143 J. Crop Sci. Biotech. 2009 (September) 12 (3) : 143 ~ 148 DOI No. 10.1007/s12892-009-0106-8 RESEARCH ARTICLE Molecular and Morphophysiological Characterization of Superior Cluster Bean (Cymopsis tetragonoloba) Varieties Anita Punia1, Rakesh Yadav2, Pooja Arora2, Ashok Chaudhury2 1 2 University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra-136119 (Haryana), India Department of Bio and Nano Technology, Guru Jambheshwar University of Science & Technology, Hisar-125001 (Haryana), India Received: July 9, 2009/ Revised September 17/ Accepted: September 21, 2009 Abstract Cluster bean (Cymopsis tetragonoloba) belongs to tribe Indigoferae of family Leguminosae. India is the world-leader for cluster bean production as it contributes 80% shares of its total production. Cluster bean (guar) is a cash crop for its application in textile, paper, petroleum, mining, pharmaceuticals, explosives, and food industries. Owing to its immense wealth of variable morphophysiological and industrial qualities there is a strong need for appropriate addressing and well documentation of the germplasm. Efforts are to be made to organize research programs on germplasm characterization, utilization, and molecular characterization. Superior cluster bean varieties were selected on the basis of morphophysiological characters and subjected to DNA-based molecular marker analysis. Eighteen of the best genotypes were chosen for DNA extraction, optimization of PCR conditions, and genetic diversity studies using 37 random primers. A total of 381 random amplification fragments were obtained; number of amplifications ranging from 4 to 22 with an average of 10.29 amplified fragments per primer. Evaluation of RAPD data reveals a magnificent range (0.34-0.76) of genotypic similarity coefficients. The UPGMA dendrogram was constructed based on similarity indices which illustrated discrete clustering of different genotypes into groups. Results recorded a positive correlation amongst varieties vis-à-vis cluster analysis generated by NTSYSpc and morphophysiological characteristics. The degree and distribution of genetic diversity in cluster bean would facilitate an evolutionary relationship between numerous accessions that eventually catalogues genetic resources in a more concerted fashion. Key words: Cluster analysis, DNA fingerprinting, genetic diversity, guar (Cymopsis tetragonoloba), RAPD Introduction Cymopsis tetragonoloba (L.) Taub commonly known as guar is a cash crop of the family Leguminosae (Gillet 1958). It is a self-pollinated crop with 2n = 14 chromosomes (Ayyanagar and Krishnaswami 1933; Hymowitz and Upadhya 1963). It is widely cultivated in countries like India, Pakistan, USA, Italy, Morocco, Germany, Greece, Spain, and is thus considered as a new crop for western agricultural practices (Hymowitz and Matlock 1963). Guar seed is highly valued in numerous industries because of its galactomannan rich endosperm. Its nutritional and industrial value relies on one of the significant hydrocolloid products with high-thickening strength which constitutes 78-82% of the endosperm (Das and Arora 1978). The non-ionic hydrocolloid Ashok Chaudhury ( ) E-mail: ashokchaudhury@hotmail.com Tel: +91-1662-263306 / Fax: +91-1662-276240 The Korean Society of Crop Science commercially known as guar gum is chemically a galactomannan derivative that exhibits all the properties of a high viscosity, natural polysaccharide. Owing to these properties, guar gum has magnified applications in textile, paper, petroleum, mining, cosmetic, oil and pharmaceuticals, explosives, purification of potash, and tobacco and food industries. India conserves an enormous wealth of guar along with a wide variability for morphophysiological and industrial qualities. As cluster bean germplasm has either been lost or unidentified, hence there is an urgent need that the germplasm should be well documented. Many of the agronomic trait estimation-based problems associated with breeding programs such as major environmental