Introduction
Rice (Oryza sativa L.) is the main food source for more than two fifths (2.4 billion) of the world’s population (Halder et al., 2016). Asia is the leading continent for the production and consumption of rice in the world. Rice occupies 11% of the world’s crop field annually, and it ranks next to wheat (Chakravarthi and Naravaneni, 2006; Won et al., 2017). The conservation and characterization of high yielding varieties (HYV) rice germplasm is an important issue for breeding programme in Bangladesh. An effective management and exploitation of rice germplasm prerequisites an accurate characterization and classification. However, with an increasing global population, the demand for rice will continue to rise, which raises challenges for the breeding of high yielding rice cultivars (Zhang et al., 2013). On the other hand, several researchers reported that the most reliable method based on DNA sequence by molecular markers (Kresovich and McFerson, 1992; Mani et al., 2010).
Perspectives of crop improvement mostly rely on the genetic diversity of rice genotypes and the implementation of modern biotechnological findings. A rich diversity of rice accessions exists in Bangladesh, as it is the centre of origin of indica type rice. However, the diversity of Bangladeshi rice accessions has not been studied comprehensively at the molecular level. Whereas, many of these rice accessions are on the edge of extinction. Hence, it is essential to conduct proper conservation and characterization of existing rice varieties.
Some of the local varieties are not properly represented to conduct genetic diversity. A number of molecular markers studied Rice characteristics. Random amplified polymorphic DNA (RAPD) is a prevalent and powerful typing method based on marker technique to analyse genetic diversity at the population level and among different genotypes (Saker et al., 2018). The RAPD technique presents a higher level of polymorphism, very informative and speedy process. Enzymatic amplification of target DNA studied by PCR using arbitrary primers with the RAPD technique, also intra and inter distances of genetic markers is determined more accurately by the RAPD with a very small amount of sampling DNA (Weising et al., 1995; Islam et al., 2015).
The RAPD technique has been used extensively in the analyses of rice to estimate genetic identification and classification of accessions (Davierwala et al., 1990; Fukuoka et al., 1992; Saker et al., 2018), genetic potential and diversity (Cao and Oard, 1997), fingerprinting and duplication of accessions (Virk et al., 1995; Virk et al., 1996), and particularly important for variety evaluation and conservation existing diverse gene pool, hybridization, selection and breeding purposes (Rabbani et al., 2008). The molecular markers are vital to study the genomic variability and genetic relatedness among rice genotypes of Bangladesh (Alam et al., 2016).
Lack of information on the genetic diversity of HYV rice in Bangladesh requires using the RAPD technique. The knowledge on genetic polymorphism is essential for the conservation of existing rice germplasm and further promotion of the breeding program. Therefore, the present study is designed to assess the extent of the performance of HYV of Bangladeshi rice accessions using RAPD primers to compare genetic polymorphism between genotypes and to conduct complex analyses for rice breeding purposes.
Materials and Methods
The present study was conducted during August 2016 to May 2017 at the Molecular Genetics and Genetic Engineering Laboratory, Patuakhali Science and Technology University, Patuakhali, Bangladesh. Plant materials of fifteen HYV of rice were sampled from the Bangladesh Rice Research Institute (BRRI) to conduct this study (rice genotypes presented in Table 1). Molecular characterization of HYV of rice was done using RAPD markers employed to conduct a genetic diversity analysis on the sampled fifteen HYV of rice.
Collection of leaf sample
Fresh and healthy leaf samples were taken from 25 days old seedling of each rice variety to carry out analyses of DNA through the RAPD technique. At the beginning, the selected leaf samples were cut with sterilised scissors and thoroughly washed in distilled water and then in ethanol and dried on sterile paper to eliminate spore of microorganisms and any other sources of alien DNA. The prepared leaf samples were kept in a freezer at -20℃.
