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Genetic diversity of bitter gourd (Momordica charantia L.) genotypes revealed by RAPD markers and agronomic traits
Scientia Horticulturae 109 (2006) 21–28 www.elsevier.com/locate/scihorti
Genetic diversity of bitter gourd (Momordica charantia L.) genotypes revealed by RAPD markers and agronomic traits S.S. Dey a, A.K. Singh b, D. Chandel b, T.K. Behera a,* b
a Division of Vegetable Science, Indian Agricultural Research Institute, Pusa Campus, New Delhi 110012, India Division of Fruits and Horticultural Technology, Indian Agricultural Research Institute, Pusa Campus, New Delhi 110012, India
Received 6 September 2005; received in revised form 8 February 2006; accepted 6 March 2006
Abstract Bitter gourd or bitter melon (Momordica charantia L.) is considered as minor cucurbitaceous vegetable in spite of having considerable nutritional and medicinal properties. Although some reports on genetic diversity based on morphological characterization are available, no work has been conducted to estimate genetic diversity using molecular markers in this crop. In the present study, 38 genotypes of M. charantia including few commercially cultivars collected from different parts of India based on agro-ecological zones were analysed for diversity study both at morphological and molecular levels. Genomic DNA was extracted from young healthy leaves following the procedure of Doyle and Doyle [Doyle, J.J., Doyle, J.L., 1990. A rapid DNA isolation procedure from small quantity of fresh leaf material. Phytochem. Bull. 119, 11–15]. Pair-wise comparison of genotypes was calculated as per the procedure of Jaccard [Jaccard, P., 1908. Nouvelles recherches sur la distribution florale. Bull. Soc. Vaud. Sci. Nat. 44, 223–270]. Dendrogram was constructed using the unweighted pair group method with arithmetic averages (UPGMA) and the computation for multivariate analysis was done using the computer programme NTSYS-pc Version 2.0 [Rohlf, F.J., 1998. NTSYS-pc Numerical Taxonomy and Multivariate Analysis System, Version 2.01. Exeter Software, Setauket, NY, USA]. Diversity based on yield related traits and molecular analysis was not in consonance with ecological distribution. Among 116 random decamer primers screened 29 were polymorphic and informative enough to analyse these genotypes. A total of 208 markers generated of which 76 (36.50%) were polymorphic and the number of bands per primer was 7.17 out of them 2.62 were polymorphic. Pair-wise genetic distance (GD) based on molecular analysis ranged from 0.07 to 0.50 suggesting a wide genetic base for the genotypes. The clustering pattern based on yield related traits and molecular variation was different. # 2006 Elsevier B.V. All rights reserved. Keywords: Momordica charantia; Genetic diversity; RAPD
1. Introduction Bitter gourd (Momordica charantia L.), is an important cucurbit vegetable grown in tropics. Among the cucurbits, it is considered a prized vegetable because of its high nutritive values especially ascorbic acid and iron (Behera, 2004) besides, its immense medicinal values, mainly, for its hypoglycemic properties. The origin of this crop is probably India with secondary centre of diversity in China (Grubben, 1977). This species was domesticated in Asia, possibly in eastern India or southern China. India is endowed with large amount of genetic diversity based on morphological characters (growth habit, maturity and various fruit characters including shape, size, colour and surface texture (Robinson and Decker-Walters, 1999)). Two types of cultivars have been grown in northern India and nine * Corresponding author. Tel.: +91 11 25840306. E-mail address: [email protected] (T.K. Behera). 0304-4238/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.scienta.2006.03.006
types in southern India. Today, Indian cultivates primarily two varieties of M. charantia (i) var. charantia, which produces large fusiform fruits and (ii) var. muricata (wild) with small and round fruits (Chakravarty, 1990). In India, the genetic analysis based on quantitative traits has been made in this crop by Mishra et al. (1998) and Ram et al. (2000). However, genetic diversity among individuals or populations can be determined using morphological and molecular markers. Phenotypic characters have limitations since they are influenced by environmental factors and the developmental stage of the plant. In contrast, molecular markers, based on DNA sequence polymorphisms, are independent of environmental conditions and show higher levels of polymorphism. Among the different types of molecular markers available, random amplified polymorphic DNA (RAPD) are useful for the assessment of genetic diversity because of their simplicity, speed and relatively low cost compared to other molecular markers (William et al., 1990; Rafalski and Tingey, 1993).
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RAPD markers have been used extensively in cucurbits to classify accessions (Horejsi and Staub, 1999), identify cultivars and hybrids (Meng et al., 1996), analyse genetic diversity (Lee et al., 1996; Garacia et al., 1998; Gwanama et al., 2000; Levi et al., 2001; Sureja et al., 2006). The level of genetic diversity between parents has been proposed as a means of predicting hybrid performance and heterosis of crosses. The impetus for this approach stems from the high correlations of molecular marker-based genetic distances between parents with hybrid performance and heterosis obtained in studies by Lee et al. (1989), Sekhon and Gupta (1995) and Sureja et al. (2006). Present study is the first attempt to estimate genetic diversity in bitter melon as revealed by RAPD and morphological markers. 2. Materials and methods 2.1. Genotypes The experimental materials comprised of 38 indigenous genotypes of bitter gourd including commercially released
varieties of India and 2 promising gynoecious lines. The genotypes were selected based on genetic as well as ecogeographical diversity. They were evaluated at the Research Farm, Division of Vegetable Science, Indian Agricultural Research Institute, New Delhi, during spring–summer (dry) season of 2004. 2.2. Field evaluation and data collection The experiment was laid out in a Randomized Complete Block Design (RCBD) with three replications for phenotypic evaluation. Seeds were sown on both sides of the channel with a spacing of 2 m between channel and 60 cm between plants with 90 cm irrigation channels. The recommended NPK fertilizer doses and cultural practices along with plant protection measures were followed to raise an ideal crop. The fruits were harvested at marketable stage. Five plants were selected, after discarding the border plants at both ends, and were examined for 14 quantitative traits: (i) days to open first female flower (DTFFF), (ii) node number of first female flower (NTFFF), (iii) days to flower
Table 1 List of bitter gourd (Momordica charantia L.) genotypes used in this study Accession name
Source of collection
Salient features
Jaynagar Sel-1 Pusa Do Mausami (White) DBTG-1 DBTG-2 PusaDo Mausumi (Green) Gayeshpur Sel-1 DBTG-3 DBTG 5-1 CO-1 Priya DBTG-4 Preethi DBTG-6 Gayeshpur Sel-29 DBTG-101 Dindigul Local Mangalakudi Local Arupokkattai Local MDU-1 DBTG-5-2 DBTG-7 Mohanpur Sel-215 DBTG-8 DBTG-201 IC-2763 DBTG-9 DBTG-202 Arka Harit DBTG-10 DBTG-11 DBTG-12 DBTG-5-3 DBTG-13 Nakhara DBTG-102 DBTG-103 DBTG-14 WBK-1
Mohanpur, West Bengal I.A.R.I., New Delhi Baud, Orissa Ahmedabad, Gujarat I.A.R.I., New Delhi Mohanpur, West Bengal Baud, Orissa Sonepat, Haryana Coimbatore, Tamil Nadu Vellanikkara, Tamil Nadu Bagpat, Uttar Pradesh Madurai, Tamil Nadu Pondichery, Tamil Nadu Mohanpur, West Bengal Phulbani, Orissa Madurai, Tamil Nadu Madurai, Tamil Nadu Madurai, Tamil Nadu Madurai, Tamil Nadu Debrugarh, Assam Bhopal, Madhya Pradesh Mohanpur, West Bengal Shillong, Meghalaya Indore, Madhya Pradesh NBPGR, New Delhi Mayurbhanj, Orissa Ranchi, Jharkhand IIHR, Bangalore Barapani, Meghalaya Koenjhar, Orissa Pondicherry, Tamil Nadu Jorhat, Assam Chakdah, West Bengal Nakhara, Orissa Sambalpur, Orissa Bagpat, Uttar Pradesh Dhekanal, Orissa Raghunathpur, West Bengal
