IJERD – International Journal of Environmental and Rural Development (2021) 12-2

Research article
erd

Assessment of Some Promising Lines of Rice (Oryza sativa
L.) for Salt Tolerance using Microsatellite Markers
Associated with the saltol QTL
MOE KYAW THU*
Department of Agricultural Biotechnology, Yezin Agricultural University Myanmar
Email: dr.moekyawthu@yau.edu.mm

AUNG NAING OO
Department of Soil and Water Science, Yezin Agricultural University, Myanmar

NYO MAR HTWE
Advanced Center for Agariculturla Research and Education, Yezin Agricultural University

OHN MAR LYNN
Department of Agricultural Biotechnology, Yezin Agricultural University Myanmar

KHIN THIDA MYINT
Department of Horticulture, Yezin Agricultural University, Myanmar
Received 30 December 2020

Accepted 19 July 2021(*Corresponding Author)

Abstract Rice is one of the most important staple food crops in the world that grownextensively under irrigation. Salinity is an important physical factor influencing rice (Oryza
sativa L.) production. To assess this limiting factor, YAU developed 100 breeding lines ofrice. After screening at seedling and vegetative stages at different salinity levels (0.2, 6.0, and
8.0 dS m-1), seven rice lines were selected as moderately saline-tolerant genotypes. Theseseven lines (V1: YAU- 1211-14-1-1; V2: YAU1201-90-2-4; V3: YAU-1211-18-1-1; V4:
YAU1211-195-1-1; V5: YAU-1201-26-1-1; V6: YAU1201-26-1-3; and V7: YAU-1211-821-1) along with three local control varieties (Yatanatoe, Superhnankaut and Theehtatyin), one
salt tolerance check (Pokkali) and one susceptible check (IR 29) were used in this study.
Seven Saltol QTL associated SSR markers (RM5, RM9, RM140, RM472, RM493, RM1287
and RM3412) were used to check the usefulness of microsatellite (SSR) markers associatedwith Saltol QTL. The number of alleles on the SSR markers ranged from 2 for RM140 to 4
for RM3412. Polymorphic information content (PIC) value varied from 0.00 for RM140 to
0.62 for RM3412, with an average of 0.36. The SSR marker, RM3412, was found to besuperior for analysis as an indicator of genetic diversity in this study. Cluster analysis of therice genotypes based on SSR data divided the genotypes into three groups, each of which
include Yatanatoe, Theehtatyn, Superhnankaut and susceptible check IR29 (cluster 1), V1,V2 and V3 (cluster 2), V4, V5, V6, V7 including salt tolerance genotypes Pokkali (cluster 3),
respectively. Of the seven lines, four SSR markers (RM5, RM493, RM1287 and RM3412)
could discriminate Pokkali (saltol) from the IR29 (susceptible) genotype. Two specific alleles
were found by RM5 (170) and RM493 (220) for Pokkali. At locus RM140, almost all
genotypes possessed the same allele as Pokkali (260) except Theehtatyin and IR29 (nullallele). RM1285 indicated four YAU rice lines (V4, V5, V6 and V7) as salt tolerance lines.
The study revealed V4: YAU1211-195-1-1 as a tolerance genotype. The RM5, RM493,
RM1287 and RM3412 markers were able to discriminate the tolerant genotypes and hence
could be useful for marker-assisted selection of Saltol QTL.
Keyword promising rice lines, Saltol QTL, SSR marker

