Cross genera transferability and polymorphism of the SSR markers
Due to cost efficacy, transferability of markers from related species may become an unorthodox choice as compared to new SSR primer designing from genomic library. Keeping in that view many workers had reported cross-species transferability of SSR markers among legumes
(Choi et al., 2004; Choumane et al., 2004; Guohao et al., 2006). The basic principle behind the extent of transferability and use of molecular markers from one species to other related species relied on the extent of genomic similarity between two species. This principle was further conceptualized by
Gupta and Gopalakrishna (2010) reporting that in case of SSR markers, it depends upon the extent of conserved primer binding sites flanking the SSR loci. In the present study also, Among the 40 markers used in PCR amplification in this study all primers amplified in mungbean cultivars which shows 100% transferability rate signifying a high genomic homology between two species of
Vigna.
Tangphatsornruang et al., (2009) reported the success in transferability of SSR markers by indicating that majority of microsatellite markers were transferable in
Vigna species, whereas transferability rates were only 22.90% and 24.43% in
Phaseolus vulgaris and
Glycine max, respectively. On the contrary,
Wang et al., (2009) observed 75% adzuki bean SSR markers as transferable and only 14% as polymorphic among a total of 187 primers in 60 mungbean genotypes. Likewise,
Dikshit et al., (2012) observed transferability percentage across the genotypes ranged from 60.97 to 92.6% with 87.8% in
Vigna radiata and
Vigna mungo, 62.2% in
Vigna unguiculata, 91.8% in
Vigna umbellata, 78% in
Vigna mungo var.
sylvestris and 80% in
Vigna trilobata, respectively by using 78 mapped SSRs from adzukibean cultigens. These studies exhibited the auxiliary leeway in transfer of SSR markers to mungbean from other closely related species. These transferred markers can be used to expedite the breeding efforts in the mungbean improvement program. For example, in a pioneer study,
Ishemura et al., (2012) analyzed the genetic differences between mungbean and its presumed wild ancestor by formulating a complete linkage map of mungbean covering all the 11 linkage groups using SSR and EST-SSR markers from mungbean and its related species like adzukibean, cowpea and soybean and observed that the amplification ratio of SSR and EST-SSR primers from the five legumes was comparatively high in mungbean, with values between 76.7% (cowpea primers) and 98.0% (mungbean primers). This cross-species utilization of SSR primers made possible due to a high level of sequence conservation among the flanking regions of microsatellites which was indicated by multiple bands found in by few microsatellites because of annealing at more than one locus or duplication of primer binding sites in the cross-species legumes
(Dikshit et al., 2012; Wang et al., 2014). In accordance of these results,
Palaniappan and Murugaiah, (2012) characterized 20 elite mungbean genotypes using 16 microsatellite markers from greengram, adzukibean, common bean and cowpea. Among these 16 makers 14 had showed polymorphism. They demonstrated that adzukibean microsatellite markers are highly polymorphic and can be successfully used in the genome analysis of mungbean.
Moreover, in the present study, out of the 40 primers showing amplification in greengram, 11 markers were highly polymorphic (for example, Fig 1) and remaining were monomorphic. In order to demonstrate the potentiality of the transferable SSR markers, PIC values were used as a parameter, which varied with a mean value of 0.81 and more than 63% SSR loci had greater than this average PIC value. PIC value of these polymorphic SSR markers ranged between 0.64-0.88 with an average PIC value of 0.81 (Fig 2) while number of alleles ranged between 6 to 12 with an average of 9.27 alleles per locus (Table 3). It has been observed that markers should have many alleles to be considered useful for evaluation of genetic diversity
(Ribeio-carvalho et al., 2004). The polymorphic primers which have high PIC value can be used in further molecular studies like association mapping, tagging of gene(s) of interest and the most called approach marker assisted selection (MAS). Total 102 alleles were generated by these 11 primers. Contrastingly a large representative collection of mungbean accessions was analysed using 19 SSR primers for each linkage group (on the basis of the azuki linkage map) by
Sangiri et al., (2007) revealing detection of 309 alleles. These differences in our study pertaining to number of alleles detected are primarily due to use of 0.3% Agarose gel instead of capillary electrophoresis used in their study for genotyping as well as lines from different geographic regions and SSR markers used.
Furthermore, product size was also calculated for each of the primers by calculating the average in the present study. Some primers (CEDG141, CEDG156, VM 27and BM 146) highly deviate on their product size studied earlier by
Wang et al., (2014). The multiple locus amplification and high PIC values indicated the effectiveness of the transferable SSRs in germplasm characterization, evolution, breeding application and phylogenetic studies in greengram. Several SSR markers also showed multiple banding patterns with very weak bands but these were not considered for analysis in present study. This poor banding pattern could be due the non-specific annealing of the SSR primers
(Williams et al., 1990).
In accordance to these results,
Chattopadhyay et al., (2008) identified and successfully deployed efficient molecular markers which can minimize ambiguity in varietal identification and registration in mungbean by using 15 accessions and 10 PCR-based efficient primers identified with higher polymorphic information content (PIC) values and higher marker indexes (MI).
Diversity analysis
A dendrogram (Fig 3) based on UPGMA analysis grouped 70 genotypes of greengram in eleven major clusters (Table 4). These eleven clusters had maximum similarity of 38%. The perusal of the cluster analysis revealed that the individuals within any one cluster are more closely related than are individuals in different clusters. The cluster II consisting of 34 genotypes was the largest and was followed by cluster XI having 9 genotypes while rest of the clusters had less than 5 genotypes. The clustering pattern thus obtained in the study confirmed the discriminating power and reliability on the SSR markers for genetic diversity studies. NTSYS also analyzed the Jaccard’s similarity coefficient which was ranging from 0.17 to 0.46. This range clearly showed that a transitional amount of diversity found among the genotypes by visualizing the extent of genetic similarities among the test genotypes. Minimum similarity of 17% was found between the genotypic pair TMB 37 and Pusa Ratna as well as TMB 37 has shown considerable dissimilarity with AKM 8803 and JM 721. Furthermore, these genotypes TMB 37, Pusa Ratna, AKM 8803 and JM 721 are implicated to get minimum similarity consequently they can be used to facilitate as mapping population in various mapping studies as well as establishing the utility of microsatellite markers in identifying diverse pairs. While the maximum genetic similarity of about 46% was observed between 34 genotype pairs. This mark a possibility that the SSR markers used in the study may be linked to the genomic region in these genotypes. Furthermore, these genotypic pairs are implicated to get maximum dissimilarity consequently they can be used to facilitate as mapping population in various mapping studies as well as establishing the utility of microsatellite markers in identifying diverse pairs.