Medium vine, medium long, dark green fruits with continuous ridges Vigorous vine, medium long, white fruits with continuous ridges Medium vine, medium long, glossy green fruits with discontinuous ridges Short vine, medium long, light green fruits with discontinuous ridges Vigorous vine, long, glossy green fruits with continuous ridges Medium vine, long, dark green fruits with discontinuous ridges Medium vine, small ovate, light green fruits with discontinuous ridges Medium vine, long, glossy green fruits with continuous ridges Vigorous vine, extra long, dark green fruits with continuous ridges Short vine, medium long, dark green fruits with discontinuous ridges Short vine, long, light green fruits with discontinuous ridges Medium vine, long, white fruits with discontinuous ridges Medium vine, small round, dark green fruits with discontinuous ridges Medium vine, medium long, whitish green fruits with discontinuous ridges Medium vine, small ovate, light green fruits with continuous ridges Short vine, long, dark green fruits with discontinuous ridges Vigorous vine, small round, dark green fruits with continuous ridges Medium vine, small, light green fruits with discontinuous ridges Medium vine, extra long, dark green fruits discontinuous fruit Vigorous vine, long, light green fruits with continuous ridges Short vine, medium long, greenish white fruits with continuous ridges Medium vine, long, dark green fruits with continuous ridges Medium vine, extra long, dark green fruits with discontinuous ridges Medium vine, medium long, light green fruits with continuous ridges Medium vine, long, dark green fruits with continuous ridges Short vine, medium long, whitish green fruits with continuous ridges Medium vine, medium long, light green fruits with discontinuous fruits Vigorous vine, long, dark green fruits with continuous ridges Short vine, long, white fruits with discontinuous ridges Vigorous vine, long, dark green fruits with continuous ridges Medium vine, medium long, light green fruits with continuous ridges Short vine, long, light green fruits with discontinuous ridges Vigorous vine, long, light green fruits with continuous ridges Medium vine, extra long, dark green fruits with continuous ridges Medium vine, medium long, light green fruits with continuous fruits Short vine, medium long, dark green fruits with discontinuous fruits Medium vine, long, dark green fruits with continuous ridges Medium vine, medium long, dark green fruits continuous ridges
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opening to fruit set (DTFOFS), (iv) days to fruit set to maturity (DTFSTM), (v) days to sowing to first harvest (DTFH), (vi) female flowers per plant (FFPP), (vii) sex ratio (no. of male flowers:total no. of female flowers), (viii) total number of fruits per plant, (ix) average fruit length (cm), (x) average fruit diameter (cm), (xi) average flesh thickness (cm), (xii) average fruit weight (g), (xiii) yield per plant (kg) and (xiv) fruit index (length diadiameter). Means across three replications were calculated for each trait and used for data analysis (Table 1). 2.3. DNA isolation and RAPD assay Genomic DNA was extracted from young healthy leaves following the procedure of Doyle and Doyle (1990). Amplification reactions (25 ml final volume) contained 15 ng genomic DNA, 20 mM dNTPs, 15 ng primer (Operon Technologies, USA), 1 Taq DNA polymerase buffer containing 50 mM KCl, 10 mM Tris–Cl and 1.5 mM MgCl2 and 0.5 units of Taq DNA polymerase (Bangalore Genei, India). DNA amplification was carried out in duplicate in a DNA Thermal Cycler (Perkin-Elmer, USA). DNA denaturation was done at 94 8C for 4 min; followed by a 45-cycle amplification (94 8C, 1 min; 38 8C, 1 min; 72 8C, 2 min) and a final extension step at 72 8C for 7 min. The amplified products were resolved by electrophoresis on 1.5% agarose gels run in 1 TBE, and photographed under UV light. A total of 116 random decamer primers were screened using 38 genotypes. 2.4. Data analyses Reproducible DNA bands, i.e. bands present in both repetitions of individual sample were scored manually. Weak bands with negligible intensity were excluded from final data analysis. Band profiles for each parent were scored in a binary mode with 1 indicating its presence and 0 indicating its absence. Pair-wise comparisons of genotypes employed to calculate Jaccard’s similarity coefficient (GS): a ; nd where a is the number of positive matches, d the number of negative matches and n is the total sample size (Jaccard, 1908). Genetic distance (GD) between pairs of lines were estimated as GD = 1 GS. Dendrogram was constructed using the Unweighted Pair Group Method with Arithmetic averages (UPGMA) and the computation for multivariate analysis was done using the computer programme NTSYS-pc Version 2.0 (Rohlf, 1998). 3. Results
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(77 2.9 days after seed sowing). CO-1 is an important cultivar of southern India (hot and humid condition) when grows at hot and dry condition it becomes late in fruiting. The two gynoecious lines DBTG-201 and DBTG-202 did not produce any male flower till their final harvest. The appearance offemale flower at lowest node (6.9 0.2th) was observed in gynoecious line DBTG-202, which indicated its earliness and early harvest. Individual fruit weight (136.4 6.4 g) and fruit length (28.7 1.0 cm) were the highest in genotype MDU-1. The gynoecious lines exhibited maximum yield per plant (DBTG-201 with 1342.1 50.3 g and DBTG-202 with 1258.3 77.4 g), which indicated that these lines could be used in future breeding programmes for the development of predominately gynoecious varieties with higher yield. Yield per plant showed maximum deviation from their mean and some of the traits like, fruit weight, male flowers per plant and days to first harvest showed significant variation within the genotype indicating the role of environment in the expression of these traits. 3.2. Clustering based on quantitative traits Cluster analysis of 38 genotypes based on 14 quantitative traits was performed by UPGMA method and a dendrogram was constructed as depicted in Fig. 1. It was observed that all the genotypes were resolved into two major clusters. In clusterI, the genotype DBTG-9 was quite diverse from rest of the 23 genotypes whereas in the cluster-II, the gynoecious lines DBTG-201 and DBTG-202 were distinct from the other 12 genotypes. It was revealed from the dendrogram that the genotypes Jaynagar Sel-1, DBTG-102 and Gayeshpur Sel-1 are very close to one another. The difference between DBTG-201 and DBTG-202 and between Pusa Do Mausami (White) and Pusa Do Mausami (Green) are also very less. 3.3. RAPD polymorphism Of the 116 random 10-nt primers used to amplify DNA from 38 genotypes, 29 primers were found to produce intensely stained, polymorphic bands reproducibly and thus selected for further analysis of the 38 genotypes. The details of the primers producing polymorphic bands are presented in Table 3. These 29 primers generated a total of 208 reproducible bands, of which 76 (36.50%) were found polymorphic. The size of the amplified products varied from approximately 200 bp (OPW05) to 3000 bp (OPW05). The number of bands per primer ranged from 3 (OPE19, OPW09 and OPW18) to 15 (OPW05) with an average of 7.17 bands per primer. Maximum number (5) of polymorphic bands was obtained with the primers OPW03, OPW05 and OPX01. The average number of polymorphic bands per primer was 2.62. The percentage of polymorphic bands ranged from 14.28% (OPX01) to 60.00% (OPF08).
3.1. Performance of genotypes based on quantitative traits The data on mean performance of the genotypes with respect to yield and yield related traits ate given in Table 2. The genotype, DBTG-201 is very early in appearance of first female flower (42 2.7 days after seed sowing) whereas CO-1 was very late
