Genetic variation in drought tolerance in rice:
The analysis of variance for all traits scored in this study presented in Table 1. High significant differences between the treatments for all traits. Significant differences among replications were only found for HGW. High genetic variation was observed among all genotypes for all traits. Among all traits, PL did not have significant differences in G × T. The minimum, maximum, mean, and coefficient of variation (CV) values for each traits under normal and drought conditions are presented in Table 2. The main average of all genotypes under drought conditions was lower than nourmal conditions for DTF, Ph, CC, FLA, PL, NOP, HGW and GY. Under nourmal conditions. On the other hand, the main average under normal conditions was lower than drought conditions in LR and SP traits. The highest CV (%) was found for LR (34.19%) under N, while SP had tad the highest CV under D. The performance of each genotype in each trait under both treatments are presented in Supplementary Table 2. The lowest effect due to drought stress was found for CC (14.06%), while, the highest reduction occurred in GY with 39.84%. The drought had a great effect on sterility percentage with an increase of sterility reach to 79%.
Table 1
The analysis of variance for all traits scored on the 22 rice genotypes under normal and drought conditions.
AOV | d.f | DTF | Ph | CC | LR | FLA | PL | NOP | HKW | SP | GY |
Treat. (T) | 1 | 134.75** | 93.43** | 316.97** | 416.99** | 231.50** | 520.28** | 221.82** | 186.19** | 108.78** | 285.26** |
Rep. (R) | 2 | 1.96 | 1.68 | 0.65 | 0.30 | 2.17 | 1.40 | 2.681 | 4.98* | 2.13 | 0.38 |
Geno. (G) | 21 | 401.77** | 238.37** | 46.18** | 17.55** | 44.94** | 21.03** | 31.01** | 32.03// | 181.94** | 69.54** |
G × T | 21 | 38.79** | 35.27** | 3.07** | 3.03** | 13.55** | 1.45 | 2.37** | 5.49** | 12.87** | 13.99** |
G × R | 42 | 0.81 | 1.25 | 1.96* | 0.94 | 1.05 | 0.94 | 0.73 | 1.03 | 0.73 | 1.54 |
G × R × T | 44 | | | | | | | | | | |
*,** significant at the 0.05 and 0.01 level of the probability, respectively. |
Table 2
Minimum, maximum, mean, and coefficient of variation (CV) for each trait scored on the 22 genotypes under normal (N) and drought (D) conditions.
Trait | Treatment | | Min. | Max. | Mean | CV(%) |
DTF (days) | N | 1 | 91.67 | 1333.33 | 110.50 | 10.94 |
| D | 2 | 78 | 109.67 | 93.53 | 8.54 |
Ph (cm) | N | 3 | 95.73 | 148.87 | 113.20 | 14.99 |
| D | 4 | 75.33 | 119.10 | 92.59 | 13.78 |
CC | N | 5 | 33.59 | 46.91 | 38.01 | 9.28 |
| D | 6 | 24.4 | 43.21 | 32.66 | 12.41 |
LR | N | 7 | 1 | 3.33 | 2.23 | 34.19 |
| D | 8 | 3.67 | 7.67 | 5.88 | 21.45 |
FLA | N | 9 | 23.64 | 44.02 | 32.89 | 13.44 |
| D | 10 | 17.26 | 26.94 | 21.40 | 12.64 |
PL | N | 11 | 17.73 | 24.47 | 21.86 | 8.32 |
| D | 12 | 14.08 | 20.76 | 17.33 | 9.57 |
NOP | N | 13 | 14.63 | 25.3 | 19.04 | 11.58 |
| D | 14 | 10.74 | 21.05 | 14.17 | 18.68 |
HKW (g) | N | 15 | 1.99 | 2.99 | 2.41 | 9.49 |
| D | 16 | 1.70 | 2.21 | 1.98 | 7.45 |
SP | N | 17 | 7.32 | 12.84 | 10.24 | 13.95 |
| D | 18 | 19.23 | 80.32 | 48.23 | 35.13 |
GY (g) | N | 19 | 26.63 | 44.36 | 33.86 | 13.64 |
| D | 20 | 13.51 | 34.93 | 20.37 | 29.76 |
Drought susceptibility index (DSI) was estimated for each genotype based on six important yield traits (Ph, CC, FLA, HGW, SP, and GY) to determine the most tolerant and susceptible genotypes (Supplementary Table 3). The distribution of all genotypes for each DSI is presented in Fig. 1. The number of tolerant genotypes differed by DSI. For example 12 tolerant genotypes were found based on DSI for Ph, HGW and SP while, 11 tolerant genotypes based on DSI for CC and FLA. Eight tolerant genotypes were found for GY. The tolerant genotypes for each DSI (six DSIs) were selected (Fig. 2). Two genotypes ETT1444 and Giza 178 were found to be tolerant based on all DSIs. Moreover, three genotypes (GZ1368-S-5-4, Nahda, Giza 14) were found to be tolerant to drought in five DSI. Therefore, we considered these five genotypes as the drought tolerant genotypes (Supplementary Table 3). On the other hand, three genotypes (IR74, Giza 177, and YabaniM7) were found to be tolerant in only one DSI and susceptible to five DSI. These genotypes were considered susceptible to drought stress. Furthermore, among the tolerant genotypes for each DSI, the most three tolerant (the lowest DSI values) and three susceptible genotypes (the highest DSI values) for each DSI were selected (Supplementary Table 3). As a result, IET1444 and Giza 178 were the most tolerant genotypes having the lowest values in five DSIs (CC, FLA, HGW, SP, and GY) followed by GZ1368-S-5-4 with the lowest DSI values in three indices ( HGW, SP, and GY).
