Genetic analysis of drought tolerance in cowpea (Vigna unguiculata L.)

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Major Constraints of Cowpea Production,Phenotyping,Genotyping and genetic map construction,QTL mapping,Implications for breeding

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Genetic analysis of drought tolerance in cowpea (Vigna unguiculata L.)

  1. 1. Genetic analysis of drought tolerance in cowpea (Vigna unguiculata L.)Eugene M. Agbicodo Feb. 8th 2010
  2. 2. Outline Introduction Phenotyping Genotyping and genetic map construction QTL mapping Implications for breeding
  3. 3. Cowpea Vigna unguiculata L. Walp Family: Fabaceae Diploid: 2n = 22 Genome size: ~620 Mbp Self pollinated crop www.iita.org
  4. 4. Cowpea ProductionFAO:http://www.fao.org/inpho/content/compend/text/ch32/ch32.htm
  5. 5. Major Constraints of Cowpea Production
  6. 6. Drought stress and cowpea production Drought stress occurred throughout the cropping season (early- mid- and terminal) Mid- and late-season drought stress have received considerable attention given their negative effects on yield (Hall et al. 2004) However, drought tolerance at seedling is receiving attention Singh et al. (1999 a,b) Muchero et al. (2008; 2009a)
  7. 7. Plant Materials Danila X TVu7778 F1 F2Tolerant parent Susceptible parent Recombinant inbred lines (RILs)
  8. 8. Phenotyping RILs derived from Danila (tolerant) and TVu7778 (susceptible) were evaluated for:1. Drought tolerance at seedling2. Terminal drought tolerance
  9. 9. Drought phenotyping at seedling stage Parameters measured: • Stem greenness (Stg) • Drought-induced trifo- liate senescence (DTS) 1 2 3 4 5 6 • Survival after rewatering (Sur) 130 cm length, 65 cm width and 15 cm depth 1:1 mixture of top soil and sand
  10. 10. Phenotyping for terminal drought Terminal drought field trials •IbadanRCBD with 2 treatments, 3 rep Locations: Kano and IbadanDrought imposed at flowering
  11. 11. Phenotyping for terminal drought tolerance Parameters measured:  stomatal conductance (Gs), RWC  days to flowering  delay leaf senescence (DLS): visual scoring 1-5 classes  number and weight of pods, total seed weight, 100 seed-weight, fresh and dry fodder weight
  12. 12. Genotyping RILs/parents genotyped Illumina Goldengate SNP array, 1,536 SNPs mined from EST sequences from several sources (UCR, IITA) 1,248 SNP were selected from ESTs derived from 11 cowpea genotypes After data processing, only 322 SNPs with minor allele frequency > 0.30 were used to construct genetic map using JoinMap 4
  13. 13. QTL mapping Entry mean of terminal (field) and seedling (greenhouse) drought tolerance traits SNP genetic linkage map of 282 loci with 11 LGs QTL analysis was performed using MapQTL 5, (Kruskal-Wallis test, Interval Mapping, Multiple- QTL Model mapping )
  14. 14. ResultsStg, DTS and Sur variedsignificantly between RILsand parents RiL-117 Susceptible Tolerant RiL-106 Susceptible RiL-87 Parent Parent Parent Seedling phenotyping
