Top PDF SALINITY TOLERANCE OF RICE (ORYZA SATIVA L.) SEEDLINGS IN PRESENCE OF AQUEOUS EXTRACT OF TESTA OF CASHEW NUT (ANACARDIUM OCCIDENTALE L.)

SALINITY TOLERANCE OF RICE (ORYZA SATIVA L.) SEEDLINGS IN PRESENCE OF AQUEOUS EXTRACT OF TESTA OF CASHEW NUT (ANACARDIUM OCCIDENTALE L.)

SALINITY TOLERANCE OF RICE (ORYZA SATIVA L.) SEEDLINGS IN PRESENCE OF AQUEOUS EXTRACT OF TESTA OF CASHEW NUT (ANACARDIUM OCCIDENTALE L.)

and washed with sterile distilled water for 5 times. Petri dish (14 cm diameter in size) lined with a thin layer of cotton and Whatman filter paper 1 moistened with 20 mL salinity treatments of 0.5%, 1.0% and 2% (w/v) NaCl with or without aqueous testa extract, 30 rice seeds were disposed on it [26, 27] and distilled sterilized water used as control treatments. There were duplicates for each treatment in completely randomized block design. Petri dishes were incubated at room temperature (29±1 o C). Germination test was performed as per ISTA rules, 1999. Germination of seeds was recorded for seven days after every 24 hours. Seedling growth was measured on 7 th , 10 th and 15 th day. Germination percentage [28], shoot, root and seedling height (mm), fresh and dry weight of shoot and root were measured. Speed of germination, response index [29], seedling vigour index [30] and seedling growth parameters were used for evaluation of effect of testa aqueous extract on salinity tolerance. Data was subjected to ANOVA [31] and excel 2007 was used for data analysis and preparing graphs.
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Salinity tolerance mechanisms in glycophytes: An overview with the central focus on rice plants

Salinity tolerance mechanisms in glycophytes: An overview with the central focus on rice plants

2009). Interestingly, in the presence of 100 mM NaCl, the upward Na + transport rate in barley, which is the most salt tolerant cereal, is much lower (only 20%) when compared to that in rice plants (Munns 1985), suggest- ing a significant contribution of Na + bypass flow in salinity-induced shoot Na + accumulation in rice plants. In roots, there are morphological components to prevent non-selective apoplastic flow of water and ions into the stele. These morphological components are Casparian bands and suberin lamellae at the root exo- and endo- dermis (Enstone et al. 2003). Casparian bands and su- berin lamellae are deposited in anticlinal walls and on the inner face of the primary cell walls, respectively. Though the mechanism of bypass flow has not been completely understood, bypass flow-mediated Na + over- accumulation in shoots of rice plants is believed to be the outcome of a passive leakage of Na + into the xylem over the morphological barriers. Since the apoplastic space of the leaf is relatively small, the effect of a large quantity of Na + reaching the xylem in saline conditions is significant. In other words, the accumulation of even only a small portion of Na + in the leaf apoplastic space causes large changes in ion concentrations of the space. According to the estimate of Yeo and Flowers (1986), even if 99% of arriving Na + is successfully sequestered into the expanded rice leaves during salinity stress, the apoplastic Na + concentration could reach 500 mM within 7 days, which would lead to severe cell dehydra- tion and stomatal closure. Furthermore, shoot apoplas- tic Na + accumulations were found to be negatively correlated with the survival of rice varieties including a highly salt tolerant cultivar Pokkali (Krishnamurthy et al. 2009; Krishnamurthy et al. 2011). Therefore, reducing Na + transport to the shoots via apoplastic bypass flow is one of the primary subjects to solve in order to enhance salinity tolerance of rice plants.
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Assessing trait contribution and mapping novel QTL for salinity tolerance using the Bangladeshi rice landrace Capsule

Assessing trait contribution and mapping novel QTL for salinity tolerance using the Bangladeshi rice landrace Capsule

