Rice Science ›› 2019, Vol. 26 ›› Issue (4): 239-247.DOI: 10.1016/j.rsci.2019.01.004
• Orginal Article • Previous Articles Next Articles
Donde Ravindra1, Kumar Jitendra1, Gouda Gayatri1, Kumar Gupta Manoj3, Mukherjee Mitadru1, Yasin Baksh Sk1, Mahadani Pradosh, Kumar Sahoo Khirod2, Behera Lambodar1, Kumar Dash Sushanta1(
)
Received:2018-11-14
Accepted:2019-01-14
Online:2019-07-28
Published:2019-04-04
Donde Ravindra, Kumar Jitendra, Gouda Gayatri, Kumar Gupta Manoj, Mukherjee Mitadru, Yasin Baksh Sk, Mahadani Pradosh, Kumar Sahoo Khirod, Behera Lambodar, Kumar Dash Sushanta. Assessment of Genetic Diversity of Drought Tolerant and Susceptible Rice Genotypes Using Microsatellite Markers[J]. Rice Science, 2019, 26(4): 239-247.
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| No. | Genotypes | Eco Types | Tolerance to stresses | Other information |
| 1 | Swarna sub1 | Shallow low land | Tolerant to submergence and susceptible to drought | Popular variety |
| 2 | IR64 sub1 | Irrigated | Tolerant to Submergence and susceptible to drought | - |
| 3 | FR13A | Shallow low land | Tolerant to Submergence and susceptible to drought | International submergence tolerance donor |
| 4 | CR143-2-2 | Upland | Drought Tolerance | Drought tolerant check |
| 5 | N 22 | Upland | Drought Tolerance | Drought and heat stress check |
| 6 | Brahamanakhi | Upland/Medium land | Drought Tolerance | Landrace |
| 7 | Satyabhama | Upland | Drought Tolerance | Released variety |
| 8 | IR 20 | Irrigated | Drought susceptible | International Check |
| 9 | Nerica1 | Upland/ Aerobic | Drought Tolerance | Suitable for Africa |
| 10 | Azucena | Upland | Drought Tolerance | Tropical japonica |
| 11 | Curinga | Upland | Drought Tolerance | Tropical japonica |
| 12 | MER20 | Upland | Drought Tolerance | CSSLs/BC4F4 of O. meridionalis/ Curinga |
| 13 | RUF44 | Upland | Drought Tolerance | CSSLs /BC4F4 of O. rufipogon/ Curinga |
| 14 | RUF16 | Upland | Drought Tolerance | CSSLs /BC4F4 of O. rufipogon/ Curinga |
| 15 | RUF48 | Upland | Drought Tolerance | CSSLs /BC4F4 of O. rufipogon/ Curinga |
| 16 | RUF13 | Upland | Drought Tolerance | CSSLs /BC4F4 of O. rufipogon/ Curinga |
Supplemental Table 1 The list of drought tolerant and susceptible rice genotypes used for the assessment of genetic diversity.