  15. 15. Correlation of traits at seedling Seedling survival mostly depend on stem greenness (0.911) Stem greenness is negatively correlated with drought-induced trifoliate senescence (-0.714)
  16. 16. Results Variation of RILs for delayed leaf senescence (DLS) 1 4 1 1 3 3 1 2
  17. 17. Frequency distribution of traits in Kano (a) (b) (c) (d) Dry D Dry Dry T D Dry T T D T D Number of RILs 50 100 150 200 250 300 1 2 3 4 5 36 39 42 45 48 51 3 6 9 12 15 18 21 DT Wet Wet Wet Wet T TD D T D 50 100 150 200 250 300 1 2 3 4 5 36 39 42 45 48 51 3 6 9 12 15 18 21 Stomatal conductance Delayed leaf senescence (DLS) Days to flowering Number of Pods/plant (mmol m-2s-1) (e) (f) (g) (h) T D T Dry Dry Dry Dry T D D Number of RILs T D 3 6 9 12 15 18 0,03 0,06 0,09 0,12 0,15 0,18 0,21 3 6 9 12 15 18 21 5 10 15 20 25 30 35 D Wet Wet T Wet Wet TD T D D T 3 6 9 12 15 18 0,03 0,06 0,09 0,12 0,15 0,18 0,21 3 6 9 12 15 18 21 5 10 15 20 25 30 35 Number of seeds/pod Seed weight (g) Grain yield (g/plant) Fodder yield (g/plant)
  18. 18. Frequency distribution of traits in Ibadan (i) (j) (k) (l) Dry T D Dry T T Dry T Dry D Number of RILs D D 50 100 150 200 250 300 1 2 3 4 5 43 46 49 52 55 58 5 10 15 20 25 30 35 D Wet Wet D T Wet T Wet D T TD 50 100 150 200 250 300 1 2 3 4 5 43 46 49 52 55 58 5 10 15 20 25 30 35 Stomatal conductance Delayed leaf senescence (DLS) Days to flowering Number of Pods/plant (mmol m-2s-1) (m) (n) (o) (p) Dry T Dry Dry Dry T D T D Number of RILs T D D 2 4 6 8 10 12 0,03 0,06 0,09 0,12 0,15 0,18 0,21 4 8 12 16 20 24 28 32 5 10 15 20 25 30 35 D T Wet Wet Wet D Wet D T D T T 2 4 6 8 10 12 0,03 0,06 0,09 0,12 0,15 0,18 0,21 4 8 12 16 20 24 28 32 5 10 15 20 25 30 35 Number of seeds/pod Seed weight (g) Grain yield (g/plant) Fodder yield (g/plant)
  19. 19. Results Effect of water stress on plant performances Kano Ibadan Traits Irrigation Drought RR% Irrigation Drought RR% Gs (mmol m-2s-1) 175.4 (51-411) 95.2 (18-228) 45.7 246 (136-404) 121.1 (11-298) 50.7 RWC% 89.5 (52-98) 89.4 (74-99) 0.1 86.3 (61-100) 86.0 (62-99) 0.4 Days to flowering 49.5 (38-62) 48.3 (33-60) 2.4 43.4 (36-76) 40.6 (34-57) 6.4 No of pod/plant 17.1 (4-40) 10.9 (0-26) 36.4 13.7 (8-26) 8.1 (0-19) 40.6 100 Seed sweight (g) 12.1 (8-20 ) 10.0 (0-16) 16.6 12.0 (8-18) 10.0 (0-17) 16.6 No of seed/pod 6.9 (3-19) 6.4 (0-15) 6.3 7.6 (3-14) 7.4 (0-14) 1.4 Grain yield (g/plant) 14.7 (4-74) 8.1 (0-30) 44.7 12.1 (4-45) 6.5 (0-21) 46.7 Fodder yield (g/plant) 20.8 (11-61) 10.3 (2-41) 50.5 27.2 (11-54) 12.8 (3-45) 52.9 Total yield (g/plant) 35.5 (19-130) 18.4 (6-70) 48.2 39.3 (20-86) 19.3 (7-65) 51.0