effects or qualitative inheritance can be eliminated by molecular marker diagnosis. DNA based molecular markers have been useful in the evaluation of genetic diversity in many crop species (Agarwal et al. 2008). Marker assisted selection offers a great opportunity for imparting improved efficiency and 144 Characterization of Superior Cluster Bean Varieties effectiveness in the selection of plant genotypes. Among various recent DNA marker-assisted techniques, the random amplified polymorphic DNA (RAPD) technique (Williams et al. 1990) is becoming most popular because of its promptness, cost effective mode, and requirement of insignificant amount of plant materials as compared to restriction fragment length polymorphism (RFLP) technique (no hybridization and no use of radio isotope). Moreover, this protocol provides virtually an unlimited number of polymorphism, therefore also attains strong potential to identify cultivars at an early developmental stage. RAPD has been extensively used as a genetic marker for assessment of genetic diversity, germplasm characterization, cultivar identification, genetic purity testing, and gene tagging (Asemota 1996; Hu and Quiros 1991; Koller et al. 1993). It has also been frequently used for plant genetic studies including population genetics (Isabel et al. 1995), systematics and phylogenetic analysis (Agarwal et al. 2008; Demeke et al. 1992). Until now, to the best of our knowledge no finding has been reported for molecular characterization of superior cluster bean genotypes using RAPD makers. Thus, the prime objective was to examine the genetic diversity of elite guar genotypes of North India by employing morphophysiological aspects. DNA extraction DNA was extracted from fresh leaves as described by Zhao et al. (1989) with some minor amendments. Two grams of leaf samples were ground to fine powder in liquid nitrogen using pre-cooled pestle and mortar, and the powder was finally transferred to 10 mL of homogenization buffer (SSC 1X, SDS 2.5%, Sarkosyl 0.25%). The contents were thoroughly stirred and incubated at 65 ºC for 2 h to accommodate lysis reaction. Equal volume of phenol: chloroform: isoamyl alcohol (25:24:1) was added and mixed gently to denature proteins and to facilitate phase separation at 6500 rpm for 10 min at 15 ºC. The DNA was precipitated by adding 2 volume of ice cold ethanol and 1/10th volume of 3 M sodium acetate pH (5.2). The precipitated DNA was pelleted by centrifugation at 8000 rpm for 10 min at room temperature. The pellet was washed with 70% ethanol air dried and then dissolved in TE buffer (Tris pH 8.0 10 mM, EDTA pH 8.0, 1 mM). RNA was digested with RNase A (10 g mL-1) for 60 min at 37 ºC and protein was aloofed by treatment with proteinase-k for 60 min at 55 ºC DNA. Samples were electrophoresed in 0.8% agarose gel using TBE buffer to check the quality of DNA. PCR amplification Materials and Methods Plant materials Eighteen of the best lines were selected on the basis of various morphophysiological characters viz. plant height, seed weight, relative water content, chlorophyll content, number of clusters, and number of pods from 37 cluster bean accessions: HG 75, HG 365, HG 563, RGC 936, RGC 1022, PNB, GAUG 9002, GAUG 9009, RGC 1017, Naveen, Kiran (WF), GG-1, PLG 225, HGS 854, IC 116525, IC 102827, IC 116529, and IC 116874 (Forage Section, CCS Haryana Agricultural University, Hisar). Polymerase chain reaction was performed in a volume of 20 l reaction mixture containing 0.5 unit Taq DNA polymerase (Bangalore Genei Pvt. Ltd.), MgCl2 (1.5 mM) (Bangalore Genei Pvt. Ltd.), 200 mM each of dNTP, 0.2 M of primer, and 50 ng of genomic DNA. Amplification was performed in PTC-100 programmable thermal cycler. After initial denaturation at 94 ºC for 5 min, PCR was performed for 30-35 cycles consisting of a denaturation step for 1 min, followed by a gradient range of annealing temperatures 38º, 40º, 42º, 45º, and 50 ºC for 1 min and extension at 72 ºC for 2 min (Punia et al. 2009); at the end