International Journal of Innovative Biotechnology and Biochemistry

Vol. 1(1), 2013 pp. 15-23

International Journal of Innovative Biotechnology and Biochemistry Vol. 1(1), 2013, pp. 15-23

ISSN 2319-9938 http://mutagens.co.in/ijibb.html

GENETIC DIVERSITY ANALYSIS IN COWPEA [VIGNA UNGUICULATA (L.) WALP.] BY USING RAPD MARKERS Patil D. M., S.V. Sawardekar, N. B. Gokhale, S. G. Bhave, S. S. Sawant, S. A. Sawantdesai, K. A. Lipne, S. N. Sabale and S.N. Joshi Plant Biotechnology Centre, College of Agriculture, Dr. Balasaheb Sawant Konkan Krishi Vidyapeeth, Dapoli - 415 712, Dist. Ratnagiri (MS) India. Abstract Assessment of genetic variability within cowpea [Vigna unguiculata (L.) Walp.] is fundamental for the conservation of genetic resources and its utilization in hybridization programme. Thirty genotypes of cowpea were included in this study to estimate the genetic diversity by using RAPD markers. RAPD profiles for 30 genotypes were generated with 20 random decamer primers. Out of 20 primers screened 17 primers gave scorable DNA fragments and each of the 17 primers revealed various levels of polymorphism. These primers generated 1238 DNA fragments in the average range of 381.94 bp to 1131.71 bp, of which 908 were polymorphic. The level of polymorphism among the genotypes was found to be very high (71.20%). The overall range of similarity among 30 genotypes was found to be very wide, ranging from 0.321 to 0.800 which indicates there was high variability among the cowpea cultivars under study. Key words: Cowpea, genetic diversity, RAPD markers, polymorphism, cluster analysis.

INTRODUCTION Pulses have been recognized as a major source of vegetable proteins with required minerals and vitamins. Among the pulses, cowpea (Vigna unguiculata (L) Walp.) is most important legume crop in Asia, Africa, Australia and U.S.A. It is rich in protein (23.4%) and has an important place in a vegetarian diet. Genetic diversity is the extent to which heritable material differs within a group of plants [1]. While, Genetic differentiation is the extent to which heritable material differs between group of plants and it is the result of evolution, including domestication and plant breeding. Assessment of genetic diversity of cultivated crop plants is very important to select proper genotypes for a hybridization programme. The genetic diversity in cultivated cowpea seems to be narrow inspite of substantial variations in seed colour, seed protein, plant type, pod type etc. The placement of individual cultivars into different accessions is primarily based on morphological attributes that do not necessarily reflect real genetic relationships. To define better these relationships in genus Vigna several molecular marker studies have been reported recently. Among the DNA markers, polymerase chain reaction (PCR) based markers using arbitrary primers, such as RAPD, have been widely used for investigating genetic relatedness and diversity in plant population and cultivars. http://mutagens.co.in/ijibb.html

Keeping this in view, the present study was undertaken to evaluate the pattern and the existence of genetic variability and relatedness among cultivars for genetic improvement of cowpea using RAPD markers. MATERIAL AND METHODS Plant material For the present experimental study 30 genotypes of cowpea (Vigna unguiculata (L.) Walp.) selected from the germplasm available at the research farm of the Department of Agricultural Botany, College of Agriculture, Dapoli. All the 30 genotypes of cowpea (Table 1) were grown in the greenhouse condition. The leaf samples for DNA isolation were collected from 15 days old seedlings. DNA Extraction The genomic DNA was isolated from the young newly flushing leaves by following the protocol of Doyle and Doyle (1990)[2] i.e. Rapid method with the slight modifications of buffer composition and concentration. Purification of DNA was done to remove RNA, proteins and polysaccharides which were the major contaminants. RNA was removed by RNase treatment. RNase was added to the DNA sample @100 µg ml-1 and incubated at 37°C for 1 hr. Concentration of DNA in the sample was determined by agarose gel electrophoresis with standard DNA i.e., uncut lambda DNA on 0.8 15

