Genetic Resources and Crop Evolution (2005) 52: 285–292
Ó Springer 2005
Assessment of genetic diversity and genetic relationships among 29 populations of Azadirachta indica A. Juss. using RAPD markers R.P. Singh Deshwal1, Rakesh Singh2, Kanika Malik2 and G.J. Randhawa2,* 1
Ch. Charan Singh Haryana Agricultural University, Hisar, Haryana, India; 2National Research Centre on DNA Fingerprinting, National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India; *Author for correspondence (e-mail:
[email protected]; fax: 091-011-5819459, 091-011-5851495)
Received 16 January 2003; accepted in revised form 13 July 2003
Key words: Gene diversity, Genetic markers, Genetic relationship, Medicinal plant, Neem
Abstract Randomly amplified polymorphic DNA (RAPD) analysis was employed to assess genetic divergence among 29 neem accessions collected from two agro-ecological regions of India (11 agro-climatic sub-zones), which cover three states, Punjab, Haryana and Rajasthan. Out of 24, 10-mer random primers used for studying genetic divergence, 14 were polymorphic, generating a total of 73 amplification products with an average of 5.21 products per polymorphic primer and estimated gene diversity of 0.49. Genetic relationships among accessions were evaluated by generating a similarity matrix based on Jaccard’s coefficient, ranging from 0.70 to 0.96. The phenetic dendrogram generated by UPGMA analysis grouped accessions into five clusters. RAPD performed within accessions (individual seedlings collected from the same mother plant) showed no variation indicating homogeneous population within accessions. Primers OPA-18, OPC-08 and OPI-03 were found most informative based on their resolving power. The degree of genetic variation detected among the 29 accessions with RAPD analysis suggests that RAPD can be used for studying genetic diversity in neem. The study also demonstrated that neem germplasm collected from northwestern plains of India shows no eco-geographical isolation based on sub-zones because accessions collected from different sub-regions are grouping together in the genetic tree. Introduction Neem (Azadirachta indica A. Juss.) is a multipurpose tree species that grows naturally in the Indian subcontinent. Recently, neem has gained tremendous significance worldwide due to its therapeutic and bioactive properties (National Research Council 1992; Tiwari 1992; Schmutterer 1995). It has long history of use in India, and its medicinal properties are enshrined in ancient Indian scriptures. An understanding of the extent and organization of genetic diversity of this species could be useful for both its genetic improvement and conservation (Kundu 1999a). Provenance studies have shown high levels of variability in neem with respect to survival, growth, morphological and
physiological characters(Rajawatetal.1994;Kundu and Tigerstedt 1997, 1999; Kundu et al. 1998). Several molecular techniques are available for the assessment of plant genetic diversity. A comparative study of seed morphometric traits and isozymes has been carried out in neem (Kundu 1999a). However, environmental factors, as well as the developmental stage of the plants, influence such traits. DNA-based markers provide useful information regarding genetic diversity and relationships among accessions, as these remain unaffected by environmental factors. Polymerase chain reaction (PCR)-based markers, including random amplified polymorphic DNA (RAPD) (Williams et al. 1990), have been extensively used as genetic markers for the assessment of
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Figure 1. Distribution of neem accessions as per agro-ecological regions and sub-zones.
genetic diversity and relationship measures in various plant species (Barker et al. 1999; Degani et al. 2001; Bekessy et al. 2002). RAPD markers are generated by using short, 10-mer oligonucleotides of arbitrary sequence. These markers are mostly dominant and detect variation in both coding as well as non-coding regions of the genome. RAPD analysis is technically simple and suitable for largescale germplasm characterization and can be performed even in a moderately equipped laboratory (Rafalski and Tingey 1993). The present study was undertaken with an objective of evaluating genetic variation and genetic relationships among the neem accessions collected from two agro-ecological regions of India (11 agroclimatic sub-zones), which includes three states,
Punjab, Haryana and Rajasthan (North-western plains of India) by using RAPD markers.