Exploring rice germplasm with useful traits is a key step for pre-breeding programs to identify useful alleles. Capsule (locally known as ‘Capsail’), a salt tolerant, widely adapted Bangladeshi indica landrace, has been identified as a good donor for salinity tolerance having superior phenotype for Na + exclusion and early seedling vigor (Rahman et al. 2016). We anticipated that Capsule would have novel genetic variation for salinity tolerance, in comparison with Pokkali and Nona Bokra, which have been well exploited by physiologists and molecular biol- ogists as salt-tolerant genotypes. The superior tolerance of salinity in Pokkali is attributed to two main traits: its capacity to maintain a low Na + -K + ratio in the shoot tis- sue and its faster growth rate under saline conditions, which helps in diluting the salt and reducing toxicity stress within the tissue (Walia et al. 2005; Ismail et al. 2007; Thomson et al. 2010). Mapping of QTL is import- ant to augment our knowledge of the inheritance and genetic architecture of quantitative traits (Mackay 2001). It also facilitates developing markers for complex traits
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Introgression the Salinity Tolerance QTLs Saltol into AS996, the Elite Rice Variety of Vietnam

Introgression the Salinity Tolerance QTLs Saltol into AS996, the Elite Rice Variety of Vietnam

The donor rice variety FL478 (IR 66946-3R-178-1-1), has been promoted as an improved donor for breeding programs, as it has a high level of seedling stage salinity tolerance and is photoperiod insensitive, shorter and flowers earlier than the original Pokkali landrace. Saltol is a major QTL associated with the Na-K ratio and seed- ling-stage salinity tolerance, was identified on chromo- some 1. This QTL was tested in a hydroponic screen at the seedling stage revealed that this QTL explained 43% of the variation for seedling shoot Na-K ratio and salinity tolerance in the population [4]. Furthermore, an analysis of single feature polymorphism in the Saltol region sug- gested that FL478 contained a DNA fragment smaller than 1 Mb from Pokkali at 10.6 - 11.5 Mb on chromo- some 1 [5].
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Image-based phenotyping for non-destructive screening of different salinity tolerance traits in rice

Image-based phenotyping for non-destructive screening of different salinity tolerance traits in rice

Several studies have used image based phenotyping to measure salinity tolerance in crops, in particular wheat and barley (Rajendran et al. 2009; Sirault et al. 2009; Harris et al. 2010), where digital colour images were used to quantify plant biomass, leaf area and health (Rajendran et al. 2009; Harris et al. 2010; Golzarian et al. 2011). The measurement of senescent leaf area in combination with the measurement of shoot Na + concentration enabled the quantification of shoot tissue tolerance in salt stressed einkorn wheat (Triticum monococcum) (Rajendran et al. 2009). Infrared thermography has also been used to meas- ure leaf temperature, as a surrogate for stomatal conduct- ance, to screen the osmotic tolerance of barley and durum wheat seedlings (Sirault et al. 2009) and rice (Siddiqui et al. 2014). In the current study, high-throughput image acquisition and analysis was used to study the salinity tol- erance traits of two rice cultivars (IR64 and Fatmawati) under different levels of salt stress. The use of this tech- nology for screening individual salt tolerance traits in rice, as well as whole plant salt tolerance, is demonstrated here. These methods can now be used in genetic studies to in- form breeding programs of approaches to improve the sal- inity tolerance of rice.
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Validation of a major QTL for salinity tolerance on chromosome 1 of rice in three different breeding populations

Validation of a major QTL for salinity tolerance on chromosome 1 of rice in three different breeding populations