International Journal of Innovative Biotechnology and Biochemistry

per cent agarose gel and by comparison of the intensity of staining with ethidium bromide. RAPD Analysis PCR amplification reactions were performed with random decamer primers obtained from Operon Technology (Alamenda, USA) in an Eppendorf, Master cycler gradient (Hamburg Germany). A total of 20 random decamer primers from RAPD primers kits (A, C, D, F) were subsequently used for PCR amplification. For the RAPD analysis, initially the PCR master mix was standardized for each PCR component and the optimum concentration of each component in master mix which gave better amplification was used for further work. PCR reaction was performed in 20 µl reaction mixture consisting 3U Taq DNA polymerase (Banglore Genei Ltd.), 2.5 µl 10x Taq assay buffer with 2.5 mM MgCl2, 10 mM dNTPs, 0.5 µl of 25 mM MgCl2, 5 pmoles of random decamer primer and 25 ng of template DNA. The amplification profile for RAPD consisted of initial denaturation at 940C for 5 min, followed by 35 cycles comprising of a denaturation step at 940C for 30 sec, an annealing step at 37 0C for 1 min and an extension step at 72 0C for 30 sec. The cycling program was terminated by a final extension step at 72 0C for 7 min. The amplified products in RAPD reaction were separated by electrophoresis in 1.5 per cent agarose gel (Banglore Genei) containing ethidium bromide in 1x TAE Buffer (pH 8.0) and separation was carried-out by applying constant voltage of 80 volts for 1 hr. The standard molecular marker used was Φ x174/Hae III digest. The gels were photographed under UV light using Pentax K 312 nm camera. The images of gels were also taken by the documentation systems (Uvi-Tech. Fire reader, Cambridge, England) and saved in computer for further analysis. PCR and gel electrophoresis were carried out thrice and only reproducible banding patterns were used for data analysis. Data Analysis RAPD markers across the 30 accessions were scored for their presence (1) or absence (0) of bands for each primer. By comparing the banding patterns of genotypes for a specific primer, genotype-specific bands were identified and faint or unclear bands were not considered. The binary data so generated was used to estimate the levels of polymorphism by dividing the number of polymorphic bands by the total number of scored bands. Pair-wise similarity matrices were generated by Jaccard’s coefficient http://mutagens.co.in/ijibb.html

Vol. 1(1), 2013 pp. 15-23

of similarity by using MVSP-A Multivariate Statistical Package_5785 (Version 3.1). The cluster analysis was performed from the distance matrix using Jaccard’s similarity coefficients. RESULTS AND DISCUSSION Primer Screening Molecular markers have proven to be powerful tools in the assessment of genetic variation and in the elucidation of genetic relationships within and among the species. Different types of DNA based molecular markers such as RFLP, RAPD and AFLP etc. are available which detect polymorphism at the DNA level [3, 4, 5, 6, 7, 8]. The present study was undertaken to evaluate the pattern and the existence of genetic variability and relatedness among cultivars for genetic improvement of cowpea using RAPD markers. This would help in the identification and differentiation of various cultivars being grown for local consumption and/or for export purposes. This will also contribute to maximize the selection of diverse parent cultivar and to broaden the germplasm base in the future of cowpea breeding programs [9]. Keeping this in view, 30 cowpea genotypes were analysed with 20 random decamer primers to estimate extent of variability among the cultivated cowpea. A total of 20 random decamer primers were used to amplify the genomic DNA of the 30 genotypes of cowpea. Out of these, 17 primers OPA-01, OPA-02, OPA-03, OPA-04, OPA-5, OPA-07, OPA-08, OPA-09, OPA-10, OPC-01, OPC-02, OPC-05, OPC-07, OPC-08, OPD-10, OPD-14, and OPD-18 gave amplification and all of them were polymorphic whereas, remaining 3 primers (OPA-06, OPF-05, and OPF-13) failed to show the amplification at all, and were unable to generate PCR product with any of the genomic DNA. Thus, out of 20 random primers screened 17 primers gave scorable DNA fragments and each of the 17 random primers revealed polymorphism ( Fig. 1). Similar result is also reported in cowpea [9]. Per cent Polymorphism The analysis of binary data showed that 17 random primers produced total of 1238 DNA fragments in the average range of 381.94 bp to 1131.71 bp (Table 2). Out of these 1238 DNA fragments, 908 showed polymorphic pattern. The number of fragments per primer varied from 41 (OPA-07) to 135 (OPA-05), across the 17 random primers. The average number of DNA fragments per primer was 72.82. The percentage of polymorphism across the cowpea genotypes ranged from 30.20-100 per cent and the average polymorphism across the 17 primers was 71.20 16