| No. | Genotypes | Eco Types | Tolerance to stresses | Other information |
| 1 | Swarna sub1 | Shallow low land | Tolerant to submergence and susceptible to drought | Popular variety |
| 2 | IR64 sub1 | Irrigated | Tolerant to Submergence and susceptible to drought | - |
| 3 | FR13A | Shallow low land | Tolerant to Submergence and susceptible to drought | International submergence tolerance donor |
| 4 | CR143-2-2 | Upland | Drought Tolerance | Drought tolerant check |
| 5 | N 22 | Upland | Drought Tolerance | Drought and heat stress check |
| 6 | Brahamanakhi | Upland/Medium land | Drought Tolerance | Landrace |
| 7 | Satyabhama | Upland | Drought Tolerance | Released variety |
| 8 | IR 20 | Irrigated | Drought susceptible | International Check |
| 9 | Nerica1 | Upland/ Aerobic | Drought Tolerance | Suitable for Africa |
| 10 | Azucena | Upland | Drought Tolerance | Tropical japonica |
| 11 | Curinga | Upland | Drought Tolerance | Tropical japonica |
| 12 | MER20 | Upland | Drought Tolerance | CSSLs/BC4F4 of O. meridionalis/ Curinga |
| 13 | RUF44 | Upland | Drought Tolerance | CSSLs /BC4F4 of O. rufipogon/ Curinga |
| 14 | RUF16 | Upland | Drought Tolerance | CSSLs /BC4F4 of O. rufipogon/ Curinga |
| 15 | RUF48 | Upland | Drought Tolerance | CSSLs /BC4F4 of O. rufipogon/ Curinga |
| 16 | RUF13 | Upland | Drought Tolerance | CSSLs /BC4F4 of O. rufipogon/ Curinga |
| Marker | Na | Np | Nu | Fla | Fha | PIC | Marker | Na | Np | Nu | Fla | Fha | PIC |
| RM315 | 2 | 2 | 0 | 1 | 1 | 0.49 | RM596 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM472 | 2 | 2 | 1 | 0 | 1 | 0.12 | RM512 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM302 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM179 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM431 | 2 | 2 | 0 | 1 | 1 | 0.34 | RM277 | 1 | 0 | 0 | 0 | 2 | 0.75 |
| RM212 | 2 | 2 | 0 | 0 | 2 | 0.75 | RM313 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM543 | 2 | 2 | 0 | 0 | 2 | 0.68 | RM83 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM259 | 2 | 2 | 0 | 1 | 1 | 0.53 | RM101 | 2 | 2 | 0 | 1 | 1 | 0.53 |
| RM488 | 2 | 2 | 1 | 0 | 1 | 0.12 | RM309 | 2 | 2 | 0 | 0 | 2 | 0.75 |
| RM521 | 2 | 2 | 0 | 0 | 2 | 0.75 | RM28130 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM526 | 2 | 2 | 0 | 0 | 2 | 0.75 | RM28050 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM555 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28089 | 2 | 2 | 1 | 0 | 1 | 1.00 |
| RM530 | 2 | 2 | 0 | 1 | 1 | 0.96 | RM244 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM279 | 3 | 3 | 0 | 2 | 1 | 0.98 | RM28067 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM416 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28088 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM22 | 2 | 2 | 0 | 1 | 1 | 0.96 | RM28099 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM16030 | 2 | 2 | 0 | 1 | 1 | 0.90 | RM28078 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM60 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM3349 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM15780 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28079 | 2 | 2 | 0 | 1 | 1 | 0.96 |
| RM537 | 2 | 2 | 1 | 0 | 1 | 0.12 | RM28082 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM252 | 3 | 3 | 0 | 0 | 3 | 0.86 | RM28048 | 2 | 2 | 0 | 0 | 2 | 0.75 |
| RM136 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28069 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM527 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28088 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM528 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM1261 | 2 | 2 | 0 | 1 | 1 | 0.96 |
| RM5371 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28075 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM541 | 2 | 2 | 1 | 0 | 1 | 1.00 | RM28051 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM276 | 3 | 3 | 1 | 0 | 2 | 1.00 | RM28050 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM210 | 3 | 3 | 0 | 1 | 2 | 0.34 | RM12091 | 2 | 2 | 0 | 1 | 1 | 0.23 |
| RM339 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28090 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM337 | 2 | 2 | 0 | 0 | 2 | 0.61 | RM28059 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM25 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28095 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM464 | 2 | 2 | 0 | 0 | 2 | 0.00 | Total | 95 | 60 | 6 | 13 | 77 | 41.76 |
| RM566 | 2 | 2 | 0 | 0 | 2 | 0.81 | Mean | 1.5 | 1.0 | 0.1 | 0.2 | 1.2 | 0.66 |
| RM24390 | 1 | 0 | 0 | 0 | 1 | 0.00 |
Table 1 Number of alleles (Na), number of polymorphic alleles (Np), unique allele (Nu), low-frequency allele (Fla), high-frequency allele (Fha) and polymorphism information content (PIC) for 63 simple sequence repeats (SSRs) in 16 rice genotypes.
