51 © 2017 Conscientia Beam. All Rights Reserved. MOLECULAR CHARACTERIZATION OF PARENTAL LINES OF RICE AIMING TO ADDRESS HIGH YIELD AND NUTRITIONAL QUALITY UNDER DROUGHT AND COLD STRESS CONDITION Nomita Das1 Partha S. Biswas2+ 1Jahangirnagar University, Savar, Dhaka, Bangladesh 2Bangladesh Rice Research Institute, Gazipur, Bangladesh (+ Corresponding author) ABSTRACT Article History Received: 2 March 2017 Revised: 30 March 2017 Accepted: 3 May 2017 Published: 7 June 2017 Keywords Drought Cold Grain zinc content Genetic diversity SSR Rice. Abiotic stresses limit crop growth at different growth stages resulting low yield of rice. Molecular characterization of parental materials gives precise information on the extent of genetic diversity exists between them. A set of 60 SSRs randomly distributed over 12 chromosomes were used to analyze eight cultivars intend to be used as parent in breeding programs to address cold and drought tolerance, and nutritional quality of rice. A total of 300 alleles were detected across the cultivars for 51 polymophic markers with 5.88 alleles per loci. On average 30.6% of the genotypes shared a common allele at any given locus. UPGMA cluster analysis showed that 67% common alleles were shared by the cultivars. The cultivars were clearly grouped into two distinct clusters at 67.0% genetic similarity. Hbj. BVI showing high tolerance to cold stress at seedling stage differed from cold susceptible BR1, BRRI dhan28 and BRRI dhan29 by 33% alleles while BR18 that showed moderately cold tolerance differed by 29.0 - 29.9% alleles which indicated that only 3-4% alleles difference caused higher cold tolerance in Hbj. BVI. The moderate genetic distance between cold tolerant Hbj. BVI and high yielding BRRI dhan28 and BRRI dhan29 indicated that there is higher possibility of obtaining high yielding cold tolerant segregants from the crosses between them. On the other hand, Kalobokri, which had 31.7 mg zinc a kilogram of polished rice differed by 33.0% alleles from the drought tolerant rainfed low varieties BRRI dhan56 and BRRI dhan57 having moderate level of zinc (~20 mg/kg), which also indicated that crosses between them might produce progenies with higher nutritional quality under drought environment. Contribution/ Originality: This study is one of the few studies which have investigated the genetic distance between the parental lines that are intended to be used in the breeding program to address abiotic stresses, like drought and cold tolerance with high yield potential and enhanced nutritional quality, particularly zinc content in rice. 1. INTRODUCTION Rice (Oryza sativa L.) production in Bangladesh is affected by various abiotic stresses. The rainfed lowland rice is greatly affected by drought stress accounting for 46%, 37% and 73% yield loss if it occurs during flowering, maturity and both flowering and maturity, respectively [1]. On the other hand, Boro rice is suffered from critical Current Research in Agricultural Sciences 2017 Vol. 4, No. 2, 51-60. ISSN(e): 2312-6418 ISSN(p): 2313-3716 DOI: 10.18488/journal.68.2017.42.51.60 © 2017 Conscientia Beam. All Rights Reserved. http://crossmark.crossref.org/dialog/?doi=10.18488/journal.68.2017.42.51.60&domain=pdf&date_stamp=2017-01-14 Current Research in Agricultural Sciences, 2017, 4(2): 51-60 52 © 2017 Conscientia Beam. All Rights Reserved. low temperature at different stages of growth from germination to maturity that in turn results into low yield. However, low temperature stress at booting stage produces sterile spikelets causing direct yield loss of short duration varieties up to 100% in some years in the low lying haor areas of Bangladesh. Approximately 22.4% and 20% of total rice areas in the country are affected by moderate to severe level of drought and cold stress, respectively. Landraces play very important role as genetic resource for genetic improvement of rice [2] particularly to address abiotic stresses like drought and cold. Modern plant breeding