of the reaction final extension period was appended (72 ºC) 10 min. Amplification products were separated on 1.5% agarose gels in TBE buffer and photographed using gel documentation system (Vilber Lourmat). Table 1. Field performance of 18 superior cluster bean genotypes. Plants in the fields were raised in a randomized complete block design. All measurements were subjected to analysis of variance (ANOVA). Data represents means from three replicates ± SE. Variety/ Yield/ Days to 50% Days to Plant Branches Pods Cluster Pod Seeds Genotype Plant (g) Flowering Maturity Height(cm) /Plant /Plant /Plant Length (cm) /Pod HG365 HG563 RGC936 HG75 PNB PLG225 GG1 NAVEEN HGS854 RGC1017 RGC1022 GUAG9002 GAUG9009 KIRAN IC102827 IC116525 IC116529 IC116874 15.66±0.48 14.40±0.39 15.15±0.69 18.60±0.58 14.57±0.59 14.43±0.41 15.99±1.96 13.58±1.58 15.37±1.94 12.99±1.70 12.61±0.69 13.61±1.24 14.31±0.92 16.35±2.83 14.25±2.65 13.57±1.04 11.45±0.74 14.56±3.37 41.67±2.33 38.00±2.08 43.67±2.02 44.67±4.37 33.33±1.33 43.67±2.18 41.33±2.44 39.00±4.04 44.66±2.40 37.33±3.18 39.00±5.85 46.66±3.52 46.67±2.40 28.66±2.96 46.66±3.52 49.33±3.48 47.33±2.90 46.33±3.75 100.00±7.63 98.00 ±4.35 97.00±3.60 111.67±6.01 102.00±4.62 97.00±2.08 100.00±5.50 105.00±2.88 98.33±6.11 105.33±6.96 105.67±3.84 106.00±3.05 104.00±0.00 112.33±2.96 100.00±2.88 102.67±1.76 102.33±1.76 98.00±1.00 90.53±4.82 75.80±2.50 85.87±1.33 108.16±2.28 77.70±1.62 99.27±1.99 76.00±3.46 62.66±3.01 64.00±1.94 57.43±3.92 59.00±2.67 94.00±4.58 108.70±0.83 69.53±2.11 66.10±1.26 122.13±3.40 119.33±3.93 114.50±2.05 2.16±0.03 5.00±1.15 6.33±0.58 5.50±±0.21 0.00±0.00 2.67±0.33 6.07±0.46 1.60±0.17 2.00±0.36 0.53±0.17 0.47±0.18 4.27±0.17 2.53±0.23 3.87±0.17 8.47±0.12 9.63±0.14 9.70±0.10 8.53±0.17 40.26±1.82 30.37±2.75 46.73±2.04 71.83±0.75 26.00±1.52 26.47±1.22 41.67±1.22 25.33±1.76 43.00±0.57 21.73±0.06 21.57±0.23 31.80±0.05 27.77±0.08 65.33±1.45 71.63±0.21 79.33±0.06 69.43±0.52 91.87±0.75 11.33±0.47 10.00±3.46 21.40±1.78 17.73±1.87 11.67±0.33 10.33±0.33 13.53±0.17 12.40±0.17 13.63±0.12 7.60±0.00 7.60±0.05 12.47±0.17 9.60±0.15 26.67±1.43 22.67±1.74 22.47±0.18 21.37±0.29 23.80±1.47 5.63±0.10 6.42±0.04 5.73±0.07 5.43±0.08 13.34±0.17 5.70±0.13 5.63±0.01 4.70±0.26 6.10±0.20 5.43±0.08 5.40±0.00 4.37±0.14 6.54±0.02 7.20±0.00 6.73±0.23 6.24±0.00 6.29±0.05 6.22±0.09 8.70±0.32 8.36±0.21 8.23±0.08 7.67±0.13 8.53±0.12 7.80±0.00 8.533±0.17 7.267±0.17 8.500±0.20 6.533±0.23 6.567±0.20 6.467±0.17 8.400±0.11 6.333±1.20 8.400±0.11 9.233±0.08 8.000±2.08 7.333±1.76 JCSB 2009 (September) 12 (3) : 143 ~ 148 Data evaluation for morphophysiological characteristics All the selected superior genotypes were sown in the fields of College of Agriculture, CCS Haryana Agricultural University, Hisar during Kharif season (Punia 2004). The genotypes were grown in a complete randomized block design with all the recommended package practices. The data was collected for two consecutive years for 18 superior varieties with respect to yield/plant (g), days to 50% flowering, days to maturity, plant height (cm), branches/plant, pods/plant, clusters/plant, pod length (cm) and seeds/pod in three replicate values and analyzed using analysis of variance (ANOVA) for a completely randomized block design. The treatment means were calculated using three replicates by employing MSTAT software which represents ± SE as shown in Table 1. Data evaluation for PCR amplification The amplification of DNA samples which produced reproducible bands were considered for analysis. Each amplified product was scored across all the 18 genotypes for thirty-seven random 10-mer primers. Band positions for each guar genotype and primer combination were scored as either present (1) or absent (0). The scores were entered into a database program (Microsoft Excel) and compiled in a binary matrix for phenetic analysis using NTSYS-pc (Numerical Taxonomy & Multivariate Analysis) system. The SIMQUAL program was used to calculate Jaccard’s similarity coefficient and a dendrogram of the genetic relatedness