3.4. Cluster analysis and genetic distance among the 38 genotypes based on RAPD analysis Genetic distances were computed for all the 703 combinations of 38 genotypes based on 208 RAPD markers. The
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Table 2 Performance of 38 genotypes of Momordica charantia for 14 quantitative traits U
V
W
X
Y
Z
Sex ratio
Fruits per plant
Fruit weight
Fruit length
Fruit diameter
Flesh thick-ness
Fruit index
Yield per plant
Jaynagar Sel-1 PDM (White) DBTG-1 DBTG-2 PDM (Green) Gayeshpur Sel-1 DBTG-3 DBTG 5-1 CO-1 Priya DBTG-4 Preethi DBTG-6 Gayeshpur Sel-29 DBTG-101 Dindigul Local Mangalakudi Local Arupokkattai Local MDU-1 DBTG-5-2 DBTG-7 Mohanpur Sel-215 DBTG-8 DBTG-201 IC-2763 DBTG-9 DBTG-202 Arka Harit DBTG-10 DBTG-11 DBTG-12 DBTG-5-3 DBTG-13 Nakhara DBTG-102 DBTG-103 DBTG-14 WBBK-1 S.E.
61.7 3.1 56.8 2.1 64.6 2.3 55.4 3.1 53.8 1.9 57.6 0.4 59.3 4.9 67.3 2.8 77.2 2.9 53.2 2.9 70.2 3.0 61.7 1.4 59.0 4.0 55.6 3.8 46.1 3.9 69.0 1.2 54.5 0.6 59.6 3.0 59.2 1.4 59.8 1.1 52.6 2.9 48.4 4.6 57.6 2.8 42.0 2.7 47.2 3.8 72.3 3.7 31.0 3.3 60.4 0.7 67.8 0.9 75.0 2.8 57.1 2.8 70.8 4.9 55.5 3.2 60.3 4.1 55.8 3.1 62.1 2.6 54.5 0.7 74.7 3.0 2.29
19.7 0.6 17.2 0.9 17.2 1.42 13.0 0.7 18.8 1.2 17.1 0.6 12.0 0.0 19.8 0.7 17.5 0.4 14.5 1.3 27.4 0.5 20.8 0.2 20.0 0.9 16.7 0.9 13.8 0.7 20.4 0.5 20.6 0.3 19.3 0.9 20.4 0.6 21.0 0.4 18.9 0.9 12.9 0.1 21.3 1.9 9.0 0.3 19.7 1.5 31.8 1.0 6.9 0.2 14.7 0.3 22.2 0.6 32.4 0.4 20.0 1.1 27.4 0.8 17.2 0.5 23.2 1.9 17.4 0.6 23.9 0.9 20.9 1.7 18.0 0.4 0.72
2.0 0.1 2.0 0.0 2.0 0.1 2.2 0.1 2.0 0.0 2.0 0.0 2.0 0.1 2.0 0.0 2.0 0.1 2.0 0.0 2.0 0.1 2.0 0.0 2.0 0.1 2.2 0.1 2.2 0.2 2.1 0.1 2.0 0.0 2.0 0.1 2.0 0.1 2.0 0.0 2.0 0.1 2.0 0.1 2.0 0.0 2.0 0.1 2.1 0.1 2.1 0.1 2.0 0.0 2.1 0.1 2.2 0.2 2.1 0.1 2.2 0.2 2.0 0.0 2.0 0.0 2.3 0.1 2.0 0.1 2.0 0.0 2.2 0.0 2.3 0.1 0.08
10.4 0.1 9.9 0.1 10.8 0.1 9.9 0.1 10.1 0.1 12.4 0.2 9.2 0.2 11.8 0.1 14.7 0.3 9.8 0.0 10.5 0.1 13.8 0.2 8.2 0.1 11.8 0.2 7.3 0.2 10.4 0.2 8.8 0.2 8.4 0.2 13.5 0.2 10.5 0.3 9.9 0.3 10.9 0.2 8.9 0.3 11.0 0.2 13.7 0.3 13.0 0.8 13.3 0.5 12.3 0.3 11.3 0.2 11.8 0.1 9.1 0.3 10.1 0.3 14.2 0.4 12.1 0.3 9.2 0.2 9.1 0.1 10.9 0.1 10.5 0.3 0.22
74.4 3.1 68.8 2.1 77.8 2.4 67.7 2.6 66.0 2.0 72.0 0.3 70.7 4.9 81.2 3.0 94.1 2.6 65.1 2.8 83.3 3.1 77.6 1.5 71.0 3.8 73.2 4.1 53.9 0.1 81.6 1.1 65.6 0.6 70.2 3.2 74.8 1.4 72.4 0.9 64.6 3.1 61.4 4.4 68.6 2.9 55.0 2.8 63.2 3.8 86.0 3.1 46.4 3.5 74.9 1.1 81.4 1.1 88.8 2.8 68.5 3.0 82.7 4.8 72.0 3.4 75.0 3.7 58.8 1.9 73.4 2.6 67.8 0.8 87.8 2.7 2.27
16.4 0.3 20.4 0.6 12.7 0.6 13.2 0.6 18.3 0.4 13.7 0.3 48.8 1.6 15.0 0.7 14.7 1.0 11.9 0.4 10.1 0.5 13.2 0.7 35.9 0.7 13.6 0.2 43.2 1.7 7.6 0.3 34.2 0.4 36.1 0.9 7.8 0.2 14.8 0.9 12.4 0.6 14.6 0.4 40.6 0.5 19.9 0.6 9.0 0.4 10.4 0.3 22.4 0.5 13.2 0.6 10.2 0.8 8.8 0.3 19.2 1.2 11.4 0.5 11.4 0.8 11.3 0.4 15.3 0.7 13.5 0.3 10.8 0.5 9.0 1.0 1.87
27.8 0.1 15.5 1.0 26.9 1.7 31.8 1.4 17.8 0.9 34.5 0.2 10.3 0.5 20.2 1.4 18.9 0.8 26.4 0.8 47.9 1.6 35.1 2.1 13.8 0.2 31.9 0.8 9.7 0.3 34.0 2.0 15.0 0.2 9.5 0.2 39.3 0.4 18.2 1.8 25.9 0.5 31.8 1.6 13.8 0.1 0.0 0.0 33.0 2.5 39.0 0.7 0.0 0.0 26.7 0.8 45.1 2.6 36.7 1.2 27.4 1.8 30.7 1.0 26.9 2.5 32.6 0.4 29.7 1.7 31.0 1.2 41.4 2.1 45.9 6.2 1.36
15.8 0.3 19.6 0.9 12.0 0.8 12.8 0.5 18.1 0.3 13.1 0.1 47.0 2.0 14.5 0.7 14.3 1.2 11.3 0.6 9.0 0.2 12.0 0.7 34.8 0.9 12.8 0.1 42.0 1.0 7.0 0.2 33.6 0.4 35.9 0.9 7.5 0.3 14.4 1.2 11.8 0.4 14.3 0.5 39.6 1.2 19.4 0.5 8.6 0.6 10.1 0.3 21.6 0.5 11.8 0.2 8.9 0.3 8.1 0.3 18.4 1.1 10.5 0.6 10.6 0.9 10.8 0.1 14.6 0.3 12.9 0.2 10.0 0.2 8.8 0.9 0.60
43.7 1.5 53.5 5.0 45.6 3.6 36.0 3.4 54.9 4.4 55.0 4.3 10.4 0.8 54.9 1.5 89.3 3.9 39.8 2.4 56.1 4.5 61.5 1.6 15.2 0.9 46.6 1.9 13.8 0.1 54.0 1.6 21.0 1.5 15.6 1.5 136.4 6.4 60.0 4.6 41.2 2.3 66.5 4.0 13.5 1.2 68.9 1.1 69.3 3.5 29.3 1.8 58.2 2.8 62.2 4.2 47.6 1.4 122.2 10.4 25.3 2.2 56.4 5.0 114.6 6.2 97.3 5.1 46.1 4.4 36.8 2.4 54.0 3.5 62.6 4.0 3.13
9.0 0.3 9.6 0.4 9.6 0.4 7.7 0.4 10.5 0.7 11.8 1.2 3.2 0.1 14.0 0.1 23.0 1.0 8.7 0.4 11.1 0.3 12.7 0.9 4.7 0.2 9.0 0.2 3.6 0.1 11.6 0.8 6.0 0.3 4.8 0.2 28.7 1.0 13.3 0.7 7.8 0.3 13.2 0.8 4.3 0.2 8.8 0.6 11.3 0.8 7.7 0.5 8.4 0.6 14.4 0.6 12.1 0.8 13.5 0.5 6.1 0.2 11.3 0.7 11.5 0.7 21.9 2.8 9.1 0.3 7.8 0.6 12.9 0.3 8.8 0.5 0.61
3.2 0.3 3.2 0.1 3.2 0.1 4.5 0.2 3.7 0.1 3.3 0.2 2.6 0.1 4.1 0.1 3.1 0.1 4.1 0.3 4.5 0.4 3.4 0.3 2.5 0.1 4.2 0.3 2.6 0.1 2.7 0.1 2.9 0.1 2.7 0.3 4.7 0.1 3.4 0.2 5.3 0.3 4.1 0.2 2.7 0.1 4.1 0.2 5.9 0.2 2.9 0.2 4.3 0.3 3.7 0.1 3.3 0.3 5.9 0.2 2.8 0.1 3.7 0.3 7.4 0.6 2.7 0.2 3.1 0.2 2.6 0.3 3.2 0.2 4.6 0.3 0.22
0.4 .02 0.6 .02 0.4 .03 0.4 .07 0.6 .05 0.3 .02 0.4 .03 0.6 .03 0.4 .03 0.6 .05 0.5 .04 0.5 .06 0.3 .02 0.5 .04 0.4 .03 0.5 .05 0.6 .05 0.3 .04 0.5 .02 0.4 .06 0.7 .04 1.2 0.1 0.5 .07 1.4 .06 0.9 0.1 0.3 .04 1.0 .07 0.7 .04 0.3 .02 0.8 0.1 0.3 .03 0.5 .04 2.0 0.1 0.4 .06 0.3 .06 0.4 .09 0.3 .03 1.0 .06 0.09
29.2 1.6 30.9 1.1 30.9 1.1 35.6 3.5 37.8 1.6 39.8 1.7 8.6 0.6 58.1 1.6 76.4 5.7 36.5 2.2 49.7 4.8 43.4 2.6 11.9 0.9 38.3 2.0 9.5 0.5 30.3 2.0 17.8 1.3 11.2 1.2 136.0 2.6 46.1 6.1 41.5 4.4 54.7 3.9 11.9 0.7 36.5 4.1 67.5 6.7 22.5 1.6 36.3 4.2 54.4 3.6 41.0 4.0 81.1 3.7 17.3 0.6 41.9 4.7 85.6 12.2 60.9 14.3 28.6 2.8 20.3 1.8 42.2 3.5 40.9 2.8 3.53
694.2 12.3 1047.2 48.0 545.6 26.2 462.5 55.9 995.4 65.5 723.2 50.4 493.6 57.9 789.3 27.3 1218.5 43.4 450.5 19.9 505.2 39.2 742.6 48.5 529.9 26.9 600.3 20.3 581.2 15.9 381.8 23.3 707.6 49.0 561.1 64.4 1027.5 63.6 861.7 61.8 494.8 42.8 952.8 28.5 535.2 51.7 1342.1 50.3 600.2 43.6 297.3 25.1 1258.3 77.4 733.5 38.1 425.4 24.8 996.5 120.1 466.4 22.3 593.4 37.7 1221.2 111.3 1057.9 46.1 677.0 64.0 476.8 33.5 545.0 47.9 550.1 48.2 45.79
U, days to open first female flower (DTFFF); V, node number of first female flower (NTFFF); W, days to flower opening to fruit set (DTFOFS); X, days to fruit set to maturity (DTFSTM); Y, days to sowing to first harvest (DTFH); Z, female flowers per plant (FFPP).
S.S. Dey et al. / Scientia Horticulturae 109 (2006) 21–28
Characters
S.S. Dey et al. / Scientia Horticulturae 109 (2006) 21–28
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Fig. 1. Genetic relationships among the 38 genotypes of bitter gourd based on 14 quantitative traits by using UPGMA cluster analysis of the distance matrix.
distance among 38 genotypes ranged from 0.07 (Arupokkatai Local versus DBTG-5-2) to 0.50 (Jaynagar Sel-1 versus Mohanpur Sel-215). The dendrogram constructed based on RAPD analysis by using UPGMA (NTSYS-PC) is shown in
Fig. 2. All genotypes were found to be grouped in two major groups at the similarity coefficient of 0.54. Group I comprised of 36 genotypes whereas Group II had 2 genotypes, DBTG-101 and Mohanpur Sel-215. Group I could be further divided into
Table 3 Details of 29 polymorphic randomly selected decamer primers Name
Sequence
OPC13 OPC16 OPC17 OPD15 OPE03 OPE19 OPF08 OPF09 OPF10 OPF12 OPF13 OPF16 OPW01 OPW02 OPW03 OPW05 OPW06 OPW07 OPW08 OPW09 OPW11 OPW13 OPW16 OPW18 OPW19 OPW20 OPX01 OPX03 OPX05
50 -AAGCCTCGTC-30 50 -CACACTCCAG-30 50 -TTCCCCCCAG-30 50 -CATCCGTGCT-30 50 -CCAGATGCAC-30 50 -ACGGCGTATG-30 50 -GGGATATCGG-30 50 -CCAAGCTTCC-30 50 -GGAAGCTTGG-30 50 -ACGGTACCAG-30 50 -GGCTGCAGAA-30 50 -GGAGTACTGG-30 50 -CTCAGTGTCC-30 50 -ACCCCGCCAA-30 50 -GTCCGGAGTG-30 50 -GGCGGATAAG-30 50 -AGGCCCGATG-30 50 -CTGGACGTCA-30 50 -GACTGCCTCT-30 50 -GTGACCGAGT-30 50 -CTGATGCGTG-30 50 -CACAGCGACA-30 50 -CAGCCTACCA-30 50 -TTCAGGGCAC-30 50 -CAAAGCGCTC-30 50 -TGTGGCAGCA-30 50 -CTGGGCACGA-30 50 -TGGCGCAGTG-30 50 -CCTTTCCCTC-30
Total
Total bands
No. of polymorphic bands
Percent of polymorphic bands
9 5 4 6 6 3 5 6 4 14 8 4 5 11 11 15 8 11 9 3 7 7 3 7 7 6 10 7 7
3 2 1 2 2 1 3 2 2 3 3 1 3 3 5 5 4 3 4 1 3 3 1 3 3 2 5 1 2
33.33 40.00 25.00 33.33 33.33 38.33 60.00 33.33 50.00 21.42 37.50 25.00 60.00 27.27 45.45 33.33 50.00 27.27 44.44 33.33 42.85 42.85 33.33 42.85 42.85 33.33 50.00 14.28 28.57
208
76
36.50
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Fig. 2. Genetic relationships among the 38 genotypes of bitter gourd based on 163 RAPD markers using Jaccard’s coefficient of similarity and UPGMA clustering.
