25

Assessment of Genetic diversity on

Withania somnifera using Random Amplified

Polymorphic DNA (RAPD) Analysis

By

D.VIJAYALAKSHMI

(06PBT22)

A Thesis Submitted to the Avinashilingam University for Women,

Coimbatore- 641043.

In partial fulfillment of the requirement for the degree of

MASTER OF SCIENCE IN BIOTECHNOLOGY

May 2008

26

Assessment of Genetic diversity on

Withania somnifera using Random Amplified

Polymorphic DNA (RAPD) Analysis

By

D.VIJAYALAKSHMI

(06PBT22)

A Thesis Submitted to the Avinashilingam University for Women,

Coimbatore- 641043.

In partial fulfillment of the requirement for the degree of

MASTER OF SCIENCE IN BIOTECHNOLOGY

May 2008

27

ACKNOWLEDGEMENT

28

ACKNOWLEDGEMENT

First of all, I thank God almighty for the blessings showered

upon me to complete my project work completely.

I convey my deep sense of gratitude to Dr. T.K. Shunmugnantham,

Chancellor, Avinashilingam University for Women, Coimbatore, for providing

me with the opportunity to carry out the study in this Institution.

I express my sincere thanks to Dr. Saroja Prabhakaran, Vice-

Chancellor, Dr.Gowri Ramakrishnan, Registrar, Avinashilingam University

for Women, Coimbatore, for the support and timely help extended during the

course of the research work.

I owe my sincere thanks to Dr. R.Parvatham, Dean, Faculty of

Science, Professor and Head of the Department of Biochemistry,

Biotechnology and Bioinformatics, Avinashilingam University for Women,

Coimbatore, for her moral support, motivation and encouragement given

throughout the study period.

My deep-felt thanks to Dr. K.Kalaiselvi, Lecturer, Department of

Biochemistry, Biotechnology and Bioinformatics, Avinashilingam University

for Women, Coimbatore, for her guidance rendered at every stage of

dissertation, dynamic guidance, valuable suggestions, kind advice, untiring

help, meticulous efforts and enduring support throughout the work.

29

I wish to express my gratitude thanks to the all staff members of the

Department of Biochemistry, Biotechnology and Bioinformatics,

Avinashilingam University for Women, Coimbatore, for their superior help.

I express my special thanks to Dr. Senthil.N of Tamil Nadu

Agricultural University, Coimbatore, for his timely help rendered during the

completion of the thesis.

I express my profound gratitude and thanks to Dr. D.Thangamani,

scientist-C, Institute of Forest Genetics and Tree Breeding, Coimbatore, for her

patient guidance, constructive criticisms, inspiring and kind advice, constant

support and meticulous care and deep concern in the completion of this study.

I wish to express my heart-felt thanks to Mr.Rajesh kumar,

Ms.S.Vijaya devi and my friends for their support rendered throughout the

study.

Finally, I am short of words to express my thanks to my family who are

with me in all my endeavors.