Summary. – The effect of a major quantitative trait locus (QTL) for salinity tole- rance in rice, designated as SalTol in a previous study, was tested using three F2 bree- ding populations. The populations were derived from the following F1 hybrids: ‘BRRI dhan40’ (susceptible)/ ‘IR61920-3B-22-2-1’ (highly tolerant); ‘BRRI dhan28’ (highly susceptible)/ ‘IR50184-3B-18-2B-1’ (moderately tolerant); and ‘Kajalsail’ (tolerant)/ ‘IR52713-2B-8-2B-1-2’ (tolerant). Targeted mapping of the chromosome region con- taining SalTol (49.6 to 87.1 cM) on chromosome 1 was conducted using 20 SSR and two EST markers. Comparisons of linkage maps of the three populations were very similar to the previous QTL map that identified SalTol. A QTL was only detected for ‘BRRI dhan40’/ ‘IR61920-3B-22-2-1’ population. The SSR marker RM8094 was the most tightly-linked marker (P<0.001); four other markers, RM1287, RM3412, RM493 and CP03970, were also significantly associated with salinity tolerance (P<0.05). An F 3 population of the cross ‘BRRI dhan40’/ ‘IR61920’ was used to reconfirm this result.
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Mapping QTLs using a novel source of salinity tolerance from Hasawi and their interaction with environments in rice

Mapping QTLs using a novel source of salinity tolerance from Hasawi and their interaction with environments in rice

Results of comparative analysis of the QTL positions identified in the study compared with the QTL positions identified in earlier studies as being associated with salinity tolerance at various growth stages are shown. Rice cultivars grown in saline environments are most sensitive at both the vegetative and reproductive stages. However, the relationship between tolerances at the two stages is poor, suggesting that they are regulated by different processes and genes (Singh and Flowers 2010; Hossain et al. 2015; Rahman et al. 2016; Ahmadizadeh et al. 2016). The major QTL Saltol, derived from salt-tolerant land- race Pokkali, has been mapped on chromosome 1. This QTL confers salt tolerance at the vegetative stage and explains between 39.2% and 43.9% of the PVE in the original RIL population (Bonilla et al. 2002), but further studies found that Saltol alone does not work as a robust QTL (Thomson et al. 2010). A gene for salt tolerance at the vegetative stage, SKC1 , has been identified in the same region from Nona Bokra and positionally cloned (Ren et al. 2005). SKC1 maintains K + homoeostasis in the salt-tolerant cultivar under salt stress, and the gene encodes a member of HKT-type transporters. This gene turns out to be a protein in the HKT family that exclusively mediates K + and Na + translocation between roots and shoots, thereby regulating K + /Na + homeostasis in the shoots, resulting in improved salt tolerance (Ren et al. 2005). The eight novel QTLs ( qSES1.3, qSES1.4, qSL1.2, qSL1.3, qRL1.1, qRL1.2, qFWsht1.2, and qDWsht1.2 ) responsible for seedling-stage salinity tolerance on the long arm of chromosome 1 as reported in our study were found to be very different from SKC1 and Saltol . These eight novel QTLs span a region of 170 to 175 cM. There is a need to further test the stability of the identified QTLs being expressed before drawing a conclusion.
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Evaluation of saltol introgressed back cross inbred lines for salinity tolerance in rice (Oryza sativa L.)

Evaluation of saltol introgressed back cross inbred lines for salinity tolerance in rice (Oryza sativa L.)

However, DNA markers seem to be the best candidates for efficient evaluation and selection of plant material. Recent progress in DNA marker technology permits reduction of time and accuracy of breeding. With the advancements in the field of Marker Assisted Selection (MAS), it is possible to introgress QTLs in the desired genetic background. Using this strategy, several improved versions of rice varieties have been developed. This demonstrated the feasibility of developing improved versions of rice varieties exhibiting salinity tolerance. SSR markers are playing important role to identify gene for salt tolerance that can be helpful for plant breeders to develop new cultivars. The MAS derived back cross lines (BC 3 F 3 ) of rice for salinity tolerance
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Screening of Rice (Oryza sativa L.) Genotypes for Salinity Tolerance in Ethiopia

