Indian Journal of Biotechnology Vol 13, January 2014, pp 81-88
Efficiency of SSR, ISSR and RAPD markers in molecular characterization of mungbean and other Vigna species Akanksha Singh, H K Dikshit, Neelu Jain*, D Singh and R N Yadav1 Division of Genetics, Indian Agricultural Research Institute, New Delhi 110 012, India 1 Indian Agricultural Research Institute, Regional Station, Karnal 132 001, India Received 27 December 2012; revised 28 May 2013; accepted 15 July 2013 Genetic diversity among 35 Vigna genotypes was assessed using SSR, ISSR and RAPD markers. SSR (21), ISSR (17) and RAPD (25) markers produced a total of 319 bands, of which 284 exhibited polymorphism. Higher marker indices were obtained for ISSR markers, which also proved to be the most efficient marker system in terms of average heterozygosity values. All the marker systems characterized the genotypes effectively. The similarity coefficients were significant for all the three marker systems, but were lower for SSR compared to ISSR and RAPD markers. The pooled allelic diversity data grouped 35 genotypes into 4 major clusters with most of the genotypes reflecting relationship according to the species distribution. The DNA based markers used in the present study were efficient in discriminating the studied Vigna species. Keywords: ISSR, molecular characterization, RAPD, SSR, Vigna
Introduction Mungbean [Vigna radiata (L.) Wilczek)] is a self pollinated crop with genome size of 579 Mbp1. It is believed that mungbean originated in Indian sub-continent2-4. Archaebotanical findings and literary records also indicate that mungbean was domesticated in India5. Mungbean is a tropical/sub-tropical crop and requires warm temperatures (optimal at 30-35°C). It is grown for its protein rich seeds and considered vital ingredient of human diet as dal along with cereals in South Asian countries. Mungbean seeds are also consumed as sprouts in several countries. According to agricultural statistics, mungbean was grown to 3.55 million hectare in India with a production of 1.80 million tons during 2010-11. In India, this crop is mainly grown in rainfed area as an intercrop with sorghum, pearl millet, maize, cotton, castor, and pigeonpea, and in rice fallows of South India in winter season. In spring, summer season mungbean is grown with assured irrigation facilities. The yield level of this crop has been low and the major bottle necks limiting high yield of mungbean include susceptibility to biotic (mungbean yellow mosaic virus, powdery mildew, cercospora leaf spot and leaf curl virus) and abiotic stresses (drought, water logging and preharvest sprouting), poor harvest index, lack of genetic —————— *Author for correspondence: E-mail:
[email protected]
variability and non availability of suitable ideotypes for different cropping systems. The study of coefficient of parentage of 94 mungbean cultivars revealed extensive and repetitive use of superior genotypes with common ancestors, leading to narrow base of released cultivars6. Different Vigna species are rich source of genes for yield traits and resistance against biotic and abiotic stresses and introgression of these genes is vital for enhancing and stabilizing yield levels. Limited success has been achieved in mungbean with conventional breeding. Therefore, the application of molecular markers can play key role in directed improvement of mungbean. Previous workers had used RAPD markers7 for diversity analysis in Indian mungbean germplasm and studied the efficiency of RAPD and ISSR marker systems in accessing genetic variation of rice bean (V. umbellata) landraces8. Genetic diversity in mungbean germplasm lines had also been studied using SSR markers9,10. The present investigation was conducted with specific objective of evaluating utility of different marker systems in genetic characterization of Vigna and analysis of genetic variability in mungbean and related Vigna species. Materials and Methods Plant Material
The experimental material comprised of Vigna genotypes (35) including V. radiata (25), V. mungo (4), V. unguiculata (2), V. umbellata (3) and
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V. trilobata (1). The sources of accession of different Vigna species used in molecular analysis are presented in Table 1. Molecular Analysis Genomic DNA Extraction and Purification