30

CONTENTS

31

CONTENTS

PAGE

NO

TITLE S.NO

LIST OF TABLES

LIST OF FIGURES

LIST OF PLATES

1 INTRODUCTION

1

3 REVIEW OF LITERATURE

2

14 MATERIALS AND

METHODS

3

19 RESULTS AND DISCUSSION

4

45 SUMMARY AND

CONCLUSION

5

REFERENCES

APPENDICES

32

LIST OF TABLES

TABLE

NO

TITLE PAGE

NO

3.1 Withania somnifera used in the study

15

4.1 Morphological traits for the four varieties

of Withania somnifera

23

4.2 Descriptive statistics of quantitative traits

24

4.3 DNA ratios

27

4.4 Data matrix

34

4.5 Polymorphism in Withania somnifera using

nine RAPD markers

37

4.6 Dissimilarity index computed for the

morphological traits

40

4.7 Cluster based on morphological traits

Dendrogram

40

4.8 Similarity index computed for the RAPD

data

42

4.9 Cluster analysis based on RAPD markers

Dendrogram

42

33

LIST OF FIGURES

FIGURE

NO

TITLE PAGE

NO

4.1 Morphological characters of Withania

somnifera used in the study

26

4.2 DNA quantification

28

4.3 RAPD profile using Primer OPO 13

29

4.4 RAPD profile using Primer OPR 13

30

4.5 RAPD profile using Primer OPO 20

30

4.6 RAPD profile using Primer OPO 08

31

4.7 RAPD profile using Primer OPO 09

31

4.8 RAPD profile using Primer OPO 10

32

4.9 RAPD profile using Primer OPB 04

32

4.10 RAPD profile using Primer OPE 04

33

4.11 RAPD profile using Primer OPM 02

33

4.12 Dendrogram of Withania somnifera

genotypes based on the Morphological

characters

41

4.13 Dendrogram of Withania somnifera

genotypes based on the RAPD Markers

43

34

LIST OF PLATES

Page

No

Title Plate No

22 Withania somnifera plants used in the study

4.1

35

INTRODUCTION

36

1.0. INTRODUCTION

Genetic diversity is a characteristic of ecosystems and gene pools that

describes an attribute which is commonly held to be advantageous for survival

that there are many different versions of otherwise similar organisms. Genetic

fingerprinting has been accomplished traditionally through the use of

molecular markers. However, DNA-based markers provide powerful tools for

discerning variations within crop germ-plasm and for studying evolutionary

relationships (Daunay and Lester, 1988).

Recently, various molecular marker techniques have been developed

into powerful tools for diversity analysis and establishing relationships

between cultivars. Among these, the RAPD technique, the simplest, less

expensive, and fast does not require large infrastructure to start with (Williams

et al., 1990; Welsh and McClelland, 1990).

The RAPD method (Williams et al., 1990), is frequently applied to

reveal population-genetic variation, divergence and biogeography (Schaal and

Leverrich, 2001).

The plant selected for the present study is Withania somnifera. The

genus Withania is an important member of the family Solanaceae, Indian

ginseng, and winter cherry, it has been an important herb in the Ayurvedic and

indigenous medical systems for over 3000 years (Weiner and Weiner, 1994).

Studies pertaining to identification of morphological and

physiological variation based on extremely diversified geographical

distribution of Withania somnifera have been conducted (Atal and

Schawarting, 1962). It was observed that an extreme degree of variability

existed in Withania somnifera with respect to growth habits and morphological

characteristics of plants in different parts of India and in other countries. It was

pointed out that the classification of Withania somnifera has been

indiscriminately applied to a variety of dissimilar forms, and there is no report

that addresses the genetic variation among Withania species (Negi et al., 2000).

37

Indian genetic resources (wild and cultivated) exhibit a lot of

morphological and phytochemical variability which remains largely

undocumented. Five morphotypes exhibiting morphological variability have

been reported (Atal et al., 1975). Earlier studies on genetic divergence among

the accessions were restricted to Central India (Mishra et al., 1998).

In the present study, a systemic attempt has been made to understand

the nature and the extent of variability at molecular level in

Withania somnifera. The genetic variation among different somnifera plants

which grows naturally in different parts of India has been assessed by RAPD

marker analysis. Based on this data, the diversity among Withania somnifera

species is estimated.

The main objectives of the present study are,

• To study the morphological variation among Withania collection.

• To analyze the RAPD variation among Withania collection.

38

REVIEW OF LITERATURE

39

2.0. REVIEW OF LITERATURE

The study on "Assessment of Genetic diversity on Withania

somnifera using Random Amplified Polymorphic DNA (RAPD) Analysis"

has been reviewed under the following titles.

2.1. INTRODUTION

2.2. WITHANIA SOMNIFERA

2.3. GENETIC DIVERSITY

2.4. DNA-BASED MARKERS

2.5. RAPD-PCR

2.6. DIVERSITY IN WITHANIA SPECIES

2.1. INTRODUCTION

The traditional systems of medicine such as Unani, Ayurveda and

Homeopathy are based on the use of whole plants or their parts including roots,

stems, leaves, flowers and seeds. Even the modern allopathic medicinal

preparations depends on plants for several lead molecules and preparations.

With the development of drug resistance in pathogen and adverse

side-effects of allopathic medicines, the interest in herbal drugs for health care

is increasing globally. One of the major problems faced by the pharmaceutical

industry in maintaining the quality and efficacy of herbal drug is the lack of

purity for herbal raw materials. Creating a novel system to assess the quality

of a medicinal herb and to discriminate adulterants from authentic raw

materials is essential. Major objective therefore, is to develop molecular tools

for accurate identification of root samples of some important medicinal plant

species obtained form market or collected from wild. The isolation of DNA is

the first step in developing this technology (Khan et al., 2007)

40

With the increasing use of DNA fingerprinting in plants and its

potential use in herbal drug industry, the preparation of good quality and

quantity DNA has become major concern. The extraction from tissue needs to

be simple, rapid, efficient and inexpensive when many samples are used, such

as in population studies, molecular breeding and screening of raw herbal drug

materials. Several methods for extracting plant DNA from different plant parts

including roots have been developed (Dellaporta et al., 1983; Keim et al.,

1988; Doyle and Doyle et al., 1990; Khanuja et al.,1999; Kumar et al., 2003).