techniques can effectively use landraces having different economic traits including enhanced resistance to certain stress, better grain and nutritional quality and of course the yield contributing traits. Knowledge on genetic divergence between parents is necessary to design a breeding program in order to have transgressive segregation. Genetic diversity determines the inherent potential of a cross for heterosis and frequency of desirable recombinants in advanced generations. Several workers have emphasized the importance of genetic divergence for the selection of desirable parents [3, 4]. The estimation of genetic diversity between different genotypes is the first and foremost process in plant breeding [5]. Among various techniques available for assessing genetic variability and relatedness among crop germplasm, DNA based markers provide very effective and reliable means for measuring genetic diversity and studying evolutionary relationships. Molecular markers can reveal abundant difference among genotypes at the DNA level, providing a more direct, reliable and efficient tool for germplasm characterization, conservation and management avoiding environmental influence in contrast to morphological traits. Simple sequence repeat (SSR) markers which are abundant in rice genome and cost effective in discriminating small number of varieties/germplasm have been effectively used to identify genetic variation among rice cultivars [3, 6-8]. In this study, we used eight rice varieties/cultivars to dissect genetic variation among them using SSR markers to measure the extent of genotypic differences, genetic relationship and to assist in broadening the germplasm base of future drought and cold tolerance rice breeding programs. 2. MATERIALS AND METHODS A total of eight rice cultivars having diverged trait benefits, like drought tolerance, cold tolerance, enhanced grain zinc content, short duration and high yielding (Table 1) were analyzed using 60 SSR markers randomly distributed over the rice genome. Among the eight cultivars, BR1, BR18, BRRI dhan28, BRRI dhan29 and Hbj.B.VI were evaluated against artificial cold treatment for seedling stage cold tolerance following protocol described in Khatun, et al. [9]. Cold tolerance was estimated based on leaf discoloration (LD) score following SES of IRRI, % Survival plants at day of scoring and % Recovery of plants after seven days of cold stress withdrawal. BRRI dhan56 and BRRI dhan57, two drought tolerant varieties showing no significant yield losses even when ground water table remained 70-80 cm below the surface at reproductive stage [10] were included in this study. All the genotypes except Hbj.BVI were analyzed for polished grain zinc content using X-Ray Fluorescence method in X-Supreme 8000. For SSR analysis, DNA was extracted from young and actively growing fresh leaves using miniprep modified CTAB method as described by Virk, et al. [11]. Polymerase chain reaction (PCR) was performed in 10µl volume containing 2µl of genomic DNA, 5.3µl of DDH2O, 1µl of 1X PCR buffer, 1µl of 0.1mM dNTP mix, 0.5µl of 0.25uM of each primer, 2µl of Taq polymerase of 1U. The temperature cycles were programmed at 94oC for 5 min(initial denaturation), 94oC for 30 sec (denaturation), 55oC for 30sec (primer annealing), 72oC for 60sec (extension), 72oC for 5 min (final extension) and 10oC forever (storage). The PCR products were detected using 6% polyacrylamide gel electrophoresis. DNA bands were visualized in a UV transilluminator with ethidium bromide staining. Molecular weight of clearly resolved and unambiguous band was determined comparing with the known sized marker DNA using Alpha Ease FC 4.0. Polymorphic Information Content (PIC) values were calculated for each SSR loci using Power Marker V3.25 [12] based on the formula developed by Anderson, et al. [13]. Current Research in Agricultural Sciences, 2017, 4(2): 51-60 53 © 2017 Conscientia Beam. All Rights Reserved. PICi= 1 – where, Pij is the frequency of the jth allele for the ith marker and is summed over n alleles. The similarity matrices deduced from simple matching coefficient in PowerMarker analysis were subjected to unweighed pair-group arithmetic average (UPGMA) clustering analysis and represented in dendrogram form using NTSYS-pc program [14]. 