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Research Article

Legume Research, volume 45 issue 12 (december 2022) : 1476-1483

Simple Sequence Repeats Marker based Detection of Genetic Diversity of Indian Bean Dolichos lablab (L.) of Family Fabaceae

Vishwajeet Singh1,*, Rajdeep Kudesia1, Seema Bhadauria2
1Department of Botany, Bundelkhand University, Jhansi-284 128, Uttar Pradesh, India.
2Department of Botany, Raja Balwant Singh College, Agra-282 002, Uttar Pradesh, India.

  • Submitted24-03-2021|

  • Accepted01-05-2021|

  • First Online 08-06-2021|

  • doi 10.18805/LR-4617

Cite article:- Singh Vishwajeet, Kudesia Rajdeep, Bhadauria Seema (2022). Simple Sequence Repeats Marker based Detection of Genetic Diversity of Indian Bean Dolichos lablab (L.) of Family Fabaceae . Legume Research. 45(12): 1476-1483. doi: 10.18805/LR-4617.

ABSTRACT

Background: Assessment and molecular characterization of genetic diversity among the Dolichos lablab (L.) have huge implication in scheming strategies for breeding. In India, there is less comprehensive information on the potential genetic diversity of lablab bean and this is a major challenge for systematic use of lablab bean in genetic breeding programs. To exploit the available trait of interest, the genetic diversity of the locally available genotypes must be known. The PCR-based SSR approach requires just nanogram amounts of template DNA, subjected to quick detection and less influenced by environment. In this manner SSR have been utilizing broadly to study hereditary assorted qualities of yields.

Methods: In this study, genetic diversity on ten Indian Dolichos lablab (L.) genotypes were surveyed utilizing SSR markers at Department of Botany, Bundelkhand University, Jhansi during 2019-20 got from Indian gene bank. For SSR analysis, 5 primers were used for checking the diversity in Dolichos lablab (L.) and the performance of markers were measured by using 4 parameters (1) PIC, (2) Mean resolving Power, (3) Resolving Power and (4) MI. 

Result: SSR (05) markers produced a total of 51 bands, out of which 45 bands (88.23%) were polymorphic which varies from 6 (Primer-111) to 15 (Primer-AGB-9) with mean of 10.5 bands per primer. The polymorphic information content value ranges from 0.265 to 0.488 with a mean value of 0.390. The value of Matrix index is 3.2. The value of resolving power ranges from 2.2 to 12.60 with a mean value of 7.40. In the UPGMA dendogram, the 10 genotypes were separated into two main clusters with all the primers used. Our present examination uncovered that genetic markers might be effectively used for deciding hereditary variety and connections in Dolichos lablab (L.) genotypes and could be utilized as a part of breeding programs.

INTRODUCTION

Grain legumes hold an important position in World’s Agriculture due to their high protein content and their atmospheric nitrogen fixation capacity. The pulses represent the only concentrated type of dietary proteins for many developing countries. As far as the developed countries are concerned, legumes are key source of protein, being good biologically valuable animal feed. Indians generally favor vegetarian food and the pulses are the major source of protein. Lablab had a great number of qualities due to its adaptability, which can be used efficiently in different conditions. Grain yields are significantly higher than cowpeas (Adebisi and Bosch, 2004). It is not only resistant to drought, but it can also thrive in a variety of environmental conditions. It can be used as a cover crop for benefit, as its thick green cover protects the soil from desiccation and reduces wind or rain erosion. Up to six tons of dry matter/ha has been known to be given as green manure. It also restores nitrogen biologically into the soil, thus increasing the yields of subsequent crops in an economically and environmentally friendly way.
 
In Dolichos lablab (L.) there is an urgent need to establish a variety of lablab genotypes with intrinsic values such as highest yield, combined to their consistent production not confined to a specific area and appropriate for seasonal development from long ago. Hence, there is an urgent need to develop the all season lablab variety with determined early maturity, growth of plant and highest harvest index with excellent characteristic of pod, resistance to bean mosaic virus, pests and insects, superior storage and higher content of seed protein.
 