Screening of Rice (Oryza sativa L.) Genotypes for Salinity Tolerance in Ethiopia

Breeding crops for salt tolerance would be likely to provide economic and efficient methods of overcoming problems of saline soils. Such a crop improvement and selection program must be based on adequate variability for salinity tolerance and such variation has been observed within species. Rice is sensitive to salinity like other cereal crops, this limiting its production under salinity prone areas; however, cultivar differences were observed for salt tolerance in rice. Rice breeders have used such genetic variability to produce high yielding and salt tolerant cultivars. Screening efforts are also being made in different parts of the world exploiting this diverse genetic potential to identify rice genotypes tolerant to salinity [21, 8, 16]. However, in Ethiopia little has been done to identify rice genotypes adaptable to adverse soil conditions such as salinity and to investigate morphological characters associated with grain yield under salt stress. This study, was therefore, conducted
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QTL MAPPING FOR SALINITY TOLERANCE AT SEEDLING STAGE IN RICE

QTL MAPPING FOR SALINITY TOLERANCE AT SEEDLING STAGE IN RICE

genes/QTLs associated with salinity tolerance (Lang et al., 2001). Gregorio et al. (2002), Gong et al. (1999), Bonilla et al. (2002) and Lee et al. (2006) detected a major QTL for salt tolerance on Chromosome 1 but their position in chromosome was not exactly the same. Zhang et al. (1995), Lin et al. (1998) and Prasad et al. (2000) also detected QTL in chromosomes 7, 5 and 6, respectively. Koyama et al. (2001) identified ten QTLs for five shoot traits related to salinity tolerance; Na + uptake (one), K + uptake (two), Na + (two) and K + (two) concentration, and Na + :K + ratio (two). Lin et al. (2004) detected five QTLs for four traits associated with salinity tolerance in roots, three QTLs for three traits of shoots but they were not in the same map locations. Lee et al. (2006) detected QTLs for salinity tolerance at seedling stage of rice used visual score of leaf injury symptom as phenotypic trait.
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Genomic and transcriptomic analysis reveal molecular basis of salinity tolerance in a novel strong salt-tolerant rice landrace Changmaogu

Genomic and transcriptomic analysis reveal molecular basis of salinity tolerance in a novel strong salt-tolerant rice landrace Changmaogu

sensitive to salinity to create extreme sample pools. Gen- omic DNA was extracted using a modified CTAB (Hexa- decyltrimethylammoniumbromide) method and purified by chloroform: phenol (1:1) (Chen and Ronald 1999). The DNA quality was checked using an Agilent bioana- lyzer 1000 (Agilent Technologies, Singapore). Library preparation was performed according to the manufac- turer’s protocol. Genomic re-sequencing was conducted to generate paired-end 100-base (PE100) reads using the Illumina Hiseq 2000 platform (Illumina Technologies), which was conducted by Biomarker (China). Clean reads were aligned to reference genome sequences of the Japonica rice Nipponbare genome (http://ftp.ensembl- genomes.org/pub/release-24/plants/fasta/oryza_sativa/ dna/Oryza_sativa.IRGSP-1.0.24.dna.toplevel.fa.gz) using BWA software (Li and Durbin, 2009). SNPs and small InDelInDels were detected using GATK software (Mc- Kenna et al., 2010). The tool of Mark Duplicate in Picard (http://sourceforge.net/projects/picard/) was used to eliminate PCR duplication to increase SNP/InDel-calling accuracy. SNP/InDel-index was calculated for all the SNP/InDel positions. We excluded SNP/InDel positions with multiple genotypes and read depth < 4 from the two bulk sequences. The association analysis was con- ducted by Euclidean Distance (ED) and SNP/InDel- index, respectively (Hill et al., 2013; Fekih et al., 2013). The overlapped regions based on the above two methods were considered candidate regions for salinity tolerance.
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Identification of QTLS tolerance to salinity in rice (Oryza sativa L )

Identification of QTLS tolerance to salinity in rice (Oryza sativa L )