3. RESULTS 3.1. Evaluation for Seedling Stage Cold Tolerance All the genotypes varied significantly in all three cold related traits. LD scores ranged from 2.0 to 8.7 among the genotypes. The highest LD was obtained with BR1 (8.7) followed by BRRI dhan28 (7.3) and BRRI dhan29 (7.0), while the lowest LD was observed with Hbj.BVI followed by BR18. Per cent survivability and % recovery values were also highest with Hbj.BVI followed by BR18, while BR1 had the lowest values for these traits. BR18 and Hbj.BVI were significantly different from the rest of the three genotypes in LD score. In % survivability and % recovery BR18 and Hbj.B.VI were also significantly different from other three genotypes and they were significantly different from each other as well (Table 2). 3.2. Evaluation of Polished Grain Zinc Content The genotypes showed wide variation in grain zinc content ranging from 14.5 to 31.7 mg/kg. The highest zinc content was observed with the landrace Kalobokri, while all the cultivated varieties had zinc value close to 15 mg/kg except BRRI dha57, which had 20.8 mg zinc a kilogram of polished rice grain (Table 3). BRRI dhan28 and BRRI dhan29 had 15.6 and 16.9 mg zinc in a kilogram of polished rice, respectively. 3.3. Polymorphic Information Content and SSR Diversity Sixty SSR markers were analyzed for assessing genetic divergence among eight rice cultivars. Among them, seven SSRs did not amplify at all and two markers showed monomorphism. Table 4 summarizes the results obtained from the analysis of 51 SSR loci across the test cultivars. Polymorphic information content which evident the extent of polymorphism among the cultivars varied from 0.511 to 0.861 with an average of 0.758. The highest PIC value was observed with RM 6024 and the lowest with RM193, RM 7193, RM335 and RM 1282. Out of 51 markers, 7 markers on chromosome 1, 6 markers on each of chromosome 2 and 6, 5 markers on each of chromosome 3 and 7, 4 markers on each of chromosome 12, 3 markers on each of chromosome 4, 5 and 11 and, 2 markers on each of chromosome 8, 9 and 10 were found polymorphic. A total of 300 alleles across the cultivars were detected at 51 SSR loci. The average number of alleles per locus was 5.88 with a range from 3 (RM6024 and RM6370) to 8 (RM193, RM335, RM1282 andRM7193). Among 51 SSRs, 3 alleles were detected for 2 markers, 4 alleles for 5 markers, 5 alleles for 7 markers, 6 alleles for 24 markers, 7 alleles for 9 markers and 8 alleles for 4 markers. The frequency of occurrence of an allele at each locus ranged from 12.5 % (RM193, RM335, RM1282 andRM7193) to 50% (RM329, RM497, RM6023, RM6024, RM6370 and RM7341) with a mean of 30.6%. The occurrence of number of alleles per loci was found variable irrespective of the numbers of repeat motifs and their base composition. Among 51 SSRs, 26 makers anchoring dinucleotide motif produced 154 alleles, 15 markers anchoring trinucleotide produced 82 alleles, 5 markers having tetranucleotide motifs produced 32 alleles and mixture of di- and trinucleotide motifs produced 32 alleles. The UPGMA cluster analysis based on Shanon indices obtained from binary data that were deduced from DNA profiles of the test genotypes for the SSR markers showed high genetic variation among the cultivars with similarity coefficient values ranging from 0.67 to 0.73 (Figure 1). The cultivars were clearly grouped into two Current Research in Agricultural Sciences, 2017, 4(2): 51-60 54 © 2017 Conscientia Beam. All Rights Reserved. distinct clusters at 67.0 % genetic similarity. Local variety, Kalobokri and local improved variety, Hbj.BVI were grouped into cluster I, while BRRI varieties constellated into cluster II, which was further subdivided into two sub- clusters at 70.5% similarity. BR1 and BRRI dhan56 were grouped into one sub-cluster and rest all the varieties into other sub-cluster. BRRI dhan28 and BRRI dhan29 shared 73% common alleles between them, while both of them had 71% common alleles with BR18. 