Diversity and phylogenetic relation of four Salacia species collected from the
western Ghats of Karnataka was assessed and compared using RAPD, ISSR markers
and ITS sequence. For RAPD and ISSR marker 21 samples were analyzed using ten
primers each. Nineteen ITS sequences along with an outgroup was used to
generated phylogenetic tree and diversity assessment. RAPD and ISSR primers
generated 76 and 68 loci of which 70 and 61 loci respectively were polymorphic.
In ITS analysis 18 sequences alignment generated overall length of 739bp of
which 137 bp were found to be polymorphic. Maximum likelihood analysis of the
ITS sequences revealed three clades. UPGMA analyses of RAPD and ISSR banding
variation revealed two and four major clusters respectively. Similar clustering
pattern was observed in PCoA. The level of polymorphism revealed by RAPD was
41.45%±10%, ISSR is 33.58%±6.52% and ITS was 25.50%± 17.25%. AMOVA revealed
significant variance within and among the Salacia
species. Tajima’s D neutrality test were negative for all species indicating
presences of rare alleles and population expansion.
Salacia species, RAPD, ISSR, ITS, Diversity.
Salacia is a liana
which belongs to family Celastraceae
subfamily Salacioideae. In India, Salacia
is distributed in Western Ghat regions of Karnataka, Kerala, Tamil Nadu and is
also distributed in eastern Ghats. Most of the species of genus Salacia are used in traditional medicinal
systems for treatment of diabetes and obesity (Paarakh
et al, 2008). Salacia species are known to
contain anthocyanidines, catechins, quinones, friedo-oleanones, quinonemethide
and mangiferin which are anti-diabetic (Yoshikawa
et al, 2001), anticancer (Yoshimi
et al, 2001), antiviral agent effective against
HIV, Herpes simplex (Guha
et al, 1996; Zheng & Lu, 1990) and major bioactive components such
as salacinol and kotalanol which have ?-glucosidase inhibitory activity (Xie
et al, 2011; Yoshikawa et al, 2002) .
Species identification in the genus Salacia is difficult when based solely on morphological
characteristics. Although most of the vegetative characters of the species within
the genus are same differences are observed in floral and some fruit
et al, 2012; Udayan et al, 2013). Therefore, accurate methods of
validation and authentication is indispensable to ensure safe use and efficacy
of extracted raw drugs.
RAPD and ISSR simple and quick techniques which does not
require any specific knowledge of the DNA sequence of the target organism. RAPD
detects nucleotide sequence polymorphisms, using a single primer of arbitrary
nucleotide sequence where as ISSR detects of polymorphisms in identical
inter-microsatellite loci oriented in opposite direction, using a 16–25 bp long
primer which are dinucleotide or trinucleotide tetranucleotide or
penta-nucleotide simple sequence repeats (Wu et
al, 1994; Zietkiewicz et al, 1994).ISSRs have high reproducibility
possibly due to the use of longer primers (16–25-mers) as compared to RAPD
primers (10- mers) which permits the subsequent use of high annealing
temperature (45– 60 ?C) leading to higher stringency. Inter transcribed spacer
(ITS) having universal set of primers is biparentally inherited, which varies
in length from 500–700 base pairs and is a popular choice for phylogenetic
& Wendel, 2003).
present study two DNA markers RAPD and ISSR, and a DNA barcoding region ITS was
used to evaluate genetic diversity within and among four Salacia species-S. chinensis,
S. macrosperma, S. fruticosa, S. oblonga sampled from Western Ghats of
2 Materials and methods
samples were collected from various parts of western Ghats (Table 1 for details).
The 21 samples are grouped in four population of Salacia chinensis L., Salacia
macrosperma Wight., Salacia fruticosa
Lawson., Salacia oblonga Wall. ex
Wight & Arn.