Phenotypic correlations among traits:
The phenotypic correlation among traits under normal and drought stress are presented in Fig. 3 and Fig. 4, respectively. Remarkably, the number of significant phenotypic correlations among traits under drought stress was higher than those under normal conditions.
Under normal conditions, the highest positive significant correlation was found between NOT and NOP (r = 0.91**), while, the lowest positive significant correlation was between LR and Ph; NOT and GY and NOP and GY with r of 0.54*. SP had a negative significant correlation with CC, NOT, PL, NOP and GY with a range extending from − 0.49* (NOP) to – 0.73** (GY).
Under drought stress, the highest positive significant correlation was again between NOT and NOP (r = 0.96**) while, the lowest significant correlation was found between FLA and NOP (r = 0.45*). SP had negative significant correlations with CC, FLA, PL, NOP and GY. Moreover, LR was negatively and significantly correlated with FLA and GY. A negative significant correlation was found between CC and LR (r = -0.50*).
The phenotypic correlation among the DSIs for the seven traits is presented in Fig. 1. A positive and significant correlation was between DSI for GY and DSIs for SP, PL, FLA, and CC. DSI for SP was significantly correlated with DSIs for HGW, PL, and CC. The DSI for FLA was positively and significantly correlated with CC, PL, and HGW. A positive significant correlation was found between HGW and PL.
Single marker analysis for drought tolerance:
Marker-trait association was tested between the SSR markers and all phenotypic traits scored in this study (normal conditions and drought stress). The summary of QTL associated with traits under normal and drought stress conditions is presented in Table 3. As a total, the number of QTLs found under normal (16) was higher than those detected under drought stress (14). LR had the highest number of QTL under normal, while FLA and GY had only one QTL for each. Under drought stressCC and GY had the highest number of QTL under control conditions. NOP, Ph, and HGW had only one QTL for each. All traits had QTLs under drought stress except FLA, while three traits Ph, DTF, and HGW haven’t any QTL under normal conditions.
Table 3
Number of QTLs detected under normal and drought conditions using single-marker analysis
Traits | Treatments |
| Normal | Drought |
CC | 3 | 3 |
FLA | 1 | - |
GY | 1 | 3 |
LR | 5 | 2 |
NOP | 2 | 1 |
SP | 2 | 2 |
Ph | - | 1 |
DTF | - | 2 |
HKW | - | 1 |
Total | 16 | 14 |
The details of the SMA for all traits are presented in Table 4. The highest number of QTLs detected in LR with two QTLs under drought stress and five QTLs under normal conditions. One QTL was found for DTF (D), HGW (D), FLA (N), and PL (N). Chromosome 4 had the highest number of QTLs, while, chromosome 3 had only one QTL. The phenotypic variation explained by marker (R2) ranged from 33.34% ( qHGW_D) to 50.21% (qLR_D2) under drought stress, while, it extended from 34.06% (qLR_N3) to 84.61% (qLR_N5) under normal conditions. The effect of the visible alleles for each QTL was estimated. In CC, GY, NOP, HGW and Ph all detected alleles had a positive and increasing effect on the traits. In LR one and two SRR marker alleles were found to be associated with decreased the trait under normal and drought conditions, receptively. In SP, two SSR markers alleles located on chromosome 4 were significantly associated with decreasing the trait under drought stress condition. Two marker alleles associated with earliness in flowering under drought stress. Finally, one marker allele was found to be associated with decreased FLA under normal conditions.