4. DISCUSSION Genetic diversity among the progenitors is crucial for any successful breeding program. Strong genetic diversity means diverse morphological traits and potentially valuable genetic information. Rice varieties with high level of genetic variation are extremely beneficial resources for broadening genetic base of the germplasm and therefore, play a good foundation for rice breeding [15]. The genotypes of this study are highly diverged in different traits of benefits. Some of them are very high yielding but they lack some specific traits of interest. These traits are present in other specific genotypes of this study (Table 1). Among eight genotypes in this study, BRRI dhan28 and BRRI dhan29 are the two most popular and high yielding rice varieties of Bangladesh with yield potential up to 7.5 and 9.1 t/ha, respectively [16]. Since release in 1994 these two varieties are still giving the highest average yield in the farmers field in the Boro rice ecosystem (November to May) [17] although there a series of new high yielding modern rice varieties have been released recently in Bangladesh but they are not being cultivated widely by the farmer due to adoption lags [18]. However, both BRRI dhan28 and BRRI dhan29 lack cold tolerance which is very important to uphold the potential yield in cold prone environment. In this present study we also observed cold susceptibility of these two varieties in different cold related traits, viz. LD score, % survivability and % recovery (Table 2). Khatun, et al. [9] also reported cold sensitivity of these two varieties. Among the five genotypes tested for seedling stage cold tolerance, BR18 and Hbj.BVI showed moderate to high tolerance to cold stress at seedling stage, respectively. Importantly, BR18 was released for cold prone low lying haor areas for it long stature and Hbj.BVI is a local improved Boro rice of haor areas of Bangladesh. On the other hand, Kalobokri which showed higher zinc content (Table 3) is a landrace of upland Aus ecosystem. This genotype might significantly contribute in enhancement of nutritional quality in the high yielding segregating progenies when crossed with high yielding varieties like BRRI dhan28 and BRRI dhan29. Mohiuddin [19] mapped QTLs for grain zinc content from a F2:3 population of BRRI dhan28×Kalobokri. BRRI dhan56 and BRRI dha57, the two drought tolerant rainfed low varieties having early maturing traits also showed moderate level of zinc (~20 mg/kg) in polished grains. Thus, possibility of obtaining progenies with higher nutritional quality under drought environment would be higher from the crosses of Kalobokri with BRRI dhan56 and BRRI dhan57. SSR markers are powerful tool for analyzing genetic variability among the germplasm accessions, particularly when they are closely related [20-22]. In this study, 60 microsatellite markers were analyzed to reveal genetic distance among eight rice varieties aiming to use in a breeding program targeting high yield and nutritional quality under drought and cold prone environments. Seven markers out of 60 did not amplify and two markers showed monomorphic amplification. The non-amplification of SSRs might be due to their japonica based sequence [23] of which complementary sequence may not be present in the indica type rice in this study. On the other hand, monomorphism of the markers reflected genetic closeness of the cultivars. In closely related cultivars, these phenomena are frequent and are reported in many previous studies [22, 24-26]. However, comparatively high average PIC value (0.758) with a range from 0.511 to 0.861 that was calculated based on 51 polymorphic makers indicated that the cultivars are much diverged. In fact, the local varieties (Kalobikri and Hbj.BVI) had diverse morphological traits and specific adaption under certain stress condition than the other cultivars (Table 1). In this study, Kalobokri showed to have 31.7±0.7 mg zinc in a kilogram of polished rice and Hbj.BVI showed strong cold tolerance at seedling stage. Although, all 51 SSRs markers had higher PIC values than 0.50 (an arbitrary value which is considered as threshold value for determining informative markers), RM193, RM7193, RM335 and Current Research in Agricultural Sciences, 2017, 4(2): 51-60 55 © 2017 Conscientia Beam. All Rights Reserved. RM1282 had the highest PIC values (0.861), which indicated them to be the best markers for diversity analysis (Table 4). The level of PIC values of our study is comparatively higher than the reported PIC values in previous works [27-31]. The occurrence of alleles per SSR locus ranged from 3 (RM6024 and RM6370) to 8 (RM193, RM335, RM1282 andRM7193) alleles across 51 SSRs accounting a total of 300 alleles for eight cultivars. The average number of alleles (5.88) obtained in this study was bit higher than the mean allele values reported by Etemad, et al. [32] (3.57), Hossain, et al. [31] (3.8), Matin, et al. [27] (4.4), however it was much lower than the mean allele number reported by Yasmin, et al. [33]; Xu, et al. [34]; Jain, et al. [35]; Jayamani, et al. [36]; Zeng, et al. [37] and Prathepha [38] who reported an average of 13, 11.9, 7.8, 14.6, 7.7 and 11.85 alleles per locus using US rice genetic resources, Indian quality rice germplasm, a diverse collection of Portuguses rice, rice landraces from China and Wild rice (Oryza rufipogon) from Northeastern Thailand and Laos, respectively. The reason behind the detection of higher number of alleles in those studies was the wider variability among the germplasm. In our study, the wide genetic distance of Kalobokri and Hbj.BVI from other varieties might contribute a lot in occurrence of higher mean allele per SSR locus. Another cause might be the low resolution of markers density covering the whole genome and less number of germplasm used in the diversity analysis. However, on average 30.6% of the total genotypes shared at least a common major allele at any given locus ranging from 12.5% (RM335 and RM1282) to 50% (RM6024 and RM6370) common alleles at each locus. The gene diversity across the SSR loci ranged from 0.594 (RM6024) to 0.875 (RM193, RM335, RM1282 andRM7193) with an average of 0.788. This higher gene diversity indicated that there was wide range genetic variation among the genotypes and this was due to inclusion of local varieties in the study. The highest number of alleles (8) at each locus for RM193, RM335, RM1282 and RM7193 also confirmed this finding. However, detection of higher number of alleles at each locus was not found correlated with the anchoring motifs of the SSR loci. Majority of the SSR markers had dinucleotide repeat motifs (GA/AG, CT/TC and TA). Di-ncleootide repeat motifs are thought to be perfect repeat motif for discerning high level of variation among the genotypes [39]. In this study, the loci with perfect dinucleotide repeat motifs detected almost similar level of alleles per locus (on average 5.9, n = 26) to those with tri-, tetra- and mixture of compound di- and tri- and tetra nucleotide motifs. UPGMA cluster analysis also revealed the existence of genetic distance among the genotypes using Shahon similarity index. The cultivars varied among themselves in a range between 67% and 73% in common allele sharing. The cultivars were clearly grouped into two distinct clusters at 67.0% genetic similarity. Kalobokri and Hbj.BVI which shared around 67.8% common alleles were grouped into one cluster and all the HYVs constellated into a second cluster. However, the second cluster was further grouped at 70.4% genetic similarity discriminating cultivars of Bangladesh origin from Philippines origin except BR18, which was introduced from Indonesia. Cold tolerant Hbj.BVI differed from cold