Evaluation of germplasm lines in any crop improvement program to evaluate the existing variability is a first step. The chances of evolving desired plant types would be greater the variability present in the breeding material. Clear understanding of the variability of the different quantitative characters of the breeding material is an asset for the breeder of plants to select superior genotypes phenotypic expression basis. Estimation of phenotypic and genotypic variances for different quantitative characters along with the heritability and genetic advance expected by yield selection and its components are useful in designing an effective breeding program in this regard. Yield is a complex character affected by diverse components that contribute to the crop’s genetic potential.
It is also essential to understand the genetic variety and population structure of Dolichos lablab (L.) for its conservation, management and exploitation of the variation for its improvement. Genotyping gives essential information on the genetic diversity of the materials under consideration. Genetic variation assessments at the DNA level became simple after the development of molecular markers (Reif et al., 2003). The quantity of molecular marker systems that are utilized for the genetic diversity study of Dolichos lablab (L.) include; random amplified polymorphic DNA (RAPD) (Williams et al., 1990; Sultana et al., 2000; Tian et al., 2005; Gnanesh et al., 2005), amplified fragment length polymorphism (AFLP) (Vos et al., 1995; Venkatesha et al., 2007; Tefera et al., 2006; Patil et al., 2009) and simple sequence repeats (SSRs) (Singh, 1999; Wang et al., 2004; Wang et al., 2007). Of these, SSR markers are provided with the number of benefits as compared to any other marker systems applied in plant breeding. These advantages include SSR polymorphisms of co-dominant nature (Slavov et al., 2005), easiness to assay, a great amount of reproducibility, which is the most significant in a genetic examination, high polymorphic genetic information contents (Powell et al., 1996), their huge quantity as well as a division in genomes (Varshney et al., 2005). They have been preferentially associated with non-repetitive DNA (Morgante et al., 2002). On account of the high reproducibility and polymorphic data substance of SSR marker, our investigation set to analyse genetic diversity in Indian Dolichos lablab (L.) bean genotypes by using SSR Marker.
 
Objectives of our study is to check the genetic diversity and genetic relatedness among Dolichos lablab (L.) bean genotype through SSR marker; to construct a Phylogenetic tree and a similarity matrix Data and generate polymorphism  data by using SSR marker among Dolichos lablab (L.) from the state of UP. India.

MATERIALS AND METHODS

Genotypes used
 
For the present Investigation, ten genotypes (VRSEM- 847, VRSEM-739, VRSEM-799, VRSEM-757, VRSEM-776, VRSEM-733, VRSEM-730, VRSEM-746, VRSEM-843, VRSEM-702) procured from Indian Institute of Vegetable Research, Varanasi were used for studying the genetic diversity among  them.
 
Extraction of DNA
 
Leaves were used by CTAB process for extraction of DNA, with little change in the procedure (Doyle and Doyle, 1987). Around 150 mg of leaves with extraction buffer (1 ml) were crushed by using mortar and pestle. Extraction buffer was then applied to tubes already having crushed leaf. With normal mixing, incubate the tubes for 45 minutes at 65°C. Isoamyl alcohol: Chloroform (1:24) has been added in equal volume and mixed for 5 minutes, following centrifugation for 15 minutes at 14000 rpm. 2/3 amount of isopropanol has been added to the supernatant. Centrifuged for 10 minutes at 14000 rpm and drained the supernatant and washed the pellet with 70% ethanol containing DNA and suspended in 100 μl sterile Distilled Water. 10-15 μl RNAse, incubated at 65°C for 30 minutes. Qualitative DNA assessment was conducted on 0.8 per cent agarose gel by running sample and quantification was made by recording its absorbance at 260 nm and 280 nm.
 
SSR analysis
 
The SSR amplification were carried out by the method given by Tautz, (1989) with minor modifications A total of five SSR primers were used for amplification of 10 genotypes. Each 50 µl PCR reaction consisted of 0.4 mM dNTPs, 1 X PCR buffer, 0.5 unit of Taq polymerase, 2.5 mM MgCl2, 0.5 µM of forward and reverse primer and 20 ng of DNA. The amplification conditions were 1 minutes at 94°C (Initial Denaturation), followed by Denaturation at 94°C for 1 min., 55°C for 55 sec. (Annealing), 72°C for 1 min. (Extension) and final extension of 10 minutes at 72°C. The samples of PCR were casted on 2.5% molecular grade Agarose gel (Hi-media) after amplification, which were ready in 0.5 X buffer (TBE) with 0.5 μg/ml EtBr. Finally, amplified products were resolved for 180 min on 2.5 per cent Agarose gel at 50V and gel was visualized under UV light and the image was captured.
 
