Evaluation of SSR-based genetic diversity, protein and mineral content in black gram genotypes

2.1 Plant material and field trial

A set of 60 genotypes of black gram were used in the present experiment, of which 19 were varieties released by various institutions of India. All the genotypes were grown in three replications in randomized complete block design (RCBD) in summer 2016 at Regional Research Station (RRS), Anand Agricultural University, Anand with plant × plant and row × row to distance of 10 and 45 cm, respectively, in a plot size of 4 × 0.9 m.

2.2 Estimation of protein and minerals

At the time of maturity, pods were picked from randomly tagged 5 competitive plants of every genotype for protein and mineral analysis. After de-hulling, seeds were washed with tap and distilled water to remove dust. Seeds were fine powdered in cyclone sample mill. The Kjeldahl method was used to estimate the nitrogen content in seed powder (AOAC, 1960). Protein content was acquired with the conversion factor of 6.25.

For estimation of minerals (mg/100 g), acid extract with powder was prepared by di-acid mixture (HNO₃:HCLO₄- 4:1). From the acid extract, potassium was determined through flame photometric method (Jackson, 1973), calcium was determined by versanate titration method (Cheng and Bray, 1951) while the vanadate-molybdate yellow colour method of Jackson (1973) was deployed for estimation of phosphorus content.

2.3 DNA extraction and SSR-PCR

DNA was isolated from young leaves of 5 plants following the protocol described by Doyle and Doyle (1990). Agarose gel (0.8%) electrophoresis was carried out to assess DNA quality followed by spectrophotometry on Nanodrop (Thermo, USA) to estimate DNA concentration. A working stock of 10 ng/μL was prepared with nuclease-free water for polymerase chain reaction (PCR) of SSR markers.

Various researchers reported that microsatellite markers from Vigna unguiculata (cowpea) and V. angularis (azuki bean) revealed a high amplification success in black gram (Kaewwongwal et al., 2015). Therefore, during PCR amplification, microsatellite primers from V. unguiculata, V. angularis and Glycine max (soybean) along with SSR markers of urdbean were used. For SSR-PCR, 15 μL reaction mixture containing 2.5 μL gDNA, 6.5 Master-mix (Takara, India), and 1.0 μL of primer (10 pM) and 5 μL distilled water was used. PCR was carried out with following thermal conditions: initial denaturation of 94 °C for 5 min, then 35 cycles of 94 °C for 45 s, T °C (specified primer) for 45 s, 72 °C for 45 s and a final extension at 72 °C for 7 min. PCR products were separated using 6% non-denaturing polyacrylamide gels (PAGE) on sequencing gel system (Bio-Rad Sequi-Gen GT Sequencing Cell) followed by silver staining of gel. The stained gels were scanned using scanner to capture gel images (Microtek, Taiwan).

2.4 Statistical analysis of biochemical and molecular data

The mean value of biochemical traits was figured out, and analysis of variance (ANOVA) was calculated as per Panse and Sukhatme (1978). For molecular diversity assessment, SSR allele calling in base pairs was carried out manually with consideration of the heterozygous or homozygous status of genotype. The number of alleles from each primer, frequency of major allele, gene-diversity, heterozygosity and polymorphism information content (PIC) was calculated by PowerMarker v.3.25 (Liu and Muse, 2005). Neighbor-Joining (NJ) algorithm in DARwin 6.0 was deployed to compute pair-wise inter-genotype genetic distance.

3.1 Mean performance and correlation

ANOVA exposed a significant difference among the genotypes for four biochemical traits (Table 1) suggesting the presence of genetic variation in studied set of genotypes for the traits. This also gives abundant opportunity to select promising genotype from the studied material for improving protein and mineral content of black gram. The presence of ample variability might be due to a diversity and/or effect of edaphic and environmental conditions.

Pulses are inexpensive source of protein in comparison to animal proteins in developing countries (Singh and Jambunathan, 1991). In general, legumes contain 18–25% protein, about double that of the cereals. Moreover, the protein content of black gram is considerably higher than chickpea and pigeonpea (Singh and Singh, 1992). Being a pulse, high protein is a necessary trait in black gram. The average value of protein content was 22.96%. Among the genotypes studied, VUG-14 (26.41%) had the highest protein content and was at par with VUG-10 (26.26%), VUG-55 (26.12%) and VUG-7 (26.12%). Lowest protein was recorded in genotype PU-30 (20.28%). Significant difference for this trait has also reported by Konda et al. (2009) and Patidar et al. (2018).

In human cell, calcium and phosphorus play important roles in countless biochemical reactions. They are also the main components of the skeleton. Moreover, phosphorus is an important constituent of soft tissue and has function in the formation of bones and teeth. The deficiency of dietary calcium is widespread, especially in developing countries (Pettifor, 2014). Black gram contains a high amount of calcium (Patwardhan 1962). In the current study, the mean for calcium was 135.26 mg/100 g in seed with a range from 117.17 (VUG-56) to 148.33 mg/100 g (LBG-20). Kavitha et al. (2013) also detected a wide range of variation for calcium content in black gram. The level of calcium in black gram was up to twice as many legumes like red gram, green gram and peanut (Singh and Singh, 1992; Bukya, 2014). Though, the calcium in black gram was significantly lower than soybean (Singh and Singh, 1992). Thus, regular consumption of black gram can help in maintaining bone health.

