GENETIC DIVERSITY OF OKRA (ABELMOSCHUS ESCULENTUS L.) GENOTYPES FROM DIFFERENT AGRO- ECOLOGICAL REGIONS REVEALED BY AMPLIFIED FRAGMENT LENGTH POLYMORPHISM ANALYSIS

This study was carried out to assess the genetic di versity in 48 genotypes and accessions using eight Amplified Fragment Length Polymorphism (AFLP) prime r-pairs. The eight selected AFLP primer-pairs generated a total of 150 polymorphic loci. Using th e generated AFLP data, the Un-Weighted Pair Group Method with Arithmetic Average (UPGMA) ordered the g notypes into six groups based on Dice similarity coefficient. The range in taxonomic distance was fr om 0.23 to 1.0. Each cluster was found to have genotypes and accessions from different regions and climate and sometimes different continents. The si z range of the loci ranged from 87-662 bp. Great vari ation between the genotypes and accessions in the different cluster could be of high value as the gen etically diverse okra genotypes represent a potenti ally valuable source for improved pathogen and pest resi stance.


INTRODUCTION
Okra is a member of the malvaceae family, which includes fiber crops such as cotton (Gossypium spp) and kenaf (Hibiscus cannabianus). The present accepted binomial is Abelmoschus esculentus (L.) Moench (Siemonsa, 1982), formerly Hibiscus esculentus L. (Borssum Waalkes, 1966;Bates, 1968). The genus Abelmoschus comprises nine species (IBPGR, 1990). It is a traditional vegetable crop in many tropical, subtropical and Mediterranean countries. The origin of okra remains unclear but centers of genetic diversity include West Africa, India and Southeast Asia (Charrier, 1984;Hamon and Van Sloten, 1989).
Van Borssum-Waalkes distinguished only six species: three cultivated (A. moschantus, A. manihot and A. esculentus) and three wild (A. ficuleus, A. crinitus and A. angulosus). Kundu and Biswas (1973;Terell and Winters, 1974) distinguished the genus Abelmoschus from Hibiscus. Okra is increasing in popularity and is now commonly available as a boiled or fried vegetable dish at restaurants salad bars and cafeterias. Fresh tender fruit provide dietary fiber, protein and vitamin C in human nutrition (Candlish et al., 1987). Okra seeds have also gained much interest as a new oil and protein source (Düzyaman, 1997).
Without a broad base of heterogeneous plant material, it is impossible for plant breeders to produce cultivars that meet the changing needs regarding adaptation to growing conditions, resistance to biotic and a biotic stresses product yield or specific quality requirements (Friedt et al., 2007). Therefore, the most efficient way to farther improve the performance of crop varieties is to access to large diverse pool of genetic diversity.
In recent years molecular markers and especially DNA-based markers, have been extensively used in Science Publications AJAS many areas such as gene mapping and tagging (Kliebenstein et al., 2001) characterization of sex, (Flachowsky et al., 2001), analysis of genetic diversity (Erschadi et al., 2000), or genetic relatedness (Mace et al., 1999). DNA based methodologies are now the method of choice to differentiate closely related organisms (Widen et al., 1994). Rawashdeh (1999) reported significant differences between 19 local landraces of Jordan using RAPD. To overcome the limitation of reproducibility associated with RAPD, AFLP technology (Vos et al., 1995) was developed. A method that has become widely applied in plant population genetics.
Knowledge of genetic diversity of a species has an important impact on the improvement of crop productivity as well as the conservation of genetic resources. In recent years more attention has been given to the genetic analysis of diverse genotype sets, which are particularly attractive for association analysis of qualitative traits such as disease resistance or special quality characteristics (Hasan et al., 2006). To our knowledge, scarcely studies have been focused on studying the genetic diversity at DNA level of okra benefiting from the advantages of AFLP. Therefore this research aims to estimate the genetic relationship between 48 okra genotypes from different agro-ecological regions using the AFLP marker.