2.2. WITHANIA SOMNIFERA

BOTANICAL NAME : Withania somnifera

COMMON NAME : Ashwagandha

TAMIL NAME : Amukran

Classification

Kingdom - Plantae

Division - Angiosperma

Class - Dicotyledoneae

Order - Tubiflorae

Family - Solanaceae

Genus - Withania

Species - somnifera

Botanical description

An erect branching under shrub reaching about 150cm in height,

leaves ovate up to 10cm long, densely hairy beneath and sparsely above,

flowers greenish or yellow in axillary fascicles, bisexual, pedicerl long, fruits

globule berries which are orange coloured when mature, enclosed in a

persistant calyx. The fleshy roots when dry are cylindrical gradually tapering

down with the brownish white surface and pure white inside when broken.

41

Traditional uses

Withania somnifera popularly, known as “Ashwagandha” is one of the

major herbal components of geriatric tonics mentioned in Indian system of

medicine. It improves learning ability and memory capacity. The traditional

use of “Ashwagandha” was to increase energy, youthful, vigor, endurance,

strength, health nurture the time elements of the body, increase vital fluids,

muscle fat, blood, weakness, loose teeth, thirst, impotency and muscle tension.

It helps invigorate the body by rejuvenating the reproductive organs, just as a

true is invigorated by feeding the roots (Vaidyaratnam,1994).

It has generated a lot of scientific interest in recent years. Roots of

this plant are used in several indigenous drug preparations. The plant is

attributed with curative property against a number of disease including cancer

(Devi,1996).

2.3. GENETIC DIVERSITY

An essential factor for a species to survive against environmental

pressure is the availability of a pool of genetic diversity and in the absence of

that extinction would appear inevitable (Frankel, 1983). Determining, how

much genetic diversity exists in a species and explaining this diversity in terms

of its origin, organization and maintenance are thus of fundamental

significance in the application of genetic principles to conservation. Moreover,

while assessing genetic diversity it is essential to have quantitative measure of

the hierarchy of organisms as genes, population, etc. This is often based on

characterization of amount and distribution of genetic diversity in the

hierarchy, i.e., the population genetic structure, which is the most fundamental

piece of information for species that require genetic management.

It has been well documented that geographical conditions affect the

active constituents of the medicinal plant and hence their activity profile.

(Oleszek et al., 2002.) Many researches have studied geographical variation at

the genetic level. Estimates of genetic diversity are also important in designing

42

crop improvement programmes for management of germ-plasm and evolving

conservation strategies. RAPD-based molecular markers have been found to

be useful in differentiating different accessions of Taxus wallichaiana,

Azadiracta indica,, Juniperus communis L, Andrographis paniculata collected

from different geographical regions (Joshi et al., 2004).

Genetic diversity within population is considered to be of great

importance for possible adaptation to environmental changes and consequently

for long term survival of a species (Hanski and Ovaskainen, 2000). The loss of

genetic variation in a population leads to increasing number of homozygous

individuals fitness (Ellstrand and Elam, 1999). Thus the quantification of

genetic variation is currently regarded as a primary goal in conservation efforts

and accounts for the current utilization of genetic information in conservation

(Abdel et al., 2005).

Preliminary study of genetic diversity of the existing population is

required for the purpose of conservation and reintroduction of rare and

endangered species. In recent years, the method of polymerase chain reaction

with random primers (RAPD) is widely applied for specific, population, and

individual identification of organisms with undetermined DNA nucleotide

sequences (Shin, et al., 1998; Ma, et al., 1998; Oganisyan et al., 1996,

Gustaine, et al., 1999). By this method, intervarietal and interlinear

polymorphism was established in ginseng cultivated in Korea and the genetic

distances were determined between natural and cultivated population of

P. quinquefolis (Schluter et al., 2002).

The spatial distribution of genetic diversity could yield clues to resolve these

uncertainties. Introduction events are often associated with a population

bottleneck, which should reduce genetic diversity. The short time elapsed

since introduction should not have been sufficient for mutation to counter such

reduction in diversity. The diversity in an area of introduction should thus be a

subset of initial diversity (Diallo et al., 2007).