DNA extraction and its quantification on agarose gel
DNA extraction was conducted from the prepared leaf samples of each variety pursuing the procedure of the cetyl trimethylammonium bromide (CTAB) method. Eight µL 2X loading dye was thoroughly mixed with 2 µL dilute DNA for each sample. Then these DNA samples (10 µL) were loaded in the 1% agarose gel. After electrophoresis, the gel was stained with ethidium bromide for at least 20 min and the bands were visualized under UV light using Gel Doc system (Bio-Rad, Hercules, USA).
Primer test
Initially, a set of 30 primers of random sequences were used to screen for amplification of the DNA sequence. After thoroughly screening, the final subset of 10 primers was selected on the bases of good quality banding patterns with sufficient variability and 9 of them were chosen for further analyses (Table 2).
RAPD marker analysis
The prior protocol with minor modification was employed to perform RAPD analysis (Williams et al., 1990). PCR was completed for DNA amplification. For each sample, 10x Taq buffer (B) 1.0 µL, dNTPs 1.0 µL, Taq polymerase 0.2 µL, primer forward 1.0 µL, primer reverse 1.0 µL, ddH2O 3.8 mL were used. Two µL sample DNA was used for each reaction. Total 10 µL PCR reaction mixture was primed. Amplification of PCR was conducted using the following procedure: denaturation at 94℃ for 3 min; 40 cycles of 1 min denaturation at 94℃, 1 min annealing at 54℃, 2 min extension at 72℃ and a final extension at 72℃ for 7 min. The RAPD amplification products were separated in a horizontal 1.6% agarose gel. DNA fragments were revealed using ethidium bromide staining. The gels were stained for 20 - 25 min and were documented with a gel documentation system. The RAPD markers were analyzed for Nei's genetic distance, Shannon's information index, identity values, and the similarity index were computed from frequencies of polymorphic markers to estimate the genetic relationship between the studied 15 HYV rice varieties. The dendrogram was constructed using the software NTSYS-pc (https://ntsyspc.software.informer.com/2.2/). The unweighted paired group of arithmetic means (UPGMA) method was used to conduct cluster analysis of NTSYS-pc 2.1 software was employed to generate a dendrogram.
Results and Discussion
Molecular characterization of cultivated rice varieties in Bangladesh by using RAPD markers
Nine primers were initially screened from the 30 RAPD primers for their ability to produce polymorphic patterns. The primers OPA 02, OPA 04, OPK 06, OPB 09, OPB 08, OPB 12, OPC 12, OPB 18 and OPJ 01 were reproducible and distinct polymorphic amplified products. The other primers amplified DNA was not consistently reproducible, that is a very common feature of RAPD technique (Pervaiz et al., 2010). A total of 45 RAPD bands were scored of which 40 (88.89%) polymorphic amplification products were obtained by using these arbitrary primers (Table 3). The dissimilar numbers of bands were generated by primer OPB 18, OPB 08, OPK 06, OPA 09, OPC 12, OPC 09, and OPJ 01. Besides, the primer OPB 18, OPB 08, OPK 06, OPA 09, OPC 12, OPC 09, and OPJ 01 amplified maximum numbers of polymorphic bands (100%) while the primer OPA 04 generated the least (60%) polymorphic bands. This result is consistent with the previous finding by Skaria et al. (2011) who obtained 82.27% of polymorphic products by RAPD analysis in rice genotypes. Ravi et al. (2003) and his colleagues observed 40 cultivated rice varieties and 5 wild genotypes that produced 499 RAPD markers of which polymorphism percentage estimated to be 90.0. Pervaiz et al. (2010) studies the genetic polymorphism of 75 rice genotypes of Pakistan, a total of 145 RAPD fragments were produced by 28 decamer-primers, of which 116 (80%) were polymorphic. Polymorphic bands generated by each primer varied from 3 to 9 with a mean of 5.2 alleles per primer. The banding patterns by using primers OPK 06 are shown in Fig. 1.
Table 3. Random amplified polymorphic DNA (RAPD) primers with corresponding bands score and their size range together with polymorphic bands observed in fifteen rice genotypes.