Data analysis and polymorphic information content
 
In Gel Documentation Unit, digital camera took a photograph of the gel to score banding results. Bands were shown according to their molecular size (length of polynucleotide amplified). To evaluate the molecular scale, each sample of primer was filled by 1 kb DNA Ladder. The distance covered by bands generated from the well has been converted into molecular sizes in relation to molecular marker weight. Absence of band was scored as ‘0’ and existence of band as ‘1’. Lightly seen bands weren’t scored however measured for scoring if found equivalent to major band. To check the existence of the bands and to assess the reproducibility, all the tested primers were repeated three times.
 
Genetic profile of Dolichos lablab (L.) were estimated by the performance of the primers which were calculated by means of following four parameters i.e. Polymorphic information content (Roldan-Ruiz et al., 2000), Mean resolving power (Prevost and Wilkinson, 1999), resolving power (Prevost and Wilkinson, 1999) and matrix index (Varshney et al., 2007).

RESULTS AND DISCUSSION

SSR analysis
 
The bands of DNA were amplified from five SSR primers against Dolichos lablab (L.). From the molecular weight of 1636 base pair to 128 base pair, different primers revealed a total of fifty-one bands indicating 88.23 per cent polymorphism (45 bands). The polymorphism varies between 90% and 100%. Banding arrangement with primer AGB 9 generates the largest no. of bands viz. 15 followed by 11 bands (VM 4); 10 bands (CEDG 198 and DMB SSR 182) while, primer (111) revealed a total of 6 bands which is least (Table 2, Fig 1).
 

Table 2: Polymorphism detected and Parameters by the use of 5 SSR primers.


 

fig1


 
The ten bands generated with primer DMB SSR 182 exhibited 90 per cent of polymorphism. The uppermost band generated at about 1247 bp and the lowest at about 176 bp. Ten bands generated with primer CEDG 198 exhibited 90 per cent of polymorphism. The uppermost band generated at about 822 bp whereas the lowest at about 190 bp. Against primer VM 4, eleven bands were generated; of which polymorphic bands are nine thus revealing 90.90 per cent polymorphism. The uppermost band generated at about 562 bp whereas the lowest at about 128 bp. The pattern of banding generated by primer AGB 9 revealed 15 bands having 80 per cent polymorphism among the accessions considered. The uppermost band generated at about 738 bp and the lowest at 178 bp. Finally, the pattern of banding generated with primer 111 intensified six bands with 100 percent polymorphism rate. The uppermost band generated at about 1636 bp and the lowest at 152 bp (Table 1).
 

Table 1: Band matrix of 10 Dolichos lablab (L.) genotypes with all SSR primers.


 
SSR Markers are co-dominant (Narshimulu et al., 2011) and locus-specific and generally amplify one locus (Gupta and Varshney, 2000). These markers evaluate the variability and the identification of connections between accessions for breeders (Li et al., 2011). From the molecular weight of 1636 base pair to 128 base pair, different primers revealed a total of fifty-one bands indicating 88.23 per cent polymorphism. The polymorphism varies between 90% and 100%. Banding arrangement with primer AGB 9 generated the largest no. of bands viz. 15 while, primer (111) revealed a total of 6 bands which is the least. In evaluating Dolichos lablab (L.), SSR markers have proven a more accurate variety in genes. In 143 germplasm of bean (Indian) with one hundred and thirty-four SSR markers (Lablab purpureus),  genetic diversity is reported by Rai et al., (2011). With the 5 RAPD primers, ten Dolichos lablab (L.) accessions demonstrated major genetic variation. As a result, primer AGB 9 produced max. numbers of bands (15) and bands with a minimum number were revealed by primer 111 i.e. 6. Our findings support Zhong et al., (2008) and Zhang et al., (2013) who investigated various markers and identified a large degree of variability between the twenty-four Dolichos lablab (L.) accessions studied (Keerthi et al., 2018). The accession classification based on the EST-SSRs was similar to the genomic AFLP and SSR work by Woodhead et al., (2005). The variation in the band number, governed by various markers (Kernodle et al., 1993) is induced by the various variable factors like the structure of primer, some annealing site, etc. The revealed bands also had specific molecular weight to check the distinctions in length between primary connections and the DNA that resulted in band changes (Devos and Gale, 1992).
 