MATERIALS AND METHODS
A total of 48 seed samples of okra genotypes and accessions were obtained from National Center for Agricultural Research and Extension (NCARE) Amman-Jordan and The World Vegetables Center/Taiwan, together with a commercial check cultivar (Fairooz) ( Table 1). Okra seeds were grown in the greenhouse (Plant Breeding Department, Giessen, Germany). In order to take into account possible genetic variability within each accession, total genomic DNA was extracted from bulked young leaves (100-200 mg per accession) of ten 4-5-week-old plants following the CTAB procedure according to Doyle and Doyle (1990). After RNAse treatment, DNA content was fluorometrically quantified (DynaQuant 200 Hoefer Scientific Instruments) and diluted to 25 ng µ −1 working solution. AFLP analysis was performed according to Vos et al. (1995) by using the Invitrogen AFLP ® Core Reagent Kit following the manufacturer's instructions. Here, 125 ng of genomic DNA (i.e., 5 µL of working solution) were digested using EcoRI and MseI restriction enzymes and generated fragments were ligated with double-stranded site-specific adapters using T4 DNA ligase. Ligation was followed by two pre-amplifications (+0, +1) prior to the final amplification phase performed by using primer combinations having three selective nucleotides.

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The selective amplification mixture (total volume of 25 µL) consisted of 7.5-12.5 ng fluorescent dye-labelled EcoRI primer, 30 ng MseI primer, 0.2 mM of each dNTPs, 2 µL PCR buffer, 0.5 U Taq-polymerase (Qiagen, Germany) and 5 µL of pre-amplified PCRproduct in deionised distilled water. Selective ampliWcation products were separated on 8% denaturing polyacrylamide gels using a Li-Cor 4200 DNA Analyzer. Fragments size was estimated incomparison to a 50-750 bp labelled DNA-ladder Scoring and analyses of AFLP data AFLP fragments were detected using the RFLPScan 2.1 software package (Scananalytics, Fairfax, USA). Clear and unambiguous fragments were scored as present (1) or absence (0) to generate a binary data matrix. The number of polymorphic fragments was determined for each primer pair used. Only polymorphic fragments were used for further data analysis. Pairwise relatedness based on genetic similarity (Dice, 1945) was estimated between all okra accessions using the SIMQUAL module of NTSYS pc software version 2.20e (Rohlf, 1993). UPGMA (unweighted pair-grouped method using arithmetic averages) cluster analysis was performed following GenDist and NEIGHBOR programs available in the software package PHYLIP 3.6 (Felsenstein, 1985).

AFLP Data Analysis
In our study, eight AFLP marker combinations were used to profile the 48 okra (Abelmoschus esculentus L.) genotypes including the control cultivar Fairooz (Fig. 1). Table 2 a total of 150 polymorphic loci were generated, ranging in size from 6 to33 bp. The number of amplified loci per primer varied from 6 loci (MseI_GAC and EcoRI_ATC) to 33 loci (MseI _CTC and EcoRI_ACA

Cluster and Principal Coordinate Analyses
Dice similarity coefficient (Dice, 1945) which is a matching coefficient for binary data generated AFLP analysis, was used to cluster the 48 okra (Abelomschus esculentus L.) genotypes together with the control cultivar Fairooz with the Unweighted Pair Group Method with Arithmetic Average (UPGMA). The 48 genotypes felt into 6 groups (Fig. 2). The similarity level between genotypes and accessions in cluster I ranged from 0.56 to 0.83. The highest genetic similarity percentage (0.83) was observed between (Sade) and (TOT 7963/Guatemala), while the lowest level (0.56) was found to be between (Bati Trakya I/Turkey) and the rest of the genotypes and accessions in the same cluster.  While in cluster II, the similarity level between the genotypes and accessions ranged from (0.44) to (0.62). The higher genetic similarity percentage was found between (Sultani May/Turkey) and (Kabakli/Turkey) while the lowest similarity coefficient (0.44) was between (JO 12) and (JO 49). Cluster III, which consists of only three genotypes, the highest similarity coefficient (0.45) was observed between (Egypt I) and (TOT 7102/Philippines). Cluster IV, the similarity coefficient ranged between 0.4 to 0.42, the highest was found between (UGA red) and (JO 84), while the lowest similarity coefficient was found between (TOT7346/Vietnam) and the rest of the cluster IV. Cluster V indicated the highest similarity coefficient (0.44) to be between (Egypt II) and (TOT 6214/Thailand), while the lowest coefficient was found to be (0.2) between (JO 169) and the rest of the clusters genotypes and acessions.