two subgroups at similarity coefficient of 0.70. Subgroup I contained only 1 genotype, Jaynagar Sel-1 and rest 35 genotypes were represented in Subgroup II. Very minor differences were observed in Subgroup II, which could be further divided into two clusters at similarity coefficient of 0.75. The small cluster represented only 2 genotypes Dindigul Local and DBTG-8 and rest of the genotypes (33) formed the large cluster. In this large cluster 2 lines genotypes (IC-2763 and DBTG-9) were closely related and other 31 genotypes formed separate cluster at similarity coefficient of 0.77. The differences among the clusters gradually narrowed down. The clustering pattern was very random and not in consonance with the geographical distribution or with the grouping based on quantitative traits.
number of polymorphic bands (5). This was higher than the number of polymorphic bands reported in diversity analysis in melon (2.1; Mo et al., 1998) and in ash gourd (1.8; Sureja et al., 2006). The average number of polymorphic bands per primer is 2.62 and the percent of polymorphic bands ranged from 14.28% (OPX01) to 60.00% (OPF08). The degree of RAPD polymorphism detected was relatively higher than that reported in melon (18%; Garcia-mas et al., 2000), watermelon (21%; Lee et al., 1996), pumpkin (23%; Gwanama et al., 2000) and ash gourd (28%; Sureja et al., 2006). In contrast, while analysing the genetic diversity among some accession of the Cucurbita maxima, Cucurbita pepo, Cucurbita ficifolia and Lagenaria
4. Discussion The bitter gourd germplasm showed a very large morphological variation with respect to fruit shape, size and colour (Plate 1). Number of fruits per plant was found more in the small fruited (var. muricata) genotypes (DBTG-3, DBTG-6 and DBTG-8) although they exhibited lower yields as compared to the large fruited (var. charantia) genotypes. Two gynoecious lines DBTG-201 and DBTG-202 showed maximum potential for yield per plant and early yield and these lines could be used in future breeding programmes for increasing productivity of bitter gourd. Ram et al. (2002) also reported the potential of the gynoecious lines in bitter gourd. Based on RAPD polymorphism (Plate 2), the primers namely OPW03, OPW05 and OPX01 showed maximum
Plate 1. Variability in shape, size and colour of the bitter gourd fruits.
S.S. Dey et al. / Scientia Horticulturae 109 (2006) 21–28
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Plate 2. RAPD polymorphism amongst Momordica charantia genotypes, detected with primer OPW 06.
siceraria using 26 primers, Ferriol et al. (2003) observed 57% polymorphic bands from a total of 92 consistent bands. Such a high level of polymorphism may be attributed to the use of different species and genus rather than use of cultivars or inbred lines within a species. Eleven primers (37.7%) showed high percentage (>40%) of polymorphic bands and only one primer (3.4%) produced low percentage (<15%) of polymorphic bands. Sureja et al. (2006) while analysing genetic diversity among nine parental lines of ash gourd observed that five primers (19.2% of primers used) showed high percentage (>50%) of polymorphic bands and three primers (11.5% of primers) showed low percentage (<15%) polymorphic bands. So, it can be interpreted that the primers identified and used for diversity analysis in the present study are highly reliable and can be utilized efficiently for analysis of bitter gourd germplasm in the future study as no such reported work is there in this crop. The range of genetic distance among 38 genotypes varied from 0.07 to 0.50. The wide range of dissimilarity values suggests that the germplasm collection represents a genetically diverse population. This range of diversity is similar to that observed in 31 accessions (landraces) of Cucurbita moschata by using 31 RAPD primers by Gwanama et al. (2000). In a recent study, Sureja et al. (2006) employed 26 RAPD primers to analyse diversity among nine parental lines of Benincasa hispida and found very low range of dissimilarity which varied from 0.056 to 0.179, with a mean of 0.113. In the present study, morphological diversity based on 14 quantitative traits and molecular diversity based on 29 random 10-nt primers did not show any correspondence and the grouping obtained from molecular analysis not matched with grouping obtained from quantitative traits. Youn and Chung (1998) also did not observe any correlation between the grouping obtained with RAPD markers and morphological traits, mainly of the fruit of pumpkin. Chowdhury et al. (2001) in genetic diversity studies with 47 soybean lines did not find any correspondence between morphological and molecular diversity based on RAPD marker system. Garcia et al. (2002) also did not observe any similarity in dendograms based upon morphological and molecular analysis. Ferriol et al. (2003)
failed to correlate morphological and RAPD characterization in strawberry. The results in the present study was in contrast to the results obtained by Garacia et al. (1998) in melon and Hoey et al. (1996) in pea. The main reason of mismatch between clustering based on RAPD and quantitative traits may be that most of the quantitative traits are controlled by a large number of genes (polygenes) and these traits are highly influenced by environment. Besides, RAPD markers are randomly distributed throughout the genome and in majority of cases most regions of the genome (nearly 90%) are not expressed at phenotypic level (Dahlberg, 2000). So, it is very difficult to find out similarity between groupings based on RAPD and quantitative traits. The non-coding regions (un-expressed) which constitute the major portion of genome (90%) is not accessible to phenotypic expression and as marker system like RAPDs which randomly assay the genome result in disagreement between the phenotypic and molecular diversity. A poor correlation is also reported when a large numbers of agronomically neutral botanical traits are used (Ortiz, 1997). The selection of morphological traits is also very important. The quantitative traits which were selected to evaluate the genetic diversity might not explain the genetic variation completely; there could be other traits physiologically and biochemically more important which might explain molecular genetic diversity more precisely. The lack of correlation between molecular and quantitative data could be also due to less number of markers used in the cluster analysis. Based on quantitative data the potentiality of the gynoecious lines with respect to yield and earliness and the genetically divergent genotypes identified in the present study will be used in future breeding programmes for increasing productivity of bitter gourd. In the present study, only 76 polymorphic markers were generated which were possibly not sufficient to cover bitter gourd genome particularly the regions influencing the expression of quantitative traits. Hence, sufficient and more efficient RAPD primers showing maximum number of polymorphic bands or other available marker systems could be utilized for analysis of bitter gourd germplasm.