Delta (MRD) are being seriously influenced by salt intrustion with estimated to be about 19.0% - 37.8% of MRD and about 1.5% - 11.2% of RRD. Vietnam is formidably dealing with salinity problem which is causing adverse influence on 1 million ha, equally with 3% of total Vietnam areas (Nguyen et al., 2006; Linh et al., 2012). On the other hand, the economic loss annually by salt intrusion is up to 45 million USD, which is equivalent to 1.5% of rice productivity per year in MRD (MARD, 2005). To overcome reduction of rice yield affected by salt in the country, one of the feasible method is to use the salinity tolerance of rice cultivars as the target crop. The work on mapping and identifying QTLs which are responsibe and controlled salinity tolerance play a key role to generate the rice lines with high salinity tolerance. Therefore, the objective of the current study was to identify and map the QTLs which controlling salinity tolerance of rice. The data will provide good information for the breeders to further generate salt tolerance rice cultvars and grow in the salt affected areas to enhance rice yield and ensure food security in the country.
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Identifying QTLs Associated and Marker-Assisted Selection for Salinity Tolerance at the Seedling, Vegetative and Reproductive Stages in Rice (Oryza Sativa L.)

Identifying QTLs Associated and Marker-Assisted Selection for Salinity Tolerance at the Seedling, Vegetative and Reproductive Stages in Rice (Oryza Sativa L.)

chromosomes 1 and chromosome 3 were QST01 and QST-3, respectively. Recently, Thomson et al, [37] reported that four QTLs related to salt tolerance are on chromosome 1 (1 QTL), chromosome 2 (1 QTL), chromosome 3 (1 QTL) and chromosome 12 (1 QTL). Markers linked the QTLs in MAS breeding permits to exactly identify the major and minor QTL regions. Results from QTL map analysis showed that marker RM3532S was tightly linked to Saltol locus (4.6 cM in genetic distance) on chromosome 1. QTLs for major traits detected on chromosome 1. The results are useful for MAS breeding as well as pyramiding breeding in the future.
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Genetic Structure of Salinity Tolerance in Rice at Seedling Stage

Genetic Structure of Salinity Tolerance in Rice at Seedling Stage

In the present study, QTLs were identified for SHL on chromosomes 8, 9 and 10, which were common in normal and normal stress conditions. Also, in the distance between the ISSR4-6 and ISSR13-3 markers on chromosome 8, the location of the genotype controlling the KSH was detected, which was common in both normal conditions and salinity stress. In this study, genetic locations with more than 20% genes were identified for some traits, including qCHLN-8, qSLN-8, qWLN-3, qWLN-9, qLAN-3, qLAN-8 and qLAN-9, qRFWN-1, qRFWN-3b and qRFWN-8, qFBN- 7, qRDN-1a and qRDN-3 and qNaKSHN-5 under normal conditions and qSL-8, qLL-1a, qNaR-3, qKSH-1 and qKSH-4 and qNaKSH-4 under salinity stress condition. These QTLs, due to the high percentage of justification after validation, could be a good candidate for selection programs with the help of markers in the population of recombinant lines of rice. References
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Characterizing the Saltol quantitative trait locus for salinity tolerance in rice

Characterizing the Saltol quantitative trait locus for salinity tolerance in rice

