Top PDF QTL MAPPING FOR SALINITY TOLERANCE AT SEEDLING STAGE IN RICE

QTL MAPPING FOR SALINITY TOLERANCE AT SEEDLING STAGE IN RICE

QTL MAPPING FOR SALINITY TOLERANCE AT SEEDLING STAGE IN RICE

in this region of the chromosome 8 segment. A LOD peak was found from IM and CIM line graph which was located near RM210 and flanking between RM25 and RM210. From this result it was assumed that a major QTL was tightly linked with this region with the LOD score of 7.0 and R 2 value was 0.2900. This QTL represents a potential candidate for marker assisted selection because of the high LOD score and relatively large effects. This is the first report of QTL identification from the IR61920-3B-22-2-1 parent, despite the high salinity tolerance of this genotype. Ammar (2004) also detected 4 QTLs with LOD scores ranging from 3.95 to 4,84 on chromosome 8 for the traits of Na + concentration in the leaf tissue at vegetative stage, Na + concentration in the leaf tissue at reproductive stage, Na + concentration in the stem tissue at vegetative stage, and Na + /K + ratio in the stem tissue at reproductive stage and their positions were in between of RM3395 and RM281 in chromosome 8 by using SSR markers in F 2
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Genetic Structure of Salinity Tolerance in Rice at Seedling Stage

Genetic Structure of Salinity Tolerance in Rice at Seedling Stage

Rice (Oryza sativa L.) is a major source of food and energy for more than 2.7 billion people on a daily basis and is planted on approximately one- tenth of the earth's arable land (Bizimana et al., 2017). Rice is one of the most important cereal crops and serves as the staple food for over one- third of the world's population (Mohammadi- Nejad et al., 2010). However, the productivity of rice is greatly affected by soil salinity which is the second most widespread soil problem after drought, in rice growing areas of the world (Sabouri and Sabouri, 2008; Islam et al., 2011). Soil salinity is key abiotic stress for crop productivity worldwide and it is a major abiotic stress for rice (Ren et al. 2005; Jing et al. 2017). Salinity is an increasing concern for the productivity of staple food crop. Crops with improved salt tolerance are highly needed to cultivate saline lands (Srivastava et al., 2018 ).
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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

Farmers have grown traditional rice landraces adapted to salt-affected areas for generations despite their numerous undesirable traits, including long duration, low yield, and poor grain quality. Some of these landraces possess remarkable tolerance to salt stress through a complex set of physiological mechanisms, including sodium exclusion, higher tissue tolerance by compartmenting salts into the apoplasts, effective sequestration of toxic salts into older tissues, stomatal responsiveness, and upregulating the antioxidant system during stress (Yeo and Flowers 1986; Ismail et al. 2007; Moradi and Ismail 2007). Moreover, tolerance during seedling stage seems to correlate poorly with tolerance during reproduction, suggesting different sets of traits are probably involved at each stage (Moradi et al. 2003). Despite this complexity, most salt-tolerant cultivars seem to posses only a few of these mechanisms, signifying the prospects for developing highly tolerant rice varieties through combining superior alleles of genes controlling these traits. Recent advances in molecular biology and genomics have led to a more detailed understanding of the genes and pathways involved in the salt stress response in rice, including those involved in ion transport and homeostasis, osmoregulation, and oxidative stress protection (Blumwald et al. 2000; Mäser et al. 2002; Garciadeblás et al. 2003; Chinnusamy et al. 2004; Horie and Schroeder 2004; Nakayama et al. 2005; Bohnert et al. 2006; Rodriguez-Navarro and Rubio 2006; Sahi et al. 2006; Martinoia et al. 2007; Munns and Tester 2008; Singh and Flowers 2010)
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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