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References Behera, T.K., 2004. Heterosis in bitter gourd. J. New Seeds 6 (2/3), 217–222. Chakravarty, H.L., 1990. Cucurbits of India and their role in the development of vegetable crops. In: Bates, D.M., Robinson, R.W., Jeffrey, C. (Eds.), Biology and Utilization of Cucurbitaceae. Cornell University Press, Ithaca, NY, pp. 325–334. Chowdhury, A.K., Srinivas, P., Tongpamnak, P., Saksoong, P., 2001. Genetic diversity based on morphology and RAPD analysis in vegetable soybean. Korean J. Crop Sci. 46, 112–120. Dahlberg, J.A., 2000. Classification and characterization of sorghum. In: Smith, C.W., Frederiksen, R.A. (Eds.), Sorghum: Origin, History, Technology and Production. John Wiley and Sons, Inc., New York, pp. 99–130. Doyle, J.J., Doyle, J.L., 1990. A rapid DNA isolation procedure from small quantity of fresh leaf material. Phytochem. Bull. 119, 11–15. Ferriol, M., Pico, M.B., Nuez, F., 2003. Genetic diversity of some accessions of Cucurbita maxima from Spain using RAPD and SBAP markers. Genet. Res. Crop Evol. 50, 238–277. Garacia, L., Jamilena, M., Alvarez, J.I., Arnedo, T., Oliver, J.L., Lozano, R., 1998. Genetic relationships among melon breeding lines revealed by RAPD markers and agronomic traits. Theor. Appl. Genet. 96, 878–885. Garcia, M.G., Ontivero, M., Diaz, P.A., Ricci, J.C., Castagnaro, A., 2002. Morphological traits and high resolution RAPD markers for the identification of the main strawberry varieties cultivated in Argentina. Plant Breed. 121, 76–80. Garcia-mas, J., Oliver, M.H., Gomez-Paniagua, de Vicente, M.C., 2000. Comparing AFLP, RAPD and RFLP markers for measuring genetic diversity in melon. Theor. Appl. Genet. 101, 860–864. Grubben, G.J.H., 1977. Tropical Vegetable and their Genetic Resources. IBPGR, Rome, pp. 51–52. Gwanama, C., Labuschagne, M.T., Botha, A.M., 2000. Analysis of genetic variation in Cucurbita moschata by random amplified polymorphic DNA (RAPD) markers. Euphytica 113, 19–24. Hoey, B.K., Crowe, K.R., Jones, V.M., Polans, N.O., 1996. A phylogenetic analysis of Pisum based on morphological characters, and allozyme and RAPD markers. Theor. Appl. Genet. 92, 92–100. Horejsi, T., Staub, J.E., 1999. Genetic variation in cucumber (Cucumis sativus L.). as assessed by random amplified polymorphic DNA. Genet. Res. Crop Evol. 46, 337–350. Jaccard, P., 1908. Nouvelles recherches sur la distribution florale. Bull. Soc. Vaud. Sci. Nat. 44, 223–270. Lee, M., Godsalk, E.B., Lamkey, K.R., Woodman, W.W., 1989. Association of restriction fragment length polymorphisms among maize inbreds
with agronomic performance of their crosses. Crop Sci. 29, 1067– 1071. Lee, S.J., Shin, J.S., Park, K.W., Hong, Y.P., 1996. Detection of genetic diversity using RAPD-PCR and sugar analysis in watermelon [Citrullus lanatus (Thunb.) Mansf.] germplasm. Theor. Appl. Genet. 92, 719–725. Levi, A., Thomas, C.E., Keinath, A.P., Wehner, T.C., 2001. Genetic diversity among watermelon (Citrullus lanatus and Citrullus colocynthis) accessions. Genet. Res. Crop Evol. 48, 559–566. Meng, X.D., Wei, Y.Y., Ma, H., Zhang, W.H., Li, J.R., 1996. Identification of Chinese was ground and chieh-qua cultivars using RAPD markers. Acta Agric. Shanghai 12, 45–49. Mishra, H.N., Mishra, R.S., Parhi, G., Mishra, S.N., 1998. Diallel analysis of variability in bitter gourd (Momordica charantia). Ind. J. Agric. Sci. 68 (1), 18–20. Mo, S.Y., Im, S.H., Go, G.D., Ann, C.M., Kim, D.H., 1998. RAPD analysis for genetic diversity of melon species. Korean J. Hort. Sci. Tech. 16, 21–24. Ortiz, R., 1997. Morphological variation in Musa germplasm. Genet. Res. Crop Evol. 44, 393–402. Rafalski, J.A., Tingey, S.V., 1993. Genetic diagnosis in plant breeding: RAPDs microsatellites and machines. Trends Genet. 9, 275–280. Ram, D., Kalloo, G., Singh, Major, 2000. Genetic analysis in bitter gourd (Momordica charantia) using modified triple test cross. Ind. J. Agric. Sci. 70 (10), 671–673. Ram, D., Kumar, S., Banerjee, M.K., Kalloo, G., 2002. Occurrence, identification and preliminary characterisation of gynoecism in bitter gourd. Ind. J. Agric. Sci. 72 (6), 348–349. Robinson, R.W., Decker-Walters, D.S., 1999. Cucurbits. CAB International, Wallingford, Oxford, UK, p. 226. Rohlf, F.J., 1998. NTSYS-pc Numerical Taxonomy and Multivariate Analysis System, Version 2.01. Exeter Software, Setauket, NY, USA. Sekhon, M.S., Gupta, V.P., 1995. Genetic distance and heterosis in Indian mustard: developmental isozymes as indicator of genetic relationships. Theor. Appl. Genet. 91, 1148–1154. Sureja, A.K., Sirohi, P.S., Behera, T.K., Mohapatra, T., 2006. Molecular diversity and its relationship with hybrid performance and heterosis in ash gourd [Benincasa hispida (Thunb.) Cogn.] J. Horti. Sci. Biotech. 81 (1), 33–38. William, J.G.K., Kubelik, A.R., Livak, K.J., Rafalski, J.A., Tingery, S.V., 1990. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acid Res. 18, 6531–6535. Youn, S.J., Chung, H.D., 1998. Genetic relationship among the local varieties of the Korean native squashes (Cucurbita moschata) using RAPD technique. J. Korean Soc. Hort. Sci. 39, 517–521.
Genetic diversity of bitter gourd (Momordica charantia L.) genotypes revealed by RAPD markers and agronomic traits S.S. Dey a, A.K. Singh b, D. Chandel b, T.K. Behera a,* b
a Division of Vegetable Science, Indian Agricultural Research Institute, Pusa Campus, New Delhi 110012, India Division of Fruits and Horticultural Technology, Indian Agricultural Research Institute, Pusa Campus, New Delhi 110012, India
Received 6 September 2005; received in revised form 8 February 2006; accepted 6 March 2006
Abstract Bitter gourd or bitter melon (Momordica charantia L.) is considered as minor cucurbitaceous vegetable in spite of having considerable nutritional and medicinal properties. Although some reports on genetic diversity based on morphological characterization are available, no work has been conducted to estimate genetic diversity using molecular markers in this crop. In the present study, 38 genotypes of M. charantia including few commercially cultivars collected from different parts of India based on agro-ecological zones were analysed for diversity study both at morphological and molecular levels. Genomic DNA was extracted from young healthy leaves following the procedure of Doyle and Doyle [Doyle, J.J., Doyle, J.L., 1990. A rapid DNA isolation procedure from small quantity of fresh leaf material. Phytochem. Bull. 119, 11–15]. Pair-wise comparison of genotypes was calculated as per the procedure of Jaccard [Jaccard, P., 1908. Nouvelles recherches sur la distribution florale. Bull. Soc. Vaud. Sci. Nat. 44, 223–270]. Dendrogram was constructed using the unweighted pair group method with arithmetic averages (UPGMA) and the computation for multivariate analysis was done using the computer programme NTSYS-pc Version 2.0 [Rohlf, F.J., 1998. NTSYS-pc Numerical Taxonomy and Multivariate Analysis System, Version 2.01. Exeter Software, Setauket, NY, USA]. Diversity based on yield related traits and molecular analysis was not in consonance with ecological distribution. Among 116 random decamer primers screened 29 were polymorphic and informative enough to analyse these genotypes. A total of 208 markers generated of which 76 (36.50%) were polymorphic and the number of bands per primer was 7.17 out of them 2.62 were polymorphic. Pair-wise genetic distance (GD) based on molecular analysis ranged from 0.07 to 0.50 suggesting a wide genetic base for the genotypes. The clustering pattern based on yield related traits and molecular variation was different. # 2006 Elsevier B.V. All rights reserved. Keywords: Momordica charantia; Genetic diversity; RAPD
1. Introduction Bitter gourd (Momordica charantia L.), is an important cucurbit vegetable grown in tropics. Among the cucurbits, it is considered a prized vegetable because of its high nutritive values especially ascorbic acid and iron (Behera, 2004) besides, its immense medicinal values, mainly, for its hypoglycemic properties. The origin of this crop is probably India with secondary centre of diversity in China (Grubben, 1977). This species was domesticated in Asia, possibly in eastern India or southern China. India is endowed with large amount of genetic diversity based on morphological characters (growth habit, maturity and various fruit characters including shape, size, colour and surface texture (Robinson and Decker-Walters, 1999)). Two types of cultivars have been grown in northern India and nine * Corresponding author. Tel.: +91 11 25840306. E-mail address: [email protected] (T.K. Behera). 0304-4238/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.scienta.2006.03.006
types in southern India. Today, Indian cultivates primarily two varieties of M. charantia (i) var. charantia, which produces large fusiform fruits and (ii) var. muricata (wild) with small and round fruits (Chakravarty, 1990). In India, the genetic analysis based on quantitative traits has been made in this crop by Mishra et al. (1998) and Ram et al. (2000). However, genetic diversity among individuals or populations can be determined using morphological and molecular markers. Phenotypic characters have limitations since they are influenced by environmental factors and the developmental stage of the plant. In contrast, molecular markers, based on DNA sequence polymorphisms, are independent of environmental conditions and show higher levels of polymorphism. Among the different types of molecular markers available, random amplified polymorphic DNA (RAPD) are useful for the assessment of genetic diversity because of their simplicity, speed and relatively low cost compared to other molecular markers (William et al., 1990; Rafalski and Tingey, 1993).
