Genotypic Screening of Water Efficient Extra-Long Slender Rice Derived from MAS25 X IB370

The current research studied the F3 and F4 population derived from MAS25 (Aerobic rice) X IB370 (Lowland Basmati) for different physio-morphological traits under water limited aerobic condition in field and net house. Frequency distribution curves for various physio-morphological and root traits were parabolic and in some cases, curves were partially inclined towards the respective aerobic rice parent. Phenotypic correlation coefficient analysis showed significant positive correlation between grain yield per plant and different yield related traits yield-related attributes. These mapping population contains all types of allelic variations for BAD2A locus similar to the basmati (585 and 257 bp) or non-Basmati (585 and 355 bp) and heterozygous (585, 355 and 257 bp), respectively. Out of 604 SSR markers well distributed on 12 rice chromosomes, 70 markers showed polymorphism in parental rice genotypes and were used to assess the genetic diversity. The NTSYS-pc UPGMA tree cluster analysis and two dimensional PCA scaling showed that the populations were quite divergent and segregation among them were interspersed between the parents. Composite Interval Mapping analysis (WinQTL Cartographer 2.5) using SSR databases of various populations led to the mapping of 7 large-effect QTLs for different yield related traits in both mapping populations. Many superior genotypes having higher or comparable grain yield, and other yield related traits than the parental genotypes with intact Basmati specific BAD2A allele in homozygous and heterozygous conditions were selected for potential stable aerobic Basmati rice genotypes. *Corresponding author: Kuldeep Kumar, Department of Molecular Biology and Biotechnology, CCS HAU, Haryana, India, Tel: +919711394039; E-mail: Kuldeepdbc@gmail.com Received March 21, 2018; Accepted May 22, 2018; Published May 28, 2018 Citation: Meena RK, Kumar K, Rani K, Pippal A, Bhusal N, et al. (2018) Genotypic Screening of Water Efficient Extra-Long Slender Rice Derived from MAS25 X IB370. J Rice Res 6: 194. doi:10.4172/2375-4338.1000194 Copyright: © 2018 Meena, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Introduction
Rice (Oryza sativa L.) is a major staple food and source of energy for almost 50% of the world's population [1]. It is a moisture loving crop which requires 3000-5000 liters of water to produce one kg of grain which is almost 2-3 times higher than any other cereal crops such as wheat and maize [2]. Minimizing the demand of water is a big challenge and several strategies are being pursued to reduce rice water requirements, such as saturated soil culture [3], alternate wetting and drying, ground cover system [4], system of rice intensification [5], aerobic rice [6] and cultivation using raised beds.
Aerobic rice system is a novel and promising alternative water management system to meet the need to produce, "more rice less water". Aerobic rice refers to a cultivation system in which rice is direct seeded in well tilled leveled fields with uniform slope under non puddled, aerated and unsaturated soil conditions [7].
Traits controlling the water uses are complex in nature hence direct selection of these traits on the basis of phenotype is hardly of any use. Marker assisted breeding proves to be an important technique in order to dissect the presence of locus governing the trait of concern in the progeny. SSR marker remains the most used and efficient in the analysis of the progenies derived from a particular cross to detect the presence of a particular locus associated with it.
Genetic variations for adaptation of rice under aerobic conditions in upland have already been deciphered. Many SSR markers have been reported to be linked to QTL promoting aerobic adaptation in rice such as yield under drought [8,9], maximum root length [10], basal root thickness [11] and root dry weight [12,13] and for grain yield under drought [14].
Keeping all these points the current study has objectives to identify the gene(s)/QTL(s) related with less water requirement and it's transfer in extra-long slender background in mapping population.

Planting material
IB370 is lowland high-yielding aromatic rice cultivars unadapted to cultivation in aerobic conditions obtained from PAU, Ludhiana and MAS25 is a rice variety adapted to aerobic conditions obtained from UAS, Bangalore. The F 3 and F 4 population were analyzed from selected F 2 and F 3 population of MAS25 X IB370 crosses.