| Marker | Na | Np | Nu | Fla | Fha | PIC | Marker | Na | Np | Nu | Fla | Fha | PIC |
| RM315 | 2 | 2 | 0 | 1 | 1 | 0.49 | RM596 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM472 | 2 | 2 | 1 | 0 | 1 | 0.12 | RM512 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM302 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM179 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM431 | 2 | 2 | 0 | 1 | 1 | 0.34 | RM277 | 1 | 0 | 0 | 0 | 2 | 0.75 |
| RM212 | 2 | 2 | 0 | 0 | 2 | 0.75 | RM313 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM543 | 2 | 2 | 0 | 0 | 2 | 0.68 | RM83 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM259 | 2 | 2 | 0 | 1 | 1 | 0.53 | RM101 | 2 | 2 | 0 | 1 | 1 | 0.53 |
| RM488 | 2 | 2 | 1 | 0 | 1 | 0.12 | RM309 | 2 | 2 | 0 | 0 | 2 | 0.75 |
| RM521 | 2 | 2 | 0 | 0 | 2 | 0.75 | RM28130 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM526 | 2 | 2 | 0 | 0 | 2 | 0.75 | RM28050 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM555 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28089 | 2 | 2 | 1 | 0 | 1 | 1.00 |
| RM530 | 2 | 2 | 0 | 1 | 1 | 0.96 | RM244 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM279 | 3 | 3 | 0 | 2 | 1 | 0.98 | RM28067 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM416 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28088 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM22 | 2 | 2 | 0 | 1 | 1 | 0.96 | RM28099 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM16030 | 2 | 2 | 0 | 1 | 1 | 0.90 | RM28078 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM60 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM3349 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM15780 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28079 | 2 | 2 | 0 | 1 | 1 | 0.96 |
| RM537 | 2 | 2 | 1 | 0 | 1 | 0.12 | RM28082 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM252 | 3 | 3 | 0 | 0 | 3 | 0.86 | RM28048 | 2 | 2 | 0 | 0 | 2 | 0.75 |
| RM136 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28069 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM527 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28088 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM528 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM1261 | 2 | 2 | 0 | 1 | 1 | 0.96 |
| RM5371 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28075 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM541 | 2 | 2 | 1 | 0 | 1 | 1.00 | RM28051 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM276 | 3 | 3 | 1 | 0 | 2 | 1.00 | RM28050 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM210 | 3 | 3 | 0 | 1 | 2 | 0.34 | RM12091 | 2 | 2 | 0 | 1 | 1 | 0.23 |
| RM339 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28090 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM337 | 2 | 2 | 0 | 0 | 2 | 0.61 | RM28059 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM25 | 1 | 0 | 0 | 0 | 1 | 0.00 | RM28095 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| RM464 | 2 | 2 | 0 | 0 | 2 | 0.00 | Total | 95 | 60 | 6 | 13 | 77 | 41.76 |
| RM566 | 2 | 2 | 0 | 0 | 2 | 0.81 | Mean | 1.5 | 1.0 | 0.1 | 0.2 | 1.2 | 0.66 |
| RM24390 | 1 | 0 | 0 | 0 | 1 | 0.00 |
| Microsatellite marker | Amp. range (bp) | Markers positions (cM) | Chr. | QTLs | Reference |
| RM315 | 120-133 | 165.0 | 1 | qDTY1.1 | Dixit et al, 2012 |
| RM472 | 296-300 | 168.2-172.0 | 1 | qDTY1.1 | Venuprasad et al, 2012 |
| RM431 | 296-250 | 178.3 | 1 | qDTY1.1 | Gimhani et al, 2016; Vikram et al, 2011; Kumar et al, 2014 |
| RM212 | 136-150 | 163.1 | 1 | qDTY1.1 | Vikram et al, 2011 |
| RM488 | 177-200 | 101 | 1 | qDTY1.1 | Kumar et al, 2014 |
| RM555 | 223 | 20.3 | 2 | qDTY2.2 | Kumar et al, 2014 |
| RM279 | 140-174 | 134 | 2 | qDTY2.2 | Sandhu et al, 2018 |
| RM60 | 165 | - | 3 | qDTF3.2 | Vikram et al, 2011; Awasthi, 2014 |
| RM22 | 180-194 | 7.2 | 3 | qDTF3.2 | Vikram et al, 2011; Awasthi, 2014 |
| RM541 | 150-158 | 75.5 | 6 | qDTY 6.2 | Dixit et al, 2012 |
| RM28048 | 80-93 | - | 12 | qDTY12.1 | Awasthi, 2014;Bernier et al, 2009 |
| RM1261 | 160-167 | 61.6 | 12 | qDTY12.1 | Dixit et al, 2012 |
Supplemental Table 2 List of microsatellite markers associated with drought-tolerant QTLs used for assessment of genetic diversity study.