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A frequency of polymorphic loci
The presence and absence of the band was a mark to find the DNA polymorphisms. The failure of primer caused to the absence of band to anneal a site in some individuals due to nucleotide sequences difference or by deletions or insertions between primer sites (Clark and Lanigan, 1993). Frequencies of polymorphic loci RAPD markers for studied 15 rice genotypes ranged from 0.5102 in OPB 08-2 up to 1.0000 in OPA 02-2, OPA 04-1, OPA 04-4, OPB 12-2, and OPB 12-3 (Table 4). Similar results were found in the studies of Koizumi et al. (2013) where the expected heterozygosity ranged from 0.031 to 0.965 and observed heterozygosity ranged from 0.031 to 1.000. Earlier, Akagi et al. (1997) reported that an identification system based on combinations of polymorphism using PCR was an effective method to identify individual genotypes and maintain the seed purity of rice cultivars.
Genetic variation
The values of different accessions of rice for across all loci were estimated by Nei's (1973) gene diversity and Shannon's information index (Table 5 and Table 6). The mean value of Nei's genetic diversity for 15 genotypes of rice accessions was estimated to be 0.26, the highest level of genetic diversity was observed with the locus OPB 18-2 and OPB 12-4 (0.4978) followed by OPJ 01-2 (0.4970), while the lowest level of genetic diversity were detected on OPA 02 -2, OPA 04-1, OPA 04-4, OPB 12-2¸ OPB 12-3 with value 0.0000.
The Shannon's information index values varied greatly among loci, ranged from 0.6909 (OPC 12-3 and OPB 18-2) to 0.0000 (OPA 02-2, OPA 04-1, OPA 04-4, OPB 12-2, OPB 12-3) with an average of 0.41 per locus. Genetic variation level was high among the studied rice genotypes according to the proportion of polymorphic loci. In the recent studies of Mukherjee et al. (2018), a higher diversity among the drought tolerant rice genotypes was found within the sub-populations (75%) compared among the populations (25%) with dissimilarity coefficient estimated to be 0.486. Jena et al. (2015) reported that genetic studies based on the characterization of the polymorphic loci of a marker are highly informative and extremely important. The authors categorized pest resistant rice genotypes through 22 gene markers into 4 major clusters with the genetic similarity rate almost 40% by using genetic diversity analysis.
Genetic differentiation and rate of migration among the subdivided population
Gene diversity in subdivided populations estimated the gene flow (Nm+) value of 0.000 according to the Nei's standard genetic distance analyses, whereas the proportion of total genetic diversity (Gst) was computed to be 1.0000. An expectation of average heterozygosity in sub-population (Ht) was 0.0772 according to the Hardy–Weinberg equilibrium, among the heterozygosity in sub-population of loci, Ht coefficients ranged from -0.0625 (OPA 09-5) to 0.3314 (OPJ 01-2 and OPJ 01-3) whereas the heterozygosity (Hs) was found to be constant 0.0000 (Table 7 and Table 8). In their study, Cirillo et al. (2009) found genetic differentiation among Italian rice genotypes by using RAPD technique despite low genomic variability.
Table 4. Frequencies of polymorphic random amplified polymorphic DNA (RAPD) markers in fifteen rice genotypes.
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Similarity index
Jaccard’s correlation coefficient (Jaccard, 1908) was effective to analyse the similarity between the rice accessions. Correlation matrices acquired from all the used primers were combined in one single matrix and the mean values ranged from 0.42 to 0.94 (Table 9). Jaccard’s pair-wise similarities estimated between the rice genotypes exhibited that BRRIdhan45 and BRRIdhan28 were the closest (0.94). The highest distance was detected between the genotypes BRRIdhan68 and BRRIdhan47 (0.42). The experiments conducted by Rashid (2007) found similarity coefficient ranged from 47.83 to 97.52 of 34 rice genotypes from different origin by using RAPD technique, and interestingly, in this study the author found that the accessions belonging to Pakistan and Philippines with similarity index more than 94% and 62.0 - 93.6%, respectively were grouped in separate clusters. Pervaiz et al. (2010) found similarity coefficients ranged from 0.22 to 0.90 and 0.19 to 0.72 among the basmati and non-basmati types landraces, respectively. This study proved that RAPD markers are the reliable technique to estimate genetic diversity of rice germplasm.