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RAPD markers have been used extensively in cucurbits to classify accessions (Horejsi and Staub, 1999), identify cultivars and hybrids (Meng et al., 1996), analyse genetic diversity (Lee et al., 1996; Garacia et al., 1998; Gwanama et al., 2000; Levi et al., 2001; Sureja et al., 2006). The level of genetic diversity between parents has been proposed as a means of predicting hybrid performance and heterosis of crosses. The impetus for this approach stems from the high correlations of molecular marker-based genetic distances between parents with hybrid performance and heterosis obtained in studies by Lee et al. (1989), Sekhon and Gupta (1995) and Sureja et al. (2006). Present study is the first attempt to estimate genetic diversity in bitter melon as revealed by RAPD and morphological markers. 2. Materials and methods 2.1. Genotypes The experimental materials comprised of 38 indigenous genotypes of bitter gourd including commercially released
varieties of India and 2 promising gynoecious lines. The genotypes were selected based on genetic as well as ecogeographical diversity. They were evaluated at the Research Farm, Division of Vegetable Science, Indian Agricultural Research Institute, New Delhi, during spring–summer (dry) season of 2004. 2.2. Field evaluation and data collection The experiment was laid out in a Randomized Complete Block Design (RCBD) with three replications for phenotypic evaluation. Seeds were sown on both sides of the channel with a spacing of 2 m between channel and 60 cm between plants with 90 cm irrigation channels. The recommended NPK fertilizer doses and cultural practices along with plant protection measures were followed to raise an ideal crop. The fruits were harvested at marketable stage. Five plants were selected, after discarding the border plants at both ends, and were examined for 14 quantitative traits: (i) days to open first female flower (DTFFF), (ii) node number of first female flower (NTFFF), (iii) days to flower
Table 1 List of bitter gourd (Momordica charantia L.) genotypes used in this study Accession name
Source of collection
Salient features
Jaynagar Sel-1 Pusa Do Mausami (White) DBTG-1 DBTG-2 PusaDo Mausumi (Green) Gayeshpur Sel-1 DBTG-3 DBTG 5-1 CO-1 Priya DBTG-4 Preethi DBTG-6 Gayeshpur Sel-29 DBTG-101 Dindigul Local Mangalakudi Local Arupokkattai Local MDU-1 DBTG-5-2 DBTG-7 Mohanpur Sel-215 DBTG-8 DBTG-201 IC-2763 DBTG-9 DBTG-202 Arka Harit DBTG-10 DBTG-11 DBTG-12 DBTG-5-3 DBTG-13 Nakhara DBTG-102 DBTG-103 DBTG-14 WBK-1
Mohanpur, West Bengal I.A.R.I., New Delhi Baud, Orissa Ahmedabad, Gujarat I.A.R.I., New Delhi Mohanpur, West Bengal Baud, Orissa Sonepat, Haryana Coimbatore, Tamil Nadu Vellanikkara, Tamil Nadu Bagpat, Uttar Pradesh Madurai, Tamil Nadu Pondichery, Tamil Nadu Mohanpur, West Bengal Phulbani, Orissa Madurai, Tamil Nadu Madurai, Tamil Nadu Madurai, Tamil Nadu Madurai, Tamil Nadu Debrugarh, Assam Bhopal, Madhya Pradesh Mohanpur, West Bengal Shillong, Meghalaya Indore, Madhya Pradesh NBPGR, New Delhi Mayurbhanj, Orissa Ranchi, Jharkhand IIHR, Bangalore Barapani, Meghalaya Koenjhar, Orissa Pondicherry, Tamil Nadu Jorhat, Assam Chakdah, West Bengal Nakhara, Orissa Sambalpur, Orissa Bagpat, Uttar Pradesh Dhekanal, Orissa Raghunathpur, West Bengal
Medium vine, medium long, dark green fruits with continuous ridges Vigorous vine, medium long, white fruits with continuous ridges Medium vine, medium long, glossy green fruits with discontinuous ridges Short vine, medium long, light green fruits with discontinuous ridges Vigorous vine, long, glossy green fruits with continuous ridges Medium vine, long, dark green fruits with discontinuous ridges Medium vine, small ovate, light green fruits with discontinuous ridges Medium vine, long, glossy green fruits with continuous ridges Vigorous vine, extra long, dark green fruits with continuous ridges Short vine, medium long, dark green fruits with discontinuous ridges Short vine, long, light green fruits with discontinuous ridges Medium vine, long, white fruits with discontinuous ridges Medium vine, small round, dark green fruits with discontinuous ridges Medium vine, medium long, whitish green fruits with discontinuous ridges Medium vine, small ovate, light green fruits with continuous ridges Short vine, long, dark green fruits with discontinuous ridges Vigorous vine, small round, dark green fruits with continuous ridges Medium vine, small, light green fruits with discontinuous ridges Medium vine, extra long, dark green fruits discontinuous fruit Vigorous vine, long, light green fruits with continuous ridges Short vine, medium long, greenish white fruits with continuous ridges Medium vine, long, dark green fruits with continuous ridges Medium vine, extra long, dark green fruits with discontinuous ridges Medium vine, medium long, light green fruits with continuous ridges Medium vine, long, dark green fruits with continuous ridges Short vine, medium long, whitish green fruits with continuous ridges Medium vine, medium long, light green fruits with discontinuous fruits Vigorous vine, long, dark green fruits with continuous ridges Short vine, long, white fruits with discontinuous ridges Vigorous vine, long, dark green fruits with continuous ridges Medium vine, medium long, light green fruits with continuous ridges Short vine, long, light green fruits with discontinuous ridges Vigorous vine, long, light green fruits with continuous ridges Medium vine, extra long, dark green fruits with continuous ridges Medium vine, medium long, light green fruits with continuous fruits Short vine, medium long, dark green fruits with discontinuous fruits Medium vine, long, dark green fruits with continuous ridges Medium vine, medium long, dark green fruits continuous ridges
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opening to fruit set (DTFOFS), (iv) days to fruit set to maturity (DTFSTM), (v) days to sowing to first harvest (DTFH), (vi) female flowers per plant (FFPP), (vii) sex ratio (no. of male flowers:total no. of female flowers), (viii) total number of fruits per plant, (ix) average fruit length (cm), (x) average fruit diameter (cm), (xi) average flesh thickness (cm), (xii) average fruit weight (g), (xiii) yield per plant (kg) and (xiv) fruit index (length diadiameter). Means across three replications were calculated for each trait and used for data analysis (Table 1). 2.3. DNA isolation and RAPD assay Genomic DNA was extracted from young healthy leaves following the procedure of Doyle and Doyle (1990). Amplification reactions (25 ml final volume) contained 15 ng genomic DNA, 20 mM dNTPs, 15 ng primer (Operon Technologies, USA), 1 Taq DNA polymerase buffer containing 50 mM KCl, 10 mM Tris–Cl and 1.5 mM MgCl2 and 0.5 units of Taq DNA polymerase (Bangalore Genei, India). DNA amplification was carried out in duplicate in a DNA Thermal Cycler (Perkin-Elmer, USA). DNA denaturation was done at 94 8C for 4 min; followed by a 45-cycle amplification (94 8C, 1 min; 38 8C, 1 min; 72 8C, 2 min) and a final extension step at 72 8C for 7 min. The amplified products were resolved by electrophoresis on 1.5% agarose gels run in 1 TBE, and photographed under UV light. A total of 116 random decamer primers were screened using 38 genotypes. 2.4. Data analyses Reproducible DNA bands, i.e. bands present in both repetitions of individual sample were scored manually. Weak bands with negligible intensity were excluded from final data analysis. Band profiles for each parent were scored in a binary mode with 1 indicating its presence and 0 indicating its absence. Pair-wise comparisons of genotypes employed to calculate Jaccard’s similarity coefficient (GS): a ; nd where a is the number of positive matches, d the number of negative matches and n is the total sample size (Jaccard, 1908). Genetic distance (GD) between pairs of lines were estimated as GD = 1 GS. Dendrogram was constructed using the Unweighted Pair Group Method with Arithmetic averages (UPGMA) and the computation for multivariate analysis was done using the computer programme NTSYS-pc Version 2.0 (Rohlf, 1998). 3. Results
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(77 2.9 days after seed sowing). CO-1 is an important cultivar of southern India (hot and humid condition) when grows at hot and dry condition it becomes late in fruiting. The two gynoecious lines DBTG-201 and DBTG-202 did not produce any male flower till their final harvest. The appearance offemale flower at lowest node (6.9 0.2th) was observed in gynoecious line DBTG-202, which indicated its earliness and early harvest. Individual fruit weight (136.4 6.4 g) and fruit length (28.7 1.0 cm) were the highest in genotype MDU-1. The gynoecious lines exhibited maximum yield per plant (DBTG-201 with 1342.1 50.3 g and DBTG-202 with 1258.3 77.4 g), which indicated that these lines could be used in future breeding programmes for the development of predominately gynoecious varieties with higher yield. Yield per plant showed maximum deviation from their mean and some of the traits like, fruit weight, male flowers per plant and days to first harvest showed significant variation within the genotype indicating the role of environment in the expression of these traits. 3.2. Clustering based on quantitative traits Cluster analysis of 38 genotypes based on 14 quantitative traits was performed by UPGMA method and a dendrogram was constructed as depicted in Fig. 1. It was observed that all the genotypes were resolved into two major clusters. In clusterI, the genotype DBTG-9 was quite diverse from rest of the 23 genotypes whereas in the cluster-II, the gynoecious lines DBTG-201 and DBTG-202 were distinct from the other 12 genotypes. It was revealed from the dendrogram that the genotypes Jaynagar Sel-1, DBTG-102 and Gayeshpur Sel-1 are very close to one another. The difference between DBTG-201 and DBTG-202 and between Pusa Do Mausami (White) and Pusa Do Mausami (Green) are also very less. 3.3. RAPD polymorphism Of the 116 random 10-nt primers used to amplify DNA from 38 genotypes, 29 primers were found to produce intensely stained, polymorphic bands reproducibly and thus selected for further analysis of the 38 genotypes. The details of the primers producing polymorphic bands are presented in Table 3. These 29 primers generated a total of 208 reproducible bands, of which 76 (36.50%) were found polymorphic. The size of the amplified products varied from approximately 200 bp (OPW05) to 3000 bp (OPW05). The number of bands per primer ranged from 3 (OPE19, OPW09 and OPW18) to 15 (OPW05) with an average of 7.17 bands per primer. Maximum number (5) of polymorphic bands was obtained with the primers OPW03, OPW05 and OPX01. The average number of polymorphic bands per primer was 2.62. The percentage of polymorphic bands ranged from 14.28% (OPX01) to 60.00% (OPF08).
3.1. Performance of genotypes based on quantitative traits The data on mean performance of the genotypes with respect to yield and yield related traits ate given in Table 2. The genotype, DBTG-201 is very early in appearance of first female flower (42 2.7 days after seed sowing) whereas CO-1 was very late
3.4. Cluster analysis and genetic distance among the 38 genotypes based on RAPD analysis Genetic distances were computed for all the 703 combinations of 38 genotypes based on 208 RAPD markers. The
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Table 2 Performance of 38 genotypes of Momordica charantia for 14 quantitative traits U
V
W
X
Y
Z
Sex ratio
Fruits per plant
Fruit weight
Fruit length
Fruit diameter
Flesh thick-ness
Fruit index
Yield per plant
Jaynagar Sel-1 PDM (White) DBTG-1 DBTG-2 PDM (Green) Gayeshpur Sel-1 DBTG-3 DBTG 5-1 CO-1 Priya DBTG-4 Preethi DBTG-6 Gayeshpur Sel-29 DBTG-101 Dindigul Local Mangalakudi Local Arupokkattai Local MDU-1 DBTG-5-2 DBTG-7 Mohanpur Sel-215 DBTG-8 DBTG-201 IC-2763 DBTG-9 DBTG-202 Arka Harit DBTG-10 DBTG-11 DBTG-12 DBTG-5-3 DBTG-13 Nakhara DBTG-102 DBTG-103 DBTG-14 WBBK-1 S.E.