International Journal of Innovative Biotechnology and Biochemistry

per cent. The average number of polymorphic DNA fragments per primer was 53.41. The primers OPA-04, OPA-05, OPC-02, OPC-05 and OPC-08 gave 100 per cent polymorphism with the maximum number of DNA fragments. The primer OPA-01, OPA-07 and OPA-09 were gave 100 per cent polymorphism but with less number of DNA fragments. The primer OPA-03 showed lowest per cent of polymorphism (30.23%) followed by OPD-18 (31.82%) and OPA-10 (36.17%). In cowpea landraces 25100% polymorphism is also observed [8]. The monomorphic bands are constant bands and cannot be used to study diversity while polymorphic bands revealed differences and can be used to examine and establish systematic relationship among the genotypes [10]. The genetic diversity recognized was much higher than the genetic diversity (54%) previously detected in cowpea based on RAPD markers [11]. The amount of genetic diversity recognized in such studies depends on the primer used and the amount of diversity among the genotypes. The high genetic diversity detected in the cowpea accessions analysed, probably indicated that cultivars were originally generated by different ancestors of cowpea in the past. Discrimination Power A total number of 316 unique phenotypes were produced by 17 random primers. The average number of unique phenotypes per primer was 18.59 (Table 3). The average discrimination power among the 17 primers was 62 per cent. The value showed that the primer OPA-04 and OPC-02 had highest discrimination power of 83.30 per cent, while primer OPC-07 showed the lowest discrimination power of 43.30%. The discrimination power of OPA-01, OPA-05, OPA-07 and OPC-08 was found to be same i.e. 70 per cent. Similarly, the discrimination power of OPA-02, OPA-10, OPC-05, OPD-10 and OPD-18 was found to be 60 per cent. Therefore, these primers can be used to identify all 30 cowpea genotypes, i.e. genetically fingerprint them. Varietal differentiation based on DNA markers is an important aspect for further investigations such as construction of genetic maps, gene-tagging and other manipulations. However, the individual random primers are of the little value in any of these studies, including analysis of genetic diversity. Large numbers of primers have to be used to get a reasonable assessment of the status of a given genotypes in relation to others and groups, the genotypes based on the DNA markers with reference to

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Vol. 1(1), 2013 pp. 15-23

contrasting phenotypic classes [12]. The present study indicates that this is possible. Genetic distance The genetic distance was computed considering all the genotypes from the pooled data. The overall range of the similarity among 30 genotypes was found to be very wide ranging from 0.321 to 0.800 which indicates there was high variability among the cowpea cultivars under study. Based on the similarity matrix (Table 3) and clustering pattern, the genotypes ACP-1264 and PCP-9726 were found to have maximum similarity coefficient 0.800 followed by ACP-39 and BCS-6 with 0.782 similarity, while the lowest similarity coefficient (0.321) was observed in between the genotypes DCP-11 and Pusa Phalguni. Similar observations are recorded in other studies [13]. Based on RAPD analysis Vigna umbellate accessions estimated 53 per cent of genetic similarity [11]. In the present study it was observed that, the genotype PCP-97223 occupied a unique position and was most diverse from rest of 29 genotypes of cowpea. Cluster analysis The dendrogram and similarity coefficient values give an idea about the nature of the individual sample in the whole sample set. The dendrogram (Fig.2 ) based on Jaccard’s similarity coefficient was constructed using UPGMA after analysis of banding patterns generated by all the accessions with 17 primers across the 30 cowpea genotypes. The dendrogram separated 30 cowpea genotypes into two main clusters i.e. cluster-I and cluster-II. The first cluster (I) included only single genotype PCP-97223 and second cluster (II) was further divided into three subclusters (IIA, IIB, IIC) revealing sufficient amount of diversity within the cluster. Among the second cluster, the first subcluster (IIA) includes 9 genotypes namely; CPP-20116, DCP-11, PCP-9757, OCS6, Punjab, PCP-97021, Konkan Sadabahar, N10, and DCP-2. The second subcluster (IIB) was the larger cluster which included 16 genotypes viz., DSP-97226, BND-2, TCN-781-10, Pusa Phalguni, HC-03-04, HC-9863, CH-9863, Konkan Safed, 97111, CPS-9240, PCB-97102, CHV-240, ACP-39, BCS-6, HC-03-01 and Kunde Local. The third subcluster (IIC) was formed with remaining 4 genotypes namely; HC-03-3, ACP-1264, PCP-9726, and COCP711/242. From the above clusters formed it was observed that, the genotype PCP-97223 was more diverse from other 29 genotypes of cowpea. 17

International Journal of Innovative Biotechnology and Biochemistry

Vol. 1(1), 2013 pp. 15-23

Table 1. Cowpea genotypes studied for diversity analysis. Name of the Sr. Name of the Sr. No. genotype No. genotype 1. COCP-711/242 2. PCP-9776 3. ACP-1264 4. HC-03-3 5. Kunde Local 6. HC-03-01 7. BCS-06 8. PCP-97223 9.

ACP-39

10.

CHV-240

11.

