
Salinity, among all the abiotic stresses is a highly promi-nent issue that severely affects plant growth and develop-ment (Nazar
Rice is the major staple food crop in Bangladesh, which covers about 81% of total cropped area (BBS 2012). The country ranked 4th position in 2014 both in area (11.77 million ha) and production (52.231 million MT) of rice, and 39th in the yield per hectare (4.42 tha-1) among the rice growing countries (FAOSTAT, http://faostat.fao.org/site/291/default.aspx). In Bangladesh,
However, development of salinity tolerance in crop plants through breeding programs largely depends on the good understanding of the tolerance mechanisms against salinity in the susceptible and tolerant genotypes (Cha-um
In our present study, we tested salt tolerance and classified 20 coastal
We screened 20 coastal
To screen the salt tolerant coastal
For studying the seedling salinity tolerance of coastal
Data were recorded on salt injury score (SIS), ion-leak percent, reduction percent on chlorophyll concentration, shoot length and root length from three individual plants per experiment.
Ion leakage from the leaf tissue as an indicator of early response of rice genotypes against salinity was measured following De Leon
After 4 days post-salinization (DPS) the leaf yellowing was noticed. The comparative chlorophyll intensity (SPAD value) was estimated from the central part of the second youngest leaf both in control and salt-induced rice genotypes using chlorophyll meter (SPAD-502 Plus, Konica Minolta, Japan) to find out differences among rice genotypes. The reduction percent (% R) of chlorophyll content was calculated by the formula: Chl_R = 100 (Chl0 ‒ Chlt/Chl0); here Chl_R means the percent reduction of chlorophyll concentration; ‘Chl0’ denoted for the chloro-phyll content in control condition; ‘Chlt’ represent the chlorophyll content in saline treatment.
We monitored root length and shoot length both in control and salt-induced rice genotypes at 7 DPS. All assessments were done with regard to the control plant to find genotypic differences. The percent (%) reduction in root length and shoot length were measured employing similar formula as in the case of chlorophyll percent reduction.
Symptoms of salt injury in plants started to appear from 7 DPS. Here, standard evaluation scoring (SES) method of IRRI was followed for visual scoring (Gregorio
To test the treatment effects on genotypes, morpho- physiological data were statistically analyzed and mean trait values were compared at 0.05%, 0.01% and 0.001% level of significance. Correlation among traits was also computed based on the mean trait values of three repli-cations. To classify the salinity tolerant genotypes, the mean trait values of genotypes for five traits were em-ployed for multivariate cluster analysis using JMP8 soft-ware (JMPⓇ8, SAS Institute Inc., Cary, NC, 1989-2019). The clustering of genotypes were done as moder-ately tolerant (MT), tolerant (T), highly tolerant (HT), highly sensitive (HS) and sensitive (S) based on the scoring of the group average SIS. Classification of genotypes was confirmed using discriminant analyses for each genotype with the same data used for clustering. To figure out the variation among salinity groups, multivariate analysis of variance (MANOVA) was run in JMP8. Thus, we classified 20
We extracted genomic DNA from rice seedlings of 25-day-old using Promega A1120 DNA cleansing kit (Promega, USA) following the producer instructions. Extracted DNA was quantified using Nano-100 micro spectrophotometer (BOYN, China) and finally concentra-tion was adjusted to 25 ng/mL through dilution.