43

The most important role of conservation is to preserve the genetic variation and

evolutionary process in viable population of ecologically and commercially

viable varieties/genotypes in order to prevent potential extinction (Palai et al.,

2007).

2.4. DNA – BASED MARKERS

In recent years, DNA based molecular markers have been used for cultivar

identification and assessment of the genetic relationships between germplasm

in many plant species providing information about the genetic relationships

between individuals and species, and contributing on evolutionary and

ecological studies (Gepts, 1993; Weishing et al., 1995; Hillis et al., 1996).

With the advent of molecular markers, new generations of markers

have been introduced over the last two decades, which has revolutionized the

entire scenario of biological sciences. DNA-based molecular markers have

acted as versatile tools and have found their own position in various fields like

taxonomy, physiology, embryology, genetic engineering etc., they are no

longer looked upon as simple DNA fingerprinting markers in variability studies

or as mere forensic tools. The discovery of PCR was a landmark in this effort

and proved to be a unique process that brought about a new class of DNA

profiling markers. These DNA markers offer several advantages over

traditional phenotypic markers, as they provide data that can be analyzed

objectively (Joshi et al., 1999).

Properties desirable for ideal DNA markers are highly polymorphic

nature, co dominant inheritance, and frequent occurrence in genome, selective

neutral behavior, easy access (availability), easy and fast assay, high

reproducibility and easy exchange of data between laboratories (Joshi et al.,

1999).

Molecular markers have provided a powerful new tool for breeders to

search for new sources of variation and to investigate genetic factors

controlling quantitatively inherited traits. The molecular approach for

44

identification of plant varieties/genotypes seems to be more effective than

traditional morphological markers because it allows direct access to the

hereditary material and makes it possible to understand the relationships

between plants (Williams, et al., 1990, Paterson, et al., 1991).

The conservation of plant population and species is mostly concerned

with the number of genetic individuals present in population in order to assess

factors such as genetic drift, inbreeding depression and lack of mates in self-

compatible species (Barrett and Kohn, 1991). The breeders need to be able to

estimate the degree of relatedness between the existing materials. Germplasm

characterization and evolutionary process in viable population are important

links between the conservation and utilization of plant resources.

Conventionally, morphological characters like growth habit, leaf type, floral

morphology and fruit characters have been used to define the plant name.

Molecular techniques help researchers not only to identify the genotypes, but

also in assessing exploiting the genetic variability through molecular markers

(Whitkus et al., 1994).

AFLP (Amplified Fragment Length Polymorphism) technique was

introduced as a reliable and reproducible marker system (Vos et al. 1995). It

was preferred over other DNA-based markers mainly because of its high

multiple ratio and non requirement of prior sequence information (Breyne et

al., 1997). Another advantage of AFLP markers is its wide genome coverage

(Ellis et al. 1997; Zhu et al. 1998).

2.5. RAPD-PCR

Several PCR-based markers have been used to provide information on

genetic variation in plant species (Jones et al., 1997). A more recently

employed approach in plant systematic and population biology is RAPD

markers, a PCR-based technique. Although, earlier studies (Pan et al.,

1983,1995; Zhang et al., 1983; Li et al., 1987; Sheh and Su, 1987; Su and

Sheh, 1990; Cheng et al.,1993) have reported some results of research on

chemical, cytological, pollen morphological, ecological, geographical and

45

karyotypic characters of the species; neither the genetic diversity nor the

divergence were clear. The purpose of the present study is to assess genetic

diversity and divergence within and among population of the species using

RAPD markers and to compare the results with those obtained from allozymes.

Another important aim is to provide genetic data and a theoretical basis for

production of the species.

RAPD markers are based on the amplification of unknown DNA

sequences using single, short, random oligonucleotide primers, therefore,

RAPD polymorphism is the reflection of variation of the whole genomic DNA,

and would be a better parameter to measure the pattern of genetic diversity of

the rare and endangered plants (Jayaram and Prasad, 2008).

DNA fingerprinting techniques such as random amplified

polymorphic DNA (RAPD) (Williams et al., 1990) permit the identification of

taxa and the determination of phylogenetic relationships and intraspecific

diversity at a molecular genetic level. The use of such techniques for

germplasm characterization facilitates the conservation and utilization of plant

genetic resources, permitting the identification of unique accessions or sources

of genetically diverse germplasm. The ability of this method to distinguish

between taxa also has useful implication in botanical quality analysis.