Data analysis and polymorphic information content  
 
Performance of marker was checked by the use of different parameters i.e. polymorphic information content, resolving power, mean resolving power and matrix index. Primer 111 (0.265) has lowest PIC value whereas primer AGB 9 had highest (0.488) with a mean PIC value of 0.390. In compare, Asare et al., (2010) imply low value of PIC about 0.38 at an average of 3. 8 alleles for every loci in 141 cowpea genotype gathered starting with nine geographic locales for Ghana. In 92 common bean PIC value detected is 0.54 (Díaz and Buendía, 2011). Similarly, Benchimol et al., (2007) found a PIC value varied from 0.05-0.83 while studying genetic dry beans diversity  with 87 SSR loci the average value of PIC was 0.45. PIC values range from one (very high discriminative power with many alleles in equal frequencies) to zero (which is an indicative of monomorphism) and the higher the PIC value, the more informative is the SSR marker (Nagy et al., 2012). The value of matrix index ranges from 4.68 (AGB 9) to 1.59 (111) with a mean of 3.2. Higher the MI, better the method is. The value of resolving power ranges from 2.2 to 12.60. The highest value of RP and MRP was recorded for the primer AGB 9 and lowest for primer 111 (Table 2).
 
Genetic relationship and phylogenetic study
 
For every marker, genetic relationship among the Genotypes was determine based on Jaccard’s Pairwise similarity coefficient. Genetic Relationships and pooled diversity data by using  marker grouped each genotype into its clusters. According to Beaumont et al., (1998) the genetic gap is any quantitative evaluation of genetic difference at the level of the sequence or the level of allele frequency, measured between persons, populations or species. Pairwise similarity among the genotypes ranged from 0.55 to 0.93 (Primer-AGB-9), followed by 0.33 to 0.89 (Primer-CEDG 198), 0.40 to 0.86 (Primer- VM4), 1 to 0.67 (Primer 111) and 0.33 to 0.86 (Primer DMB-SSR182).
 
Dendrogram formed was derived from the matrix similarity analysis by UPGMA (Unweighted pair group method with arithmetic averages) cluster analysis by using GenAlEx (Genetic Analysis in Excel, version 6.2) software (Peakall and Smouse, 2006). Based on the genetic distances with all primers, the UPGMA neighbour-joining tree method generated two distinct clusters for the 10 Dolichos lablab (L.) genotypes (Hair et al., 1995) (Fig 2). Thus, cluster analysis groups individuals or objects based on characteristics they possess so that individuals with similar descriptions are mathematically gathered into the same cluster (Atienza et al., 2005).
 

fig2

CONCLUSION

It is conclude that SSR markers are helpful in the evaluation of lablab diversity and the choice of a collection to make strides the proficiency of genotypes for utilizing in lablab conservation and breeding. Studies shows the presence of moderate genetic variability among the elite Dolichos lablab (L.) genotypes. It confirmed that the potential efficiency of SSR molecular markers in cultivars of lablab and landraces classification and indicate the feasibility of comprehensive attempt in determining the relationships among lablab landraces by the use of some molecular markers. The success were improved by using SSRs based EST-SSRs on (expressed sequence tags-SSR) instead of using genomic SSR (g-SSRs) because EST-SSRs comes from genome transcribed regions and are expected to be conserved across a larger taxonomic range. It is studied that EST-SSRs were three times more transferable across genus Helianthus species as compared to g-SSRs.

ACKNOWLEDGEMENT

Authors are thankful to Department of Botany, Bundelkhand University, Jhansi for providing necessary facilities and there is no conflict of interest among authors.

REFERENCES


  1. Adebisi, A.A. and Bosch, C.H. (2004). Lablab purpureus (L.) Sweet. In Grubben, G.J.H, Denton O.A., (Eds.): Plant Resources of Tropical Africa (PROTA), no. 2, vegetables. PROTA Foun-dation, Wageningen, The Netherlands / Backhuys, Leiden, The Netherlands / CTA, Wageningen, The Netherlands. 343-348.

  2. Asare, T.A., Gowda, S.B., Galyuon, A.I., Aboagye, L.L., Takrama, F.J. and Timko, P.M. (2010). Assessment of the genetic diversity in cowpea (Vigna unguiculata l. Walp.) germplasm from Ghana using simple sequence repeat markers. Plant Genetic Resources: Characterization and Utilization. 8: 142-150.

  3. Atienza, S.G., Torres, A.M., Millan, T. and Cubero, J.I. (2005). Genetic diversity in Rosa as revealed by RAPDs. Agriculturae Conspectus Scientificus. 70: 75-85.

  4. Beaumont, M.A., Ibrahim, K.M., Boursot, P. and Bruford, M.W. (1998). Measuring genetic distance In: Molecular Tools for Screening and Biodiversity, [Karp, A., Isaac, P. G. and Ingram, D. S. (eds.)] Chapman and Hall, pp.. 315-325. 