PCB-97102

12.

CPS-9240

13.

97111

14.

Konkan Safed

15.

HC-9863

16.

DCP-02

17.

N-10

18.

PCP-97021

19.

DCP-11

20.

Konkan Sadabahar

21.

CPP-20116

22.

Punjab

23.

OCS-06

24.

PCP-9757

25.

HC-03-04

26.

TCN-781-10

27.

Pusa Phalguni

28.

CH-9863

29. BND-02 30. DSP-97226 Table 2. Polymorphism percentage and range of amplification.

Primer

No. of DNA fragments produced

No. of polymorphic fragments

Polymorphism (%)

1.

OPA-01

62

62

100.00

450-1500

2.

OPA-02

99

69

69.70

580-1400

3.

OPA-03

43

13

30.23

603-1078

4.

OPA-04

89

89

100.00

430-1078

5.

OPA-05

135

135

100.00

430-1078

6.

OPA-07

41

41

100.00

450-1180

7.

OPA-08

52

22

42.31

500-1353

8.

OPA-09

44

44

100.00

650-872

9.

OPA-10

47

17

36.17

520-800

10.

OPC-01

70

40

57.14

220-1100

11.

OPC-02

82

82

100.00

200-1200

12.

OPC-05

81

81

100.00

200-900

13.

OPC-07

52

22

42.31

200-1300

14.

OPC-08

73

73

100.00

150-1000

15.

OPD-10

118

58

49.15

300-1300

16.

OPD-14

62

32

51.61

310-900

17.

OPD-18

88

28

31.82

300-1200

Total

1238

908

-

-

Sr. No.

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Range or size of fragments (bp)

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International Journal of Innovative Biotechnology and Biochemistry

Vol. 1(1), 2013 pp. 15-23

Table 3. Discrimination power of 17 random decamer primers for differentiating 30 cowpea genotypes. Sr. No.

Primer

No. of unique

Total no. of

Discrimination

phenotypes

phenotypes

power (%)

1.

OPA-01

21

30

70.0

2.

OPA-02

18

30

60.0

3.

OPA-03

15

30

50.0

4.

OPA-04

25

30

83.3

5.

OPA-05

21

30

70.0

6.

OPA-07

21

30

70.0

7.

OPA-08

14

30

46.7

8.

OPA-09

15

30

50.0

9.

OPA-10

18

30

60.0

10.

OPC-01

15

30

50.0

11.

OPC-02

25

30

83.3

12.

OPC-05

18

30

60.0

13.

OPC-07

13

30

43.3

14.

OPC-08

21

30

70.0

15.

OPD-10

18

30

60.0

16.

OPD-14

20

30

66.7

17.

OPD-18

18

30

60.0

Total

316

510

-

Average

18.59

30

62.0

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International Journal of Innovative Biotechnology and Biochemistry

Vol. 1(1), 2013 pp. 15-23

Table 4. Genetic distances based on RAPD data pooled over the 17 primers in 30 cowpea genotypes. code

