Assessment of genetic diversity and genetic relationships among twenty varieties of Brasicca juncea L. using RAPD markers.
Materials and Method
The information about twenty genotypes of Brassica juncea used in present study, are given in Table 1. The DNA was isolated from ten day's old etiolated leaves by CTAB method (Doyle and Doyle, 1990). The concentration of DNA was determined by using UV visible spectrophotometer (Biomate, Thermo Spectronic, Cambridge, UK).
The RAPD was carried out with random decamer primers synthesized from Life Tech, India. A total volume of 25[micro]l containing 2.5 [micro]l reaction buffer (10X), 2.0 [micro]l dNTPs mix (200[micro]M each), 1 [micro]l (30 ng x[[micro]l.sup.-1]) decamer primer, 1 [micro]l (50 ng x [micro][l.sup.-1]) genomic DNA and 0.5 [micro]l (3U x [micro][l.sup.-1]) Taq DNA polymerase were used for the amplification of template DNA. PCR reactions were performed with thermal cycler (Biometra, Germany). PCR programme had an initial denaturation at 95[degrees]C for 5 min, denaturing at 94[degrees]C for 1 min, annealing at 40[degrees]C for 30 sec and polymerization at 72[degrees]C for 2 min and final extension 72[degrees]C for 5 min. After amplification, the PCR product was resolved on 1.5% agarose gel in 1X TAE buffer. The gel was visualized under UV using gel documentation system (Alfa Innotech corporation, USA)
DNA fingerprints were scored for the presence (1) or absence (0) of bands of various molecular weight sizes in the form of binary matrix. Data was analyzed to obtain Jaccard's coefficients among the isolates by using NTSYS-pc (version 2.11W; Exeter Biological Software, Setauket, NY, Rohlf, 1993). The SIMQUAL program was used to calculate the Jaccard's coefficients. A common estimator of genetic identity and was calculated as follows:
Jaccard's coefficient = [N.sub.AB]/([N.sub.AB] + [N.sub.A] + [N.sub.B])
Where, [N.sub.AB] is the number of bands shared by samples, [N.sub.A] represents amplified fragments in sample A, and NB represents fragments in sample B. Similarity matrices based on these indices were calculated and it was utilized to construct the UPGMA (unweighted pair- group method with arithmetic average) dendrograms. Principal comonent analysis was performed in order to highlight the resolving power of the ordination. To determine robustness of the dendrogram, the data were bootstrapped with 2000 replications along with Jaccard's coefficient by the computer programme WINBOOT (Yap and Nelson 1996).
RAPD analysis is widely exploited to examine genetic polymorphism between genotypes at molecular level in several crop species. The sixteen decamer primers of arbitrary sequences generated a total of 112 RAPD loci with twenty genotypes of Brassica juncea used in present investigation. Out of these 112 loci, 110 to be found polymorphic and two were monomorphic. The primers P-72, P-96 and P-114 showed maximum number (10) of polymorphic bands. Insights of these results, the average of 6.88 polymorphic and 0.125 monomorphic bands were obtained with each primer. Almost all primers depicted 100% polymorphism excluding primer P-104 (75%) and P-77 (87.5%), with an average of 97.7% across all the genotypes of Brassica juncea. The amplified amplicons were ranged from 0.1kb to 5.1 kb with primer P-77 and P78, respectively. The above facts were used to investigate the molecular diversity among all 20 varieties.
The RAPD bands were scored for presence (1) or absence (0) among the genotypes and used for UPGMA analysis. A dendrogram based on UPGMA analysis with RAPD data is shown in (Fig. 2). Jaccard's similarity coefficient ranged from 0.213 to 0.83. The genotype PAB 2001 showed maximum resemblance (83%) with genotype PAB 9334 while genotype RLM 198 manifested least similarity (21.3%) with genotype Kranti. The 20 genotypes clustered into three major clusters. Cluster I comprises eight genotypes including PAB9334, PAB2001, PAB9511, ABR14, PHR1, PAB9534, PAB2002 and PHR2 which showed somewhat tolerance to Alternaria blight disease. In Principle Component Anlysis, cluster I exhibited all above eight genotypes. Cluster II consisted of genotypes Rohini, Basanti, Kanti and Divya which showed susceptibility to Alternaria blight except genotype ABR15 but in PCA the genotypes Rohni and ABR15 were not included in cluster II. Cluster III comprised of genotypes PAB2020, Varuna, Kranti and Pusa bold in dendrogram however in two 2D view included Varuna, Kranti, Pusa bold, Krishna and RLM198. But susceptible genotypes Pusa Jai Kisan, RLM198 and Krishna were not included in any cluster of dendrogram. Cluster I was further divided into two sub-clusters and sub-cluster I consisted of genotypes PAB9334, PAB2001 and PAB9511, while sub-cluster II consisted of genotypes ABR14, PHR1, PAB9534, PAB2002 and PHR2 respectively. The result of Principle Component Analysis (PCA) was comparable to the cluster analysis upto some extent (Fig. 3). The first three most informative PC component explained 37.46% of the total variation.