  5. Benchimol, L.L., Campos, Tde., Carbonell, S.A.M. and Colombo, C. (2007). Structure of genetic diversity among common bean (Phaseolus vulgaris L.) varieties of Mesoamerican and Andean origins using new developed microsatellite markers. Genetic Resources and Crop Evolution. 54: 1747-1762.

  6. Devos, K.M. and Gale, M.D. (1992). The use of random amplified polymorphic DNA markers in wheat. Theoretical and Applied Genetics. 84: 567-572.

  7. Díaz, M.L. and Buendía, H.F. (2011). Genetic diversity of Colombian land races of common bean as detected through the use of silver-stained and fluorescently labelled microsatellites. Plant Genetic Resources. 9: 86-96.

  8. Doyle, J.J. and Doyle, J.L. (1987). A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bulletin. 19: 119-128.

  9. Gnanesh, B.N., Reddi Sekhar, M., Gopal, K., Reddy, R. and Eswara Reddy, N.P. (2005). Genetic Diversity Analysis of Field bean (Lablab purpureus L. Sweet) through RAPD Markers. Indian Journal of Plant Genetic Resources. 18(3): 233-235.

  10. Gupta, P.K. and Varshney, R.K. (2000). The development and use of microsatellite markers for genetic analysis and plant breeding with emphasis on bread wheat. Euphtyica. 113: 163- 185.

  11. Hair, J.R., Anderson, R.E., Tatham, R.L. and Black, W.C. (1995). Multi- variate data analysis with readings. 4th edition, Prentice-Hall, Englewood Cliffs, NJ.

  12. Keerthi, C.M., Ramesh, S., Byregowda, M. and Vaijayanthi, P.V. (2018). Simple Sequence Repeat (SSR) Marker Assay-Based Genetic Diversity among Dolichos Bean (Lablab purpureus L. Sweet) Advanced Breeding Lines Differing for Productivity per se Traits. International Journal of Current Microbiology and Applied Sciences. 7(5): 3736-3744.

  13. Kernodle, S.P., Cannon, R.E. and Scandalios, J.G. (1993). Concentration of primer and template qualitatively affects product in RAPD-PCR. Biotechniques. 14: 362-364.

  14. Li, G., Ra, W.H., Park, J.W., Kwon, S.W., Lee, J.H., Park, C.B. and Park, Y.J. (2011). Developing EST-SSR Markers to study molecular diversity in Liriope and Ophiopogon. Biochemical Systematics and Ecology. 39: 241-252.

  15. Morgante, M., Hanafey, M. and Powell, W. (2002). Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nature Genetics. 30: 194-200.

  16. Nagy, S., Poczai, P., Cernak, I., Gorgi, A., Hegedus, G. and Taller, J. (2012). PIC calc: An online progrmme to calculate polymorphic information content for molecular genetic studies. Biochemical Genetics. 50: 670-672.

  17. Narshimulu, G., Jamaloddin, M., Vemireddy, L.R., Anuradha, G. and Siddiq, E. (2011). Potentiality of evenly distributed hypervariable microsatellite markers in marker-assisted breeding of rice. Plant Breeding. 130: 314-320.

  18. Patil, P., Venkatesha, S.C., Ashok, T.H., Gowda, T.K.S., Byre and Gowda, M. (2009). Genetic Diversity in Field Bean as Revealed with AFLP Markers. Journal of Food Legumes. 22(1): 18-22.

  19. Peakall, R. and Smouse, P.E. (2006). GENALEX 6.2: genetic analysis in Excel. Population genetic software for teaching and research http://www.anu.edu.au/BoZo/GenAlEx/. Molecular Ecology Notes. 6: 288-295.

  20. Powell, W., Morgante, M. and Andre, C. et al. (1996). The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Molecular Breeding. 2: 225-238. 

  21. Prevost, A. and Wilkinson, M.J. (1999). A new system for comparing PCR primers applied to ISSR fingerprinting of potato cultivars. Theoretical and Applied Genetics. 98: 107-112.

  22. Rai, N., Singh, P.K., Rai, A.C. and Rai, V.P. (2011). Singh, M. Genetic diversity in Indian bean (Lablab purpureus) germ-plasm based on morphological traits and RAPD markers. Indian Journal of Agricultural Sciences. 81(9): 801-6.

  23. Reif, J.C., Melchinger, A.E., Xia, X.C. and Warburton, M.L. (2003). Genetic distance based on simple sequence repeats and heterosis in tropical maize populations. Crop Science. 43: 1275-1282.