61.7 3.1 56.8 2.1 64.6 2.3 55.4 3.1 53.8 1.9 57.6 0.4 59.3 4.9 67.3 2.8 77.2 2.9 53.2 2.9 70.2 3.0 61.7 1.4 59.0 4.0 55.6 3.8 46.1 3.9 69.0 1.2 54.5 0.6 59.6 3.0 59.2 1.4 59.8 1.1 52.6 2.9 48.4 4.6 57.6 2.8 42.0 2.7 47.2 3.8 72.3 3.7 31.0 3.3 60.4 0.7 67.8 0.9 75.0 2.8 57.1 2.8 70.8 4.9 55.5 3.2 60.3 4.1 55.8 3.1 62.1 2.6 54.5 0.7 74.7 3.0 2.29
19.7 0.6 17.2 0.9 17.2 1.42 13.0 0.7 18.8 1.2 17.1 0.6 12.0 0.0 19.8 0.7 17.5 0.4 14.5 1.3 27.4 0.5 20.8 0.2 20.0 0.9 16.7 0.9 13.8 0.7 20.4 0.5 20.6 0.3 19.3 0.9 20.4 0.6 21.0 0.4 18.9 0.9 12.9 0.1 21.3 1.9 9.0 0.3 19.7 1.5 31.8 1.0 6.9 0.2 14.7 0.3 22.2 0.6 32.4 0.4 20.0 1.1 27.4 0.8 17.2 0.5 23.2 1.9 17.4 0.6 23.9 0.9 20.9 1.7 18.0 0.4 0.72
2.0 0.1 2.0 0.0 2.0 0.1 2.2 0.1 2.0 0.0 2.0 0.0 2.0 0.1 2.0 0.0 2.0 0.1 2.0 0.0 2.0 0.1 2.0 0.0 2.0 0.1 2.2 0.1 2.2 0.2 2.1 0.1 2.0 0.0 2.0 0.1 2.0 0.1 2.0 0.0 2.0 0.1 2.0 0.1 2.0 0.0 2.0 0.1 2.1 0.1 2.1 0.1 2.0 0.0 2.1 0.1 2.2 0.2 2.1 0.1 2.2 0.2 2.0 0.0 2.0 0.0 2.3 0.1 2.0 0.1 2.0 0.0 2.2 0.0 2.3 0.1 0.08
10.4 0.1 9.9 0.1 10.8 0.1 9.9 0.1 10.1 0.1 12.4 0.2 9.2 0.2 11.8 0.1 14.7 0.3 9.8 0.0 10.5 0.1 13.8 0.2 8.2 0.1 11.8 0.2 7.3 0.2 10.4 0.2 8.8 0.2 8.4 0.2 13.5 0.2 10.5 0.3 9.9 0.3 10.9 0.2 8.9 0.3 11.0 0.2 13.7 0.3 13.0 0.8 13.3 0.5 12.3 0.3 11.3 0.2 11.8 0.1 9.1 0.3 10.1 0.3 14.2 0.4 12.1 0.3 9.2 0.2 9.1 0.1 10.9 0.1 10.5 0.3 0.22
74.4 3.1 68.8 2.1 77.8 2.4 67.7 2.6 66.0 2.0 72.0 0.3 70.7 4.9 81.2 3.0 94.1 2.6 65.1 2.8 83.3 3.1 77.6 1.5 71.0 3.8 73.2 4.1 53.9 0.1 81.6 1.1 65.6 0.6 70.2 3.2 74.8 1.4 72.4 0.9 64.6 3.1 61.4 4.4 68.6 2.9 55.0 2.8 63.2 3.8 86.0 3.1 46.4 3.5 74.9 1.1 81.4 1.1 88.8 2.8 68.5 3.0 82.7 4.8 72.0 3.4 75.0 3.7 58.8 1.9 73.4 2.6 67.8 0.8 87.8 2.7 2.27
16.4 0.3 20.4 0.6 12.7 0.6 13.2 0.6 18.3 0.4 13.7 0.3 48.8 1.6 15.0 0.7 14.7 1.0 11.9 0.4 10.1 0.5 13.2 0.7 35.9 0.7 13.6 0.2 43.2 1.7 7.6 0.3 34.2 0.4 36.1 0.9 7.8 0.2 14.8 0.9 12.4 0.6 14.6 0.4 40.6 0.5 19.9 0.6 9.0 0.4 10.4 0.3 22.4 0.5 13.2 0.6 10.2 0.8 8.8 0.3 19.2 1.2 11.4 0.5 11.4 0.8 11.3 0.4 15.3 0.7 13.5 0.3 10.8 0.5 9.0 1.0 1.87
27.8 0.1 15.5 1.0 26.9 1.7 31.8 1.4 17.8 0.9 34.5 0.2 10.3 0.5 20.2 1.4 18.9 0.8 26.4 0.8 47.9 1.6 35.1 2.1 13.8 0.2 31.9 0.8 9.7 0.3 34.0 2.0 15.0 0.2 9.5 0.2 39.3 0.4 18.2 1.8 25.9 0.5 31.8 1.6 13.8 0.1 0.0 0.0 33.0 2.5 39.0 0.7 0.0 0.0 26.7 0.8 45.1 2.6 36.7 1.2 27.4 1.8 30.7 1.0 26.9 2.5 32.6 0.4 29.7 1.7 31.0 1.2 41.4 2.1 45.9 6.2 1.36
15.8 0.3 19.6 0.9 12.0 0.8 12.8 0.5 18.1 0.3 13.1 0.1 47.0 2.0 14.5 0.7 14.3 1.2 11.3 0.6 9.0 0.2 12.0 0.7 34.8 0.9 12.8 0.1 42.0 1.0 7.0 0.2 33.6 0.4 35.9 0.9 7.5 0.3 14.4 1.2 11.8 0.4 14.3 0.5 39.6 1.2 19.4 0.5 8.6 0.6 10.1 0.3 21.6 0.5 11.8 0.2 8.9 0.3 8.1 0.3 18.4 1.1 10.5 0.6 10.6 0.9 10.8 0.1 14.6 0.3 12.9 0.2 10.0 0.2 8.8 0.9 0.60
43.7 1.5 53.5 5.0 45.6 3.6 36.0 3.4 54.9 4.4 55.0 4.3 10.4 0.8 54.9 1.5 89.3 3.9 39.8 2.4 56.1 4.5 61.5 1.6 15.2 0.9 46.6 1.9 13.8 0.1 54.0 1.6 21.0 1.5 15.6 1.5 136.4 6.4 60.0 4.6 41.2 2.3 66.5 4.0 13.5 1.2 68.9 1.1 69.3 3.5 29.3 1.8 58.2 2.8 62.2 4.2 47.6 1.4 122.2 10.4 25.3 2.2 56.4 5.0 114.6 6.2 97.3 5.1 46.1 4.4 36.8 2.4 54.0 3.5 62.6 4.0 3.13
9.0 0.3 9.6 0.4 9.6 0.4 7.7 0.4 10.5 0.7 11.8 1.2 3.2 0.1 14.0 0.1 23.0 1.0 8.7 0.4 11.1 0.3 12.7 0.9 4.7 0.2 9.0 0.2 3.6 0.1 11.6 0.8 6.0 0.3 4.8 0.2 28.7 1.0 13.3 0.7 7.8 0.3 13.2 0.8 4.3 0.2 8.8 0.6 11.3 0.8 7.7 0.5 8.4 0.6 14.4 0.6 12.1 0.8 13.5 0.5 6.1 0.2 11.3 0.7 11.5 0.7 21.9 2.8 9.1 0.3 7.8 0.6 12.9 0.3 8.8 0.5 0.61
3.2 0.3 3.2 0.1 3.2 0.1 4.5 0.2 3.7 0.1 3.3 0.2 2.6 0.1 4.1 0.1 3.1 0.1 4.1 0.3 4.5 0.4 3.4 0.3 2.5 0.1 4.2 0.3 2.6 0.1 2.7 0.1 2.9 0.1 2.7 0.3 4.7 0.1 3.4 0.2 5.3 0.3 4.1 0.2 2.7 0.1 4.1 0.2 5.9 0.2 2.9 0.2 4.3 0.3 3.7 0.1 3.3 0.3 5.9 0.2 2.8 0.1 3.7 0.3 7.4 0.6 2.7 0.2 3.1 0.2 2.6 0.3 3.2 0.2 4.6 0.3 0.22
0.4 .02 0.6 .02 0.4 .03 0.4 .07 0.6 .05 0.3 .02 0.4 .03 0.6 .03 0.4 .03 0.6 .05 0.5 .04 0.5 .06 0.3 .02 0.5 .04 0.4 .03 0.5 .05 0.6 .05 0.3 .04 0.5 .02 0.4 .06 0.7 .04 1.2 0.1 0.5 .07 1.4 .06 0.9 0.1 0.3 .04 1.0 .07 0.7 .04 0.3 .02 0.8 0.1 0.3 .03 0.5 .04 2.0 0.1 0.4 .06 0.3 .06 0.4 .09 0.3 .03 1.0 .06 0.09
29.2 1.6 30.9 1.1 30.9 1.1 35.6 3.5 37.8 1.6 39.8 1.7 8.6 0.6 58.1 1.6 76.4 5.7 36.5 2.2 49.7 4.8 43.4 2.6 11.9 0.9 38.3 2.0 9.5 0.5 30.3 2.0 17.8 1.3 11.2 1.2 136.0 2.6 46.1 6.1 41.5 4.4 54.7 3.9 11.9 0.7 36.5 4.1 67.5 6.7 22.5 1.6 36.3 4.2 54.4 3.6 41.0 4.0 81.1 3.7 17.3 0.6 41.9 4.7 85.6 12.2 60.9 14.3 28.6 2.8 20.3 1.8 42.2 3.5 40.9 2.8 3.53
694.2 12.3 1047.2 48.0 545.6 26.2 462.5 55.9 995.4 65.5 723.2 50.4 493.6 57.9 789.3 27.3 1218.5 43.4 450.5 19.9 505.2 39.2 742.6 48.5 529.9 26.9 600.3 20.3 581.2 15.9 381.8 23.3 707.6 49.0 561.1 64.4 1027.5 63.6 861.7 61.8 494.8 42.8 952.8 28.5 535.2 51.7 1342.1 50.3 600.2 43.6 297.3 25.1 1258.3 77.4 733.5 38.1 425.4 24.8 996.5 120.1 466.4 22.3 593.4 37.7 1221.2 111.3 1057.9 46.1 677.0 64.0 476.8 33.5 545.0 47.9 550.1 48.2 45.79
U, days to open first female flower (DTFFF); V, node number of first female flower (NTFFF); W, days to flower opening to fruit set (DTFOFS); X, days to fruit set to maturity (DTFSTM); Y, days to sowing to first harvest (DTFH); Z, female flowers per plant (FFPP).