Materials and methods Plant material Twenty-nine seed samples of open pollinated trees were collected from three states in northern India, namely Punjab, Haryana and Rajasthan, representing two agro-ecological regions (Sehgal et al. 1992) and 12 agroclimatic sub-zones (Ghosh 1991) (Figure 1). Except for sub-zones R4 and R6, at least two mother plants from each sub-zone were taken for the fingerprinting and genetic-diversity studies.
287 Table 1. Details of neem accessions collected from two agro-ecological regions of India (Northwestern plains). Accession
Region
Sub-zones
Place
District
State
N1 N2 N3 N4 N5 N6 N7 N8 N9 N10 N11 N12 N13 N14 N15 N17 N18 N19 N20 N21 N16 N22 N23 N24 N25 N26 N27 N28 N29
2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
R1 R1 R1 R2 R2 R2 R4 P5 P5 H2 H2 H2 R5 R5 R6 P5.1 P5.1 H1 H1 H1 R7 R7 R7 R7 R9 R9 P3 P3 P3
Bhopalgarh Bikaner1 Bikaner2 Ganganagar Suratgarh Nagor Pindwasa Malot Bhatinda Hisar1 Hisar2 Bawal Kotputli Amer Bahror Abohar1 Abohar2 Pehwa1 Pehwa2 Kaithal Gogunda Chittorgarh1 Begu Chittorgarh2 Hindoli Bundi Jagroan Ludhiana Khanna
Bhopalgarh Bikaner Bikaner Ganganagar Ganganagar Nagor Sirohi Firojpur Bhatinda Hisar Hisar Rewari Jaipur Jaipur Alwar Firojpur Firojpur Rohtak Rohtak Kaithal Udaipur Chittorgarh Chittorgarh Chittorgarh Bundi Bundi Ludhiana Ludhiana Ludhiana
Rajasthan Rajasthan Rajasthan Rajasthan Rajasthan Rajasthan Rajasthan Punjab Punjab Haryana Haryana Haryana Rajasthan Rajasthan Rajasthan Punjab Punjab Haryana Haryana Haryana Rajasthan Rajasthan Rajasthan Rajasthan Rajasthan Rajasthan Punjab Punjab Punjab
P5 sub-zone has been divided into two (P5 and P5.1) based on aridity and rainfall. Mother trees were selected randomly for sampling but were separated by a minimum distance of 500 m to avoid sampling of genetically identical individuals. For each accession (mother tree) 100 seeds were collected. A detailed description of the neem accessions used in the present study is given in Table 1. Ten seeds collected from each mother plant were randomly selected for germination and growth in the greenhouse of National Bureau of Plant Genetic Resources (NBPGR), New Delhi.
DNA was quantified by Hoefer fluorometer DyNA Quant 200 (Hoefer Pharmacia Biotech. Inc., San Francisco CA, USA) using Hoechst 33258 as the dye and calf thymus DNA as the standard (Brunk et al. 1979) and samples were diluted to a final concentration of 5 ng L1. Intra-accession and inter-accession variation For the intra-accession study, two accessions were analysed, N7 and N25, and individual plant DNA was used for the RAPD analysis. For the interaccession study, a sample of DNA from 10 individual plants was pooled for each accession.
DNA extraction RAPD analysis To study the variation within as well as among accessions, total genomic DNA was isolated from individual plant leaves (8-week old seedlings) following the method of Dellaporta et al. (1983).
A total of 24 random decamer primers (Operon Technologies Inc., Alameda, California, USA) was used for RAPD analysis. DNA amplification