A set of 10 SSR primer pairs were primarily selected for the analysis of genotypic variation to salinity tolerance among the collected 20 rice genotypes (Supplementary Table 2). Based on banding patterns and potential for population discrimination two polymorphic SSR markers RM3412 and RM493 linked to
PCR cocktail of 15 mL was prepared by mixing 1mL forward primer, 1 mL reverse primer, 7.5 mL Go TaqⓇ Green Master Mix (Promega, USA), 1.0 mL of extracted rice DNA (25 ng/mL), and 4.5 mL of nuclease free water. PCR (Applied Biosystems, USA) was done following the condition as follows: initialization for 5 minutes at 94℃ and 35 cycles of amplification for 45 secconds at 94℃, for 45 seconds at 55℃, for 1 minutes at 72℃ and final expansion at for 5 minutes at 72℃. To detect band, gel electrophoresis was done after PCR in 2% gel of agarose adding with ethidium bromide. Visualization of banding patterns was performed with UV transilluminator gel documentation unit. The banding patterns of 20 rice germplasm were genotyped comparing with tolerant and susceptible control variety. The genotypes having the same banding pattern to the salt tolerant check variety were considered as tolerant and similar to salt susceptible check variety were considered as salt susceptible. Thus, we genotyped 20
Considering morpho- physiological responses of 20
Table 1 . Mean trait values of coastal
Genotype | SIS | Ion-leakge (uS/cm) | Ion-leak (%) | Chlo-rophyll content (SPAD unit) | Chl-R (%) | Root length (cm) | RtL-R (%) | Shoot length (cm) | StL-R (%) | ||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ro | Rt | Ctr | Sal | Ctr | Sal | Ctr | Sal | ||||||
5* | 0.04 | 0.36 | 33.33** | 17 | 12 | 29.41** | 7 | 5 | 28.57 | 32 | 28 | 12.5 | |
9 | 0.6 | 0.73 | 32.5** | 12 | 4 | 66.67 | 8 | 6 | 25 | 30 | 12 | 60+++ | |
9 | 0.09 | 0.67 | 63.74 | 19 | 5 | 73.68 | 7 | 5 | 28.57 | 25 | 10 | 60+++ | |
7 | 0.05 | 0.38 | 34.74** | 15 | 8 | 46.67 | 6 | 5 | 16.67** | 26 | 13 | 50+++ | |
7 | 0.06 | 0.37 | 32.98** | 14 | 9 | 35.71* | 7 | 6 | 14.29** | 29 | 18 | 37.93+ | |
9 | 0.09 | 0.58 | 53.85 | 18 | 4 | 77.78 | 6 | 5 | 16.67** | 27 | 14 | 48.15++ | |
7 | 0.09 | 0.39 | 32.97** | 12 | 5 | 58.33 | 7 | 7 | 0*** | 21 | 19 | 9.52 | |
7 | 0.05 | 0.57 | 54.74 | 18 | 7 | 61.11 | 8 | 7 | 12.5** | 27 | 17 | 37.04+ | |
3*** | 0.07 | 0.33 | 27.96*** | 18 | 5.56*** | 8 | 7 | 12.5** | 30 | 24 | 20 | ||
7 | 0.04 | 0.55 | 53.13 | 14 | 6 | 57.14 | 9 | 8 | 11.11** | 30 | 22 | 26.67 | |
7 | 0.04 | 0.53 | 51.04 | 18 | 517 | 72.22 | 9 | 7 | 22.22 | 26 | 20 | 23.07 | |
5* | 0.61 | 0.75 | 35.90** | 20 | 15 | 25** | 7 | 6 | 14.29* | 21 | 19 | 9.53 | |
1*** | 0.05 | 0.31 | 27.37*** | 18 | 16 | 11.11*** | 8 | 6 | 25 | 32 | 25 | 21.88 | |
5* | 0.07 | 0.32 | 26.89*** | 14 | 13 | 7.14*** | 7 | 4 | 42.86 | 23 | 21 | 8.69 | |
5* | 0.03 | 0.33 | 30.93** | 15 | 13 | 13.34** | 6 | 5 | 16.67* | 23 | 22 | 4.35 | |
3** | 0.05 | 0.32 | 28.42*** | 19 | 17 | 10.53*** | 9 | 8 | 11.11** | 19 | 18 | 5.26 | |
7 | 0.06 | 0.49 | 45.74* | 14 | 8 | 42.86 | 8 | 7 | 12.5** | 32 | 16 | 50+++ | |
9 | 0.07 | 0.61 | 58.06 | 16 | 9 | 43.75 | 6 | 4 | 33.33 | 33 | 12 | 63.63+++ | |
5* | 0.08 | 0.37 | 31.52** | 15 | 12 | 20** | 7 | 6 | 14.29* | 25 | 21 | 16 | |
3** | 0.04 | 0.32 | 29.17*** | 16 | 13 | 18.75*** | 6 | 5 | 16.67* | 27 | 24 | 11.11 | |
BRRI dhan48 | 7 | 0.11 | 0.56 | 50.56 | 22 | 11 | 50 | 5 | 4 | 20 | 16 | 10 | 37.5+ |
Binadhan-10 | 3** | 0.07 | 0.34 | 29.03*** | 25.9 | 18.7 | 27.79** | 8 | 7 | 12.5** | 22 | 19 | 13.64 |
Genotypic effect (Pr > F) | < .0001 | < .0001 | < .0001 | < .0001 | < .0001 |
SIS: salt injury score, Ion-leak: index of injury by ion leakage, Ro: ion leakage in control treatment, Rt: ion leakge in saline treatment, Ctr: control, Sal: saline treatment, Chl-R: % chlorophyll reduction, Shl- R: % shoot length reduction, Rt-R: % root length reduction, *: Significantly different to BRRI dhan48 at 0.05 probability level, **: Significantly different to BRRI dhan48 at 0.01 probability level, ***: Significantly different to BRRI dhan48 at 0.001 probability level, +: Significantly different to Binadhan-10 at 0.05 probability level, ++: Significantly different to Binadhan-10 at 0.01 probability level, +++: Significantly different to Binadhan-10 at 0.001 probability level.