| Microsatellite marker | Amp. range (bp) | Markers positions (cM) | Chr. | QTLs | Reference |
| RM315 | 120-133 | 165.0 | 1 | qDTY1.1 | Dixit et al, 2012 |
| RM472 | 296-300 | 168.2-172.0 | 1 | qDTY1.1 | Venuprasad et al, 2012 |
| RM431 | 296-250 | 178.3 | 1 | qDTY1.1 | Gimhani et al, 2016; Vikram et al, 2011; Kumar et al, 2014 |
| RM212 | 136-150 | 163.1 | 1 | qDTY1.1 | Vikram et al, 2011 |
| RM488 | 177-200 | 101 | 1 | qDTY1.1 | Kumar et al, 2014 |
| RM555 | 223 | 20.3 | 2 | qDTY2.2 | Kumar et al, 2014 |
| RM279 | 140-174 | 134 | 2 | qDTY2.2 | Sandhu et al, 2018 |
| RM60 | 165 | - | 3 | qDTF3.2 | Vikram et al, 2011; Awasthi, 2014 |
| RM22 | 180-194 | 7.2 | 3 | qDTF3.2 | Vikram et al, 2011; Awasthi, 2014 |
| RM541 | 150-158 | 75.5 | 6 | qDTY 6.2 | Dixit et al, 2012 |
| RM28048 | 80-93 | - | 12 | qDTY12.1 | Awasthi, 2014;Bernier et al, 2009 |
| RM1261 | 160-167 | 61.6 | 12 | qDTY12.1 | Dixit et al, 2012 |
Fig. 1. Two-dimensional plot (A) and three-dimensional plot (B) from the principal component analysis (PCA) for 16 rice genotypes based on 63 simple sequence repeat markers.
| Genotype | Swarna-sub1 | IR64-sub1 | FR13A | CR143-2-2 | Bra | Sat | N22 | Nerical | IR20 | Azucena | Curinga | MER20 | RUF44 | RUF16 | RUF48 |
| IR64-sub1 | 0.85 | ||||||||||||||
| FR13A | 0.79 | 0.80 | |||||||||||||
| CR143-2-2 | 0.73 | 0.83 | 0.75 | ||||||||||||
| Bra | 0.77 | 0.78 | 0.75 | 0.78 | |||||||||||
| Sat | 0.79 | 0.90 | 0.78 | 0.93 | 0.82 | ||||||||||
| N22 | 0.72 | 0.77 | 0.81 | 0.85 | 0.75 | 0.86 | |||||||||
| Nerical | 0.78 | 0.84 | 0.77 | 0.86 | 0.81 | 0.93 | 0.87 | ||||||||
| IR20 | 0.73 | 0.74 | 0.68 | 0.76 | 0.73 | 0.82 | 0.77 | 0.83 | |||||||
| Azucena | 0.68 | 0.71 | 0.65 | 0.68 | 0.66 | 0.74 | 0.72 | 0.81 | 0.83 | ||||||
| Curinga | 0.65 | 0.68 | 0.66 | 0.65 | 0.63 | 0.71 | 0.73 | 0.76 | 0.76 | 0.86 | |||||
| MER20 | 0.61 | 0.64 | 0.63 | 0.62 | 0.62 | 0.67 | 0.69 | 0.73 | 0.75 | 0.84 | 0.96 | ||||
| RUF44 | 0.56 | 0.59 | 0.62 | 0.57 | 0.57 | 0.62 | 0.64 | 0.67 | 0.71 | 0.80 | 0.89 | 0.93 | |||