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In earlier investigation, RAPD considered a cheap and valuable tool to evaluate the genetic relationship among different crop species. The success of present study in identifying polymorphism is due to the use of a number of randomly selected prescreened primers. Some researchers have considered RAPD markers to represent segments of DNA with non-coding regions and to be selectively neutral (Bachmann, 1997; Landergott et al., 2001). While other studies have shown that RAPD markers are distributed throughout the genome and may be associated with functionally important loci (Penner, 1996). In present investigation, 16 RAPD primers produced 112 polymorphic bands, unambiguously discriminated 20 genotypes into three major clusters. Similarly, genetic diversity among 45 Indian mustard (Brassica juncea L.) genotypes comprising 37 germplasm collections, five advance breeding lines and three improved cultivars was investigated at the DNA level using the random amplified polymorphic DNA (RAPD) technique (Khan et al., 2008). The putatively similar bands originated for RAPDs in different individuals are not necessarily homologous, although they may share the same size in base pairs (Souframanien and Gopalakrishna, 2004). The maximum similarity was recorded 83% between genotypes PAB 2001 and PAB 9334. Similar results were obtained by Wang et al (2002) which reported maximum of 88% similarities among Brassica rapa accessions. Ali et al. (2007) also observed 21 to 59% genetic variability among Brassica juncea. The number of polymorphism detected among genotypes influence the standard errors of genetic diversity estimates (Souframanien and Gopalakrishna, 2004). The estimated cophenetic correlation (r) was 0.94 indicating very good fit of the cluster analysis. The genotypes PAB9511, and PHR-2 exhibited tolerant character as compared to Varuna used as sussceptible check. Varuna showed maximum percentage (51.50%) of Alternaria blight severity observed on leaves at 100 DAS while PAB 9511 and PHR-2 showed 46.93%. and 46.23% disease severity, respectively. The similar results were observed on pods in which Varuna depicted 32.75% of Alternaria blight whereas 27.18% and 28.20% of Alternaria blight depicted by PAB9511 and PHR-2 (AICRP annual report, 2005-06). Our results indicated the presence of wide genetic variability among elite genotypes of B. juncea. RAPD markers were found a useful tool in the assessment of genetic diversity in B. juncea.
In present investigation of genetic diversity among different genotypes of Indian mustard (Brassica juncea L.) depicted significant range of genetic relationship that would help to select the more disease tolerant variety for Alternaria blight and improving the productivity of oil seed crop.
The authors are thankful to Department of Biotechnology, Government of India, for providing financial support for conducting the investigation and fellowship to first author.
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Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture & Technology, Pantnagar-263145, Uttarakhand, India. E-mail: firstname.lastname@example.org
Department of Biosciences, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi-110025, India. E-mail: email@example.com
Department of Genetics and plant Breeding, G. B. Pant University of Agriculture & Technology, Pantnagar-263145, Uttarakhand, India E-mail: firstname.lastname@example.org
Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture & Technology, Pantnagar-263145, Uttarakhand, India. E-mail: email@example.com
Table 1: List of genotypes of B. juncea used for the study of genetic variability. S.No. Variety name Remark 1 PAB 9334 Tolerant 2 Rohni Susceptible 3 PAB 2001 Tolerant 4 PAB 9511 Tolerant 5 ABR 14 Tolerant 6 PHR 1 Tolerant 7 PHR 2 Tolerant 8 PAB 9534 Tolerant 9 PAB 2002 Tolerant 10 Basanti Susceptible 11 Varuna Susceptible 12 Kranti Susceptible 13 Kanti Susceptible 14 Pusa Bold Susceptible 15 Dibya Susceptible 16 ABR 15 Tolerant 17 Krishna Susceptible 18 RLM 198 Susceptible 19 PAB 2020 Susceptible 20 Pusa Jai Kisan Susceptible Table 2: Detail of RAPD primers used for the molecular characterization of Brassica juncea. S. Primer Primer Amplified Total Mono Poly % No. code Sequence product bands bands bands Poly. (5' to 3') Range(kb) 1 P-72 AGTCAGCCAG 1000 - 4200 10 -- 10 100.0 2 P-75 GAAACGGGTG 1000 - 4200 6 -- 6 100.0 3 P-76 GTGACGTAGG 1300 - 5100 5 -- 5 100.0 4 P-77 GGGTAACGCC 0100 - 0325 8 1 7 87.50 5 P-78 GTGATCGCAG 1300 - 5100 8 -- 8 100.0 6 P-89 AGTCAGCCAC 0700 - 1900 4 -- 4 100.0 7 P-94 GTCGCCGTCA 1500 - 4200 2 -- 2 100.0 8 P-95 TGAGCGGACA 0300 - 2100 9 -- 9 100.0 9 P-96 TTGGCACGGG 0280 - 2300 10 -- 10 100.0 10 P-99 AGCGCCATTG 0300 - 2000 7 -- 7 100.0 11 P-103 AGGGCGTAAG 3800 - 1100 8 -- 8 100.0 12 P-104 GAGAGCCAAC 3000 - 4200 4 1 3 75.00 13 P-109 ACGCACAACC 1300 - 2000 4 -- 4 100.0 14 P-111 CTCTCCGCCA 0400 - 1700 8 -- 8 100.0 15 P-114 GACGCCACAC 0200 - 1900 10 -- 10 100.0 16 P-118 TCAGAGCGCC 0100 - 0400 9 -- 9 100.0 TOTAL -- 112 2.0 110 -- AVERAGE -- 7.0 0.125 6.88 97.66
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|Title Annotation:||random amplified polymorphic deoxyribonucleic acid|
|Author:||Ahmad, Javed; Arif, Mohd.; Bhajan, Ram; Taj, Gohar|
|Publication:||International Journal of Biotechnology & Biochemistry|
|Date:||Jan 1, 2009|
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