocalisation of water-use, canopy development and agronomy related traits within 191-254cM of LG02. Water-use and agronomy related traits Water-use related traits Canopy development related traits Agronomy related traits Colocalisation of grain yield, water-use & canopy development related traits within 191-254cM (R1,R2,R3&R4) of LG02 Fig. 4 R1 R4 R1 R4 R3 R4 R3 R3 R2 R3 R2 Fig. 5a) c) b) -8 -6 -4 -2 0 2 4 -8-6-4-2024 PC1 (23.29%) PC2(17.27%) 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 3435 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 6566 67 68 69 70 71 72 73 7475 7677 78 79 80 81 8283 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 -0.6 -0.4 -0.2 0.0 0.2 0.4 -0.6-0.4-0.20.00.20.4 PLA ET_LS2016WW ETr_LS2016WW T_LS2016WW Tr_LS2016WW X3DGR_LS20 X3DLA_ ShDW_LS2 SLW_LS2016WW TNO_LS2016WW CS_LS2016WW PH_LS2016WW PGR_LS2016WW GY_F2010WW GY_F2011WW -6 -4 -2 0 2 4 -6-4-2024 PC1 (38.54%) PC2(20.09%) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1718 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 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 697071 72 7374 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103104 105 106 107 108 109110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128129 130 131 132 133 134 135 136 137138 139 140 141 142 143 144 -0.4 -0.2 0.0 0.2 0.4 -0.4-0.20.00.20.4 TrM_P2010WW TrE_P2010WW LA_P2010WW LDW_P2010WW RDW_P2010WW ShDW_P2010WW TOTDW_P2010WW SLA_P2010WW GY_F2010SS GY_F2011SS -4 -2 0 2 4 -4-2024 PC1 (22.83%) PC2(19.24%) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 2122 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 5152 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 7879 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99100 101 102103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126127 128 129 130 131 132 133 134 135 136 137 138 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 -0.6-0.4-0.20.00.20.40.6 GY_F2010SS TNO_L2010WS TOTDW_L2010SS GY_L2010SS T36DAS_L2010SS T41DAS_L2010SS T50DAS_L2010SS T57DAS_L T64DAS_L2 TE_L2010SS GY_F2011SS GY (Field; WW)  CS (LeasyScan; WW) GY (Field; SS)  RDW (Pot; WW) GY (Field; SS)  Late water extraction (T50-64DAS; Lysimeter; SS) -2 0 2 4 -2024 PC1 (27.88%) PC2(16.88%) 1 2 3 4 5 6 7 8 9 1011 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 2829 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 5152 53 54 5556 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 8788 89 90 91 92 93 94 9596 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127128 129 130 131 132 133134135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156157 158 159 160 161 162 -0.5 0.0 0.5 1.0 -0.50.00.51.0 T36DAS_L2010SS T41DAS_L2010SS PLA_LS2016WWX3DGR_LS2016WW X3DLA_LS2016WW CS_LS2016WW PH_LS2016WW PGR_LS2016WW Early water extraction (T36-41DAS; Lysimeter; SS)  CS (LeasyScan; WW) d) Results • Terminal water stress adaptation locus (LG02; 191-254cM) was further dissected into four separate QTL regions - R1 (191-205cM), R2 (229-233cM), R3 (236-239cM) and R4 (251-259cM) associated with water-use, canopy development and agronomy related traits. • The loci harboring water-use and canopy development related traits co-localized with agronomic traits assessed in the field pointing out their functional linkages. These relations were also confirmed by PCA analysis across phenotyping environments. Acknowledgements The authors thank for the funds from the USAID grant -Feed the Future Innovation Lab – Development of Abiotic Stress Tolerant Millet for Africa and South Asia For more details contact v.vadez@cgiar.org
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