1

2

3

4

5

6

7

1

1.000

2

0.635

1.000

3

0.630

0.800

1.000

4

0.600

0.588

0.615

1.000

5

0.559

0.604

0.600

0.544

1.000

6

0.527

0.540

0.455

0.538

0.615

1.000

7

0.610

0.544

0.542

0.596

0.696

0.642

1.000

8

0.472

0.392

0.345

0.451

0.500

0.429

0.528

1.000

9

0.532

0.492

0.492

0.596

0.638

0.642

0.782

0.528

1.000

10

0.559

0.491

0.467

0.544

0.533

0.585

0.667

0.529

0.727

1.000

11

0.491

0.529

0.528

0.528

0.574

0.571

0.630

0.449

0.660

0.574

1.000

12

0.509

0.431

0.462

0.434

0.509

0.500

0.566

0.467

0.596

0.455

0.622

1.000

13

0.510

0.458

0.521

0.460

0.540

0.500

0.569

0.370

0.538

0.453

0.628

0.711

1.000

14

0.467

0.446

0.424

0.474

0.544

0.481

0.625

0.510

0.596

0.544

0.558

0.551

0.521

1.000

15

0.509

0.491

0.439

0.547

0.536

0.529

0.534

0.500

0.589

0.593

0.491

0.480

0.449

0.547

1.000

16

0.413

0.367

0.371

0.349

0.413

0.397

0.460

0.415

0.508

0.459

0.519

0.453

0.451

0.441

0.431

1.000

17

0.417

0.444

0.421

0.328

0.491

0.375

0.419

0.420

0.443

0.466

0.472

0.521

0.429

0.558

0.519

0.640

1.000

18

0.464

0.415

0.444

0.322

0.390

0.370

0.441

0.388

0.441

0.439

0.531

0.556

0.558

0.529

0.434

0.519

0.563

1.000

19

0.346

0.370

0.375

0.347

0.373

0.348

0.352

0.474

0.431

0.373

0.500

0.487

0.486

0.467

0.455

0.523

0.500

0.579

1.000

20

0.429

0.431

0.483

0.410

0.500

0.390

0.550

0.434

0.576

0.475

0.566

0.625

0.531

0.623

0.474

0.611

0.694

0.667

0.511

1.000

21

0.397

0.451

0.453

0.426

0.473

0.404

0.424

0.367

0.500

0.421

0.574

0.438

0.500

0.481

0.500

0.529

0.542

0.543

0.595

0.549

1.000

22

0.586

0.545

0.571

0.419

0.533

0.474

0.532

0.418

0.583

0.533

0.518

0.509

0.510

0.517

0.509

0.589

0.604

0.640

0.522

0.607

0.653

1.000

23

0.443

0.473

0.500

0.400

0.492

0.481

0.422

0.396

0.468

0.443

0.473

0.434

0.431

0.500

0.439

0.545

0.588

0.500

0.435

0.564

0.571

0.692

1.000

24

0.483

0.439

0.491

0.393

0.435

0.421

0.484

0.364

0.508

0.435

0.519

0.481

0.510

0.417

0.361

0.564

0.464

0.612

0.489

0.526

0.500

0.648

0.604

1.000

25

0.491

0.471

0.444

0.418

0.519

0.510

0.518

0.511

0.518

0.547

0.563

0.591

0.523

0.529

0.490

0.519

0.630

0.500

0.429

0.509

0.511

0.547

0.560

0.491

1.000

26

0.469

0.450

0.452

0.406

0.516

0.458

0.492

0.455

0.516

0.492

0.403

0.464

0.411

0.429

0.492

0.492

0.500

0.500

0.358

0.533

0.456

0.593

0.500

0.492

0.527

1.000

27

0.477

0.459

0.438

0.460

0.548

0.544

0.571

0.414

0.547

0.574

0.483

0.424

0.446

0.460

0.579

0.476

0.459

0.387

0.321

0.424

0.441

0.500

0.533

0.525

0.593

0.581

1.000

28

0.450

0.333

0.383

0.407

0.500

0.436

0.552

0.460

0.552

0.450

0.481

0.596

0.532

0.596

0.588

0.474

0.481

0.481

0.444

0.574

0.462

0.475

0.456

0.474

0.453

0.534

0.517

1.000

29

0.400

0.448

0.475

0.426

0.492

0.482

0.492

0.400

0.541

0.569

0.556

0.491

0.490

0.475

0.466

0.467

0.448

0.446

0.408

0.534

0.481

0.492

0.554

0.492

0.558

0.632

0.557

0.564

1.000

30

0.565

0.429

0.453

0.500

0.492

0.534

0.563

0.383

0.587

0.590

0.500

0.491

0.519

0.525

0.569

0.469

0.475

0.526

0.389

0.532

0.458

0.590

0.525

0.469

0.475

0.623

0.530

0.586

0.627

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8

9

10

11

12

13

14

15

16

17

18

19

20

20

21

22

23

24

25

26

27

28

29

30

1.000

International Journal of Innovative Biotechnology and Biochemistry

Vol. 1(1), 2013 pp. 15-23 15

A. OPA-02

B. OPA-04

C. OPA-05 Fig. 1. RAPD profile pattern of 30 cowpea genotypes using different primers.

Fig. 2 : Dendrogram depicting 30 cowpea genotypes based on the genetic distances generated by 17 random primers. http://mutagens.co.in/ijibb.html

21

International Journal of Innovative Biotechnology and Biochemistry

CONCLUSION The presence of unique RAPD marker among the various cowpea genotype indicate the utility of approach for DNA fingerprinting purposes. RAPD fingerprinting has potential applications and includes determination of cultivar purity, efficient use and management of genetic

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resources particularly for identification of diverse genotype for hybridization. This study represents only the first step in using RAPD markers for the assessment of genetic diversity among group of genotypes and identification of diverse sources in crop germplasm collection.

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13. Chattopadhyay K., Ali M. N., Sarkar H. K., Mandal N. and Bhattacharyya S. (2005). Diversity analysis by RAPD and ISSR markers among the selected mungbean (Vigna radiata (L.) Wilczek) genotypes. Indian Journal of Genetics., 65(3):173-175.

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