  20. 20. Correlation and path analyses Correlation between No of pod/plant and GYD is 0.845Direct and indirect effects of variables on GYD [rij] x [Pi-Y] = [ri-Y]Indirect effect via seed weight 0.431 x 0.086 0.037Indirect effect via number of seed/pod 0.501 x 0.200 0.100Indirect effect via stomatal conductance 0.232 x 0.055 0.013Indirect effect via flowering time 0.001 x 0.034 0.000Indirect effect via delayed leaf senescence 0.045 x 0.023 0.001Indirect effect via fodder yield 0.438 x 0.246 0.107Direct effect of number of pods/plant with GYD 0.587Total (correlation between number of pod/plant and GYD) 0.845
  21. 21. Drought IrrigationResults X1 X1 r=0.431Correlations and X2 X2 .334 r=0.445path coefficient for r=-07 traits with direct X3 X3 .040 .105and indirect effect r=-0 r=-0 P=0.055 P=0.064on grain production X4 GYD X4 r=0.011 r=-0.042under drought in Kano X5 X5 r=0.198 X6 X6 r=0.242 .401 Kano r=0 X7 X7 (X)Residual (X)Residual factors factors
  22. 22. SNP genetic linkage map LG No Markers Length cM Distance between Markers 1 58 111.6 2 2 21 31.6 1.5 3 26 66.3 2.6 4 27 59.6 2.2 5 28 52.8 2 6 27 78.6 3 7 26 60.4 2.3 8 21 44.1 2 9 19 33.7 1.7 10 17 40 2.3 11 12 54.3 4.5 Total 282 633 2.2This genetic linkage map is integrated in consensus map of 7 RILspopulations with 928 SNPs (Muchero et al. 2009b)
  23. 23. Genetic linkage map and QTL identified at seedling
  24. 24. QTL mapping for terminal drought tolerance traits Kruskal-Wallis Year 1 (Kano) Year 2 (Kano) Year 2 (Ibadan) Range % Variation QTL LG Position (cM) Flanking Markers Significant level Dry Wet RR Dry Wet RR Dry Wet RR ExplainedStomatal Conductance Gs; permutation threshold (GW)* 2.10 Gs-1 2 40.03 - 50.98 1_0595 - 1_1158 0.01 -0.001 na na na 2.91 1.34 0.28 1.12 1.03 0.62 2.1 - 10.7 Gs-2 7 2.06 - 10.95 1_1249 - 1_0559 0.01 -0.001 na na na 1.97 1.05 0.45 2.29 0.94 0.24 3.4 - 9.7 Gs-3 7 2.06 - 20.68 1_1249 - 1_1414 0.01 -0.001 na na na 2.63 1.14 1.32 2.15 0.66 0.87 3.8 - 12.8 Gs-4 8 23.13 - 31.32 1_1168 - 1_0530 0.01 -0.001 na na na 3.12 2.35 0.92 1.82 2.05 1.05 5.5 - 18.5Dealyed leaf senescence (DLS); permutation threshold 3.60 DLS-1 3 7.73 -32.66 1_0853 - 1_1349 0.01 - 0.001 na na na 4.20 4.31 2.34 3.78 4.09 2.08 9.3 - 17.8 DLS-2 3 19.33 - 28.96 1_1195 - 1_0104 0.01 - 0.001 na na na 3.97 2.87 1.98 4.33 3.11 2.19 3.9 - 16.2 DLS-3 3 54.25 - 70.41 1_1027 - 1_0594 0.05 - 0.001 na na na 3.91 2.71 2.03 3.75 2.06 2.02 6.1 -19.4 DLS-4 5 5.81 - 38.03 1_0309 - 1_0037 0.05 - 0.001 na na na 4.87 3.67 1.98 2.76 2.32 1.82 7 - 15.2 DLS-5 7 17.68 - 37.68 1_1414 - 1_0056 0.001 - 0.0001 na na na 10.75 4.89 3.10 5.21 2.59 2.26 10.3 - 46.3 DLS-6 7 20.68 - 41.89 1_1414 - 1_1249 0.001 - 0.0001 na na na 3.91 2.82 2.81 7.86 3.95 3.00 8.7 - 32.7Days to flowering; permutation threshold 3.20 Flow-1 8 0 - 15.19 1_0298 - 1_0141 0.01 - 0.001 4.07 2.90 1.77 7.19 5.42 2.32 3.39 2.01 3.26 3.8 - 27.8 Flow-2 8 0 - 9.19 1_0298 - 1_1370 0.01 - 0.0001 3.89 3.10 2.46 5.29 3.42 3.64 4.61 3.43 3.29 5.6 - 19.6 Flow-3 5 16.34 - 31.70 1_0924 - 1_0800 0.001 - 0.0001 1.78 1.07 0.37 3.62 3.10 2.09 1.97 0.59 0.21 7.9 - 16.2 Flow-4 9 23.18 - 39.99 1_1467 - 1_1408 0.01 - 0.001 2.65 2.03 1.02 2.05 3.54 0.93 1.04 0.22 0.09 3.9 - 8.6 