The original IR29/Pokkali QTL study using 80 extreme RILs identified Saltol as the QTL with the highest significance for shoot Na–K ratio with an LOD of 14.5 and R 2 of 64%, based on selective genotyping (Gregorio 1997). A follow-up study categorized the RILs into sensitive and tolerant groups and mapped the position of Saltol between RM23 and RM140 (10.7–12.2 Mb on chromosome 1), and confirmed the effect of the shoot Na – K ratio with an LOD of 6.6 and R 2 of 43% using 54 RILs (Bonilla et al. 2002). While neither of these studies presented the percent variation explained for visual SES tolerance scores or survival, it was assumed that by controlling the key mechanism of Na + /K + homeostasis under stress, Saltol is a major contributor to seedling stage tolerance. The data from the current study confirmed that Saltol contributes to Na + /K + homeostasis with an LOD of 7.6 and R 2 of 27% across the 140 RILs and a 30% decrease in the shoot Na – K ratio, from 1.7 to 1.2 in the IR29/Pokkali backcross lines, while the Saltol effect on SES scores in the QTL population and backcross lines was much smaller. The fact that Saltol affected the Na – K ratio more than other traits supports the possibility that the sodium transporter SKC1 (OsHKT1;5 as in Platten et al. 2006) may be the causal gene underlying the Saltol QTL. SKC1 was found to encode a sodium transporter that helps control Na + /K + homeostasis through unloading of Na + from the xylem (Ren et al. 2005), which has been suggested to function primarily in roots to reduce the amount of Na + ions that are transported to the leaves (Hauser and Horie 2010). Although the SKC1 QTL was originally detected using Nona Bokra, more research is needed to characterize the Pokkali allele at SKC1 to determine if it serves a similar function to maintain Na + /K + homeostasis in the shoots. Interestingly, a recent study identified a QTL for Na–K ratio between 11.1 and 14.6 Mb on chromosome 1 from the upland japonica variety Moroberekan (Haq et al. 2010) suggesting that the Saltol region may have functional significance for salt tolerance across both indica and japonica varieties.
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Molecular characterization for salinity tolerance in rice using microsatellite markers

Molecular characterization for salinity tolerance in rice using microsatellite markers

greater number of alleles per locus detected more number of unique alleles in accordance with the earlier reports (Bajracharya et al. 2006; Brondani et al. 2006; Joshi and Behera, 2006; Lapitan et al. 2007; Ebana et al. 2008; Herrera et al. 2008; Borba et al. 2009; Pervaiz et al. 2010; Rabbani et al. 2010; Vanaza et al. 2010; Singh et al. 2011). The presence of unique alleles indicated that the materials used in this study are useful and represent good source of genetic diversity for their purposeful and effective utilization in rice breeding for salt tolerance. The markers differed in their ability to determine variability among different entries based on their polymorphism. The polymorphism information content (PIC) values, which reflect allele diversity and frequency of the markers among the cultivars, were not uniform for all the primer pairs tested. The value varied from one primer to another primer. Numerically, the value was found to vary from 0.376 in the case of primer RM4 to 0.827 in the case of primer RM242 with an average value of 0.677 across all the primers. The PIC values observed in the present study are more or less comparable to previous estimates reported on the basis of analysis of microsatellite markers in rice. The mean PIC value obtained in the present study was higher than 0.57, 0.57 and 0.48 as reported by Zeng et al (2004), Faridul Islam et al (2012) and Sajib et al (2012) respectively. Contrarily, the value obtained in the present study was lower than the value of 0.732 as obtained in an earlier study (Shanthi et al 2012). Findings of these high PIC value might be due to inclusion of more diverse set of rice germplasm as observed in present investigation. Higher PIC value of a marker indicates higher probability of detecting the number of allele among cultivars. Considering the number of alleles generated by different primer pairs in conjunction with level of polymorphism detected in the present study, the primers RM2 and RM204 appeared to be the most informative primers for the purpose of molecular characterization and grouping of rice cultivars on the basis of their salt tolerance.
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Introgression the SALTOL QTL into Q5DB, the Elite Variety of Vietnam Using Marker- Assisted - Selection (MAS)

Introgression the SALTOL QTL into Q5DB, the Elite Variety of Vietnam Using Marker- Assisted - Selection (MAS)

Research at International Rice Research Institute (IRRI) resulted in the development of high yielding rice varieties tolerant of abiotic stress such as submergence and salt stress, and these varieties can help make these unfavorable coastal areas less vulnerable to climate change impacts (11) . The newly improved varieties have been developed using both conventional and modern breeding tools. Breakthroughs in salinity tolerance breeding became feasible after the identification of major chromosomal regions (Quantitative trait loci, QTLs) underlining salinity (Saltol) stress, and the development and use of a marker system for their speedy incorporation into modern high yielding and popular varieties through marker assisted backcrossing (11) .
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Assessing genetic diversity of promising wheat (Triticum aestivum L.) lines using microsatellite markers linked with salinity tolerance