288 Table 2. Polymorphic primers with their corresponding gene diversity and resolving power.
Primer name
Sequence (50 —————30 )
Total no. of bands
No. of polymorphic bands
Gene diversity
Resolving power (Rp)
OPA-03 OPA-10 OPA-17 OPA-18 OPA-19 OPB-5 OPC-6 OPC-8 OPC-13 OPC-20 OPG-13 OPG-18 OPI-3 OPI-10
AGTCAGCCAC GTGATCGCAG GACCGCTTGT AGGTGACCGT CAAACGTCGG TGCGCCCTTC GAACGGACTC TGGACCGGTG AAGCCTCGTC ACTTCGCCAC CTCTCCGCCA GGCTCATGTG CAGAAGCCCA ACAACGCGAG
7 5 6 5 7 6 3 7 4 4 5 6 3 5
6 3 3 4 6 6 1 6 2 2 3 4 1 4
0.45 0.39 0.28 0.81 0.88 0.33 0.33 0.78 0.20 0.23 0.24 0.47 0.86 0.74
1.45 1.03 0.21 2.28 1.86 0.68 0.07 2.62 0.21 0.96 0.62 0.96 2.00 1.55
reactions were performed in 25 L reaction volumes consisting of 2.0 mM MgCl2, 200 M of each dATP, dGTP, dTTP, and dCTP, 1 U of Taq DNA Polymerase (Perkin Elmer, Norwalk, CT, USA), 0.2 M primer, and 25 ng of genomic DNA. Amplification reactions were carried out on Perkin-Elmer DNA thermal cycler 9600 with the following thermal profile: one cycle of 94 C for 5 min (initial denaturation) followed by 40 cycles of 1 min at 94 C (denaturation), 1 min at 37 C (primer annealing) and 2 min at 72 C (primer elongation), and finally, one cycle of 7 min at 72 C (final extension). Amplified PCR products were separated on 2% (w/v) agarose gel in 1 Trisacetate EDTA (TAE) buffer at 80 V for 4 h, stained with ethidium bromide and photographed under ultraviolet light using polaroid film #667. A 100bp ladder (MBI Fermentas, Hanover, USA) was used as a molecular size marker. The reproducibility of the amplification products was checked twice for each polymorphic primer. Data analysis RAPD bands were scored for presence (1) and absence (0) across all neem accessions for each primer. The pair-wise genetic similarities among all pairs of samples were estimated with Jaccard’s coefficient (Jaccard 1908). The statistical analysis was carried using NTSYS Software (version 1.70) (Rohlf 1993). A dendrogram was constructed by employing UPGMA (Unweighted pair grouping method of averaging) (Sneath and Sokal 1973), in
order to group genotypes into discrete clusters. In addition, principal coordinate analysis was also performed. Gene diversity was calculated as 1 Pi2 (Anderson et al. 1993). Resolving power (Rp) for each primer was calculated following Prevost and Wilkinson’s (1999) method for selecting primers that can distinguish a maximal number of accessions. Resolving power (Rp) of a primer is Rp ¼ Ib, where Ib (band informativeness) is calculated as 1 |2 (0.5 p)|, p being the proportion of the 29 accessions containing the bands.
Results Fingerprint profile Twenty-nine accessions of neem were analysed with 24 random primers, of which 14 (58.33%) were polymorphic (Table 2). Polymorphic primers generated a total of 73 fragments with an average of 5.21 products per polymorphic primer. The number of products amplified by the polymorphic primers varied from 3 to 7, the most were detected with the primers OPA-03, OPA-19, and OPC-08 (Figure 2). Gene diversity were calculated for each primer, which varied from 0.88 to 0.20 (Table 2), with a mean diversity of 0.49. Based on resolving power, the primers OPA-18, OPC-08 and OPI-03 were found most informative (Table 2). The variation study within accessions (collected from the same mother plant) with the most polymorphic primers OPA-03, OPA-19, OPC-08,
289
Figure 2. RAPD profile of 29 accessions of neem using primer OPC-08. Lane1 – Molecular weight marker Gene RulerTM 100 bp DNA ladder plus (MBI), Lanes 2–30 – accessions (N1 to N29) of neem.
Figure 3. RAPD profiles of four individual seedlings of accession N25 collected from Bundi (Rajasthan) with primer OPG-13. Lane 1 – Gene RulerTM 100 bp DNA ladder plus (MBI), Lanes 2–5 – RAPD profiles of individual seedlings collected from the same mother plant.
