Optimization of RAPD reaction and polymorphism
Nine RAPD primers were used to characterize the genetic diversity present among the soybean germplasm. The banding patterns were obtained with all the primer showed a total of 59 bands (Table 2). The primers assorted greatly in their ability to resolve variability among the germplasms. Individually the range of the bands generated varied from 4 to 8 bands with an average of 6.5 bands per primer. Out of the 59 bands 17 bands were monomorphic
i.
e. it was present in all the isolates. The amplification ranged from 100 bp to 960 bp. The percentage of polymorphism was calculated by multiplying the total number of scored bands by the number of polymorphic bands shown by each primer which was ranged between 50.00 (OPC-15) to 87.5 (GM-3). Polymorphism information content values provides the information of effectiveness of each primer and the maximum number of PIC for RAPD marker is 0.5 because of two alleles per locus are assumed in RAPD analysis. In this study the PIC value ranged from 0.16-0.50. The highest PIC value is depicted was 0.50 by GM-3, while the lowest by OPC-15 (0.16) total with an average of 0.34. Similarly,
Thompson et al., (1998) used these markers to assess the diversity among soybean germplasms using SMC similarity matrix and cluster analysis. They found out that these results help in the exploration of soybean breeding to increase yield. This method to detect variability has been widely used by various researchers like
Sharma et al., (2018) used RAPD marker to access the diversity among soybean varieties using cluster analysis. Similarly,
Wahyudi et al., (2020) studied the diversity in a mutagenized soybean variety by calculating the percent polymorphism and by using Jaccard’s similarity matrix and cluster analysis.
Casas et al., (1999) was also found out that the RAPD results appear to play a vital role in the differentiation among different genotypes.
Evaluation of similarity matrix
The pair-wise Jaccard coefficients for the genetic similarities among the sixteen germplasms are presented in Table 3. The values of the coefficients are estimated on the basis of nine primers to ascertain the degree of genetic relationship among all. The range of similarity coefficients varies from 0.87 to 0.36. The highest similarity matrix was observed between germplasms namely DS 3108 and NRC 131 (0.91) followed by NRC 132 and NRC 136 (0.87) then, NRC 128 and NRC 130; NRC 130 and NRC 136; NRC 136 and NRC 137; NRC SL-1 and SKF-SP-11 (0.83), then by NRC 128 and NRC 132 (0.82) showing that all these germplasms have very similar genetic constituent with each other while lowest similarity was observed between germplasms DS 3108 and RSC 11-03 (0.36) followed by NRC 131 and RSC 11-03 (0.39) then NRC SL-1 and RSC 11-03 (0.41), JS-335 and RSC 11-03 (0.42) and RSC 11-07 and RSC 11-03 (0.44) showing farther relations of these germplasms with other germplasms indicating the difference amongst the soybean germplasms.
Mokate et al., (2017) conducted an experiment to find out the comparison of divergence assessment through RAPD and ISSR molecular marker among 24 soybean genotypes. Through RAPD primer analysis they found out that the similarity matrix among soybean genotypes ranges from 0.41 and 1.00. The highest divergence was observed in only two genotypes KDS 753 and DS 228. The study reveals that among ISSR and RAPD, RAPD markers shows the target regions efficiently and target for a specific trait.
Sharma et al., (2018) estimated the genetic diversity among eight soybean varieties through fourteen RAPD primers. In single RAPD marker they found highest level of polymorphism (80%) with most of the primers with Jaccard’s similarity coefficient values ranges from 0.44 to 0.76. Dendogram based on cluster analysis showed relationship among soybean varieties shows clearly two groups in which group-I was further divided into two groups.
Cluster analysis showing similarity among soybean germplasms
The binary data matrix based on the PCR amplification results was then subjected to clustering and distance method using an unweighted pair group method with arithmetic mean (UPGMA) algorithm. A dendogram was constructed for all germplasms using data pooled from all the primers. The result showed distinction among all the germplasms (Fig 2) by dividing the germplasms into two major groups. The first major group consist sixteen germplasms and the second major group consisted two germplasms namely DSB 34 and RSC 11-03. Group one is further divided into two subgroups in which first subgroup consist nine germplasms namely AMS 100-39, BAUS 102, NRC 128, NRC 130, NRC 132, NRC 136, NRC 137, PS 1613 and MACS 1493 while the second subgroup consist DS 3108, NRC 131, RSC 11-07, NRC SL-1, SKF-SP-1, JS-335 and Bragg.
Lakhanpaul et al., (2000) also analyzed the
Vigna radiata cultivars through RAPD markers and found out that a total 267 amplification products were formed at an average of 12.71 per primer with an overall polymorphism of 64%, while Jaccard similarity coefficient values show range from 0.65 to 0.92. The cluster analysis resulted in three clusters revealing greater homology between cultivars released from the same source indicating that RAPD primers are the best source for cultivar improvement program.
Macial et al., (2001) evaluated the variability among the
Phaseolus vulgaris cultivars and a landrace of soybean with the help of RAPD markers. They found out a great variability with an average of 20.3 bands per primers with an average of 88.8% polymorphism among
Phaseolus genotypes. The result of this analysis revealed that the diversity of the cultivars was certainly determined through cluster differentiation.