The genomic DNA was isolated from 5-d-old seedlings by using cetyltrimethyl ammonium bromide (CTAB) method11. The DNA pellet was dissolved in TE buffer (pH 8.0). For purification of DNA, RNAse treatment was given11. The purified DNA was quantified by running 2 µL of each DNA sample on 0.8 % agarose gel along with uncut lambda DNA (30 and 60 ng) to adjust final concentration for use in PCR analysis. RAPD and ISSR Markers
A total of 40 RAPD primers (from Kits SBS A, B, D & F) and 25 ISSR primers were screened for DNA amplification. Of which 25 RAPD and 17 ISSR primers produced sharp and clear bands, and were used for further analysis. The PCR amplifications were carried out in a total volume of 20 µL reaction mixture containing 40-50 ng of genomic DNA, 40 ng of each primer, 0.2 mM dNTPs, 1× PCR buffer and 1 unit Taq DNA polymerase for both the markers. The PCR profile for RAPD primers consisted of initial denaturation at 94ºC for 2 min, and subsequent 45 cycles, each with denaturation at 94ºC for 1 min, primer annealing at 40ºC for 1 min and primer extension at 72ºC for 1 min. The final extension step was performed at 72ºC for 7 min. PCR amplifications for ISSR markers were performed with initial denaturation at 94ºC for 2 min, and subsequent 40 cycles, each with denaturation at 94ºC for 2 min, primer annealing at 56ºC for I min and primer extension at 72ºC for 1 min with a final extension at 72ºC for 7 min. The list of primers, annealing temperature along with some of the characteristics of the amplification products obtained in different Vigna species are given in Table 2. The amplified PCR products for RAPD and ISSR markers were resolved by electrophoresis on 1.5% and 1.8% agarose gel, respectively, stained with ethidium bromide and the photographs were taken by using Gel Documentation System (Alpha Innotech Corporation, USA). Mol wt of bands was estimated using 1 Kb ladder (MBI Fermantas). Microsatellite Markers
Thirty adzuki bean SSR markers transferable to mungbean12 were chosen for the study. About 21 SSR markers produced clear and distinct bands and were
Table 1—Source of Vigna genotypes used in the study No.
Variety/accession
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
V-578 V-585 RBL-1 RBL-35 RBL-50 IPU-94-1 Barabanki Local PU-31 PU-06-20 Pusa Ratna Pusa-9531 Pusa Vishal Pusa 9072 Pusa 09-4 Pusa 09-5 AKM 9904 S-9 VC-1673 VC-6173 C C-15-7 TM-96-2 TJM-3 ML-1451 MH-521 MH-96-1 MH-318 PDM-91-269 Pant M-4
29 30 31 32 33 34
HUM-1 HUM-16 Gwalior Local IPM-02-17 IPM-02-19 IC 556571
35
Pusa-0672
Species
Source
V. unguiculata IARI, New Delhi V. unguiculata IARI, New Delhi V. umbellata PAU, Ludhiana V. umbellata PAU, Ludhiana V. umbellata PAU, Ludhiana V. mungo IIPR, Kanpur V. mungo IIPR, Kanpur V. mungo IIPR, Kanpur V. mungo IIPR, Kanpur V. radiata IARI, New Delhi V. radiata IARI, New Delhi V. radiata IARI, New Delhi V. radiata IARI, New Delhi V. radiata IARI, New Delhi V. radiata IARI, New Delhi V. radiata PDKV, Akola V. radiata IARI, New Delhi V. radiata AVRDC, Taiwan V. radiata AVRDC, Taiwan V. radiata IARI, New Delhi V. a radiata PDKV, Akola V. radiata PDKV, Akola V. radiata PAU, Ludhiana V. radiata HAU, Hisar V. radiata HAU, Hisar V. radiata HAU, Hisar V. radiata IIPR, Kanpur V. radiata GBPUAT, Pantnagar V. radiata BHU, Varanasi V. radiata BHU, Varanasi V. radiata IARI, New Delhi V. radiata IIPR, Kanpur V. radiata IIPR, Kanpur V. trilobata NBPGR, New Delhi V. radiata IARI, New Delhi
IARI=Indian Agricultural Research Institute, PAU=Punjab Agricultural University, IIPR=Indian Institute of Pulse Research, PKV=Punjabrao Deshmukh Krishi Vidyapeeth, AVRDC=Asian Vegetable Research Development Centre, HAU=Haryana Agricultural University, GBPUAT=G B Pant University of Agriculture and Technology, BHU=Banaras Hindu University, NBPGR=National Bureau of Plant Genetic Resources
selected for further analysis. PCR amplification was performed with initial denaturation at 94ºC for 4 min, and subsequent 35 cycles, each with denaturation at 94ºC for 1 min, primer annealing at 57-60ºC for 30 sec and primer extension at 72ºC for 1 min with
SINGH et al: MOLECULAR DIVERSITY IN VIGNA SPECIES