susceptible varieties BR1, BRRI dhan28 and BRRI dhan29 by 33% while moderately cold tolerant variety BR18 differed by 29.0 - 29.9% alleles, which indicated that 3-4% allelic difference between Hbj.BVI and BR18 was responsible genetic factors for higher cold tolerance in Hbj.BVI. Generally, modern HYVs of rice share a relatively narrow genetic background as because they are mostly derived from common progenitors [40]. The high level of genetic similarity might be due to predominance of the HYV (6 out of 8 cultivars) in this study. The moderate level of genetic distance between Hbj.BVI and the high yielding BRRI dhan28 and BRRI dhan29 indicates that there is possibility to obtained high yielding and cold tolerant segregating progenies if crosses are made between them. On the other hand, the drought tolerant BRRI dhan56 and BRRI dhan57 differed from BRRI dhan28 and BRRI dhan29 by only 29.6% and 28.85% alleles and from Kalobokri by 33% alleles. These moderate level of allele difference might produce better recombinant if crosses are made between them, particularly to address zinc nutritional quality of rice under drought prone environments, as Kaloborkri possesses high zinc content and drought tolerant BRRI dhan56 and BRRI dhan57 have moderate level of zinc in their grains. Current Research in Agricultural Sciences, 2017, 4(2): 51-60 56 © 2017 Conscientia Beam. All Rights Reserved. 5. CONCLUSION The larger range of similarity values for cultivars revealed by the SSR markers provides greater confidence for assessment of genetic diversity and relationships, which can be used in future breeding programs. With the aid of the SSR makers used in this study, beneficial traits (cold or drought tolerance and nutritional quality) from Hbj.BVI, BRRI dhan56 or Kalobokri could be combined with modern HYVs by intercrossing. Furthermore, genetic mapping, population structure or kinships could be explored by increasing marker resolution. 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Rice variety Origin Characteristics BR1 IRRI, Medium duration HYV for Boro ecosystem, cold susceptible, short statured plant, SB grain BR18 Indonesia HYV for Boro ecosystem, cold tolerant at seedling stage, tall statured plant, long growth duration, MB grain BRRI dhan28 Bangladesh Medium duration HYV for Boro ecosystem, cold susceptible, LS grain, BRRI dhan29 Bangladesh Long duration HYV for Boro ecosystem, cold susceptible, MS grain, BRRI dhan56 IRRI Short duration HYV for RLR, drought tolerant, MS grain, BRRI dhan57 Bangladesh Short duration HYV for RLR ecosystem, drought tolerant Hbj.BVI Bangladesh Local improved short duration variety suitable for irrigated condition and has strong cold tolerance at both vegetative and reproductive stage, bold grain Kalobokri Bangladesh Landrace of upland ecosystem, black husk color, high grain zinc content, tall statured plant, medium duration , bold grain Note: SB, short bold; HYV, High yielding variety; MB, Medium bold; MS, Medium slender; LS, Long slender; RLR, Rainfed lowland; Boro, Irrigated dry season rice Table-2. Cold response of five genotypes at seedling stage under artificial cold stress of 13⁰C Genotype Leaf discoloration score % Survivability % Recovery BR1 8.7a 17.0c 3.3c BR18 4.0b 62.3b 47.9b BRRI dhan28 7.3a 31.0c 10.7c BRRI dhan29 7.0a 31.0c 12.7c Hbj.B.VI 2.0b 94.9a 80.3a https://scholar.google.com/scholar?hl=en&q=Determination%20of%20genetic%20relatedness%20among%20selected%20rice%20(Oryza%20Sativa,%20L.)%20cultivars%20using%20microsatellite%20markers https://scholar.google.com/scholar?hl=en&q=Molecular%20characterization%20of%20inbred%20and%20hybrid%20rice%20genotypes%20of%20Bangladesh https://scholar.google.com/scholar?hl=en&q=A%20marker%20based%20approach%20to%20broadening%20the%20genetic%20base%20of%20rice%20in%20the%20USA https://scholar.google.com/scholar?hl=en&q=Genetic%20analysis%20of%20Indian%20aromatic%20and%20quality%20rice%20(Oryza%20Sativa%20L.)