Table 4
Detailed single-marker analysis for each trait under normal (N) and drought (D) conditions.
Trait | Treatment | QTL | Marker1 | Chro.2 | p-value | R2 23 | AE4 |
CC | D | qCC_D1 | Rm285-405 | 9 | 0.0030 | 39.40 | 11.56 |
| | qCC_D2 | RM307-128 | 4 | 0.0030 | 39.45 | 11.56 |
| | qCC_D3 | RM277-122 | 12 | 0.0074 | 33.52 | 4.871 |
| N | qCC_N1 | RM277-122 | 12 | 0.0044 | 36.97 | 4.410 |
| | qCC_N2 | Rm285-405 | 9 | 0.0030 | 38.40 | 9.840 |
| | qCC_N3 | RM307-128 | 4 | 0.0030 | 38.40 | 9.841 |
GY | D | qGY_D1 | Rm144-228 | 11 | 0.0050 | 36.12 | 15.632 |
| | qGY_D2 | RM307-128 | 4 | 0.0039 | 37.79 | 15.990 |
| | qGY_D3 | Rm285-405 | 9 | 0.0039 | 37.79 | 15.990 |
| N | qGY_N | RM307-122 | 4 | 0.0044 | 36.97 | 5.710 |
LR | D | qLR_D1 | Rm154-192 | 2 | 0.0021 | 41.66 | -1.632 |
| | qLR_D2 | Rm433-214 | 8 | 0.0005 | 50.21 | 1.800 |
| N | qLR_N1 | Rm154-182 | 2 | 0.0062 | 34.75 | 1.291 |
| | qLR_N2 | Rm154-192 | 2 | 0.0025 | 40.67 | -0.998 |
| | qLR_N3 | Rm161-185 | 5 | 0.0069 | 34.06 | -0.957 |
| | qLR_N4 | RM271-100 | 12 | 0.0014 | 44.10 | 1.20 |
| | qLR_N5 | Rm433-214 | 8 | 0.0006 | 48.61 | 1.096 |
NOP | D | qNOP_D | Rm144-228 | 11 | 0.0020 | 42.05 | 7.497 |
| N | qNOP_N1 | Rm144-228 | 11 | 0.0007 | 47.70 | 6.769 |
| | qNOP_N2 | Rm161-165 | 5 | 0.0065 | 34.47 | 2.560 |
SP | D | qSP_D1 | RM215-146 | 9 | 0.0047 | 36.66 | 23.308 |
| | qSP_D2 | Rm55-214 | 3 | 0.0015 | 43.66 | 27.52 |
| N | qSP_N1 | RM307-122 | 4 | 0.0049 | 36.30 | -1.648 |
| | qSP_N2 | RM307-126 | 4 | 0.0029 | 39.79 | -1.931 |
DTF | D | qDTF_D1 | Rm433-214 | 8 | 0.0037 | 32.19 | -11.347 |
| | qDTF_D2 | Rm154-192 | 2 | 0.0090 | 38.16 | -10.37 |
HKW | D | qHKW_D | RM307-122 | 4 | 0.0077 | 33.34 | 0.1826 |
FLA | N | qFLA_N | RM215-146 | 9 | 0.0064 | 34.62 | -6.521 |
Ph | D | qPh_D | RM215-146 | 9 | 0.0072 | 33.80 | 17.689 |
(1) Maker allele refers to the name of the SSR primer followed by the band size. |
(2) Chromosome number in rice genome |
(3) Phenotypic variation explained by marker alleles |
(4) allele effect of the present allele. AE referee to the effect of visible band (marker allele) of the SSR marker on the trait. Positive values increase the trait, while negative values decrease the trait. |
Interestingly, a set of eight markers were found to be associated with more than one trait under normal and drought conditions (Table 4). Under normal conditions, the seven markers were associated with only one trait except RM307-122 which controlled GY and SP. Five markers; Rm144-228, Rm154-192, Rm285-405, RM307-128, and Rm433-214 were associated with two traits under drought stress. Noticeably, some SSR markers were associated with the same trait under normal and drought conditions. For example, Rm285-405 and RM307-128 markers were associated with increased CC under normal and drought stress. The same two markers were associated with increased GY under drought stress. Rm144-228 marker was associated with increased NOP under both treatments and GY under drought stress. Rm154-192 was associated with decreased LR under both treatments, while, Rm433-214 was found to be associated with increased LR under the two treatments and DTF under drought stress. Two markers were associated with different traits under both treatments. Rm144-218 marker was associated with decreased CC under normal and PL under drought. RM215-146 was associated with decreased Ph and SP under drought stress.