| RUF16 | 0.54 | 0.56 | 0.59 | 0.58 | 0.54 | 0.59 | 0.65 | 0.64 | 0.68 | 0.77 | 0.82 | 0.86 | 0.87 | ||
| RUF48 | 0.54 | 0.56 | 0.59 | 0.58 | 0.54 | 0.59 | 0.65 | 0.64 | 0.68 | 0.77 | 0.82 | 0.86 | 0.87 | 1.00 | |
| RUF13 | 0.56 | 0.57 | 0.58 | 0.57 | 0.55 | 0.58 | 0.62 | 0.61 | 0.65 | 0.73 | 0.78 | 0.82 | 0.83 | 0.96 | 0.96 |
| Bra, Brahamanakhi; Sat, Satyabhama. | |||||||||||||||
Table 2 Genetic similarity coefficient among 16 rice genotypes.
| Genotype | Swarna-sub1 | IR64-sub1 | FR13A | CR143-2-2 | Bra | Sat | N22 | Nerical | IR20 | Azucena | Curinga | MER20 | RUF44 | RUF16 | RUF48 |
| IR64-sub1 | 0.85 | ||||||||||||||
| FR13A | 0.79 | 0.80 | |||||||||||||
| CR143-2-2 | 0.73 | 0.83 | 0.75 | ||||||||||||
| Bra | 0.77 | 0.78 | 0.75 | 0.78 | |||||||||||
| Sat | 0.79 | 0.90 | 0.78 | 0.93 | 0.82 | ||||||||||
| N22 | 0.72 | 0.77 | 0.81 | 0.85 | 0.75 | 0.86 | |||||||||
| Nerical | 0.78 | 0.84 | 0.77 | 0.86 | 0.81 | 0.93 | 0.87 | ||||||||
| IR20 | 0.73 | 0.74 | 0.68 | 0.76 | 0.73 | 0.82 | 0.77 | 0.83 | |||||||
| Azucena | 0.68 | 0.71 | 0.65 | 0.68 | 0.66 | 0.74 | 0.72 | 0.81 | 0.83 | ||||||
| Curinga | 0.65 | 0.68 | 0.66 | 0.65 | 0.63 | 0.71 | 0.73 | 0.76 | 0.76 | 0.86 | |||||
| MER20 | 0.61 | 0.64 | 0.63 | 0.62 | 0.62 | 0.67 | 0.69 | 0.73 | 0.75 | 0.84 | 0.96 | ||||
| RUF44 | 0.56 | 0.59 | 0.62 | 0.57 | 0.57 | 0.62 | 0.64 | 0.67 | 0.71 | 0.80 | 0.89 | 0.93 | |||
| RUF16 | 0.54 | 0.56 | 0.59 | 0.58 | 0.54 | 0.59 | 0.65 | 0.64 | 0.68 | 0.77 | 0.82 | 0.86 | 0.87 | ||
| RUF48 | 0.54 | 0.56 | 0.59 | 0.58 | 0.54 | 0.59 | 0.65 | 0.64 | 0.68 | 0.77 | 0.82 | 0.86 | 0.87 | 1.00 | |
| RUF13 | 0.56 | 0.57 | 0.58 | 0.57 | 0.55 | 0.58 | 0.62 | 0.61 | 0.65 | 0.73 | 0.78 | 0.82 | 0.83 | 0.96 | 0.96 |
| Bra, Brahamanakhi; Sat, Satyabhama. | |||||||||||||||
Fig. 2. Unweighted pair-group method with arithmetic means (UPGMA) dendrogram for 16 rice genotypes based on genetic similarity by 63 simple sequence repeat markers.
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