S.S. Dey et al. / Scientia Horticulturae 109 (2006) 21–28
Characters
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Fig. 1. Genetic relationships among the 38 genotypes of bitter gourd based on 14 quantitative traits by using UPGMA cluster analysis of the distance matrix.
distance among 38 genotypes ranged from 0.07 (Arupokkatai Local versus DBTG-5-2) to 0.50 (Jaynagar Sel-1 versus Mohanpur Sel-215). The dendrogram constructed based on RAPD analysis by using UPGMA (NTSYS-PC) is shown in
Fig. 2. All genotypes were found to be grouped in two major groups at the similarity coefficient of 0.54. Group I comprised of 36 genotypes whereas Group II had 2 genotypes, DBTG-101 and Mohanpur Sel-215. Group I could be further divided into
Table 3 Details of 29 polymorphic randomly selected decamer primers Name
Sequence
OPC13 OPC16 OPC17 OPD15 OPE03 OPE19 OPF08 OPF09 OPF10 OPF12 OPF13 OPF16 OPW01 OPW02 OPW03 OPW05 OPW06 OPW07 OPW08 OPW09 OPW11 OPW13 OPW16 OPW18 OPW19 OPW20 OPX01 OPX03 OPX05
50 -AAGCCTCGTC-30 50 -CACACTCCAG-30 50 -TTCCCCCCAG-30 50 -CATCCGTGCT-30 50 -CCAGATGCAC-30 50 -ACGGCGTATG-30 50 -GGGATATCGG-30 50 -CCAAGCTTCC-30 50 -GGAAGCTTGG-30 50 -ACGGTACCAG-30 50 -GGCTGCAGAA-30 50 -GGAGTACTGG-30 50 -CTCAGTGTCC-30 50 -ACCCCGCCAA-30 50 -GTCCGGAGTG-30 50 -GGCGGATAAG-30 50 -AGGCCCGATG-30 50 -CTGGACGTCA-30 50 -GACTGCCTCT-30 50 -GTGACCGAGT-30 50 -CTGATGCGTG-30 50 -CACAGCGACA-30 50 -CAGCCTACCA-30 50 -TTCAGGGCAC-30 50 -CAAAGCGCTC-30 50 -TGTGGCAGCA-30 50 -CTGGGCACGA-30 50 -TGGCGCAGTG-30 50 -CCTTTCCCTC-30
Total
Total bands
No. of polymorphic bands
Percent of polymorphic bands
9 5 4 6 6 3 5 6 4 14 8 4 5 11 11 15 8 11 9 3 7 7 3 7 7 6 10 7 7
3 2 1 2 2 1 3 2 2 3 3 1 3 3 5 5 4 3 4 1 3 3 1 3 3 2 5 1 2
33.33 40.00 25.00 33.33 33.33 38.33 60.00 33.33 50.00 21.42 37.50 25.00 60.00 27.27 45.45 33.33 50.00 27.27 44.44 33.33 42.85 42.85 33.33 42.85 42.85 33.33 50.00 14.28 28.57
208
76
36.50
26
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Fig. 2. Genetic relationships among the 38 genotypes of bitter gourd based on 163 RAPD markers using Jaccard’s coefficient of similarity and UPGMA clustering.
two subgroups at similarity coefficient of 0.70. Subgroup I contained only 1 genotype, Jaynagar Sel-1 and rest 35 genotypes were represented in Subgroup II. Very minor differences were observed in Subgroup II, which could be further divided into two clusters at similarity coefficient of 0.75. The small cluster represented only 2 genotypes Dindigul Local and DBTG-8 and rest of the genotypes (33) formed the large cluster. In this large cluster 2 lines genotypes (IC-2763 and DBTG-9) were closely related and other 31 genotypes formed separate cluster at similarity coefficient of 0.77. The differences among the clusters gradually narrowed down. The clustering pattern was very random and not in consonance with the geographical distribution or with the grouping based on quantitative traits.
number of polymorphic bands (5). This was higher than the number of polymorphic bands reported in diversity analysis in melon (2.1; Mo et al., 1998) and in ash gourd (1.8; Sureja et al., 2006). The average number of polymorphic bands per primer is 2.62 and the percent of polymorphic bands ranged from 14.28% (OPX01) to 60.00% (OPF08). The degree of RAPD polymorphism detected was relatively higher than that reported in melon (18%; Garcia-mas et al., 2000), watermelon (21%; Lee et al., 1996), pumpkin (23%; Gwanama et al., 2000) and ash gourd (28%; Sureja et al., 2006). In contrast, while analysing the genetic diversity among some accession of the Cucurbita maxima, Cucurbita pepo, Cucurbita ficifolia and Lagenaria
4. Discussion The bitter gourd germplasm showed a very large morphological variation with respect to fruit shape, size and colour (Plate 1). Number of fruits per plant was found more in the small fruited (var. muricata) genotypes (DBTG-3, DBTG-6 and DBTG-8) although they exhibited lower yields as compared to the large fruited (var. charantia) genotypes. Two gynoecious lines DBTG-201 and DBTG-202 showed maximum potential for yield per plant and early yield and these lines could be used in future breeding programmes for increasing productivity of bitter gourd. Ram et al. (2002) also reported the potential of the gynoecious lines in bitter gourd. Based on RAPD polymorphism (Plate 2), the primers namely OPW03, OPW05 and OPX01 showed maximum
Plate 1. Variability in shape, size and colour of the bitter gourd fruits.
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Plate 2. RAPD polymorphism amongst Momordica charantia genotypes, detected with primer OPW 06.
siceraria using 26 primers, Ferriol et al. (2003) observed 57% polymorphic bands from a total of 92 consistent bands. Such a high level of polymorphism may be attributed to the use of different species and genus rather than use of cultivars or inbred lines within a species. Eleven primers (37.7%) showed high percentage (>40%) of polymorphic bands and only one primer (3.4%) produced low percentage (<15%) of polymorphic bands. Sureja et al. (2006) while analysing genetic diversity among nine parental lines of ash gourd observed that five primers (19.2% of primers used) showed high percentage (>50%) of polymorphic bands and three primers (11.5% of primers) showed low percentage (<15%) polymorphic bands. So, it can be interpreted that the primers identified and used for diversity analysis in the present study are highly reliable and can be utilized efficiently for analysis of bitter gourd germplasm in the future study as no such reported work is there in this crop. The range of genetic distance among 38 genotypes varied from 0.07 to 0.50. The wide range of dissimilarity values suggests that the germplasm collection represents a genetically diverse population. This range of diversity is similar to that observed in 31 accessions (landraces) of Cucurbita moschata by using 31 RAPD primers by Gwanama et al. (2000). In a recent study, Sureja et al. (2006) employed 26 RAPD primers to analyse diversity among nine parental lines of Benincasa hispida and found very low range of dissimilarity which varied from 0.056 to 0.179, with a mean of 0.113. In the present study, morphological diversity based on 14 quantitative traits and molecular diversity based on 29 random 10-nt primers did not show any correspondence and the grouping obtained from molecular analysis not matched with grouping obtained from quantitative traits. Youn and Chung (1998) also did not observe any correlation between the grouping obtained with RAPD markers and morphological traits, mainly of the fruit of pumpkin. Chowdhury et al. (2001) in genetic diversity studies with 47 soybean lines did not find any correspondence between morphological and molecular diversity based on RAPD marker system. Garcia et al. (2002) also did not observe any similarity in dendograms based upon morphological and molecular analysis. Ferriol et al. (2003)
failed to correlate morphological and RAPD characterization in strawberry. The results in the present study was in contrast to the results obtained by Garacia et al. (1998) in melon and Hoey et al. (1996) in pea. The main reason of mismatch between clustering based on RAPD and quantitative traits may be that most of the quantitative traits are controlled by a large number of genes (polygenes) and these traits are highly influenced by environment. Besides, RAPD markers are randomly distributed throughout the genome and in majority of cases most regions of the genome (nearly 90%) are not expressed at phenotypic level (Dahlberg, 2000). So, it is very difficult to find out similarity between groupings based on RAPD and quantitative traits. The non-coding regions (un-expressed) which constitute the major portion of genome (90%) is not accessible to phenotypic expression and as marker system like RAPDs which randomly assay the genome result in disagreement between the phenotypic and molecular diversity. A poor correlation is also reported when a large numbers of agronomically neutral botanical traits are used (Ortiz, 1997). The selection of morphological traits is also very important. The quantitative traits which were selected to evaluate the genetic diversity might not explain the genetic variation completely; there could be other traits physiologically and biochemically more important which might explain molecular genetic diversity more precisely. The lack of correlation between molecular and quantitative data could be also due to less number of markers used in the cluster analysis. Based on quantitative data the potentiality of the gynoecious lines with respect to yield and earliness and the genetically divergent genotypes identified in the present study will be used in future breeding programmes for increasing productivity of bitter gourd. In the present study, only 76 polymorphic markers were generated which were possibly not sufficient to cover bitter gourd genome particularly the regions influencing the expression of quantitative traits. Hence, sufficient and more efficient RAPD primers showing maximum number of polymorphic bands or other available marker systems could be utilized for analysis of bitter gourd germplasm.
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