Field experiment
Seeds of selected lines and their parents were sown in three replicates at the Rice Research Station, Karnal, India (Latitude: 29.8526350 and Longitude: 76.6589720) during wet season 2014 (F 3 progenies) and 2015 (F 4 progenies). All the standard practices to grow aerobic rice were followed, as described by Rani et al. [15]. Five best plants among the three replicate of each line were harvested at maturity and the data were recorded on various agronomic traits like, plant height, number of effective tillers per plant, panicle length, number of panicles per plant, number of grains per panicle, 1000 grain weight, grain length/breadth ratio and grain yield per plant. Grain yield per plant was recorded after harvesting, threshing and drying to moisture content adjusted to 14%. the physio-morphological traits (Tables S1 and S2). Clearly the yield of aerobically adapted parent i.e. MAS25 is more than the basmati parent i.e. IB370 under aerobic conditions, this result is clearly in accordance with Sandhu et al. [22] and Promilla et al. [23]. Phenotypic correlation coefficient analysis of both populations showed variation in correlation coefficient between various physio-morphological traits (Tables S3 and S4 Under net house conditions also enormous variation was observed for all the physio-morphological traits grown under aerobic condition for both F 3 and F 4 plants consisting of 62 and 14 plants respectively (Tables S5 and S6). In F 3 population positive correlation between grain yield per plant and effective number of tillers/plant (0.416, p=0.01); plant height and root length (0.408; p=0.01); plant height and fresh root weight (0.432; p=0.01) (Table S7). In F 4 also positive correlation was observed between grain yield/plant and plant height (0.903, p=0.01); grain yield/plant and 1000 grain weight (0.939, p=0.01); grain yield/ plant and length/breadth ratio (0.964, p=0.01); grain yield/plant and root thickness (0.826, p=0.01); grain yield/plant and dry root weight (0.946, p=0.01); Root length and Dry root (0.639, p=0.01); dry root weight and root thickness (0.581, p=0.01) (Table S8) [24][25][26][27][28][29][30]. Frequency distribution curves were prepared for all the traits analyzed. In most of the cases it was parabolic, in some trait it was parabolic but skewed toward MAS25 (panicle length and grain yield in both generation) and IB370 (root thickness in both generation) ( Figures S2 and S3).
In F 3 all 100 plants from field and 43 from net house were analyzed for BAD2A allele (Figures 1 and 2, here allelic state of only 60 plants from field is shown). 60 plants were found to poses all the three alleles were selected for further analysis. Quantification of 2-acetyl-1-pyrroline (2AP) in large populations has been difficult and expensive. Consequently, molecular polymorphism at BAD2 aroma locus, which is highly efficient and cost-effective, has been widely used in discriminating fragrant and non-fragrant rice genotypes; it shows perfect co-segregation with the trait of fragrance in the mapping population [31][32][33][34].

Pot experiment
Each selected line and their parents were sown in the replication of five, with one plant per pot. Manual weeding was done whenever required. The pots were irrigated with 1 liter of water for the first 15 days, and then with 1 liter after every third day up to panicle emergence. After twenty and forty days the pots were supplemented with Yoshida solution [16]. The data on root morphological traits i.e. root length, root thickness, fresh and dry root weight from five plants from each line at maturity were recorded and analyzed.

Statistical analysis
Statistical parameter of variability and phenotypic correlation coefficient were analyzed by using OPSTAT statistical tool [17].

Molecular Markers for Analysis of Aroma in Rice
Progenies showing the desired phenotypic results were used for genotypic analysis. Specific primers for betaine aldehyde dehydrogenase 2 (BAD2A) genes [18] were used for assessing the presence/absence of fragrance allele in rice progenies. Basmati rice variety, Improved Basmati 370 amplified two alleles of 585 and 257 bp, while MAS25 amplified 585 and 355 bp size alleles (Table 1 and Figure 1). The progenies having at least the BAD2A alleles of IB370 were selected for SSR marker analysis.

Genotyping of Mapping Population
For genotyping of desired plants from both field and net house conditions were selected. Performances of plant for yield and root traits were the main criteria for selection in field and net house respectively. Genomic DNA was isolated from young leaves using the CTAB method [18,19]. DNA quantity was estimated by ethidium bromide staining on 0.8% agarose gels using a standard containing 100 ng/ μl λ genomic DNA. PCR amplification was essentially carried out as described earlier by Jain et al. [20]. PCR products were separated on 8% polyacrylamide gels.
A total of 604 SSR markers widely distributed on 12 rice chromosomes ( Figure S1) were used to analyze polymorphism and 70 polymorphic markers were detected. The molecular markers were obtained based on published rice genome maps IRGSP, 2005 and their physical position (Mb) on the indica genome [21] were used as a reference. Genetic similarities between the cultivars were measured by the similarity coefficient based on the proportion of shared electromorphs using the 'Simqual' subprogram of the NTSYS-PC (Version 2.02 Exeter Software, Setauket, NY, USA) software package.