INTRODUCTIONⒸ ISERD

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Rice (Oryza sativa) is the staple food of half of the population of the world. Identifying a rice cropthat resists saline incursions due to climate change is prevalent among farmer’s requirements. Soilsalinization has become a serious problem all over the world and around 20% of the world's
cultivated land is affected (Sumner, 2000). In Myanmar, soil salinization is found in both coastal andinland regions, and about 3% of the total rice sown area is affected by salinity (DOA, 2012). Coastal
salinity is often due to seawater intrusion/ infiltration during floods, resulting in salt accumulation in
the topsoil in the summer season. It occurs commonly in Ayeyarwady, Yangon, Yakhaing andTaninthari regions. Inland salinity is common in dry zone areas of central Myanmar such as the
Mandalay, Magway and Sagaing regions. Rice productivity is quite low due to this salinization, withlimited water resources, and low soil fertility in these inland areas of Myanmar (Oo et al., 2017). Sweand Ando (2017) have pointed out that salinity is becoming a prominent abiotic problem, withdeclining rice production in the central dry zone and which has had little attention paid to it. An
improvement in rice breeding programs which offers rice varieties suitable for these changing
conditions is important.
There are many salt tolerant rice varieties providing an opportunity to improve crop salt-stress
tolerance through genetic means. Some attempts based on highly tolerant traditional rice cultivars i.e.
Pokkali and Nona-Bokra have been made to these develop salt-tolerant genotypes (Akbar et al., 1985;
Gregorio and Senadhira, 1993). DNA based molecular markers have been used extensively to assess
the genetic diversity in most crop species (Mohammadi-Nejad et al., 2008). Currently, simple
sequence repeats (SSRs) or microsatellite markers have been used to study genetic diversity,
phylogenetic relationships, classification, evolutionary processes and quantitative trait loci in many
crops. This technique has been used effectively to map QTLs associated with salt tolerance (Lang etal., 2000 and 2001; Singh et al., 2007). A major QTL located on chromosome 1 has been identified
for salt tolerance using F8 recombinant inbred lines (RILs) of Pokkali/ IR29 cross (Gregorio et al.,1997). Therefore, it could be stated that Pokkali represents the most widely used salt tolerant parent
by rice breeders. Our group have developed hundreds of rice breeding lines to transfer salt tolerance
gene of Pokkali to local height yielding varieties.
OBJECTIBESThe present study intended to (i) evaluate salt tolerant rice breeding lines at different growth stages;
seedling and vegetative, and (ii) test the usefulness of microsatellite (SSR) markers associated with
Saltol QTL to identify promising YAU rice lines.
MATERIALS AND METHODS
Evaluation of Selected Improved Rice Lines at Vegetative Stage
This experiment was conducted as a two-factor factorial in a randomized complete block design,with three replications at vegetative stage. Seven promising lines out of YAU 100 improved line
were formerly selected by conducting farmer participatory variety selection based on their preferenceof eating quality and visual assessment in the field. The seven rice selected lines with Pokkali(tolerant check) and IR29 (susceptible check), were grown at three different levels of salinity (0.2,
6.0, and 8.0 dS m-1). Salinity tolerance was rated using a modified standard evaluation system (SES)
rating the visual symptoms of salt toxicity (Gregorio et al., 1997) as shown in Table 1. Following
Gregorio et al. (1997), who modified the method for the screening of rice genotypes at vegetative
stage, the wall of plastic pot was drilled with 3-4 mm diameter holes 2 cm apart, with the topmost
circle of holes at least 3 cm below the rim of the plastic pot. Cotton cloth was used to line the plastic
pots. The pots were filled with fertilized soil, and then placed in the plastic tray filled with ordinary
tap water, which served as a water bath. Four to five pre-germinated seeds of the tested varieties wereplaced on the soil surface of each pot. Two weeks after seeding, seedlings were thinned to one per
pot and the water level was raised to a level about 1 cm above soil. When the seedlings were 25 days
old, all water was siphoned out. Then salinized water, at the different EC saturations, was introduced.
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The water level was maintained on a daily basis and the plants protected from any pests and diseases.
Scoring was started at two weeks after salinization by using a modified standard evaluation system
to rate the visual symptoms of salt toxicity (Gregorio et al., 1997) with results presented in Table 1.
Plant height (cm) and the number of tillers per hill were recorded at 6 weeks after salinization.
Table 1 Modified Standard Evaluation Score (SES) of visual salt injury at seedling andvegetative stages
Score
Observation
1
Normal growth, no leaf symptoms
3
Nearly normal growth, but leaf tips of few leaves whitish and rolled
5
Growth severely retarded, most leave rolled
7Complete cessation of growth, most leaves dry, some plant dying
9
Almost all plant dead or dying
Source; Gregorio et al., 1997

Tolerance
Highly tolerant
Tolerant
Moderately tolerant
Susceptible
Highly susceptible