final extension at 72ºC for 7 min. All the amplified PCR products obtained from SSR markers were resolved by electrophoresis on 3.0% high resolution metaphor agarose, stained with ethidium bromide and photographed by using Gel Documentation System (Alpha Innotech Corporation, USA). 100 bp DNA ladder was used for approximate sizing of the bands (MBI Fermantas). Data Analysis Fragments amplified by primer sets were scored manually in term of position of the bands relative to the ladder, sequentially from the smallest to the largest-sized bands. Diffused bands or bands revealing ambiguity in scoring were considered as missing data and designated as ‘9’ in comparison with ‘1’ for the presence of a band and ‘0’ for the absence of a band in the data matrix. A binary matrix was then transformed to genetic similarity (GS) matrix using Jaccard’s coefficient13. A dendrogram based on similarity coefficients was prepared by using Unweighted Pair Group Method with Arithmetic Mean (UPGMA) using the computer package NTSYS-pc 2.0214. Principal component analysis (PCA) based on Jaccard similarity was used to estimate the actual number of groups that may be obtained by cluster analysis. Boot strap analysis was carried out to statistically support the branches of the cluster with 1000 replicates using Winboot software program15. Mantel’s test was performed on cophenetic correlation coefficient to test the goodness of fit of the cluster analysis16. Utility of a marker for detecting genetic variation was estimated17. It includes: a) Expected heterozygosity (Hn) by calculating sum of the squares of allele frequencies, Hn=1–Σpi 2, where pi is the allele frequency for the ith allele18; b) Arithmetic mean heterozygosity (Hav) was calculated as, Hav=ΣHn/n, where n is the number of markers (loci) analyzed; c) Effective multiplex ratio (EMR=npβ), which is the product of number of polymorphic loci (np) in the germplasm analyzed and the fraction of markers that were polymorphic (β); and d) Marker index (MI), which is the product of expected heterozygosity (Hav) and effective multiplex ratio, were calculated. The resolving power (Rp) of each primer was calculated as Rp=ΣIb, where Ib (band informativeness) takes the value: 1−[2×(0.5−p)], p being the proportion of genotype of different Vigna species containing that band19.
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Results and Discussion Characterization of Genetic Variation
The genetic variation was detected among 35 Vigna genotypes using ISSR (17), RAPD (25) and SSR (21) primers (Table 2). The 63 markers amplified a total of 319 bands, of which 284 were polymorphic. The maximum number of 9 bands was amplified with ISSR 9 and ISSR 11, and minimum 2 bands with SSR primers CEDG 13, CEDG 18, CEDG 21, CEDG 73, CEDG 127, CEDG 139 and CEDG 178. The 17 ISSR markers amplified a total of 95 bands, of which 83 were polymorphic with an average of 4.882 polymorphic bands per primer. RAPD (25) markers generated 148 bands with an average of 5 polymorphic bands per primer. However, SSR (21) markers produced 76 bands with an average of 3.619 polymorphic bands per primer. Comparison of Different Marker Systems
Average heterozygosity and marker indices were estimated as measure of polymorphism and utility of different marker systems. For comparison of the three marker systems, expected heterozygosity (Hn) for each individual marker and average heterozygosity (Hav) for each marker system was calculated. The expected heterozygosity varied from 0.11 to 0.97 in different marker systems. The average heterozygosity values were 0.72 for ISSR, 0.80 for RAPD and 0.47 for SSR markers. Of 63 studied markers, 40 were found to be effective in detecting polymorphic loci (β=1). The fraction of polymorphic loci was highest for SSR (1.0) followed by ISSR and RAPD markers. EMR ranged from 1 to 9 among the studied markers. All these marker systems efficiently discriminated the different Vigna species. The average MI for RAPD was 3.48, followed by ISSR with 3.42 and SSR with 1.68. The mean expected heterozygosity was lower in ISSR in comparison to RAPD markers. The resolving power ranged from 0.36 to 2.61 for the studied marker systems. Average genetic similarity values between pair of cultivars were highest for ISSR markers (0.57), followed by RAPD (0.48) and SSR marker (0.41) systems. The value of mantel’s test correlation showed a positive correlation between the three marker systems. The cophenetic correlation coefficients between the cluster analysis and the similarity matrix showed a very high correlation value for ISSR, RAPD and SSR marker; r=0.93, r=0.84 and r=0.82, respectively. The pooled diversity data also showed very high goodness of fit (r=0.903).