A highly significant genotypic differences (
A highly significant (
Highly significant (
Percent (%) root length reduction (RtL-R) and shoot length reduction (ShL-R) revealed the differences among genotypes (
Among the check varieties, BRRI dhan48 showed highest shoot length reduction (37.5%), while Binadhan-10 showed lowest shoot length reduction (13.64%). Among the coastal genotypes,
From the individual relationship of physiological traits, a positive and high correlation in case of SIS was observed with %R of chlorophyll, ion-leak, and shoot length but negatively correlated with %R of root length (Table 2). Ion-leak was positively correlated with percent reduction of chlorophyll, root length, shoot length, and SIS. Percent of chlorophyll reduction was negatively correlated with %R of root length and positively correlated with SIS, ion-leak, as well as %R of shoot length. Root length %R was positively linked with %R of shoot length, ion-leak but negatively correlated with SIS, chlorophyll %R.
Table 2 . Pearson correlation matrix of five seedling traits against salinity (12 dS/m) in 20
Traits | SIS | Ion-leak | Chl-R | RtL-R | ShL-R |
---|---|---|---|---|---|
SIS | 1 | ||||
Ion-leak | 0.6968*** | 1 | |||
Chl-R | 0.7721*** | 0.7048*** | 1 | ||
RtL-R | ‒0.1606 | 0.0273 | ‒0.0927 | 1 | |
ShL-R | 0.6586*** | 0.6521*** | 0.6385*** | 0.2289 | 1 |
SIS: salt injury score, Chl-R: % chlorophyll reduction, Shl- R: % shoot length reduction, Rt-R: % root length reduction, *: Significant at the 0.05 probability level, **: Significant at the 0.01 probability level, ***: Significant at the 0.001 probability level.
Clustering study through dendogram revealed 2 highly tolerant (HT) genotypes including one local genotype (Binadhan-10 and
We performed canonical discriminant analysis to evalu-ate the level of diversity among salinity groups (Fig. 2). We found two canonical discriminant functions. Canonical discriminant function 1 (Can 1) was positively correlated to SIS, Ion-leak, Chl-R, RtL-R, ShL-R. In contrast, a negative correlation with SIS, Ion-leak and RtL-R was evident in case of canonical discriminant function 2 (Can 2). Therefore, this result indicates Can 1, Can 2 differentiates genotypes based on their ion-leak (%), percent reduction of chloro-phyll concentrations, root length, and shoot length. In Can 1, the largest detachment of group means regarding HT and S (4.18 and 3.59) was observed, while mean separation between HS and T was 3.99 vs. 2.22 (Fig. 2). Examination of Can 2 indicated the detachment of group HT from the T (4.18 vs. 2.22) and differences of MT from the S group (3.31 vs. 3.59). Four groups (T, MT, S and HS) except HT had negative mean values to Can 2. In contrast, positive mean sores were found for each of the group to Can 1. In canonical plot, MT group was located in the middle of the T and S groups (Fig. 2). The HT group with positive value (+4.18) in both the case for Can1 and Can 2 indicating their low values in SIS, Chl-R, RtL-R, and ShL-R. The T group with positive mean value to Can 1 (+2.20) and negative mean value to Can 2 (‒2.20), suggesting their proximity to the HT group, but it has higher shoot length and chlorophyll reduction as opposed to HT categories. For the T and MT, a positive and negative mean values for T group were observed, respectively in the Can 1 and Can 2. Finally, a positive mean value to Can 1 (+3.59) and negative mean value to Can 2 (‒3.59) were found in case of the sensitive (S) group.