UPGMA dendrogram
A dendrogram was constructed by using NTSYS-pc the UPGMA. The 15 rice genotypes were divided into 2 main clusters, namely cluster 1 and cluster 2 (Fig. 2). The genotype BRRI47 was added in cluster 2. Cluster 2 i.e., BRRI dhan47 was different from other genotypes according to the similarity index. So, the genetic relatedness was not found between rice genotypes belonging to the cluster 1 and cluster 2. The following genotypes belong in cluster 1 BR2, BR9, BR16, BR17, BR18, BR26, BRRIdhan27, BRRIdhan28, BRRIdhan35, BRRIdhan45, BRRIdhan50, BRRIdhan61, BRRIdhan67, BRRIdhan68. The subsequent dividing of genotypes of the cluster 1 created sub-cluster 1 and sub-cluster 2. Sub-cluster 1 consisted of genotypes BR2 and BR9. Sub-cluster 2 formed by BR16, BR17, BRRIdhan68, BR18, BRRIdhan28, BRRIdhan45, BRRIdhan50, BRRIdhan35, BRRI dhan27, BRRIdhan67 genetic relationship was present between sub-clusters. The genotypes of sub-cluster 2 again split into two sub-sub-cluster 1 and sub-sub-cluster 2. Sub-sub-cluster 1 consisted of genotypes BR16. Sub-sub-cluster 2 formed by BR17, BRRIdhan68, BR18, BRRIdhan28, BRRIdhan45, BRRIdhan50, BRRIdhan67, BRRIdhan35, BRRIdhan27 and BRRIdhan67. Molecular characterization of the genotypic variations indicated that genetic components are an important factor to characterise genotypes belonging to different clusters, whereas geographical origin doesn’t have any impact. Recently, Singh et al. (2018) came up with similar results that most of the studied rice genotypes occurred in different clusters and subclusters without any close relationships. Also, Ravi et al. (2003) speculated that natural environmental factors might have an impact on the phonological diversity of genotypes in same groups.
Conclusion
The study of molecular characterization of fifteen high yielding variety of rice showed the variation among the variety. Nei's analysis of gene diversity in subdivided populations presented the gene flow (Nm+) value of 0.000 and the proportion of total genetic diversity (Gst) was 1.0000. Hardy Weinberg expectation of average heterozygosity in sub-population (Ht) was 0.0772, whereas the heterozygosity (Hs) was 0.0000. From the similarity matrix, the highest similarity was observed between genotype BRRIdhan45 and BRRIdhan28 and the lowest result between BRRIdhan68 and BRRIdhan47. From the dendrogram, it was observed that each studied variety was genetically different from other varieties. Molecular characterization of genotypic variations indicated that the genetic components of genotypes are important to divide them into different clusters. Therefore, it is meaningful to conclude that for further research purposes, mainly for hybridization, genotypes should be selected from different clusters to provide maximum genetic information especially related to the yield.
Authors Information
Isma Akter Epe, Patuakhali Science and Technology University, Researcher
Md. Shahidul Haque Bir, Chungnam National University, Researcher
Abul Kashem Choudhury, Patuakhali Science and Technology University, Researcher
Asma Khatun, Patuakhali Science and Technology University, Researcher
Most Mohshina Aktar, Bangladesh Agricultural University, Researcher
Md. Shamsul Arefin, Bangladesh Agricultural University, Researcher
Mohammed Aminul Islam, Bangladesh Agricultural University, Researcher
Kee Woong Park, https://orcid.org/0000-0003-0053-9543