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Table 2—Comparative analysis of ISSR, RAPD and SSR markers assayed in 35 genotypes of Vigna spp. Primer
Tm(°C)
TB
ISSR 1 ISSR 2 ISSR 5 ISSR 7 ISSR 9 ISSR 11 ISSR 12 ISSR 15 ISSR 16 ISSR 17 ISSR 20 ISSR 21 ISSR 22 ISSR 24 ISSR 27 ISSR 31 ISSR 32 Average
56 56 56 56 56 56 56 58 58 56 56 56 56 56 56 56 56
4 5 3 3 9 9 5 4 7 4 4 6 7 4 6 7 8 5.59
SBS A11 SBS A12 SBS A13 SBS A14 SBS A15 SBS B1 SBS B2 SBS B3 SBS B4 SBS B5 SBS D1 SBS D2 SBS D3 SBS D4 SBS D5 SBS D6 SBS D7 SBS D8 SBS D9 SBS D10 SBS F6 SBS F7 SBS F8 SBS F9 SBS F10 Average
40.8 36.7 34.8 30.2 38.7 33.7 33.9 38.6 34.6 45.6 44.1 36.8 41.4 28.0 36.9 33.4 46.5 40.6 34.0 32.0 38.3 33.4 33.4 33.9 33.9
5 7 6 6 6 6 6 6 6 5 6 6 5 6 6 6 6 6 6 6 6 6 6 6 6 5.92
PB ISSR 3 5 3 2 9 3 5 4 6 4 4 5 7 2 6 7 8 4.88 RAPD 4 5 6 5 4 6 5 5 5 5 5 4 4 5 6 6 5 6 5 5 6 6 4 4 4 5
β
EMR
Hn
MI
Rp
0.75 1 1 0.67 1 0.33 1 1 0.86 1 1 0.83 1 0.5 1 1 1 0.88
2.25 5 3 1.33 9 1 5 4 5.14 4 4 4.17 7 1 6 7 8 4.52
0.75 0.78 0.47 0.44 0.77 0.74 0.73 0.72 0.83 0.44 0.63 0.81 0.86 0.75 0.83 0.82 0.85 0.72
1.68 3.92 1.42 0.59 6.96 0.74 3.67 2.88 4.25 1.78 2.52 3.4 6.03 0.75 5 5.72 6.82 3.42
2 2.01 2 2 2.61 1.99 1.99 2 1.98 2.09 2 1.98 1.94 2 1.97 1.9 2 2.03
0.8 0.71 1 0.83 0.66 1 0.83 0.83 0.83 1 0.83 0.66 0.8 0.83 1 1 0.83 1 0.83 0.83 1 1 0.66 0.66 0.66 0.84
3.2 3.57 6 4.16 2.66 6 4.16 4.16 4.16 6 4.16 2.66 3.2 4.16 6 6 4.16 6 4.16 4.16 6 6 2.66 2.66 2.66 4.31
0.76 0.83 0.97 0.75 0.79 0.79 0.81 0.79 0.82 0.78 0.81 0.78 0.80 0.79 0.78 0.81 0.80 0.83 0.82 0.80 0.82 0.80 0.78 0.81 0.74 0.80
2.42 2.98 5.81 3.14 2.12 4.72 3.35 3.28 3.40 3.90 3.39 2.09 2.58 3.29 4.68 4.88 3.35 4.97 3.39 3.35 4.90 4.80 2.08 2.16 1.98 3.48
1.93 1.97 0.36 1.99 1.99 1.99 1.99 1.99 1.79 2.09 1.76 1.99 1.97 1.93 1.99 1.93 1.98 1.99 1.99 1.99 1.93 1.88 1.99 1.99 1.92 1.89 (Contd.)