Microsatellite (SSR) Analysis
A total of twelve genotypes including seven YAU promising rice line (V1: YAU- 1211-14-1-1; V2:
YAU1201-90-2-4; V3: YAU-1211-18-1-1; V4: YAU1211-195-1-1; V5: YAU-1201-26-1-1; V6:
YAU1201-26-1-3; and V7: YAU-1211-82-1-1) and three local control varieties (Yatanatoe,
Superhnankaut and Theehtatyin), one susceptible check (IR29) and one tolerance check (Pokkali)
were used to extract total genomic DNA. A modified CTAB method was used to extract DNA fromthe plants’ young leaves. The relative purity and concentration of extracted DNA was estimated with
NanoDrop ND-1000 (NanoDrop Technologies, Inc., Wilmington, DE, USA). The final concentrationof each DNA sample was adjusted to 50 ng/µl.
Seven Saltol QTL associated SSR markers (RM5, RM9, RM140, RM472, RM493, RM1287
and RM3412) were used to check the usefulness of microsatellite (SSR) markers associated with
Saltol QTL in the identification of promising YAU rice lines (Mohammadi-Nejad et al., 2008).
GoTaq®Colorless Master Mix M713 was used according to the manufacturer’s procedure for PCR
amplification. The PCR reaction was a 10 μl volume using a Boeco Thermal Cycler TC-SQ (Boeco
Germany). The PCR profile; 5 min of denaturation at 94°C, 35 cycles were performed for 1 min at
94°C, 45 s at 55°C, 1 min at 72°C, and a final extension step of 5 min at 72°C. PCR amplified
products were separated in 2% agarose gel at 100 V for 1 h in 1 x TBE buffe. RedSafe™ Nucleic
Acid Staining Solution (20,000x) was used to stain DNA in the agarose gel. The resulting DNA
bands were scored as base pairs using grid lines in photoshop, comparing 100 bp DNA ladder bands.
Data Analysis
The data collected were analyzed statistically using Analysis of Variance (ANOVA) techniques, andrice lines means were compared by least significant different (LSD) method at a 5% probability level.
All statistical analyses were done using Statistix 8.0 software and Excel program (2010).
The variability at each locus was measured in terms of the number of alleles, major allele
frequency (MAF), and polymorphic information content (PIC) using PowerMarker 3.25 (Liu andMuse, 2005). The UPGMA algorithm of MEGA6 software embedded in PowerMarker was used toconstruct an unrooted neighbour-joining tree of each accession based on the shared allele distances(Tamura et al., 2007).
RESULTS AND DISCUSSION
Evaluation of Selected Improved Rice Lines at the Vegetative Stage
The sight evaluation scores (SES), showed a variation in response to salt stress among the rice lines.
SES increased with an increase in stress level, indicating greater susceptibility at higher stress levelⒸ ISERD

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(Table 2). All seven improved rice lines at vegetative stage grew strongly and showed uniform green
colour in non-salinized conditions (0.2 dS m-1 ). In salinized conditions (6.0 and 8.0 dS m-1 ), the ricelines showed significant differences for salt tolerance at the vegetative stage, with scores ranging
from score 1 (highly tolerant) to score 9 (highly susceptible) (Table 2). The seven rice lines selected
showed a high degree of tolerance and moderate tolerance, respectively, under increasing salinity
levels (6.0 and 8.0 dS m-1).
The reactions of the selected improved rice lines in terms of plant height and number of tillers
per hill, under three different salinity levels at the vegetative stage, are showed in Table 3. The plantheights are significantly different among the rice lines in the non-salinized condition (0.2 dS m-1). In
contrast, these parameters were not significantly different among the rice lines in the two salinizedconditions. Similarly, the number of tillers per hill was not significantly different among the ricelines in all conditions.
Table 2 Reactions of improved rice lines at vegetative stage to salinity at three different levels
measured by Standard Evaluation Score (SES)
Improved rice lines
YAU-1211-14-1-1
YAU-1201-90-2-4
YAU-1211-118-1-1
YAU-1211-195-1-1
YAU-1201-26-1-1
YAU-1201-26-1-3
YAU-1211-82-1-1
PokkaliIR29

0.2 dS m-1
Highly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerantHighly tolerant

Reaction to salinity at 6 weeks after salinization
6.0 dS m-1
8.0 dS m-1
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Moderately tolerant
Tolerant
Tolerant
Highly susceptible
Highly susceptible