From a multivariate analysis of variance (MANOVA), significant differences were evident for salinity tolerance groups (HS, HT, MT, S and T) against five variable parameters (ion-leak, SIS, Chl-R, Rtl-R and Shl-R). Moreover, comparison study for each of the trait between groups through LS mean values indicated significant variations between HT vs. S & HS groups in all the cases (Table 3). Similarly, a significant difference was evident for the group T from HT in case of RtL-R, ShL-R and from MT in ion-leak, Chl-R, RtL-R. Besides, the group S and MT were significantly different due to having significantly different values for ShL-R, SIS, Chl-R and the group S differed with HS only for the significant difference in ShL-R. Thus, the whole pairwise comparison is highly significant indicating complete partitioning among groups based on the five important quantitative parameters.
Table 3 . Least square (LS) means of salinity groups in five parameters.
Group | SIS | Ion-leak(%) | Chl-R(%) | RtL-R(%) | ShL-R(%) |
---|---|---|---|---|---|
HS | 9 | 52.04 | 65.47 | 25.89 | 57.95 |
HT | 1 | 27.37 | 11.11 | 25.00 | 21.88 |
MT | 5 | 33.37 | 22.05 | 26.19 | 13.81 |
S | 7 | 43.08 | 54.50 | 13.73 | 33.07 |
T | 3 | 28.47 | 14.63 | 12.04 | 12.97 |
SIS: salt injury score, Chl-R: % chlorophyll reduction, Shl- R: % shoot length reduction, Rt-R: % root length reduction, HS: highly sensitive, HT: highly tolerant, MT: moderately tolerant, S: sensitive.
From the morpho-physiological and genotypic perfor-mance, we considered Binadhan-10 as tolerant and BRRI dhan48 as susceptible. Coastal genotypes were identified as tolerant having banding pattern similar to Binadhan-10 and as salt susceptible alike to banding pattern of BRRI dhan48 (Supplementary Figs. 1, 2 and Table 4). In respect to primer RM493, we found 3 coastal genotypes
In a nutshell as represented in Table 4, 7 genotypes
Table 4 . Genotypic profiles of 19 coastal
Sl No. | Genotype | Predicted salt tolerance levels using SSR | |
---|---|---|---|
RM 493 | RM3412 | ||
1 | T | T | |
2 | S | T | |
3 | S | T | |
4 | S | T | |
5 | S | S | |
6 | S | T | |
7 | T | T | |
8 | T | T | |
9 | T | S | |
10 | S | T | |
11 | S | S | |
12 | T | S | |
13 | T | T | |
14 | T | T | |
15 | T | T | |
16 | S | S | |
17 | S | S | |
18 | S | S | |
19 | S | T | |
20 | BRRI dhan48 | S | S |
21 | Binadhan-10 | T | T |
T: tolerant, S: susceptible.
Here, we have done genotypic diversity analysis of 20
We observed that genotypes were significantly different in case of shoot parameters than that of roots (Table 1), indicating about greater role of shoots in salt tolerance. This might be the fact that shoots confronted higher levels of salinity provoked DNA methylation compared with roots in many of the tested rice varieties under salt stress (Karan
We employed cluster analysis to identify the HT, T, MT, S and HS salinity group (Fig. 1). Discriminant analyses along with multivariate analysis of the target traits were also conducted in investigating the phenotypic and genetic diversity of the salt induced coastal genotypes. From the discriminant analysis and multivariate analysis of traits at seedling stage, highly significant genotypic differences and correlations among ion-leakage, SIS, chlorophyll content, shoot length and root length reduction were observed and thus, delineated the differences in salt tole-rance among 20 coastal genotypes which coincides the results of Yeo
In the final validation study, we used SSR marker for determining any genetic variation and unraveling cultivars’ identity (Ni
For final molecular validation two polymorphic SSR markers
Further, Babu
To compare the data on multivariate analyses of several morpho-physiological traits regarding seedling salinity tolerance of coastal rice with their subsequent validation using RM3412 and RM493 reveals 4 genotype
Here we successfully identified the diversity among 20 Bangladeshi coastal
We thank Research and Training Centre (Grant# 4829: Ag-19; 2018-2019); Patuakhali Science and Technology University, Bangladesh for providing the fund for this research work.
GS, SCS and AKC conceived the concept. HS carried out research work under supervision of GS, SCS and AKC. HS and US analyzed data and drafted the manuscript. GS, SCS and AKC critically edited the manuscript. All authors read and approved the final version of the manuscript.
The authors declare that there is no potential conflict of interest relevant to this article.
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