OPG-13 and OPI-10 showed no polymorphic bands that is, no variation (Figure 3).
coefficient of 0.96. The similarity matrix representing Jaccard’s coefficients was used to cluster the data following the UPGMA algorithm (NTSYSPC, version 1.70). The resultant phenogram (Figure 4) grouped 25 of the 29 accessions into five clusters. Clusters 1 and 5 are each represented by two samples collected from different sub-zones of Rajasthan. In cluster 2, five samples were grouped together, except for two samples from the H2 sub-zone (Hissar2 and Bawal), all are from different sub-zones. Cluster 3 represents the major cluster, in which 12 samples from seven different agro-climatic sub-zones were grouped together, showing more than 88% similarity. The accession collected from Hindoli (R9 sub-region of Rajasthan) is distinct from all other samples. The UPGMA analysis does not show clustering based on the regions or agro-climatic sub-zones, though high variability exists among the samples. In the principal co-ordinate analysis all the analysed samples were separated, which is coherent with the phenogram generated by UPGMA cluster analysis. The first three most-informative principal coordinates explained 88.96 percent of total variation.
Genetic similarity matrix and cluster analysis RAPD data were used to make pair-wise comparisons of the accessions based on shared and unique amplification products to generate a similarity matrix with NTSYS-PC (Version 1.70). Similarity values for all the 29 accessions ranged from 0.70 to 0.96. Of twenty-nine samples analysed, two accessions (N8 and N21) collected from Malot (Punjab) and Kaithal (Haryana), respectively, displayed the greatest genetic similarity, with a similarity
Discussion Ecological and geographical differentiation are important factors, influencing strategies for breeding and sampling tree crops. Keeping this in mind, two agro-ecological regions (including two agroclimatic sub-zones of Punjab, two sub-zones of Haryana and seven sub-zones of Rajasthan) representing the northwestern plain of India
290
Figure 4. Dendrogram of 29 accessions of neem collected from the northwestern plain of India.
were selected for the present study. Regions and agro-climatic sub-zones have been classified according to National Bureau of Soil Survey and Land Use Planing (NBSS&LUP) and National
Agriculture Research Project (NARP) classification, respectively (Sehgal et al. 1992; Ghosh 1991). The values of similarity based on Jaccard’s coefficient for all 29 accessions ranged from 0.70 to
291 0.96, reflecting broad level of genetic variability. The similar range has been reported by Singh et al. (1999) based on their study using amplified fragment length polymorphism (AFLP). Allogamous woody plants generally display considerable variability (Hamrick 1990), which is true in the present study. But our results on within accession (Figure 3) shows that even the most polymorphic primer could not distinguish different individuals of same accession, giving an indication that neem reproduction may be autogamous. The autogamy in neem has also been reported by Gupta et al. (1996) and Jindal and Vir (1992). Based on resolving power, no single primer was able to distinguish among all 29 accessions, but OPA-18, OPC-08 and OPI-03 were found more informative. Cluster analysis has clearly indicated that there is no eco-geographical isolation between the samples collected from the two agro-ecological regions. The reason for the grouping of samples to one cluster collected from different sub-zones may be due to human intervention, which makes partitioning and distribution of variability complex. This assumption has been further supported by the Ranade et al. (2002), that neem has distributed throughout India from only a few groups of founder population. Common methods of estimating gene flow and mating system are dependent on the ability to detect heterozygotes (Clegg 1980). Kundu (1999b) has used isozyme markers (codominant) system for the study of mating behavior of neem and showed that outcrossing rate is very high in neem. Similarly, Singh et al. (2002) have reported high level of variation in neem at intra population level as revealed by AFLP and selectively amplified microsatellite polymorphic loci (SAMPL) analysis. Ranade et al. (2002) have used single primer amplification reaction (SPAR) in conjugation with simple sequence repeats (SSR) and reported less variability in inter-simple sequence repeats (ISSR) and mini satellite region at population level, which is in contrary to the earlier studies. There is a need to estimate gene flow patterns and mating systems in neem populations, which are important determinants of the genetic structure of tree populations. Therefore, a comprehensive marker study is required, so that exact pattern of gene flow and mating behavior of neem can be predicted. Which can assist the breeders to design effective breeding programme.
Acknowledgements The authors thank Dr B.S. Dhillon (Director, NBPGR) and Dr J.L. Karihaloo (Project Director, NRC on DNA Fingerprinting) for extending facilities and support for the work.
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