Int J Pharm Pharm Sci, Vol 11, Issue 3, 62-65Original Article


POPULATION STRUCTURE OF KAEMPFERIA GALANGA L. FROM EASTERN INDIA

REENA PARIDA, SUJATA MOHANTY, SANGHAMITRA NAYAK

Centre for Biotechnology, SPS, Siksha ‘O’ Anusandhan University, Bhubaneswar, Odisha, India
Email: ms.reenas@gmail.com

Received: 07 Dec 2018 Revised and Accepted: 26 Jan 2019

ABSTRACT

Objective: India has been a producer of a large number of aromatic medicinal plants which serves as a valuable genetic resource for future quality improvement to meet the ever-growing demand of human essential products. Thus, an urgent need arises for germplasm conservation of these high yielding varieties to help the pharmaceutical and other industries. For this understanding, the population structure is essential in order to explore their genetic identification by fingerprinting and molecular characterization.

Methods: In the present study DNA was isolated using modified Cetyl Trimethyl Ammonium Bromide (CTAB) method and Polymerase Chain Reaction (PCR) was performed according to standardized method along with its data analysis. This study was undertaken to characterize the highly medicinal Kaempferia galanga collected from 4 different populations of Odisha using the molecular markers as Random Amplified Polymorphic DNA and Inter-Simple Sequence Repeats for the first time.

Results: A dendrogram constructed through Sequential Agglomerative Hierarchical and Nested (SAHN) clustering and Unweighted Pair Group Method with Arithmetic mean (UPGMA) analysis showed an average similarity of 0.993 ranging between 0.967 to 1.000. Jaccard’s similarity coefficient of combined markers segregated the genotypes into two main clusters, 1 with six samples and the others at 0.98 similarity coefficient.

Conclusion: Hence, the molecular analysis could be further used for the identification of important novel gene present in Kaempferia galanga which can be utilized for future crop improvement as well as pharmacological activities.

Keywords: Kaempferia galanga, Polymerase Chain Reaction, Random Amplified Polymorphic DNA, Inter-Simple Sequence Repeats

© 2019 The Authors. Published by Innovare Academic Sciences Pvt Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
DOI: http://dx.doi.org/10.22159/ijpps.2019v11i3.31226

INTRODUCTION

Kaempferia galanga L. (Zingiberaceae) an important medicinal herb is distributed in Asia and Africa [1]. Kaempferia galanga locally known as ‘gandhasunthi’ is famous as a health-promoting herb used in ayurvedic drugs, perfumery, cosmetic industries and as spice ingredients [2-5]. The plants have handsome, showy flowers and foliage due to their arching form and shining leaves and are cultivated as ornamentals. The plant stays close to the ground achieving a height of 3 inches, no central stem and its leaves just grow right off the rhizomes up to 6 inches. The plant blossoms with small white fragrant flowers with a splash of purple at the center but lasts only for a few hours. Leaves are used to flavour foodstuffs, mouthwashes possessing antioxidant, antinociceptive and anti-inflammatory activities [6, 7]. The rhizomes are used to treat piles, tumours, coughs, epilepsy, asthma, spleen disorders, fever, abdominal pain, toothache, flatulence and anti-food-borne bacteria [8-9]. Natural sunscreens and Sun Protection Factor (SPF) boosters, a natural material that protects from Ultra Violet (UV) rays also isolated from Kaempferia galanga has been reported. This plant is economically important having a price value of Rs.300/Kg in dry rhizomes whereas its oil is US$ 700/Kg internationally and is used by tribal and pharmaceuticals. The plant is conventionally propagated by rhizome with very low multiplication rate. Also due to demand and depletion of this highly valued medicinal plant, it is decreasing naturally and being recognized as an endangered [10]. The taxonomic identification of Kaempferia is difficult without its floral parts due to the problem in its morphological simi­larity with other related Zingiberaceae species. This paper aims the novelty of steps taken to identify the Kaempferia galanga species in molecular level present in various places of eastern India which is not yet reported. The species after identification could be used for various activities testing by the pharmaceutical industries and others to be used as medicines. This technique could further help in multiplication and conservation of the plant to fulfil the ever-growing human demand.