The population mean for seed phosphorus content was 325.96 mg/100 g. Among all genotypes, highest phosphorus content (398.07 mg/100 g) was detected in VUG-22, and it was statistically at par with VUG-5 (394.60 mg/100 g), VUG-67 (388.56 mg/100 g), VUG-39 (377.43 mg/100 g). The genotype PANT U 40 (237.00 mg/100 g) exhibited the lowest phosphorus content. Significant difference for this trait was recorded by Kavitha et al. (2013) in black gram.

Similar to calcium, black gram is also a rich source of potassium (K). Potassium is linked with movement of H₂O, nutrients and sugars in plant cell. It is a key mineral for activation of many enzymes which affects protein, starch and adenosine triphosphate production (ATP) in the plant. The results revealed that the mean potassium content was 468.59 mg/100 g in seeds of black gram though it ranged from 337.96 (VUG-63) to 548.08 mg/100 g (VUG-66) which indicated sufficient variation. After VUG-66, VUG-22 also exhibited high K (539.01 mg/100 g) in the current study. Earlier, Gopalan et al. (1989) reported high potassium (800 mg/100 mg) in black gram.

The genotypic and phenotypic correlation coefficient among characters is presented in Table 2. In the present study, phosphorus was significantly correlated with potassium at both levels in a positive direction. Vandemark et al. (2017) recorded a similar result for phosphorus and potassium content in chickpea and lentil.

3.2 Molecular diversity analysis

PCR dependent co-dominant marker based diversity estimation has proven useful due to high polymorphism level loci and easy analysis. Molecular markers can overcome the limitations especially of genotype × environment interaction associated with morphological/biochemical markers (Kumar et al., 2016). Hence, molecular markers are very powerful for genetic diversity estimate. In the current study, a total of 42 markers were used for amplification and polymorphism survey in sixty genotypes. Out of 42 primers, 27 (66.66%) were amplified successfully. However, out of 27, 16 markers (59.25%) were found to be monomorphic while remaining 11 markers (40.74%) were recorded polymorphic (Table 3). The no amplification and high rate of monomorphism of SSR primers have been reported by Tondonba et al. (2018).

The molecular weight of the amplified DNA ranged from 110 (CEDG 08) to 386 bp (Vmg SSR 53) reflecting a significant difference in the repeat motifs between the different alleles. A total of 66 alleles were identified from 60 black gram genotypes. The average number of allele per locus was 6 with a range of 2 (AG 81, Bmd 12) to 12 (Vmg SSR 53 and Vmg SSR 29). The average number alleles per locus in the current investigation was lesser than the earlier reported by Kaewwongwal et al. (2015) where mean alleles per locus was 9.05 and higher than Gupta and Gopalakrishna (2009) where mean alleles per locus were 4.1 (Table 3). The major allelic frequency is ranging from 0.13 (Vmg SSR 29) to 0.78 (CEDG 92 and Vmg SSR 82).

The maximum gene diversity (0.91) was linked for Vmg SSR 29 and Vmg SSR 53 while, it was minimum (0.35) for CEDG 92. Though, mean gene diversity was 0.65. Kaewwongwal et al. (2015) reported mean gene diversity 0.75 in wild black gram species which was higher than present investigation, while 0.59 mean diversity reported in cultivated black gram species which was lower than present investigation.

Heterozygosity varied widely from 0.00 to 0.40 (CEDG 08) with an average of 0.04. In overall, low heterozygosity is due to self-pollinating nature of legumes which prevent inter-population gene flow eventually precludes the blending of the different gene pools and thereby, decreasing the genetic variation and increasing the homozygosity (Gediya et al., 2019).

The PIC value is a discriminating power of a particular marker in a defined germplasm (Smith et al., 2000). The PIC value of a marker dependents on the number of alleles and their relative frequencies in studied germplasm. In the present study, PIC values for SSR markers ranged from 0.30 (CEDG 92) to 0.90 (Vmg SSR 29 and Vmg SSR 53) with average 0.60 which was close agreement with PIC value of SSR marker (0.60) reported by Kaewwongwal et al. (2015). The PIC was higher than Gupta and Gopalakrishna (2009) where mean PIC was 0.49. However, except four, seven markers were found to be more informative as displayed PIC >0.5.

Sixty black gram genotypes were grouped into three main clusters A, B and C with 28, 28 and 4 genotypes, respectively (Fig. 1). Gupta and Gopalakrishna (2009) and Tondonba et al. (2018) also reported three groups with SSR markers. In the current study, main cluster A was further divided into two sub clusters A1 (18 genotypes) and A2 (10 genotypes). Main cluster B was divided into two sub-clusters B1 (22 genotypes) and B2 (6 genotypes). The pair wise comparison value of Nei’s (1973) genetic distance ranged from 0.09 to 1.00. A total of 31 pairs depicted extreme genetic distance (1.00) indicated that these pairs of genotypes are highly dissimilar at the genomic level and can be used in heterosis breeding to widen the genetic background and to create mapping populations to ignite molecular breeding program. The lowest genetic distance (0.09) was observed between VUG-31/VUG-41 and T-9/GU-1. The mean genetic distance in current study was 0.69. Pyngrope et al. (2015) recorded 0.50 average distance was in 30 black gram genotypes which were lower than the present study.

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Fig. 1

Dendrogram showing clustering of sixty black gram genotypes constructed using un-weighted Neighbour-Joining analysis (Genotypes in red font are released varieties).

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