among 18 genotypes was produced by means of the Unweighted Pair Group Method with Arithmetic Average (UPGMA) analysis. The reliability of the cluster analysis was assessed by applying bootstrap procedure which was carried out with Win Boot computer program (Yap and Nelson 1996). The two-dimensional and three-dimensional Principal Component Analysis (PCA) was constructed for providing suitable means of testing the relationship among 18 superior cluster bean genotypes using the EIGEN program NTSYSpc. Results and Discussion Genetic diversity analysis based on RAPD markers Several conditions influencing PCR amplifications such as amount of genomic DNA, Mg2+ ion concentration, levels of Taq DNA polymerase, and denaturing temperature for reproducible RAPD banding pattern were optimized (data not shown). In the present investigation, RAPD analysis of 18 superior guar genotypes was performed with a total of 381 amplified reproducible bands produced from 37 random decamer primers. The number of bands ranged from 4 to 22 with an average of 10.29 bands per primer. Fig. 1 shows the RAPD amplification profiles obtained using decamer primer E-02 and AI-08 in 18 superior guar genotypes. On similar findings, (De Laia et al. 2000) reported, total of 62 amplification products from 15 random 10-mer primers out of which 39 products were polymorphic in Eucalyptus clones. Similarly, Asante and Offei (2003) reported 39 polymorphic products among 50 cassava genotypes from four primers. Fig. 1. Ethidium bromide stained agarose gel showing RAPD products obtained from PCR amplification profile of 18 superior cluster bean genotypes generated from RAPD primers AI08 and E02. Lane M contains molecular weight marker (1 kb ladder). Lane 1-18 represents the genotypes as RGC936, IC116525, GAUG9002, PNB, IC116874, RGC1017, HGS854, HGS563, GG1, NAVEEN, HG365, RGC1022, HG75, IC102827, PLG225, KIRAN, GAUG9009, and IC116529, respectively The mean number of fragments per accession per primer ranged from 5.5±1.04 to 7.0±0.71. Correlation of genetic diversity based on morphophysiological characteristics and RAPD analysis The field performance of 18 superior cluster bean varieties for yield/plant (g), Days to 50% flowering, days to maturity, plant height (cm), branches/plant, pods/plant, clusters/plant, pod length (cm), and seeds/pod in three replicates has been summarized in Table 1. Pooled analysis of two year’s data was carried out using one-way ANOVA. The analysis of variance indicated that management practices have improved crop fabrication skills and 145 146 Characterization of Superior Cluster Bean Varieties Fig. 2. Dendrogram (NTSYS-pc) constructed with UPGMA clustering method among 18 superior cluster bean genotypes using 37 different primers. Similarities were computed from 381 random polymorphic data loci. The scale in the figure is genetic similarity coefficient calculated according to Jaccard’s. Clusters were delineated at an arbitrary level of 70%. Numbers at the nodes represent bootstrap values generated by 1000 replications using WinBoot Program farmers practices. All the values were calculated by ANOVA technique which showed significant increase in mean values (Table 1). The results were found to be highly significant at P ≤ 0.05. Out of 18 selected varieties, yield/plant was highest in HG75 (18.60 g) and lowest in IC116529 (11.45 g). The variety Kiran exhibited 28.66 days to 50% flowering, whereas, IC116525 showed 49.33 days. HG75 and Kiran showed the highest number of days to maturity (112 days), while PLG225 and RGC936 were the earliest maturing varieties (97 days) as shown in Table 1, thus making the latter desirable for breeding purposes. Plant height from the base of the plant to the shoot tip was highest in IC116525 (122.13 cm) followed by IC116529 and IC116874, whereas, RGC 1017 and RGC 1022 showed the lowest values (57.43 and 59 cm, respectively). The variety IC116529 exhibited the highest number of branches/plant of 9.7, whereas, PNB is a non-branching