Results of PCA classification of rice genotypes gener- ally agreed with results obtained from the total salt stress response index (TSSRI) method, particularly for the two extreme groups (high salt tolerant and salt sen- sitive). The intermediate categories (low and moderate salt tolerance) showed slight differences with some geno- types categorized interchangeably. Both PCA and SSRI methods identified root parameters including SA, FR, TRL, RV, CR, LRL, AD, TP to be better descriptors under stress conditions than the shoot traits, indicating the higher importance of root traits in screening rice ge- notypes for salinity tolerance. SSRI also showed that when salt stress was increased from 6 dSm − 1 to 12 dSm − 1 , the variation explained increased from 62% to 82%. It may be beneficial to screen all genotypes at higher salinity levels and different growth stages, inclu- ding the flowering stages to find the most salt tolerant genotypes. Similar results between PCA and SSRI sup- port the accuracy of the experiment and the equivalent reliability of the two methods (SSRI and PCA) in screen- ing for stress conditions, including salinity.
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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

The overall phenotypic performance under salt stress reflected by visual SES scores is determined by several key traits, including survival, sodium and potassium concentration and rate of growth. Here we used path analysis to assess the genetic contribution of different mechanisms of salinity tolerance during early vegetative stage in the rice landrace Capsule, to identify key factors associated with salt tolerance. The results suggest that selection should be made based on Na + and K + concen- trations and ratios in plant tissue, and seedling survival to fast track the development of improved salt tolerant varieties. Most of the QTL identified here through single marker analysis were also detected using interval map- ping and composite interval mapping, and were further confirmed through graphical genotyping. Several QTL were identified on chromosomes 1 ( qNa1.1 , qK1.1 , qNaK-R1.1 , qSur1.1 ), 2 ( qNa2.2 ), 3 ( qSES3.1, qNa3.3, qK3.2, qNaK-R3.3, qSur3.2 ), 5 ( qSES5.2, qNa5.4, qNaK- R5.4 ) and 12 ( qSES12.3, qK12.3, qSur12.3 ), that are asso- ciated with tolerance at seedling stage, and the newly mapped loci on chromosomes 1 and 3 are novel. These QTL are good targets for subsequent fine mapping and cloning to develop gene-based SNP markers. Pyramiding these QTL with previously identified loci will help develop highly tolerant varieties for salt affected areas, especially coastal areas where salt stress is a major impediment for rice production during both dry and wet seasons; an effect further worsening with climate change.
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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.)

Salinity is the second type of stress and is the most important loss rice yield production after drought [1]. Salty soil is one of the most common stress has a negative effect on crop production. Salty soil is the main limiting factor in the production of rice, a type of salt-sensitive plants, productivity is affected greatly by the ion toxicity [2]. The difference between plant species and on the tolerance to salinity [3]. Rice crops are relatively resistant to stress during germination, active and mature branches lying but very sensitive at the beginning stage of seedlings [4, 5]. Two stages of the rice plant sensitivity independent of each other and are controlled by genes, meaning, in the reproductive period the tree no resistant varieties in the stage of seedlings and vice versa. Moreover, salt tolerance at the reproductive stage is very important because the process of fertilization and seed formation occurs in this period and reproductive stages directly related to yield [6]. In rice, important traits such as salt-tolerance, yield and quality are controlled by polygenes that are described as quantitative trait loci (QTLs) [7]. QTL mapping related to environmental stresses, yield and quality are very important for the application of map-based cloning and marker-assisted selection (MAS) in rice breeding programs [8]. In rice, QTL analysis of salt tolerance has been conducted by several researchers [9, 10]. Lang et al, [11] reported that salt tolerant genes tagging based on SSR markers with advanced backcross populations (BC 2 F 2 ) of
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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

Despite the importance of developing rice varieties with salinity tolerance, only a small number of quantitative trait loci (QTL) mapping experiments have been conducted. QTLs for salinity tolerance in rice have been mapped using Amplified Fragment Length Polymorphism (AFLP), Restriction Fragment Length Polymorphism (RFLP), and mic- rosatellite or simple sequence repeat (SSR) markers in different popula- tions (Gregorio, 1997; Lang et al, 2000; Tuan et al, 2000; Bonilla et al, 2002, Niones, 2004). Microsatellite markers have been useful for tagging and mapping of genes/QTLs associated with salinity tolerance (Lang et al, 2001). A major QTL for salt tolerance was mapped at chro- mosome 1 by using F 8 recombinant inbred line (RIL) of Pokkali/ IR29
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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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Molecular Dissection of Seedling Salinity Tolerance in Rice (Oryza sativa L.) Using a High-Density GBS-Based SNP Linkage Map