By looking for the number of QTL existed in the most five drought tolerant genotypes, the highest number of total detected QTL (15) was found in Giza 178 and GZ1368-S-5-4, while IET1444 had the lowest number of detected QTLs. The five genotypes had a higher number of QTLs detected under drought compared with those detected under normal. Three drought tolerant genotypes (Giza 178, GZ1368-S-5-4 and Nahda) had eight QTLs controlling yield traits under drought stress. GZ1368-S-5-4 had the highest number of QTLs controlling yield traits under normal conditions.
The number of different significant marker alleles among the most five tolerant genotypes is presented in Table 6. Nahda had different seven marker alleles from Giza 178, IET1444, GZ1368-S-5-4. Likewise, the same results were found between Giza 14 and both Giza 178 and GZ1368-S-5-4. Giza 178 and GZ1368-S-5-4 had the same significant marker alleles.
Table 6
Number of different QTLs under drought conditions among the promising drought tolerant rice genotypes selected based of drought susceptibility index (DSI).
Genotypes | Subpop1. | Giza178 | IET1444 | GZ1368-S-5-4 | Nahda | GIZA 14 |
Giza178 | G2 | | 4 | 0 | 7 | 7 |
IET1444 | G1 | | | 4 | 7 | 5 |
GZ1368-S-5-4 | G2 | | | | 7 | 7 |
Nahda | G1 | | | | | 6 |
GIZA 14 | G2 | | | | | |
1 subpopulation according to Salem and Sallam (2015) |
Use of genetic diversity analysis to improve drought tolerance:
The genetic analysis and population structure were performed on the 22 )see material and methods). The analysis of genetic diversity and population structure divided the 22 genotypes into two possible subgroups (subpopulations). The first subpopulation (G1) included AgamiM1, Arabi, Bala, IET1444, IR20, IR22, IR24, IR50, IR64, IR74, Nahda, YabaniM1, while, the second subpopulation (G2) included Yabani15, Yabanilulu, YabaniM7, Giza14, Giza171, Giza172, Giza177, Giza178, Giza181, and GZ1368-S-5-4. The mean of all genotypes in each group was calculated for each trait to study the properties of genetic diversity between the two groups in terms of yield attributes and drought tolerance (Table 7). Interestingly, genotypes in G2 performed better in six and five agronomic traits under normal and drought than those in G1, respectively. Under control and drought stress conditions and compared with genotypes in G1, genotypes in G2 were late in flowering, taller stems, higher in CC, higher in PL, higher in NOP. Moreover, genotypes in G2 were lower in SP under normal, and higher in GY under drought conditions. For DSI, genotypes in G2 had a higher level of drought tolerance (five DSIs; CC, FLA, HGW, SP, and GY) compared with genotypes in G1.
Table 7
Drought susceptibility index (DSI) and phenotypic characters under normal and drought conditions on all genotypes in both subpopulations.
| Control | Drought | DSI |
| G1 (1) | G2 (1) | G1 | G2 | G1 | G2 |
DTF | 108.67 | 112.70 | 90.97 | 96.60 | NA | NA |
Ph | 109.41 | 116.47 | 92.38 | 92.77 | 0.95 | 1.00 |
CC | 37.00 | 38.74 | 31.54 | 33.57 | 1.07 | 0.89 |
LR | 1.86 | 2.67 | 5.39 | 6.47 | NA | NA |
FLA | 34.23 | 31.85 | 21.20 | 20.99 | 1.05 | 0.94 |
PL | 21.69 | 22.52 | 16.83 | 17.90 | NA | NA |
NOP | 18.05 | 20.23 | 13.76 | 14.67 | NA | NA |
HKW | 2.43 | 2.39 | 1.98 | 1.98 | 1.01 | 0.96 |
SP | 10.72 | 9.45 | 44.65 | 52.44 | 0.99 | 0.93 |
GY | 32.26 | 35.77 | 18.59 | 21.74 | 1.05 | 0.98 |
Number of favorable traits | 4.00 | 6.00 | 4.00 | 5.00 | 2.00 | 6.00 |
(1) All genotypes were divdied into two subpopulation according to Salem and Sallam (2016) |