variety. The highest pods/plant of 91.87 was obtained in IC116874 variety. The variety PNB exhibited largest pod length of 13.34 cm among the 18 varieties employed as shown in Table 1. The highest seeds/pod of 9.233 was shown by the variety IC116525. It was observed that grouping of varieties obtained by molecular marker analysis was supported by grouping obtained on the basis of morphophysiological characteristics. There was a positive correlation between the grouping of varieties by NTSYSpc and morphophysiological characteristics. The genotypes RGC936, IC116525, GAUG 9002, IC116874, and HG365 (Fig. 2) occupied the sub-cluster of the second major cluster. Out of these varieties, IC 116525 and IC 116874 pooled in the same cluster on the basis of cluster/plant, yield/plant, biological yield/plant and plant height. Another sub-cluster generated by HGS563, IC116529, and GG1 showed a positive clustering with dendrogram on the basis of morphophysiological characters, among these HG563 and GG1 formed the same group on the basis of plant height. Similarly, HG75, PLG225, IC102827, Naveen, and Kiran also grouped in one cluster for plant height. Cluster analysis was done on the basis of similarity coefficients generated from RAPD data of 381 bands. Similarity coefficients ranged from 0.34 to 0.76 among 18 genotypes. All the 18 superior varieties were grouped into two major clusters at 0.34 similarity coefficient (Fig. 2). The first cluster consisted of PNB, RGC 1017, and HGS854. The second major cluster was occupied by other 15 varieties. The second cluster was further divided into sub clusters at 0.57% similarity level. These sub-groups are further divided into small clusters as the similarity coefficient level increases. HG365 and IC116874 showed JCSB 2009 (September) 12 (3) : 143 ~ 148 diagonalized the two- and three-dimensional scales among the various cluster bean genotypes, which depicted average and low redundancy as shown in Figs. 3 and 4, respectively. Principal components with EIGEN value greater than one were selected for interpretation. First Principal component scored 57.04% variation while second component scored 8.1% variation. Similar grouping was observed in 3D analysis. Chiorato et al. 2007 has created a biplot of principal coordinates related to 220 accessions of the common bean germplasm bank based on genetic similarity matrix and concluded that both molecular and morphoagronomical data sets were equally effective to quantify and organize the genetic diversity studies. Similar supportive analysis associating morphological and RAPD data of common beans were performed by Duarte et al. (1999). Nevertheless, no correlation was detected. Conclusions Fig. 3. A 2D scaling representation by principal component analysis (PCA) of 18 superior cluster bean genotypes A positive correlation between different genotypic varieties with respect to morphophysiological characteristics using RAPD analysis as well as in cultivar identification was designated in cluster bean lines. The degree and distribution of genetic diversity in commercially important cluster bean enables us to understand evolutionary relationship between accessions as well as cataloguing genetic resources in future. This is the first report of genetic diversity studies of superior genotypes of cluster bean using DNA based molecular markers. It is anticipated that the data presented here will augment biological conservation and evolutionary process as well as serve as basis for selection of elite parents in undertaking breeding programs in future. Acknowledgements Dr Anita Punia duly acknowledges help and support by Dr. J V Singh (Late) and Dr. PP Gupta, Senior Scientists Forage Section, CCS Haryana Agricultural University, Hisar in providing and maintaining plant material. References Fig. 4. A 3D scaling representation by principal component analysis (PCA) of 18 superior cluster bean genotypes maximum relatedness with each other. 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