A detailed study on genetic diversity, antioxidant machinery, and expression profile of drought-responsive genes in rice genotypes exposed to artificial osmotic stress

Abstract

Seasonal variations in rainfall patterns, particularly during sowing, early growing season, and flowering, drastically affect rice production in northeastern India. However, sensitivity to drought stress is genotype-specific. Since 80% of the land in this region is used for rice production, it is crucial to understand how they have adapted to water stress. This study evaluated 112 rice genotypes grown in NE India for seed germination percentage and seedling development under PEG-mediated drought stress. Among the rice genotype, Sahbhagi dhan, RCPL-1-82, Bhalum-3 and RCPL-1-128 showed drought-tolerant traits, while Ketaki Joha, Chakhao, Chandan, RCPL-1-185 and IR-64 were the most drought-sensitive rice genotypes. Drought-tolerant rice also showed significantly higher seed germination potential, proline content, antioxidant activity and expression of drought-responsive genes than drought-sensitive rice genotypes. A similar expression pattern of genes was also observed in the rice genotype treated with a 50% water deficit in pot culture. In addition, drought stress reduced the pollen fertility and yield per plant in sensitive rice genotypes. Molecular markers associated with drought stress were also used to characterize genetic diversity among the rice genotypes studied.

Figure 1

(a) A representative picture showing effect of different concentrations of PEG mediated osmotic stress on the seed germination percentage. (b) A representative picture of EVANS blue dye staining of the root of rice genotype treated with 30% PEG and control (0% PEG); (c) picture showing15 days old rice genotype under different concentrations of PEG-stress; (d) picture showing 112 rice genotype grown under 30% PEG; 1. AALIDUMAJU; 2. AJUCENA; 3. ANJALI; 4. SAMBA MAHSURI; 5. BANG; 6. BHALUM 1; 7. BHALUM 2; 8. IR-7277-7-22-1-1; 9. BHALUM 4; 10. IR-78667-1-2-1-1-2; 11. RCPL-1-47; 12. BP-2890-MR8; 13. RCPL-1-13; 14. CHARANGPHOU; 15. RCPL-1-86; 16. COL-4; 17. DAGARDESHI; 18. RCPL-1-101; 19. Fullbadam; 20. GOMTIDHAN; 21. GOVINDOBHOG; 22. Hakuchung; 23. HPR—2558; 24. IORO EPYO; 25. IR-1552; 26. RANJIT; 27. IR-71524-44-1-2-8; 28. BHALUM 3; 29. IR-74052-80-1-1; 30. BHUTMURI; 31. KMP-34; 32. Katak-tara; 33. KASALATH; 34. V-Dhan; 35. KRISHNA; 36. LUNISHREE; 37. MAI-CHING; 38. Megha aromatic; 39. MEGHA RICE 1; 40. MNEO; 41. N-902; 42. NAVEEN; 43. NDR-97; 44. NEPAL RICE; 45. PAIJONG; 46. POKKALI; 47. PR-23079-10; 48. PR-25679-B-9-1; 49. PR-26850-P-J-18-6; 50. PSB-RC2; 51. PURPLE RICE; 52. PYNTHOR; 53. RADHUNIPAGOL; 54. IR64; 55. RCPL-1-102; 56. RCPL-1-108; 57. SAHBHAGI DHAN (IR74371-70-1-1); 58. RCPL-1-113; 59. RCPL-1-100; 60. RCPL-1-117; 61. RCPL-1-104; 62. RCPL-1-105; 63. RCPL-1-107; 64. RCPL-1-109; 65. RCPL-1-110; 66. RCPL-1-115; 67. RCPL-1-115; 68. EPYO; 69. RCPL-1-128; 70. RCPL-1-127; 71. BOG BUTAL; 72. Baglami; 73. RCPL-1-132R; 74. RCPL-1-91; 75. RCPL-1-46; 76. RCPL-1-74; 77. RCPL-1-77; 78. RCPL-1-78; 79. Chandan; 80. RCPL-1-96; 81. RCPL-1-90; 82. RCPL-1-185; 83. RCPL-1-82; 84. RCPL-1-97; 85. RCPL-1-98; 86. SLICKY RICE; 87. Amubi (Chakhao amubi); 88. SANG CHANG; 89. SATABDI; 90. SHASHARANG; 91. SHENGNYA; 92. HANSA; 93. SKAU-390; 94. RCPL-1-112; 94. SUKARDHAN; 96. SUNDARI; 97. SWARNA; 98. TSAMUM FIRRI; 99. TSUMATSUK; 100. UPR-2919; 101. UPR-2992; 102. VANDANA; 103. VL-31331; 104. VIETNAM-3; 105. VIETNAM-1; 106. VL-31329; 107. Ketaki Joha; 108. VPLR-1-7; 109. VR-14; 110. WAB-450-1-1-1-2-P41-HB; 111. YEMSO; 112. ZAM.

Figure 2

A representative electrophoresis gel pic showing amplified DNA bands in 19 rice genotype using RAPD maker (a) and SSR marker (b); barplot (c) of 112 rice genotype developed based on the presence or absence of bands (SSR and RAPD markers) using STRUCTURE software, similar colour indicates genetic similarity between the rice genotype; A line graph depicting K value of the population study (d).

Figure 3

Graphical representation of MDHAR, CAT, DHAR, GPX, GR and SOD activity in the shoot and root tissues of Sahbhagi Dhan, RCPL-1-82, RCPL-1-185 and IR-64 under PEG-mediated drought stress on 15th day after treatment. Each value is representation of mean ± sd, N = 9 and different letters indicates statically significant at p < 0.05.

Figure 4

Graphical representation of expression profile of DREB1, p5cs, rbcs, AAO1, SOD, WRKY11, WRKY114, SDR1, NAC9, ZFP252, ZFP182 and DRAP1 genes in shoots (a) and roots (b) of Sahbhagi Dhan, RCPL-1-82, RCPL-1-185 and IR-64 under control (C) and PEG-mediated drought stress (T) on 15th day after treatment. Each value is representation of mean ± sd, N = 9 and statically significant at p < 0.05.

Figure 5

Graphical representation of proline content in the shoot (a), proline content in the root (c), shoot relative water content (b), root relative water content (d), % pollen viability (e), total number of filled seeds per plant (f), total number of seeds per panicle (g); tillers per plant (h) in Sahbhagi dhan, RCPL-1-82, IR64 and RCPL-1-185 maintained at control (well watered) and 50% water deficit condition. Each value is representation of mean ± sd, N = 9 and different letter indicates statically significant at p < 0.05.

Figure 6

Graphical representation of relative expression of DREB1, p5cs, rbcs, AAO1, SOD, WRKY11, WRKY114, SDR1, NAC9, ZFP252, ZFP182 and DRAP1 genes in shoots (a) and roots (b) of Sahbhagi Dhan, RCPL-1-82, RCPL-1-185 and IR-64 under control (well watered) and 50% water deficit condition. Each value is representation of mean ± sd, N = 9 and statically significant at p < 0.05.

Figure 7

Graphical representation of relative expression of DREB1, LOC_Os12g04500, LOC_Os02g50970, LOC_Os12g26290, LOC_Os05g08480, MYB80 and WRKY114 genes in the young panicle of Sahbhagi Dhan, RCPL-1-82, RCPL-1-185 and IR-64 under control (well watered) and 50% water deficit condition. Each value is representation of mean ± sd, N = 9 and different letter indicates statically significant at p < 0.05.