Molecular Dissection of Seedling Salinity Tolerance in Rice (Oryza sativa L.) Using a High-Density GBS-Based SNP Linkage Map

Results: We evaluated a population of 187 recombinant inbred lines (RILs) developed from a cross between Bengal and Pokkali for nine traits related to salinity tolerance. A total of 9303 SNP markers generated by genotyping-by-sequencing (GBS) were mapped to 2817 recombination points. The genetic map had a total map length of 1650 cM with an average resolution of 0.59 cM between markers. For nine traits, a total of 85 additive QTLs were identified, of which, 16 were large-effect QTLs and the rest were small-effect QTLs. The average interval size of QTL was about 132 kilo base pairs (Kb). Eleven of the 85 additive QTLs validated 14 reported QTLs for shoot potassium concentration, sodium-potassium ratio, salt injury score, plant height, and shoot dry weight. Epistatic QTL mapping identified several pairs of QTLs that significantly contributed to the variation of traits. The QTL for high shoot K + concentration was mapped near the qSKC1 region. However, candidate genes within the QTL interval were a CC-NBS-LRR protein, three uncharacterized genes, and transposable elements. Additionally, many QTLs flanked small chromosomal intervals containing few candidate genes. Annotation of the genes located within QTL intervals indicated that ion transporters, osmotic regulators, transcription factors, and protein kinases may play essential role in various salt tolerance
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Genome-wide Association Mapping of Cold Tolerance Genes at the Seedling Stage in Rice

Genome-wide Association Mapping of Cold Tolerance Genes at the Seedling Stage in Rice

Rice cold tolerance is genetically controlled by multiple quantitative trait loci (QTLs). Traditional QTL mapping using bi-parental or multiple cross populations identified more than 250 QTLs on all 12 chromosomes for rice cold tolerance at different growth and development stages (Yang et al. 2015; Xiao et al. 2015; Mao et al. 2015; Zhu et al. 2015). Among these QTLs, several genes have been fine mapped, including Ctb1 (Saito et al. 2004), qCT8 (Kuroki et al. 2007), qCTB7 (Zhou et al. 2010), qCTB3 (Shirasawa et al. 2012), and qCT-3-2 (Zhu et al. 2015) for cold tolerance at the booting stage, qCTS12 (Andaya and Tai, 2006), qCTS4 (Andaya and Tai, 2007), qCtss11 (Koseki et al. 2010), qSCT1 and qSCT11 (Kim et al. 2014), qLOP2 and qPSR2-1 (Xiao et al. 2015) for CTS, qLTG3-1 for germination cold tolerance
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Mapping QTLs for Cold Tolerance at Seedling Stage Using an Oryza sativa O. rufipogon Backcross Inbred Line Population

Mapping QTLs for Cold Tolerance at Seedling Stage Using an Oryza sativa O. rufipogon Backcross Inbred Line Population

Tolerance to low temperature is an important factor affecting the growth and development of rice (Oryza sa- tiva L.) at an early growing season in the temperate region, and at high altitudes of tropical regions. In this study, a backcross inbred line (BIL) population derived from an interspecific cross between Xieqingzao B (O. sativa L.) and an accession of Dongxiang wild rice (O. rufipogon Griff.) was used to identify quantitative trait loci (QTLs) associated with cold tolerance at the seedling stage. Seedlings were treated with a temperature of 6°C for 2 days and seedling mortality was measured for QTL mapping. QTL analysis was performed on the whole BIL popula- tion and on one subpopulation that showed Xieqingzao B homozygous at QTL detected in the whole population. One major QTL, qSCT8, and one QTL, qSCT4.3, with smaller effect was found in the whole population. The QTLs qSCT8 and qSCT4.3 were mapped on chromosome 8 and 4, explaining 60.96% and 8.83% of the phenotypic variance, respectively. In the subpopulation, three QTLs, qSCT4.1, qSCT4.2 and qSCT12, accounting for 56.22%, 57.62% and 53.09% of the phenotypic variance, respectively, were detected on chromosome 4 and 12. At all five loci, the alleles introduced from the Dongxiang wild rice were effective in decreasing seedling mortality. Our results provide a basis for fine mapping and cloning of QTLs associated with cold tolerance, and the markers linked with QTLs could be used to improve the cold tolerance of rice varieties by marker-assisted selection. Keywords: Dongxiang wild rice; QTL analysis; rice; seedling cold tolerance
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Genome-wide association study and candidate gene analysis of alkalinity tolerance in japonica rice germplasm at the seedling stage