PCR- based molecular markers have been widely used in many plant

species for identification, phylogenetic analysis, population studies and genetic

linkage mapping (Williams et al., 1990). The RAPD markers can also be used

in the study of the genetic variability of species or natural population

(Lashermes et al., 1993, Wilkie et al., 1993) and in the identification of

genotypes (Wilde et al., 1992, Koller et al., 1993, Wolff and Peters-Van Run

1993). For efficient conservation and management, the genetic compositions

of the species in different geographic locations need to be assessed. Due to

technical simplicity and speed, RAPD methodology has been used for diversity

analysis in many red listed plants (Li et al., 2002; Fu, et al., 2003, Padmalatha

and Prasad, 2006 a, b; 2007).

46

Studies pertaining to identification of morphological and

physiological variation based on extremely diversified geographical

distribution of Withania somnifera have been conducted by Atal and

Schawarting (1962). It was observed that an extreme degree of variability

existed in Withania somnifera with respect to growth habits and morphological

characteristics of plants in different parts of India and in other countries. It was

pointed out that the classification of Withania somnifera has been in

discriminately applied to a variety of dissimilar forms, and there is no report

that addresses the genetic variation among Withania species(Negi et al.,2000).

The problem encountered in the isolation and purification of DNA

specially from MAPS include degradation of DNA due to endonucleases, co-

isolation of highly viscous polysaccharides, inhibitor compounds like

polyphenols and other secondary metabolites which directly or indirectly

interfere with the enzymatic reactions. Moreover, the contaminating RNA that

precipitates along with DNA causes many problems including suppression of

PCR amplification (Pikkart and Villeponteau,1993), interfere with DNA

amplification involving random primers e.g.RAPD analysis and improper

priming of DNA templates during thermal cycle sequencing (Padmalatha and

Prasad, 2005).

The use of molecular techniques in genetic diversity studies supported

by the finding that evolutionary forces such as natural selection and genetic

drift produce divergent phylogenetic branching which can be recognized

because the molecular sequences on which they are based share a common

ancestor (Singh et al., 2006).

Total genomic DNAs were extracted from several populations of pine

species and amplified. RAPD markers was high sufficient in distinguishing

each of the species. Genetic relationships among eight pine species were

analyzed. The degree of band sharing was used to evaluate genetic distance

between species to construct a phylogenetic tree (Nkongolo et al., 2001).

47

2.6. DIVERSITY IN WITHANIA SPECIES

AFLP markers were employed to assess genetic variation among 35

genotypes of W. somnifera (Kashmiri and Nagori genotypes) and five

genotypes of W. coagulans (Negi et al., 2006). High percentage of

polymorphism was revealed among W. somnifera genotypes. Twenty-five

Withania genotypes were analyzed with the AFLP and SAMPL assay. Young,

unexpanded leaves were collected and lyophilized before

DNA extraction. All DNA extractions were done using the modified

CTAB procedure (Weishing et al., 1995). The AFLP procedure was performed

following the protocol developed by Vos et al., (1995) with minor

modifications (Das et al., 1999). All reagents required for AFLP analysis were

obtained from Life Technologies Inc, USA. SAMPL analysis was performed

using the procedure described by Singh et al. (2002).

AFLP analysis of the Withania species was performed. Seven primer

combinations were employed. All the primer combinations generated

amplification products in the size range of 50 to 400 bp. A typical AFLP

profile generated by employing the primer combination EACC and MCAG.

Both monomorphic and polymorphic bands were amplified with this primer

combination. Only unambiguous bands were analyzed. A total of 79 bands

were scored with this primer combination, of which 80% was polymorphic.

SAMPL assay was standardized for the Withania species by testing six

SAMPL primers in conjunction with several MseI primers. Stuttering of bands

was obtained with many primer combinations. Seven MseI primers were

utilized in combination with two SAMPL primers for analysis of genetic

diversity within the 25 Withania genotypes. This primer combination yielded a

total of 52 bands, of which 79% was polymorphic (Negi et al., 2006).

PCR and RFLP were used in order to authenticate Panax ginseng C.A.

Meyer (Korean ginseng) in different vegetable forms of ginseng commercial

products and to differentiate it from other Panax species and from some of

their adulterants. Useful amounts of DNA were extracted from the entire

48

considered sample. PCR amplification was made using 18df/28ccr primers.

For a total of 486 determinations (19 samples, 3 repetitions, 3 extraction

protocols, following PCR and restriction with 3 endonucleases), the molecular

analysis confirmed the presence of Panax species in 12 out of 19 samples

tested. (Serrone et al., 2006).