Results and Discussion
Under field conditions enormous variation was observed for all scaling of rice genotypes by principal component analysis. In this study, clustering or grouping of Basmati rice varieties in a different group than lowland and aerobic Indica rice is in the conformity with the earlier reports [22,33,35,36].
SSR database developed for MAS25 x IB370 F 3 population comprising of 60 plants was used to map QTL for important physiomorphological traits using Composite Interval Mapping (CIM) analysis (WinQTL Cartographer 2.5). Analysis revealed a total of seven QTL (three for grain yield/plant, two QTL for effective number of tillers/ plant, one each for plant height and l/b ratio) which individually explained 3.6-72.1% phenotypic variance (Tables 1 and 2). Two QTL were associated with effective number of tillers/plant (qENT6.1 and qENT6.2) at map position of 7.4 and 28.81 cM on chromosome 6 and 9 respectively. One QTL was associated with panicle length (qPL1.1) at map position of 5.0 cM on chromosome 1, which had maximum LOD score of 7.0 and accounted for 54.43% phenotypic variation. Three QTL were associated with grain yield/plant (qGYP5.1, qGYP9.1, and qGYP12.1) at map positions of 34.2, 16.9 and 59.6 cM on chromosomes 5, 9 and 12, respectively. These QTL had LOD score of 5.3, 3.2 and A DNA fingerprint database of selected 60 MAS25 x Improved Basmati 370 F 3 plants (field experiment) and 13 net house plants was developed using 70 markers. Allelic state of the selected plant at SSR locus RM163 and RM219 are given in Figures 3 and 4.
The proportion of shared alleles of 70 polymorphic SSR markers was used to calculate the coefficient values among the selected 60 MAS25 × Improved Basmati 370 F 3 plants (field experiment) and subjected to UPGMA tree cluster analysis. The allelic diversity was used to produce a dendrogram (cluster tree analysis, NTSYS-pc) to demonstrate the genetic relationship among 60 F 3 plants from field ( Figure 5) and 13 from net house with the parental rice varieties ( Figure 6).
Parental rice genotypes, MAS25 and Improved Basmati 370, were quite diverse and bifurcate at the coefficient value of 0.48. The 60 F 3 plants clustered in two major groups at a similarity coefficient of 0.51. Major group I consisted of MAS25 along with 60 F 3 plants and group II had only Improved Basmati 370. Two-dimensional PCA scaling exhibited that F 3 population was interspersed between the two parental lines with distribution of most plants towards MAS25 (Figures 7 and  8). The resultant distance matrix data were used for two-dimensional         2.5 and accounted for 28.6, 33.6 and 72.1% phenotypic variation, respectively. One QTL associated with grain length/breadth ratio (qLB1.1) at map position of 69.4 cM on chromosome 1, had a LOD score 3.1 and explained 52.4% phenotypic variation.

Trait QTL name Chromosome No Position (cM) Flanking markers Position of flanking markers (cM) LOD Additive effect R 2 % DPE
In Tables 2 and 3 DPE (direction of phenotypic effect); M and IB indicate "MAS25" and "Improved Basmati 370" alleles, respectively. R 2 is phenotypic variation, Additive effect is half the difference between the effect of "MAS25" allele and "Improved Basmati 370" allele; its positive value indicates that the effect of genotype "MAS25" was in the direction of increasing the trait value, LOD-log10 of an odd ratio.
Three of the seven QTL had positive values for additive effect indicating that the favoring alleles were from donor parent MAS25 (Figures 9 and 10).
A total twenty-two (17 from field and 5 from net house) plants were selected to grow F 4 progeny from F 3 plants on the basis of physiomorphological performance and root traits (in case of net house evaluation) and status of allelic profile at BAD2A and SSR locus for further progeny analysis. BAD2A marker analysis was done in F 4 plants. Plants possessing the desirable BAD2A alleles were selected for SSR marker analysis. SSR database of 60 and 14 F 4 plants selected from the     field and net house experiments were developed using 70 polymorphic SSR markers. Polyacrylamide gels displaying allelic polymorphism in MAS25 × Improved Basmati 370 F 4 population for SSR markers are shown (Figures 11 and 12).
The 60 F 4 plants (field experiment) clustered in three major groups at similarity coefficient of 0.51 ( Figure 13). Major group I consisted of IB370 along with four F 4 plants, major group II had MAS25 with 54 F 4 plants and major group III had only two F 4 plants. Similarly net house plants also clustered at similarity coefficient of 0.51 ( Figure 14). Genetic relationships among these rice genotypes (both net house and field) were also assessed by PCA analysis (Figures 15 and 16).
SSR database developed for MAS25 x IB370 F 4 population comprising of 60 plants was used to map QTL for important physiomorphological traits using Composite Interval Mapping analysis    (WinQTL Cartographer 2.5). A total of seven QTL were mapped which individually explained 93.2% phenotypic variation ( Table 3). One of these QTL was associated with effective number of tillers/plant (qENT3.1) at map position of 58.2 cM on chromosome 3 with LOD score of 4.5 another one with panicle length (qPL3.1) at map position of 31.2 cM on chromosome 3. Three QTL were associated with grain yield/ plant (qGYP2.1, qGYP6.1, and qGYP6.2) at map positions of 62.0, 39.4 and 104.4 cM on chromosomes 2, 6 and 6 with LOD score of 5.7, 2.7 and 2.7 respectively. Two QTL were mapped for L/B ratio (qLB6.1 and qLB9.1) at map position of 76.4 and 32.5 cM on chromosome 6 and 9; qLB9.1 accounted for 93.2% phenotypic variation having LOD score 6.3 (Figures 17 and 18).
QTL mapping of drought resistance traits in the background of locally adapted Indica/Basmati rice lines have been reported by several research groups in rice [8,34]. However, identification of QTL linked    to yield under water-limited aerobic conditions in target populations is critical. Marker-assisted selection using consistent-effect QTL promoting aerobic adaptation is an efficient approach for developing water-efficient aerobic rice varieties. As in the case of drought, QTL for a number of physio-morphological traits have been identified but with limited implications in breeding drought-tolerance rice varieties. Large-effect QTL for grain yield under drought have been identified [8,37] and their successful introgression has established yield-advantage under drought [38].