Genome-wide association study and candidate gene analysis of alkalinity tolerance in japonica rice germplasm at the seedling stage

Genome-wide association study (GWAS) is a powerful approach for gaining insight into the genetic architecture of complex traits in many crops and has been used to identify loci and candidate genes (Zhao et al. 2011; Zhou et al. 2015; Huang et al. 2016). Compared to traditional QTL linkage analysis, GWAS is based on high-density variation in natural populations and can detect multiple alleles at the same site (Flint-Garcia et al. 2003). Many QTLs associated with multiple traits have been identi- fied, such as agronomic traits (Huang et al. 2010; Zhao et al. 2011; Yang et al. 2014) and traits associated with abiotic stress (Lv et al. 2015; Pan et al. 2015; Wang et al. 2016; Shakiba et al. 2017). Several loci associated with salt tolerance were also identified in rice based on GWAS. Campbell et al. (2017) found that the genetic basis of root Na + content varied between indica acces- sions and japonica accessions via GWAS, and a major QTL (RNC4) associated with root Na + /K + ratio and root Na + content was identified in a region of approximately 575 kb on chromosome 4. Yu et al. (2017) used 295 rice varieties to perform a GWAS of salt tolerance-related traits in rice at the seedling stage, and 25 SNPs were sig- nificantly associated with six phenotypes. Kumar et al. (2015) performed a GWAS of 12 different salt tolerance-related traits in rice and identified 22 SNPs significantly associated with Na + /K + ratio and 44 SNPs with other traits observed under salt stress condition. In summary, GWAS is a powerful strategy for mapping QTLs of salt tolerance in rice. However, no studies have dissected the QTLs associated with alkalinity tolerance of rice through GWAS.
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QTL mapping of physiological traits at the booting stage in rice under low temperature combined with nitrogen fertilization

QTL mapping of physiological traits at the booting stage in rice under low temperature combined with nitrogen fertilization

Experimental design and cold-stress treatment. The field experiments were conducted under cold- water stress and different N rates in two consecutive years (2016 and 2017) in SanDan (25.04°N, 102.49°E, and altitude 2171 m) of Yunnan Province, China. The soil type was clay loam, with the characteristics of pH 6.5 (1 : 2.5 soil/water ratio), organic matter (2.81%), total N (2.36%), alkaline N (98.71 mg/kg), avail- able P (22.34 mg/kg) and available K (143.52 mg/kg). Fifteen plants per each line were transplanted in a single row at a spacing of 15/25 cm between plants and rows with one seedling per hill according to a randomized complete block design with three rep- licates. Three N levels in the form of urea with an N content of 46% were applied, 0 kg N/ha (N1), 120 kg N/ha (N2) and 240 kg N/ha (N3). Basal nitrogen was applied at 50% of the total amount before transplant- ing, and remaining N was split-applied at tillering (20%) and booting stage (30%), respectively. Entire phosphorus and potassium fertilizers were applied into the soil pre-transplanting as superphosphate and potassium sulphate at rates of 80 kg/ha (P 2 O 5 ) and 80 kg/ha (K 2 O). According to the method described by Endo et al. (2016), NIL and two parental cultivars were irrigated with cool water (16–19°C) and at a depth of about 25 cm from tillering stage (20 days after transplanting) to grain maturity. In the entire rice growth stage, atmospheric temperatures (T a )
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Early growth stages salinity stress tolerance in CM72 x Gairdner doubled haploid barley population