Table 3 Reactions of selected improved rice lines at the vegetative stage to salinity at threedifferent levels measured by plant height and number of tillers per hill
Plant height (cm)Number of tillers per hill
0.2 dS m-1
6.0 dS m-1
8.0 dS m-1
0.2 dS m-1
6.0 dS m-1
8.0 dS m-1
YAU-1211-14-1-1
39.0 bcd
32.7
26.3
4.7
4.0
3.0
YAU-1201-90-2-4
37.3 de
32.3
25.7
4.3
4.0
3.3
YAU-1211-118-1-1
42.0 ab
32.7
23.7
4.3
3.7
3.3
YAU-1211-195-1-1
39.7 bcd
33.3
24.0
4.0
3.7
3.3
YAU-1201-26-1-1
44.7 a
32.0
26.7
5.0
4.3
4.0
YAU-1201-26-1-3
38.0 cde
35.7
22.7
4.0
3.3
3.3
YAU-1211-82-1-1
40.7 bc
34.0
27.3
4.3
3.7
4.0
Pokkali
35.3 ef
36.3
25.0
4.3
3.3
3.3
IR29
33.0 f
31.7
24.0
3.7
3.7
3.3
F-test
**
ns
ns
ns
ns
ns
C.V %
4.6
5.5
9.2
15.2
18.6
19.4
Values in the same column followed by the same letter are not significantly different at the 5% level by the LSD test, (**)
significantly different at P≤0.01, ns − not significant
Improved rice lines

Microsatellite (SSR) Analysis
The number of alleles of the SSR markers ranged from 2 for RM140 to 4 for RM3412. Polymorphic
information content (PIC) values varied from 0.00 for RM140 to 0.62 for RM3412, with an averageof 0.36 (Table 4). The measure, or value of the PIC, is determined by the ability of a marker toestablish polymorphism in the population depends on the number of alleles detected and on theirdistribution frequency (Botstein et al., 1980). The PIC value of the marker is defined as the expected
fraction of informative offspring from the type of pedigree (Hildebrand, et al. 1992). In this regard,
SSR marker, RM3412, was found to be superior for discrimination of potential breeding lines in thisstudy.

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Cluster analysis of the rice genotypes based on SSR data, separated the genotypes into threegroups, each of which had Yatanatoe, Theehtatyn, Superhnankaut and susceptible check IR29
(cluster 1), V1, V2 and V3 (cluster 2), V4, V5, V6, V7, including salt tolerance genotypes Pokkali(cluster 3), respectively (Figure 1). Out of the seven varieties, four SSR markers (RM5, RM493,
RM1287 and RM3412) were able to discriminate Pokkali (Saltol) from IR29 (susceptible) genotype.
Two specific alleles were found by RM5 (170) and RM493 (220) for Pokkali. At locus RM140,
almost all genotypes possessed the same allele as Pokkali (260), except for Theehtatyin and IR29
(null allele). Null alleles were likely to be encountered in populations with a large size, with unusuallyhigh mutation rates in the flanking regions, and those that have diverged from the population fromwhich the cloned allele state was drawn and the primers designed (Chapuis and Estoup, 2007).
Theehtatyin and IR29 would exhibit mutations in this locus, RM140. RM1285 was an indicator thatfour YAU rice lines (V4, V5, V6 and V7) are salt tolerant lines. These results, in combination,
revealed V4: YAU1211-195-1-1 as saline tolerant genotypes. The RM5, RM493, RM1287 andRM3412 markers were able to discriminate for tolerant genotypes and hence could be useful formarker-assisted selection of Saltol QTL.
Table 4 Number of alleles and polymorphism information content (PIC) values of
SSR markers for 12 rice genotypes
Marker
RM5
RM9
RM140
RM472
RM493
RM1287
RM3412Frequency ofmajor allele
0.92
0.44
1.00
0.83
0.50
0.56
0.42

No. of allele
2
3
1
2
3
3
4

PIC
0.14
0.57
0.00
0.24
0.48
0.49
0.62

Amplicon size
range (bp)150-170
100-170260
320-350
220-250
125-160
200-260

Fig. 1 Dendrogram of 12 rice genotypes based on 7 polymorphic SSR markers
derived from the Shared allele distance with neighbor joint method
CONCLUSION
In conclusion, in this study seven YAU improved rice lines were observed for relative salt tolerance
in terms of agronomic parameters such as tiller numbers, panicle numbers and grain yield. Results
show that four rice breeding lines; V4, V5, V6, V7 have the potential to be developed for future
improvement as salt tolerant rice varieties. Furthermore, the result highlights the usefulness of SSR
markers associated with saltol QTL for the screening of rice breeding lines. The RM5, RM493,
RM1287 and RM3412 markers may be useful for marker-assisted selection.
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ACKNOWLEDGEMENTS
The authors would like to thank the JICA (Japan International Cooperation Agency) for theirfinancial support for this project and the capacity development they have fostered at Yezin
Agricultural University.
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