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The last cluster (Cluster VI) has been found to consist of only six landraces including the commercial cultivar Fairooz, The highest similarity (0.30) between (Bati Trakya II/Turkey) and (TOT 7345/Vietnam), while the lowest (0.14) was found between (Balikesir T1/Turkey) and the rest five landraces in the same cluster.

DISCUSSION
Forty eight genotypes and accessions of okra has been collected from different regions with the aim to measure genetic distinctiveness using AFLP markers. The result of the study demonstrated the suitability of AFLP data for the analysis of genetic diversity in Abelmoschus esculentus L. genotypes and accessions. Unlike genetic diversity, diversity based on phenotypic and morphological characters, usually varies with environments and evaluation of traits requires growing the plants to full maturity prior to identification, but now the rapid development of biotechnology allows easy analysis of large number of loci distributed throughout the genome of the plants (Chakravarthi and Naravaneni, 2006). Information on the genetic diversity in okra (Abemoschus esculentus L.) collections can give breeders and geneticists important information on the allelic diversity present in genebank materials and may help to identify genetically diverse pools for use in cross combinations to improve important agronomic traits or to better exploit heterosis (Diers and Osborn, 1994).
AFLP is a powerful fingerprinting technique, which detects polymorphism on the level of restriction enzymes sites. It is based on PCR amplification of restriction enzymes and oligonucleotides adaptors of few nucleotide bases. This method generates a large number of restriction fragment bands facilitating the detection of polymorphism. Therefore, AFLP markers combine the advantages of RFLP's and PCR-based markers. This technology has been adopted for fingerprinting and mapping of different plants (Hussein et al., 2005) as well as some pathogens (Meza-Moller et al., 2011). Omahinmin and Osawaru (2005) reported that high degree of wide morphological variation exist among accession of okra which requires further evidence using molecular markers to clarify. Molecular markers have been successfully used in the genus Abelmoschus to select parents for hybrid production, for intraspecific or inter-specific classification and for the analysis of variation. Akash et al. (2013) indicated a lack of significant correlation between phenotypic and actual AFLP genetic profile inferred by UPGMA clustering in 21 landraces of Jordanian okra (Abelmoschus esculentus L).
In conservation programs for plant genetic resources, the availability of characterization data and information on available genetic diversity can help germplasm users to identify accessions of interest and also provide plant breeders with initial data regarding materials for use in crop improvement programs (Cruz et al., 2007). The Asian accessions was found to be more diverse than the accessions from African or USA, this could be mainly due to that the accession have be collected from different geographical regions from East to South of the continent, this result agress with Aladele et al. (2008) who indicated more diversity among the Asian genotypes using RAPD markers, this variation could be due to that the genotypes were originally collected from six different countries in the region. From this study, the Jordanian accessions were found to be diverse as they have been located in different clusters, the results agree with Kaur et al., (2013) who found great diversity between okra accession using RAPD. Many studies using Cluster analysis showed that similarity between the okra lines was from 100 to 15.41%. Gulsen et al. (2007) found the relatedness value based on SRAP markers ranging from 100 to 86% among 23 okra genotypes. Aladele et al. (2008) observed relatively more molecular diversity in the Asian genotypes as compared to those of African origin. Genetic distance values ranging from 0.00 to 0.66 were observed among okra accessions (Saifullah et al., 2010). The present investigation has provided a useful insight into the extent of genetic diversity in the okra germplasm and can be exploited in future breeding programs as well as for the development of mapping populations/linkage map.
The result of AFLP indicate a genetic diversity between the different accessions from different regions (cluster I and VI), this could be of high interest for breeders to start a successful breeding programs.

ACKNOWLEDGMENT
The researcher wishes to thank Prof. Dr. Dr. h.c. Wolfgang Friedt, Department of Plant Breeding (Justus-Liebig-University Giessen/Germany) for making it possible for the research to be made in his lab, Dr. Maen Hasan for the great assistance with the AFLP analysis, Dr Düzyaman for providing the Turkish genotypes, World vegetable Center and the National Center for Agricultural Research and Extension. This work was partially funded by the Deutsche For Schungsgemeinschaft (DFG).