2.2 DNA isolation, RAPD, ISSR, ITS reaction
DNA was isolated according to Stange
et al (1998) protocol. DNA was quantified using NanoDrop
2000 Spectrophotometer (Thermo Fisher Scientific) and diluted to 25 ng for use
in polymerase chain reaction (PCR). Reaction mixture contained 100 uM of each
dNTPs (Merck biosciences), 5 uMole of primer (Sigma,USA), 0.5 Unit of Taq DNA
polymerase (Merck biosciences) and 1x Taq buffer (Merck biosciences) in a total
volume of 20 ul. ISSR-PCR amplification was carried out for 40 cycles, with initial
denaturation for 5 minutes at 94°C, followed by cyclic process of denaturation
for 1-minute at 94oC, annealing at temperature standardized for each
primer (Table 2) for 1 minutes and extension at 72°C for 1 minutes, and final
extension at 72 °C for 5 minutes in Applied Biosystems Veriti Thermal Cycler. For
RAPD-PCR, the protocol was similar to ISSR except for the annealing temperature
which was 36°C for all the primers. For the PCR amplification of the ITS
sequence primers ITS4- TCCTCCGCTTATTGATATGC and ITS5- GGAAGTAAAAGTCGTAACAAGG designed
(1990) were used. With amplification
profile as follows 95°C, 1 minute 30 seconds, 28 cycles of 95°C, 30 seconds,
42°C,1 minute, 72°C, 1 minute and 72°C, 3 minutes. Amplified
products were separated in 1.8% agarose gel containing ethidium bromide using
1x TBE buffer. DNA fragments were visualized under UV light. The band patterns
were photographed using Gel Doc™ XR (Bio- Rad).
2.3 Phylogenetic analysis of ITS sequence
amplified products were sent to Chromous biotech, Bangalore for sequencing. The
sequence generated were submitted to NCBI database. For phylogenetic analysis
of ITS sequence MEGA 5 (Tamura
et al, 2011) software was used. Nineteen samples
from current study and an outgroup sequence was used for sequence analysis. The
multiple sequence alignment was performed using CLUSTAL W, version 1.6 (Thompson
et al, 2002). Using MEGA 5 best-fit Model-test
was performed and model with the lowest Bayesian Information Criterion (BIC)
score was selected for further analysis. The Maximum Likelihood tree was
constructed using the best fit model with least BIC score.
2.4 Data collection and Analysis
banding patterns obtained from RAPD and ISSR were scored as present (1) or
absent (0), each of which was treated as an independent character regardless of
its intensity and binary matrix was created for RAPD and ISSR primers. The
polymorphic information content (PIC) proposed by Roldàn-Ruiz
et al (2000), marker index (MI) described by Varshney
et al (2007) and resolving power (RP) by Prevost
and Wilkinson (1999) of each marker was calculated.
POPGENE (Yeh et al, 1999) was used to calculate various paraments such as percentage of
polymorphic band, observed number of alleles (na), effective number of alleles
(ne), Shannon’s information index (I) and Nei’s gene diversity (H) total
heterozygosity (Ht), average heterozygosity (Hs) and gene flow (Nm) between the
populations and among the individuals within each population. The similarity
matrix was subjected to cluster analysis by unweighted pair group method for
arithmetic mean (UPGMA) and a dendrogram was generated.
& Smouse, 2006) was also used to calculate Principal
Coordinates Analysis (PCA) that plots the relationship between distance matrix
elements based on their first two principal coordinates. The product-moment
correlation (r) based on Mantel Z value was computed to measure the degree of
relationship between similarity index matrices produced by any two-marker
systems. The RAPD, ISSR and ITS data were subjected to a hierarchical analysis
of molecular variance (AMOVA), as described by Excoffier
et al (1992).
3.1 RAPD and ISSR analysis details
study, initially 40 RAPD primers that is 2 set of Operon primer kits OPG and
OPR (20 primer from each kits) were used to detect genetic polymorphism of S. oblonga, S. fruticosa, S. chinensis
and S. macrosperma. Out of the 40
RAPD primers, 10 primers i.e. OPG-02,
14, -16, -17, -18, -19 and OPR-02, -03, -07, -08 showed reproducible amplified
DNA polymorphism. All the chosen primers amplified fragments across the 21
samples, with the number of amplified fragments ranging from 4 to 12. Minimum number
of bands were seen in the primer OPG18 (4 bands) and maximum bands were
observed in primer OPG17-12 bands. About 6 bands were observed in rest of the
primers. From the ten primers, a total of 76 loci were generated of which 70
were polymorphic, making polymorphism generated by RAPD makers to be 92.11%. Multiplex
ratio (total number monomorphic and polymorphic loci/ number of assays) of RAPD
analysis was calculated as 7.6. Resolving power of RAPD marker for the observed
76 loci was 54.67. While in ISSR analysis 10 primers produced 67 loci of which
61 bands were polymorphic, accounting for 91.04% of polymorphism. Number of
bands varied from four (ISSR 5) to nine (ISSR 10), and sizes ranged from 200 to
2,500 bp. Multiplex ratio of ISSR analysis is calculated as 6.8. Resolving
power of ISSR marker for the observed 67 loci was 58.48. The Marker index which
determines overall efficiency of marker system is calculated by (MI) = Hav X MR
where Hav was average heterozygosity and MR is multiplex ratio. The marker
index for RAPD was (0.859×7.60) 6.54 and ISSR marker was (0.801×6.8) 5.45.