MATERIALS AND METHODS

Plant sample collection and molecular analysis

Kaempferia galanga were collected from the wild habitats of Koraput (18 °82' N, 82 °72' E), Rourkela (22 °25' N, 85 °00' E), Mayurbhanj (21 °93' N, 86 °73' E) and Jagatsinghpur population (20 °16' N, 86 °10' E) of Odisha. DNA isolation from fresh 2 gm of leaves was done by Doyle and Doyle method [11]. Polymerase Chain Reaction (PCR) techniques namely Random Amplified Polymorphic DNA (RAPD) and Inter-Simple Sequence Repeats (ISSR) were done [12,13]. RAPD primers (Operon Tech., Alameda, USA) were dissolved in double sterilized T10E1 buffer, pH 8.0 to the working concentration of 15 ng/µl. 19 RAPD primers as per banding pattern were selected namely A4, A7, A9, A18, C2, C5, C11, D3, D7, D8, D12, D18, D20, N4, N16, N18, AF5, AF14 and AF15. 9 ISSR primers similarly used as (GAC)5, (GTGC)4, (GACA)4, (AGG)6, (GA)9T, T(GA)9, (GTG)5, (GGA)4 and (CAA)5 from Bangalore Genei Pvt. Ltd, India. PCR product for both RAPD and ISSR was electrophoresed with 1.5% and 2% agarose gel and ethidium bromide at 60 volts for three hours. These were visualized in UV-transilluminator (BioRad, USA) and gel documented in Gel Documenting System (Bio-Rad, USA) for band details.

Data scoring

The scoring of bands as ‘1’ and ‘0’ for presence and absence of amplified products was done [14].

Statistical analysis

Resolving power (Rp) and Primer Index (PI)

Rp of both were calculated as Rp=ΣIB (IB (Band informativeness) = 1-[2×(0.5-P)], P is the proportion of species containing band [15]. P I was calculated from the polymorphic index. The polymorphic index value was calculated as PIC = 1-∑P2i, Pi is the frequency of band of i th allele [16]. In both cases, PIC was 1-p2-q2, where p is the frequency of band whereas q no frequency band [17]. PIC value calculated was primer index (PI). PI is the sum of PIC of all markers amplified by the same primer.

Jaccard’s similarity and bootstrapping

Jaccard’s similarity coefficient was measured by Unweighted Pair Group Method using Arithmetic averages (UPGMA) and Sequential Agglomerative Hierarchical and Nested (SAHN) [18-19]. The whole analysis was done using NTSYS-pc 2.02e [20]. A statistical testing of robustness as bootstrapping was performed for tree building.

Chemicals and reagents

RNase A (Qiagen Inc., USA)

RAPD operon primers (Operon Tech., Alameda, USA)

ISSR primers (Bangalore Genei Pvt. Ltd, Bangalore, India)

Taq DNA polymerase (Bangalore Genei Pvt. Ltd, Bangalore, India)

dNTP (MBI Fermentas, Lithuania)

6X loading dye (MBI Fermentas, Lithuania)

DNA ladder (MBI Fermentas, Lithuania)

Agarose (SRL Pvt. Ltd, India)

RESULTS

PCR analysis

25 RAPD primers were used but only 19 amplified. The four populations each in triplicates was used that produced distinct amplicons. 88 bands in total were amplified, 82 bands were monomorphic and 6 were polymorphic in nature. The highest band was 12 in OPD18, lowest was 1in OPD3 and no unique bands present. Average band per primer was 6.2. The resolving power was 2-22.83 where maximum and minimum was in OPD20 (22.83) and OPD3 (2) presented in table 1, fig. 2 a, b. 10 ISSR primers were used and 9 amplified in table 1. (GTGC)4, T(GA)9, (GTG)5 and (CAA)5 primers showed maximum bands as 9 but (GAC)5 and (GACA)4 showed minimum as 6 number. Band amplification ranged from 190-2450bp but no unique band seen and all were monomorphic in nature. The resolving power was maximum 18 in (GTGC)4, T(GA)9, (GTG)5 and minimum 12 in (GAC)5 and (GACA)4 fig. 2 c, d.

Combined markers analysis

Total 158 bands were amplified in total where 152 were monomorphic and 6 polymorphic table 1. Samples correlation was done with an average similarity of 0.993 ranging between 0.967 to 1.000. A dendrogram was constructed using Jaccard’s similarity coefficient which resulted in 2 major clusters, 1 with six samples and the others at 0.98 similarity coefficient fig. 1. Again these were subdivided into 2 subclusters, one containing the single sample and others in 2 subcluster. The Koraput and Mayurbhanj were present in Cluster I and Rourkela and Jagatsinghpur in Cluster II.