Flow-5 7 7.37 - 13.21 1_0056 - 1_0270 0.01 - 0.0001 3.36 1.39 0.96 3.43 0.98 1.01 0.97 0.23 0.09 2.2 - 10.2Number of pod/plant; permutation threshold 2.10 Pod-1 3 73.83 - 78.30 1_0299 - 1_1349 0.01 - 0.0001 2.17 0.97 0.76 3.06 2.32 0.47 2.33 1.98 0.83 5.3 - 10.8 Pod-2 4 11.46 - 15.842 1_0275 - 1_0856 0.01 - 0.001 1.88 0.43 1.02 2.36 3.24 1.04 1.99 2.88 1.02 0.6 - 12.6 Pod-3 4 9.88 - 18.22 1_0304 - 1_1013 0.05 - 0.001 2.10 0.89 0.32 3.24 3.23 1.21 2.88 2.00 1.22 5.2 -12.7 Pod-4 5 25.58 - 32.70 1_0346 - 1_0800 0.05 - 0.001 1.22 0.88 0.46 0.27 0.43 0.01 2.21 0.37 0.08 2.5 - 8.5 Pod-5 8 18.68- 22.12 1_1370 - 1_0530 0.01 - 0.001 0.25 0.76 0.03 2.27 0.91 0.23 0.27 0.08 0.02 8.5 - 10.1 Pod-6 9 57.72 - 69.64 1_0221 - 1_1236 0.05 - 0.001 0.09 0.06 0.37 2.00 3.50 1.98 0.87 0.24 0.05 9.1 - 13.9 Pod-7 10 19.28 - 31.81 1_0416 - 1_0598 0.05 - 0.001 3.20 0.97 0.54 1.20 0.49 0.19 0.76 0.06 0.01 12.1 - 13.7
  25. 25. QTL mapping for terminal drought tolerance triats Kruskal-Wallis Year 1 (Kano) Year 2 (Kano) Year 2 (Ibadan) Range % Variation QTL LG Position (cM) Flanking Markers Significant level Dry Wet RR Dry Wet RR Dry Wet RR ExplainedNumber of seed/pod; permutation threshold 2.00 Seed/P-1 2 23.05 - 29.95 1_1352 - 1_1230 0.05 - 0.001 2.29 1.98 0.69 1.64 1.97 0.41 0.90 0.76 0.25 5.8 - 9.2 Seed/P-2 3 13.328 - 18.42 1_1073 - 1_0373 0.05 - 0.001 0.01 0.02 0.01 2.26 2.20 0.43 1.03 2.40 0.02 4.2 - 10 Seed/P-3 4 11.46 - 17.22 1_0275 - 1_0398 0.05 - 0.001 0.81 0.82 0.01 1.56 2.25 0.87 1.22 2.73 0.51 5.3 - 9.4 Seed/P-4 4 25.03 - 33.41 1_0106 - 1_0774 0.05 - 0.001 0.02 0.01 0.01 0.87 2.30 0.20 2.10 4.66 1.92 4.7 - 17.3Seed weight; permutation threshold 2.40 Seedwt-1 4 7.88 - 21.27 1_0304 - 1_0106 0.001 - 0.001 2.59 2.30 0.90 3.62 2.49 0.65 2.10 1.04 0.72 5.7 - 13.8 Seedwt-2 6 2.93 - 8.32 1_1381 - 1_0943 0.01 - 0.001 5.97 2.58 0.45 1.93 1.22 0.32 2.06 2.01 0.67 8.8 - 10.9 Seedwt-3 6 0 - 12.32 1_0911 - 1_0943 0.001 - 0.001 5.97 2.58 1.93 2.46 0.99 0.39 2.29 2.21 1.09 6 - 22.8 Seedwt-4 10 47.37 - 55.99 1_0840 - 1_0007 0.001 - 0.001 2.41 0.90 0.08 2.19 4.29 1.93 2.03 2.89 1.03 12.1 - 19.3 Seedwt-5 10 6.77 - 19.28 1_1189 - 1_1049 0.01 - 0.001 3.41 0.53 0.12 2.93 0.90 1.32 1.22 0.87 0.09 7.4 -15.1Grain yield; permutation threshold 2.00 GY-1 8 17.19 - 27.13 1_1370 - 1_0530 0.01 - 0.001 0.21 0.09 0.00 2.71 0.91 0.04 1.24 1.01 0.38 8.5 - 13.8 GY-2 5 32.72 - 43.25 1_0419 - 1_0819 0.01 - 0.001 0.91 2.01 0.82 1.24 2.77 0.03 0.78 0.54 0.19 4.6 - 10.1 GY-3 9 10.5 - 30.49 1_0703 - 1_0137 0.01 - 0.001 0.02 0.98 0.32 2.36 2.92 1.03 1.87 2.44 0.21 8.5 - 12.2 GY-4 7 2.06 - 13.52 1_0248 - 1_0270 0.01 - 0.001 2.63 1.25 0.52 2.76 1.98 1.00 1.98 1.32 0.08 4.2 - 8.3 GY-5 3 0 - 14.09 1_0105 - 1_1065 0.001 - 0.001 1.98 0.91 0.09 2.10 3.11 1.08 2.13 1.92 0.05 6.7 - 12.9 GY-6 6 16.95 - 23.59 1_0706 - 1_0123 0.001 - 0.001 1.34 1.21 0.03 0.91 0.42 0.02 2.67 0.76 0.01 4.7 - 9.8Fodder yield; permutation threshold 2.00 FY-1 5 23.54 - 