observed number of alleles, effective number of alleles, Nei’s genetic
diversity, Shannon’s information index, for 21 samples of Salacia species analyzed using ten RAPD markers and
their respective values were found as 1.9211, 1.4537, 0.2785, 0.4294 respectively
and for ISSR these values are 1.9104, 1.5108, 0.2988, 0.4509 respectively. Total
genotype diversity among population (Ht) was estimated to
be 0.2713 while within population diversity (Hs) was estimated to be 0.1514 for
RAPD and for ISSR Ht was 0.3055 and Hs was 0.1222. Mean coefficient of gene
differentiation (Gst) value for RAPD was 0.4418 which indicated that 55.8% of
the genetic diversity resided within the population and for ISSR Gst was 0.5999.
Estimates of gene flow in the population for RAPD and ISSR were 0.6318 and
0.3334 respectively. (Table 3).
3.2 Dendrogram and PCA of RAPD and
In RAPD dendrogram,
based on UPGMA analysis, 21 samples of Salacia
grouped into two clusters (Cluster 1 and 2). Cluster 1 contained S. chinensis SC1 to SC5 and cluster 2 was
further divided into two sub-clusters (sub-cluster 1 & 2). In cluster 2,
sub-cluster 1 contained all samples of S.
macrosperma along with two samples of S.
fruticosa SF1 & SF3 (Fig 1) and sub-cluster 2 contained three remaining
samples of S. fruticosa along with S. oblonga samples. The three most
informative Principle components explained 65.68 % of cumulative total
variation. Dendrogram of ISSR data showed that the samples clearly grouped into
four clusters (I, II III and IV) of its respective species S. chinensis, S. macrosperma, S. fruticosa, S. oblonga. The first
three most informative Principle components explained 74.05% of the total
variation. The results of RAPD and ISSR PcoA analysis were comparable to the
cluster analysis (Fig 2).
which helps in partitioning of the overall variations among groups and among
populations within the group were performed for RAPD, ISSR and ITS data
matrices. From RAPD, 39% of molecular variance was found among population
while, within the population this value was found to be 61% indicating that
there were more variations within the population. While in ISSR, 55% molecular
variance was found among population and 45% within the population. For ITS sequence
analysis 80% variances was among the population and 20% variance was within
population which was similar to coefficient of evolutionary differentiation.
genetic pairwise distance of Salacia
species was found to be > 0.5 for RAPD, ISSR and ITS sequence. But in ITS
sequence analyis, the pair-wise distance between the S. oblonga and S. macrosperm
was 0.061 suggesting that they are very closely related. In addition, the
pair-wise distance and identity of S.oblonga
and S.fruticosa was 0.915 and 0.088
indicating that they are highly dissimilar. (Table 6).
3.5 Statistical comparative analysis
test was employed to determine the coefficient of correlation between the genetic
distance matrices generated by RAPD and ISSR markers. The coefficient of
correlation between RAPD and ISSR marker was R2=0.3781, r=0.614
which is high. This value signifies that there were considerable correlation
between RAPD and ISSR genetic distances matrices. Twenty-one samples grouped into
two clusters in RAPD dendrogram whereas in ISSR dendrogram four cluster were
observed. Comparing RAPD dendrogram with ISSR dendrograms we can notice that S. oblonga was an Operational Taxonomic
Units (OTU). In all analysis, results of cluster analysis were comparable to PcoA.
test was also employed to analyze the ‘goodness of fit’ for each marker system.
This was done by comparing cophenetic similarity matrices of genetic distance
with cophenetic similarity matrices with the Nei Genetic Distance for each
marker technique. It revealed values higher than 0.80 for all the markers used
RAPD (r = 0.827, P = 0.01), ISSR (r = 0.816, P = 0.01) thus confirming their
authenticity and very good fit of PCA clustering.
markers have been used to evaluate genetic diversity in various plant species.