Table 1: Details of RAPD, ISSR and combined marker analysis as revealed among 4 populations of Kaempferia galanga

Markers Primer Sequence of oligonucleotides Approx fragment size (bp) Total bands Monomorphic bands Polymorphic bands Unique bands Resolving power
RAPD OPA4 5'AATCGGGCTG3' 600-1400 7 7 0 0 14
OPA7 5'GAAACGGGTG3' 750-2200 8 8 0 0 16
OPA18 5'AGGTGACCGT3' 450-1700 4 4 0 0 8
OPC2 5'GTGAGGCGTC3' 330-2250 7 7 0 0 14
OPC5 5'GATGACCGCC3' 900-2600 7 7 0 0 14
OPC11 5'AAAGCTGCGG3' 1200-1550 3 3 0 0 6
OPD3 5'GTCGCCGTCA3' 1031 1 1 0 0 2
OPD7 5'TTGGCACGGG3' 1031-2400 5 5 0 0 10
OPD8 5'GTGTGCCCCA3' 700-2400 7 7 0 0 14
OPD18 5'GAGAGCCAAC3' 220-1400 12 8 4 0 20
OPD20 5'ACCCGGTCAC3' 500-2050 10 10 0 0 22.8333
OPN4 5'GACCGACCCA3' 500-1650 7 7 0 0 14
OPN16 5'AAGCGACCTG3' 100-800 8 7 1 0 15
OPN18 5'GGTGAGGTCA3' 450-1300 2 1 1 0 3
Total 88 82 6 0
ISSR SPS1 (GAC)5 260-950 6 6 0 0 12
SPS2 (GTGC)4 190-1650 9 9 0 0 18
SPS3 (GACA)4 320-1150 6 6 0 0 12
SPS4 (AGG)6 280-820 7 7 0 0 14
SPS5 (GA)9T 280-1350 7 7 0 0 14
SPS6 T(GA)9 250-1080 9 9 0 0 18
SPS7 (GTG)5 250-1080 9 9 0 0 18
SPS8 (GGA)4 250-1750 8 8 0 0 16
SPS9 (CAA)5 575-2450 9 9 0 0 18
Total 70 70 0 0 0
Grand total 158 152 6 0

Fig. 1: Dendrogram showing genomic relationship within 4 populations in Kaempferia galanga as revealed from RAPD and ISSR analysis

Fig. 2: (a, b) RAPD banding pattern and (c, d) ISSR banding pattern of Kaempferia galanga from different populations (Lane 1-12) and M–marker

DISCUSSION

Recently, emphasis on molecular markers has been increased for identification and characterization of genotypes, fingerprinting and cloning at the molecular level. The polymerase chain reaction-based techniques are widely used for genetic integrity and cost-effectiveness [21]. There are various reports on Zingiberaceous morphological analysis but few reports in its genetic level [22-23]. Few reports on the phylogeny of Zingiberaceae have been reported [24]. Also, other studies shows variation in their chloroplast DNA of 71 Kaempfe­ria accessions as reported [25]. There are few other reports on genetic uniformity of cryopreserved Kaempferia galanga plantlets with minor variations [26]. There have been reports on the economic value, agronomy, ethnobotany, phytochemistry, pharmacology and conservation strategies [27]. The different populations having similarity within each other is grouped under the same cluster in our study is similar with other reports [28]. In their reports, 1accession from Bangladesh was identical with Pakistan and 2 accessions of Japan with China. Very few studies have been done on Kaempferia galanga and similar work by others [29-31]. The molecular analysis in the present work has proven to be useful in discrimination, characterization and differentiation of plant species by clustering them according to their origin. This indicates that combined markers provide a consistently good method for species identification than morphological characters. Genetic mapping of the genome could help in understanding their complex traits such as rhizome size, yield etc. which is useful for their breeding program.

CONCLUSION

The present study revealed moreover similarity among Kaempferia species based on its molecular data of different populations. Samples in single cluster reveal the closeness with each other but at the same time very few populations has been studied for which variation is negligible. This phylogenetic study could be valuable for Kaempferia galanga species identification from different regions of India, the exchange of healthy plant material for commercial exploitation in curing diseases.

ACKNOWLEDGMENT

We sincerely thank to Prof M. R. Nayak, President and Prof S. C. Si, Dean, Centre for Biotechnology, SPS, Siksha ‘O’ Anusandhan University for providing facilities and encouraging throughout the work.

AUTHORS CONTRIBUTIONS

Reena Parida, Sujata Mohanty under the guidance of Dr Sanghamitra Nayak designed the experiments, performed in the laboratory, analyzed the data proceeded by manuscript writing.

CONFLICTS OF INTERESTS

Declared none

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