  24. Roldan-Ruiz, I., Dendauw, J., Vanbockstaele, E., Depicker, A. and De Loose, M. (2000). AFLP markers reveal high polymorphic rates in ryegrasses (Lolium spp.). Molecular Breeding. 6: 125-134.

  25. Singh, S.P. (1999). Improvement of small-seeded race Meso-american cultivars. In Common Bean Improvement in the Twenty-First Century (ed. Singh, S.P.), Kluwer, Dordrecht, 225-274.

  26. Slavov, G.T., Howe, G.T., Gyaourova, A.V., Birkes, D.S. and Adams, W.T. (2005). Estimating pollen flow using SSR markers and paternity exclusion: Accounting for mistyping. Molecular Breeding. 14: 3109-3121.

  27. Sultana, N., Ozaki, Y. and Okubo, H. (2000). The use of RAPD markers in lablab bean (Lablab purpureus (L.) Sweet phylogeny. Bulletin of the Institute of Tropical Agriculture. 23: 45-51.

  28. Tautz, D. (1989). Hypervariability of simple sequences as a general source for polymorphic DNA markers. Nucleic Acids Research. 17(16): 6463-6471.

  29. Tefera, T, Oluoch, M. and Maass, B.L. (2006). Identifying Vegetable Lablab Types by Participatory assessment: Panelists’ Perceptions of Morphological Traits and Organoleptic Taste Assessment. The 13th Australian Society of Agronomy Conference, Perth, 11-14 September.

  30. Tian, Z., Wang, S., Wang, W. and Liu, L. (2005). Study on the Diversity of Germplasm Resources of Dolichos lablab (L.). Natural Science Journal of Hainan University. 23(1): 53-60.

  31. Varshney, R.K., Graner, A. and Sorrells, M.E. (2005). Genic micro-satellite markers in plants: Features and applications. Trends Biotechnol. 23: 48-55.

  32. Varshney, R.K., Chabane, K., Hendre, P.S., Aggarwal, R.K. and Graner, A. (2007). Comparative assessment of EST-SSR, EST-SNP and AFLP markers for evaluation of genetic diversity and conservation of genetic resources using wild, cultivated and elite barleys. Plant Science. 173: 638-649.

  33. Venkatesha, S.C., Gowda, M.B., Mahadevu, P., Rao, A.M., Kim, D.J., Ellis, T.H.N. and Knox, M.R. (2007). Genetic Diversity within Lablab purpureus and the Application of Gene-Specific Markers from a Range of Legume Species. Plant Genetic Resources: Characterization and Utilization. 5(3): 154-171.

  34. Vos, P., Hogers, R., Bleeker, M., Reijans, M., Van de lee, T. and Hornes, M. (1995). AFLP: a new technique for DNA fingerprinting. Nucleic Acids Research. 23: 4407-4414.

  35. Wang, M.L., Gillaspie, A.G., Newman, M.L., Dean, R.E., Pittman, R.N., Morris, J.B. and Pederson, G.A. (2004). Transfer of Simple Sequence Repeat (SSR) Markers across the Legume Family for Germplasm Characterization and Evaluation. Plant Genetic Resources. 2(2): 107-119.

  36. Wang, M.L., Morris, J.B., Barkley, N.A., Dean, R.E., Jenkins, T.M. and Pederson, G.A. (2007). Evaluation of Genetic Diversity of the USDA Lablab purpureus germplasm Col- lection Using Simple Sequence Repeat Markers. Journal of Horticultural Science Biotechnology. 82(4): 571-578.

  37. Williams, J.G.K., Kubelik, A.R., Livak, K.J., Rafalski, J.A. and Tingey, S.V. (1990). DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Research. 18: 6531-6535.

  38. Woodhead, M., Russell, J., Squirrell, J., Hollingsworth, P.M., Mackenzie, K. and Gibby, M. et al. (2005). Comparative analysis of population genetic structure in Athyrium distentifolium (Pteridophyta) using AFLPs and SSRs from anonymous and transcribed gene regions. Molecular Ecology. 14: 1681-1695.

  39. Zhang, G., Shengchun, Xu., Weihua, M., Yaming, G. and Qizan, Hu. (2013). Development of EST-SSR markers to study genetic diversity in hyacinth bean (Lablab purpureus L.). POJ. 6(4): 295-301.

  40. Zhong, S.B., Yang, B.J. and Alfenas, A.C. (2008).Development of microsatellite markers for the guava rust fungus, Puccinia psidii. Molecular Ecology Notes. 8: 348-350.
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