Early growth stages salinity stress tolerance in CM72 x Gairdner doubled haploid barley population

Adaptation to salinity stress in plants is often linked with three mechanisms, namely accu- mulation or synthesis of compatible solutes, antioxidant protection and regulation of ion homeostasis particularly Na+ and K+ homeostasis; the latter being acknowledged to play important roles in barley salinity tolerance [27]. Results from a study conducted on 189 Tibetan wild barley accessions showed that HvHKT1 gene is significantly associated with root Na+ concentration under saline environment and up-regulated immediately after salt stress, while HvHKT2 is substantially down-regulated after salt stress corresponding to decreased K + concentration in both shoots and roots of barley under salinity condition [27]. Na+ concen- tration controlling QTL on chromosome 2H [2, 20] and Na+:K+ ratio controlling QTL on 6H [2], on chromosome 1H and 5H [20] have been reported in the CM72 and Gairdner DH popu- lation [2] and Yangsimai 1 x Gairdner DH population [20]. The QTL on chromosome 2H reported by [2] was in a very close proximity to QTL linked with germination stage salinity stress tolerance but located distantly from QTL linked with biomass yield at seedling stage identified in our study. No QTL linked with K+ accumulation was identified in a study con- ducted on F1-derived DH population from Barque-73 (Hordeum vulgare ssp. Vulgare), a selec- tion from barley variety Barque and moderate Na+ excluder, and a wild accession CPI-71284- 48 (H. vulgare ssp. Spontaneum) capable of limiting Na+ accumulation in the shoots [28]. Rather they reported a single strong Na+ accumulation linked QTL on chromosome 7H genetic map at 13.9 cM. This QTL did not correspond to the location of Na+ exclusion Nax1 and Nax2 and thus named as barley locus HvNax3. HvNax3 locus reduced shoot Na+ accumu- lation by 10–25% in plants grown in 150 mM NaCl [28].
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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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Molecular characterization for salinity tolerance in rice using microsatellite markers

Molecular characterization for salinity tolerance in rice using microsatellite markers

Excess salt in soil interferes with several physiological and biochemical processes resulting in problems such as ion imbalance, mineral deficiency, osmotic stress, ion toxicity and oxidative stress in crop plants. These conditions ultimately interact with several cellular components including DNA, protein, lipids and pigments in plants (Zhu, 2002) impeding the growth and development of a vast majority of crops. Plants have evolved many biochemical and molecular mechanisms to protect from the detrimental effects of salt-stress. The main biochemical strategies are induction of antioxidative enzymes, ion-homeostasis and synthesis of compatible organic solutes. The development and identification of salt-tolerant genotype that can tolerate high levels of salinity in the soils would be a practical solution of such problem in crops (Yamaguchi and Blumwald, 2005). Molecular genetic studies have revealed that tolerance to salt stress in plants is controlled by interactions between several independently regulated but temporally and spatially controlled processes (Kawasaki et al. 2001; Ozturk et al. 2002; Seki et al. 2002). Using different mapping populations, quantitative trait loci (QTLs) for salt tolerance (Zhang et al. 1995) and seedling traits associated with salt tolerance have been mapped on different chromosomes (Prasad et al. 2000; Koyama et al. 2001; Gregorio et al. 2002; Lee et al. 2004; Ren et al. 2005; Lee et al. 2007). The chromosomal location of ion transport and selectivity traits that are compatible with agronomic needs have been mapped to reveal that QTLs for Na + and K + transport are likely to act through the
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QTL analysis for chalkiness of rice and fine mapping of a candidate gene for qACE9

QTL analysis for chalkiness of rice and fine mapping of a candidate gene for qACE9