29.67 1_0081 - 1_0800 0.05 - 0.001 1.23 1.98 0.91 3.10 2.77 1.22 2.12 0.03 0.01 6.7 - 9.1 FY-2 6 19.61 - 32.06 1_1381 - 1_0943 0.01 - 0.001 0.65 0.90 0.01 2.03 2.97 0.90 0.01 0.01 0.07 6.3 - 9.6 FY-3 10 31.42 - 53.05 1_0865 - 1_0354 0.05 - 0.001 0.03 0.01 0.01 1.82 1.43 0.76 4.53 2.41 0.09 6.7 -12.50 FY-4 6 8 - 31.06 1_0323 - 1_0943 0.05 - 0.001 2.01 0.04 0.06 0.98 0.62 0.03 2.07 3.96 0.21 7.4 - 13 FY-5 4 35.75 - 52.68 1_1221 - 1_1147 0.01 - 0.001 2.95 2.15 1.02 1.06 0.92 0.01 0.18 1.03 0.10 7.2 - 17.2
  26. 26. QTL-environment interactions Grain and fodder yield and grain yield components were most affected by environment with QTL specific to water regime, location and year. QTL-water treatment and location effects were also observed for stomatal conductance, but to the lesser extend for DLS and flowering time
  27. 27. QTL-environment interactions QTL-water treatment, location and year effects might be due to:1. Experimental errors during measurements2. Unstable weather conditions in Ibadan3. Soil in Ibadan is richer (N, Zn, Fe, Mn)4. Differences in soil water retention capacity with more clay in Ibadan.
  28. 28. QTL-environment interactions The QTL-environment interactions suggest that some specific sets of genes account for traits under water stress and well-watered conditions Similar results were reported by (Sangara et al. 2001; 2004; Levi et al. 2009)
  29. 29. Co-localization of physiologicaland productivity QTLs
  30. 30. Common genomic regions These 4 common regions on LG3, LG5, LG7, LG8 where QTLs for Gs, DLS, flowering time, yields and yield components co-localized represent hot spot for drought tolerance traits. These results demonstrate that some genes loci that regulate plant ability to DLS, maintain higher stomatal conductance, promote flower and pod formations.
  31. 31. Conclusion and implications for breeding Despite the higher number of 42 QTLs, four chromosomal regions contain several QTLs for physiological and productivity traits Breeding for such QTLs in the common regions may help to improve several aspects of the drought response in cowpea
  32. 32. Comparative genomics Muchero et al. 2009b
  33. 33. Implications for breeding Marker loci defining the QTLs in the common chromosomal regions represent candidates for further molecular studies for MAS The fact that our genetic map is integrated in a consensus map of 7 RILs population will help for comparative genomic studies.
  34. 34. AcknowledgementsWUR Plant Breeding IITA UCRRichard Visser Christian Fatokun Jeff EhlersGerard van der Linden Satoru Muranaka Tim CloseAbiotic research group R. Bandyopadhyay P. Roberts All Technicians M. Muchero NN. Diop Financial Support IITA-Lukas Brader Fund, all members of IITA board, Leventis Foundation and IFAR, Wageningen UR Plant Breeding
  35. 35. © Wageningen URDr Lukas Brader
  36. 36. Thanks for your attention

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