Assessing genetic diversity of promising wheat (Triticum aestivum L.) lines using microsatellite markers linked with salinity tolerance

fragment length polymorphism (RFLP) (Vaccino et al., 1993), Random Amplified Polymorphic DNA (RAPD) (Dweikat et al., 1993), specific PCR primers for low copy sequences (Chen et al., 1994; Talbert et al., 1994), simple sequence repeats (SSRs) (Plaschke et al., 1995), and polyacrylamid gel electrophoresis (PAGE) of gliadins (Röder et al., 1995). SSR markers have been confirmed as an efficient tool for estimating genetic variation in wheat (Landjeva et al., 2006). Several authors reported that microsatellites are more variable than most of other molecular markers that are useful as tools for studying the genetic diversity of germplasm (Haile et al., 2012). Increases in salinity tolerance for the world’s two staple crops, wheat and rice, are an important goal as the world’s population is increasing more quickly than the area of agricultural land to support it (FAO, 2010). In bread wheat germplasm, salinity is considered a major factor in limiting plant growth and crop productivity (Rus et al., 2000). Several research have reported information on QTLs attributed to salinity tolerance, since present germplasm has high variation of salinity tolerance therefore the microsatellite markers linked with the identified QTLs for salinity tolerance were used to assess the genetic diversity of bread wheat lines.
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The effect of salinity stress on ions and soluble sugars distribution in leaves, leaf sheaths and roots of rice (Oryza sativa L ) seedlings

The effect of salinity stress on ions and soluble sugars distribution in leaves, leaf sheaths and roots of rice (Oryza sativa L ) seedlings

concentration decreasing under salinity lead to a decrease of micro elements solubility in saline and sodic soils. This study has highlighted a relationship between plant ionic status and salinity tolerance in studied rice cultivars. Tolerant genotype was able to accumulate toxic ions in roots better than the sensitive ones, and thereby had better dry matter production. Total soluble sugars that are essential for osmotic adjustment accumulated in shoot of salt-tolerant plants were higher compared to sensitive-ones. Our results showed that IR651 was able to suppress both osmotic and toxic effects of salinity on active leaf using the above mentioned mechanisms, and showed better growth under salt stress.
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Evaluating rice for salinity using pot-culture provides a systematic tolerance assessment at the seedling stage

Evaluating rice for salinity using pot-culture provides a systematic tolerance assessment at the seedling stage

Background: Rice ( Oryza sativa L .) is one of the major staple food crops consumed globally. However, rice production is severely affected by high salinity levels, particularly at the seedling stage. A good solution would be the development of an efficient screening methodology to identify genotypes possessing genes for salt tolerance. Result: A new salinity tolerance screening technique using rice seedlings in pot-culture was tested. This method controls soil heterogeneity by using pure sand as a growth medium and minimizes unexpected extreme weather conditions with a movable shelter. Seventy-four rice genotypes were screened at three salinity treatments including high salt stress (electrical conductivity (EC) 12 dSm − 1 ), moderate salt stress (EC 6 dSm − 1 ), and control (no salt stress), imposed 1 week after emergence. Several shoot and root morpho-physiological traits were measured at 37 days after sowing. A wide range of variability was observed among genotypes for measured traits with root traits being identified as the best descriptors for tolerance to salt stress conditions. Salt stress response indices (SSRI) were used to classify the 74 rice genotypes; 7 genotypes (9.46%) were identified as salt sensitive, 27 (36.48%) each as low and moderately salt tolerant, and 13 (17.57%) as highly salt tolerant. Genotypes FED 473 and IR85427 were identified as the most salt tolerant and salt sensitive, respectively. These results were further confirmed by principal component analysis (PCA) for accuracy and reliability.
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