In general, RAPD is increasingly being employed in genetic research owing to
its speedy process and simplicity. On the other hand, ISSR marker has high potential
to reveal polymorphism at intra- and intergenomic level to determine diversity than
compared RAPDs (Zietkiewicz et al., 1994).
study, we have compared the applicability of ISSRs and RAPDs as genetic markers
to characterize the Salacia species. The
only reports on genetic diversity on genus Salacia
was carried out by Priya
et al (2016) who used RAPD molecular markers to
asses diversity of samples collected from Wayanad region in Kerala. In the
present study, an attempt has been made to examine the level of genetic
variation within Salacia species
sampled in the Western Ghats of Karnataka.
and values obtained in the current study it was quite that obvious RAPD is a
better marker than ISSR in evaluating diversity of Salacia species. However, on careful observation it can be observed
that RAPD marker was not able to differentiate S. oblonga samples and it was grouped within S. fruticosa samples. This could be attributed to the fact that the
putatively similar bands originating from RAPD analysis in different
individuals may not necessarily have to be homologous, although they may be of
same size in base pairs which in turn results the erroneous calculation of
genetic relationships (Fernandez
et al, 2002). This also explains the fact that Nei’s
genetic distance and identity between S.
oblonga and S. fruticosa were
considerably high which was contrary to observation seen in dendrogram and PCA.
Resolving power of ISSR was marginally higher than RAPD. Also, the differences
in clustering pattern in RAPD and ISSR markers may also be attributed to
differences in overall number of loci and their coverage of the overall genome,
which would affect reliable estimates of genetic relationships among samples (Loarce
et al, 1996).
In both RAPD
and ISSR analysis S. macrosperma had
high polymorphism within the population which was apparent as the samples were
collected from many different locations. However, in case of S. chinensis, S. fruticosa, and S. oblonga populations the samples were
collected from one location. Despite the samples within the population
originating from one location, a considerable high rate of polymorphism was
observed which was in correlation with the observations made earlier by Priya
et al (2016).Similarly, diversity evaluation of Memecylon species collected from western
Ghats of Karnataka by Ramasetty
et al (2016) using RAPD,ISSR and barcoding genes
found high level of polymorphism in RAPD (65.4%) and ISSR analysis (68.5%). RAPD and ISSR
markers were also able to effectively detect low polymorphism variation in Garcinia xanthochymus species sampled
across various states of western Ghats (Anerao
et al, 2017) which suggest that RAPD and ISSR are
efficient markers in for diversity analysis.
study by Dev et
al (2015) ITS2 region showed highest
interspecific divergence and 100% efficiency for species identification by nearest
distance method when compared to rbcL, matK and trnH-psbA barcoding regions.
The authors also observed reciprocal monophyly among S. fruticosa, S. chinensis, S.
agasthiamalana and S. macrosperma in the phylogenetic tree generated from
the combined dataset, which was also observed in our current results. The high
divergence of S. fruticosa sample SF5
can be attributed to amplification of ITS pseudogene as it is identified by its
high rate of substitution especially in the ITS2 region. Furthermore, this fact
was validated by AMOVA, since as compared to RAPD and ISSR, ITS had highest
percent of variance (80%) in detecting interspecific or among the species
divergence whereas the RAPD had the lowest (39%). From the AMOVA it can be seen
that there was considerable variation within and among Salacia species. The variation within the species may due to
presence of infrageneric variation in Salacia
species. Evidence can be seen from discovery of variety kakkayamana in S. oblonga (Udayan
et al, 2014). Also, the high variation among
groups was due to the component of genetic variance, as new species S. agasthiamalana (Udayan
et al, 2012)
S. vellaniana (Udayan
et al, 2013) were discovered in western Ghats
of Kerala. From the study of Dev et
al (2015) of Salacia species sampled from Kerala, S. oblonga and variety kakkayamana
showed 100% homology, while S. fruticosa,
S. vellaniana, S. chinensis, S. malabarica, S. agasthiamalana samples formed monophyletic group and S. macrosperma and S. beddomei were closely
related sister species as per the phylogram
. The results of Tajima’s D neutrality tests were negative for all the Salacia species population suggesting excess
of rare alleles within the population, which may suggest population expansion.
However, when the sample SF5 was removed and all the individual samples were
analyzed across species samples, there exist an equilibrium.
study of RAPD, ISSR and ITS for Salacia
species has given an insight into the efficiency of each technique in detecting
diversity within and among the population sampled in the western Ghats of