Differences between cultivars in their responsiveness of FLO2 expression during high-temperature stress indi- cated that FLO2 may also be involved in heat tolerance during seed development. However, as a typical quanti- tative trait, chalkiness is vulnerable to environmental conditions, especially the temperature in the filling stage, when starch is accumulated in endosperm (Lanning et al. 2011; Siebenmorgen et al. 2013). To elucidate the effect of high temperature on grain-filling metabolism, Yamakawa et al. (2007) exposed caryopses of high temperature-tolerant and sensitive cultivars to high temperature (33 °C/28 °C) or control temperature (25 °C/20 °C) during the filling stage, and found that the starch synthesis-related genes, for example, GBSSI, were down-regulated at transcript level by high temperature, whereas those for starch-consuming α- amylases and heat shock proteins were up-regulated. In general, high temperature resulted in the occurrence of grains with various degrees of chalky appearance. Never- theless, there were some varieties not influenced by the high temperature. Murata et al. (2014) developed an Apq1-NIL to evaluate the effect of temperature on various agronomic traits, and found that there is no significant difference in percentage of perfect grains (PPG) of the Apq1-NIL under high temperature and normal conditions, although PPG of the parent ‘Koshihikari’ is lower under high temperature.
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Development of sodicity tolerant rice varieties through marker assisted backcross breeding

Development of sodicity tolerant rice varieties through marker assisted backcross breeding

entries was assessed over two years of replicated yield trials, it was found that the ‘Saltol’ entry TR 13 083 registered 13.3 and 8.0 per cent increased yield over the local tolerant check variety, TRY2 and the donor FL 478 respectively. Another entry TR 13-069 also has recorded 10.7 and 5.4 per cent increased yield over the local check and the donor respectively. The results clearly confirmed the effectiveness of ‘Saltol’ QTL in conferring seedling stage sodicity tolerance in rice which in turn helped in better establishment of plants in sodic soils leading to better grain yield. Further the results of this present experiment strongly indicate the possibilities of development of sodicity tolerant fine grain rice varieties by selectively introgressing the ‘Saltol’ QTL in the desired background genome using Marker Assisted Backcross Breeding. Huang et al. (2012) have also reported about successful introgression of Saltol in BT 7 using SSR markers RM 493 and 3412b were efficient foreground selection through Marker Asssited Backcross Breeding.
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Screening Rice (Oryza Sativa L.) Genetic Resources for Cold Tolerance at the Germination Stage

Screening Rice (Oryza Sativa L.) Genetic Resources for Cold Tolerance at the Germination Stage

It is known that the rice genotypes of subspecies japonica is more resistant to low temperatures and have higher cold tolerance as compared with such traits of subspecies indica. Quantitative indication of cold tolerance of rice at seedling stage is controlled by two genes Cts-1 and Cts-2 (t); in the booting stage – by multiple genes. Although genetic mechanisms of rice cold tolerance at this stage of ontogenesis is not studied sufficiently, however, some of them were identified successfully using QTL analysis. For example, two closely related quantitative loci (Ctb-1 and Ctb-2) of cold tolerance associated with the anther length were identified by Saito et. al. 4 . Takeuchi et al.
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SEEDLING SIZE AND VARIETAL CHARACTERISTICS AS THE TOOLS FOR AVOIDANCE TO SUBMERGENCE STRESS AT SEEDLING STAGE IN RICE

SEEDLING SIZE AND VARIETAL CHARACTERISTICS AS THE TOOLS FOR AVOIDANCE TO SUBMERGENCE STRESS AT SEEDLING STAGE IN RICE

The survival and regeneration ability were improved in heavy seedling (low seed rate/unit seed bed area) than that of thin (high seed rate) and medium (intermediate seed rate) category ofrice seedlings subjected to complete submergence stress. Heavy seedlings could maintain better shoot and root fresh weight than that of other two category seedlings. The traits for avoidance to submergence stress exhibited by the cultivars had been identified to be slow or minimum degradation of dry matter, chlorophyll content and rapid elongation ability during inundation period. The cultivars with high count of survival ability after the relief of submergence stress had the lower tissue water potential (r = -0.47). TTB 202-4 was identified to be a potential rice cultivar to avoid submergence stress during seedling stage.
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