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Table 2—Comparative analysis of ISSR, RAPD and SSR markers assayed in 35 genotypes of Vigna spp.(Contd.) Primer Tm (°C) TB SSR PB SSR β SSR EMR SSR Hn MI Rp 57 2 2 CEDG13 1 2 0.60 1.21 2.17 57 3 3 CEDG15 1 3 0.21 0.62 1.94 CEDG18 57 2 2 1 2 0.55 1.10 1.89 CEDG21 57 2 2 1 2 0.36 0.73 1.94 CEDG37 57 3 3 1 3 0.35 1.05 1.89 CEDG43 60 3 3 1 3 0.24 0.74 2.71 CEDG44 57 5 5 1 5 0.70 3.49 2.17 CEDG050 53 4 4 1 4 0.75 3.00 2.00 CEDG73 60 2 2 1 2 0.40 0.79 2.00 CEDG86 60 3 3 1 3 0.42 1.27 1.60 CEDG92 60 3 3 1 3 0.83 2.48 2.00 CEDG104 60 6 6 1 6 0.29 1.76 2.17 CEDG127 60 2 2 1 2 0.57 1.13 2.00 CEDG139 62 2 2 1 2 0.67 1.34 2.11 CEDG154 60 6 6 1 6 0.34 2.06 1.54 CEDG178 60 2 2 1 2 0.20 0.40 2.00 CEDG204 61 4 4 1 4 0.49 1.95 1.54 CEDG214 57 7 7 1 7 0.11 0.75 2.00 CEDG232 57 4 4 1 4 0.35 1.41 1.77 CEDG253 57 5 5 1 5 0.96 4.82 0.51 CEDG305 57 6 6 1 6 0.52 3.14 2.23 Average 3.62 3.62 1 3.62 0.47 1.68 1.93 Tm (°C), Annealing temperature; TB, Total no. of bands amplified; PB, Polymorphic bands; β, Proportion of polymorphic bands; EMR, Effective multiplex ratio; Hn, Expected heterozygocity; MI, Marker index; Rp, Resolving power Study of Genetic Relationship
For each marker system, the genetic relationship between the genotypes was estimated based on Jaccard’s pair wise similarity coefficient. Genetic relationships and the pooled diversity data using these marker systems uniquely place each genotype into their respective cluster. Differentiation of different Vigna species into separate clusters indicated the suitability of the studied primers in characterization. All the three marker systems showed highly similar dendrograms topologies with only few differences in the positioning of genotypes in the main cluster. Based on their pooled allelic diversity data, the 35 genotypes were grouped into four major clusters (Fig. 1), with most of the genotypes placed in their respective groups. Cluster I comprised of V. unguiculata genotypes V 578 and V 585. Cluster II comprised of V. umbellata accession RBL 1, RBL 35 and RBL 50. The studied urdbean (V. mungo) genotypes IPU 94-1, Barabanki Local, PU 31 and PU 06-20 were grouped together in cluster III. The cluster IV comprised of 25 accessions of V. radiata and one accession of V. trilobata. The AVRDC introduced mungbean lines—Pusa Ratna, Pusa 9072, Pusa 9531 and Pusa Vishal—were grouped together in Cluster IV A and remaining 22 accessions in Cluster IV B. The principal component analysis (PCA) of 35 Vigna genotypes explained 59% of the total variation
by the first three principal components. The two dimensional plot of genetic diversity as revealed by PCA also indicated four broad clusters (Fig. 2). The results of PCA analysis largely correspond to those obtained through cluster analysis. Cluster I included RBL 1, RBL 35 and RBL 50. Cluster II included V 578 and V 585. Cluster III included Barabanki Local, IPU 94-1, PU 06-20 and PU 31. The remaining 25 genotypes of V. radiata and one genotype of V. trilobata were grouped together as a separate cluster. The productivity of mungbean has been low (512 kg/ha) in India. The cultivated mungbean genotypes also have narrow genetic base leading to their susceptibility to different biotic and abiotic stresses7,20. Hence broadening of the genetic base is required but conventional approaches have resulted in limited yield enhancement. Infact better estimate of similarity among the genotypes can be made by use of DNA markers with genome-wide coverage17. The real utility of marker system depends on the level of polymorphism detected and the extent to which an assay can identify multiple polymorphisms. Genetic diversity is considered to be an important factor in all the breeding programmes and estimation of genetic relationship among accessions of different Vigna spp. is essential for selection of appropriate parent for hybridization. In the present study, we used three different marker systems to define genetic
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Fig. 1—Dendrogram obtained by UPGMA analysis of combined data of ISSR, RAPD and SSR markers from 35 genotypes of Vigna spp.