%20germplasm%20using%20panels%20of%20fluorescently-labeled%20microsatellite%20markers http://dx.doi.org/10.1007/s00122-004-1700-2 https://scholar.google.com/scholar?hl=en&q=Genetic%20relatedness%20of%20Portuguses%20rice%20accessions%20from%20diverse%20origins%20as%20assessed%20by%20microsatellite%20markers https://scholar.google.com/scholar?hl=en&q=Evaluation%20of%20genetic%20diversity%20of%20rice%20landraces%20(Oryza%20Sativa%20L.),%20in%20Yunnan https://scholar.google.com/scholar?hl=en&q=Evaluation%20of%20genetic%20diversity%20of%20rice%20landraces%20(Oryza%20Sativa%20L.),%20in%20Yunnan http://dx.doi.org/10.1270/jsbbs.57.91 https://scholar.google.com/scholar?hl=en&q=Genetic%20diversity%20and%20population%20structure%20of%20wild%20rice,%20Oryza%20rufipogon%20from%20Northeastern%20Thailand%20and%20Laos https://scholar.google.com/scholar?hl=en&q=Mapping%20and%20genome%20organization%20of%20microsatellite%20sequences%20in%20rice%20(Oryza%20Sativa%20L.) http://dx.doi.org/10.1007/s001220051342 Current Research in Agricultural Sciences, 2017, 4(2): 51-60 59 © 2017 Conscientia Beam. All Rights Reserved. Table-3. Zinc content in polished rice grain Genotype Grain zinc content (mg/kg) BR1 14.5±0.6 BR18 17.3±0.9 BRRI dhan28 15.6±0.3 BRRI dhan29 16.9±0.6 BRRI dhan56 18.3±0.2 BRRI dhan57 20.8±0.3 Kalobokri 31.7±0.7 Table-4. Diversity analysis of 51 SSR markers across 8 rice cultivars SN Marker Chromosome Repeat motif No, of allele Major allele frequency Gene Diversity PIC 1 RM259 1 (CT)17 6 0.375 0.781 0.754 2 RM329 1 (CAT)7 5 0.500 0.688 0.653 3 RM431 1 (AG)16 6 0.250 0.813 0.786 4 RM495 1 (CTG)7 5 0.250 0.781 0.746 5 RM1282 1 (AG)17 8 0.125 0.875 0.861 6 RM6840 1 (TCT)17 6 0.375 0.781 0.754 7 RM7341 1 (CATT)6 5 0.500 0.688 0.653 8 RM174 2 (AGG)7(GA)10 6 0.250 0.813 0.786 9 RM207 2 (CT)25 7 0.250 0.844 0.825 10 RM497 2 (CAC)11 4 0.500 0.656 0.605 11 RM4499 2 (TA)20 5 0.250 0.781 0.746 12 RM6023 2 (CCG)8 4 0.500 0.656 0.605 13 RM7451 2 (TAAT)8 7 0.250 0.844 0.825 14 RM168 3 T15(GT)14 6 0.250 0.813 0.786 15 RM545 3 (GA)30 6 0.250 0.813 0.786 16 RM1230 3 (AG)15 7 0.250 0.844 0.825 17 RM3586 3 (GA)12 6 0.250 0.813 0.786 18 RM6349 3 (GAA)9 6 0.250 0.813 0.786 19 RM241 4 (CT)31 6 0.250 0.813 0.786 20 RM335 4 (CTT)25 8 0.125 0.875 0.861 21 RM3333 4 (CT)15 5 0.375 0.75 0.712 22 RM1248 5 (AG)15 6 0.375 0.781 0.754 23 RM3170 5 (CT)12 5 0.375 0.75 0.712 24 RM3328 5 (CT)14 6 0.250 0.813 0.786 25 RM6024 5 (CCG)8 3 0.500 0.594 0.511 26 RM30 6 (AG)9A(GA)12 7 0.250 0.844 0.825 27 RM193 6 (GCT)5 8 0.125 0.875 0.861 28 RM276 6 (AG)8A3(GA)33 7 0.250 0.844 0.825 29 RM469 6 (AG)15 6 0.250 0.813 0.786 30 RM5405 6 (TC)14 6 0.375 0.781 0.754 31 RM7193 6 (ATAG)7 8 0.125 0.875 0.861 32 RM18 7 (GA)4AA(GA)(AG)16 6 0.375 0.781 0.754 33 RM436 7 (TAA)6 6 0.375 0.781 0.754 34 RM1243 7 (AG)15 4 0.375 0.719 0.668 35 RM1362 7 (AG)25 6 0.250 0.813 0.786 36 RM6872 7 (TGG)8 5 0.375 0.75 0.712 37 RM284 8 (GA)8 6 0.250 0.813 0.786 38 RM407 8 (AG)13 6 0.375 0.781 0.754 39 RM3120 8 (CA)12 7 0.250 0.844 0.825 40 RM205 9 (CT)25 7 0.250 0.844 0.825 41 RM7048 9 (AATA)8 6 0.375 0.781 0.754 42 RM590 10 (TCT)10 7 0.250 0.844 0.825 43 RM3451 10 (CT)19 7 0.250 0.844 0.825 44 RM6370 10 (GAA)14 3 0.500 0.625 0.555 45 RM441 11 (AG)13 6 0.250 0.813 0.786 46 RM5349 11 (TC)13 4 0.375 0.719 0.668 47 RM6094 11 (CCT)13 6 0.250 0.813 0.786 48 RM1246 12 (AG)15 4 0.375 0.719 0.668 49 RM1261 12 (AG)16 6 0.250 0.813 0.786 50 RM7619 12 (TGTA)13 6 0.375 0.781 0.754 51 RM8216 12 (TAA)25 6 0.250 0.813 0.786 Total - - - 5.88 0.306 0.788 0.758 Current Research in Agricultural Sciences, 2017, 4(2): 51-60 60 © 2017 Conscientia Beam. All Rights Reserved. Figure-1. Dendogram derived from UPGMA cluster analysis using Shanon indices based on DNA profiling with 51 SSR markers across eight rice cultivars. Views and opinions expressed in this article are the views and opinions of the author(s), Current Research in Agricultural Sciences shall not be responsible or answerable for any loss, damage or liability etc. caused in relation to/arising out of the use of the content.