Fig. 2—Principal component analysis (PCA) depicting genetic diversity among 35 genotypes of Vigna spp.
SINGH et al: MOLECULAR DIVERSITY IN VIGNA SPECIES
relationship between Vigna spp. The high level of polymorphism obtained in our study is consistent with previous reports with different marker systems in Vigna species8,20,21. In the present study, three marker systems (ISSR, RAPD and SSR) were compared to characterize the genetic diversity of 35 Vigna accessions. No unique banding pattern was observed in the studied markers for any of the studied genotypes. However all the 35 genotypes could be characterized based on the combined banding pattern obtained from 63 markers. The ISSR markers exhibited high EMR and MI and were quite effective in resolving the polymorphism content in the studied genotypes. RAPD and ISSR marker systems were also found to be equally good in the detection of polymorphism and were efficient in distinguishing the 35 genotypes. Multi locus marker systems (ISSR and RAPD) are expected to produce higher EMR and MI than single locus SSRs22. Higher EMR and MI values indicated markers suitability for better analysis of both interspecific and intraspecific genetic diversity and their use as a potent marker for fine dissection of the intraspecific relationship in Vigna species. V. unguiculata is not crossable with cultivated mungbean using conventional techniques. However, this species can contribute for long pod length and high biomass. V. umbellata (rice bean) accessions are known for higher number of branches, number of clusters/plant, pods/plant, pod length, 100 seed wt and seed yield/plant. This crop can also contribute high biomass and early vigour to cultivated mungbean. However, the mungbean × ricebean F1 exhibits varying level of sterility. In the recent years, attempt has been made to transfer these traits to mungbean. V. mungo (urdbean) exhibits stable resistance against mungbean yellow mosaic virus (MYMV), a trait known to be deficient in mungbean. In addition to this, shattering tolerance from urdbean can also be transferred to mungbean. The indigenous cultivated mungbean were grouped together in the present study. This might be due to the tendency to add desirable and improved characters from few lines repeatedly. V. trilobata is in secondary gene pool for mungbean and can be valuable source for interspecific population improvement. However, successful utilization of genes from this species is yet to be explored for mungbean. The wild species have shown great potential for use in mungbean improvement programmes23 and MYMV resistance from V. umbellata to V. radiata had been successfully transferred earlier24.
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The success of our study in identifying polymorphism was due to the use of a number of randomly selected prescreened highly informative markers. Geographically isolated populations accumulate genetic differences as they adapt to different environment. Characterization and assessment of diversity among Vigna spp. have great significance in designing breeding strategies, both for qualitative and quantitative traits. The use of this/these species will add more variability in cultivated mungbean. In the present study, we were successful in assessing the level of inter and intraspecific diversity and species relationship among different cultivated and wild genotypes of Vigna spp. Differentiation of wild and released varieties into separate clusters not only indicated narrow genetic base of released varieties but also the potential of using wild types for widening the narrow genetic base of indigenous varieties through hybridization. Acknowledgement Authors are thankful to the Head, Division of Genetics, Joint Director Research and Director, Indian Agricultural Research Institute, for providing the necessary facilities. References 1
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