Molecular methods have been used to unequivocally allow the

authentication to genus Panax at species level and the results were not affected

by the nature. Compared with other methods that detect genome-wise

polymorphism simultaneously, such RAPD (Shaw and But, 1995), AP-PCR

and AFLP, the method applied, based on PCR followed by RFLP, is more

reliable for large scale screening of commercial products, is rapid and the

results are easily readable. The PCR amplification was performed on all

ginseng DNA samples using oligonucleotide primes 18df/28ccr (Serrone et al.,

2006).

At regional research laboratory, Jammu, a total of 10 selected 10 mer

primers (Operon Technologies) were used for PCR amplification in 20

accessions of W.somnifera for developing a RAPD profile. The amplification

products were separated according to their size by standardized horizontal

electrophoresis in 1.5% Agarose gels and stained with ethidium bromide. PCR

amplification was repeated twice to ensure the reproducibility of the DNA

profile with each of the primers analyzed.

AFLP markers to assess the genetic variation among 35 individuals of

W. somnifera and 5 individuals of W. coagulans, which is xerophytic in nature

and grows naturally in Baluchistan was carried out two distinct morphological

types of W. somnifera, namely Kashmiri and Nagori were identified and

employed AFLP markers to analyze the genetic variation among W. somnifera

individuals. Based on the AFLP data, an attempt has been made to estimate the

genetic similarity and identify genetic relationships within and between

Withania species (Negi et al., 2000).

49

Six phenotypic characters and three withanolide markers were assessed

in 25 accessions of Withania somnifera collected from different states of India

for studying genetic variability. The variability ranges observed at phenotypic

and chemotypic levels were polymorphic. Based on D2 values and PCA

(Principal Component Analysis) of phenotypic traits like plant height, no. of

branches/plant, no. of seeds/berry, root length, root diameter and root yield,

these 25 accessions were grouped in five clusters. The relative contribution of

each character towards genetic divergence was worked out (Kumar et al.,

2007).

50

MATERIALS AND METHODS

51

3. MATERIALS AND METHODS

In the present study on “Assessment of Genetic diversity on Withania

somnifera using Random Amplified Polymorphic DNA (RAPD) Analysis”

was employed to find out the phylogenetic relationship within the Withania

somnifera from different regions. The experimental procedures discussed

under the following heading.

3.1 SAMPLE PREPARATION

3.1.1 COLLECTION OF PLANT MATERIAL

3.2 BIOMETRIC OBSERVATIONS

3.3 DNA ISOLATION

3.4 QUALITY ASSESSMENT

3.5 FINGER PRINTING OF WITHANIA SOMNIFERA COLLECTION

USING RAPD MARKERS

3.5.1 PCR AMPLIFICATION

3.6 DATA ANALYSIS

3.6.1 DATA SCORING

3.6.2 CLUSTER ANALYSIS

52

3.1. SAMPLE PREPARATION

3.1.1. COLLECTION OF PLANT MATERIAL

The four varieties of W.somnifera collected from the different geographical

area were raised in the green house of Avinashilingam University during 2007-

2008.

Table.3.1. Withania somnifera used in the study

S.NO PARTS ORIGIN

1 Leaves Coimbatore (local)

2 Leaves Jowahar

3 Leaves Nagori

4 Leaves Poshita

3.2. BIOMETRIC OBSERVATIONS

Four varieties of Withania somnifera collected from different places of

India were planted in pots. The plants of same age were taken and the data

recorded for eleven morphometric traits: plant height, number of

branches/plant, number of leaves/plant, number of lateral roots, leaf area, seed

colour, seed coat colour, seed weight, root length(cm), shoot length(cm), dry

matter content, thousand seed weight, seed colour, and seed coat colour.

3.3. DNA ISOLATION

The fresh leaf sample was used and DNA was isolated following protocol

using CTAB (Doyle and Doyle, 1987) with some modifications. The protocol

standardized for DNA extraction from Withania somnifera is given below:

Fresh leaves of Withania somnifera were cut into pieces of

approximately 1mm size with sterile blade. The pre-chilled mortar and pestle

53

was used to grind the samples (200mg) with liquid Nitrogen. The frozen

powder was transferred in 1 mL of the extraction buffer (pH 8) into an

eppendorf tube. The extraction buffer and frozen powder were mixed well and

incubated at temperature 65˚ for 1 hour. After incubation the mixture was

cooled at room temperature and thereafter, equal volume of the mixture of

chloroform: isoamylalcohol (24:1) was added.

The mixture was centrifuged at 10,000rpm for 10min at 25˚C. The aqueous

phase was transferred to a fresh tube and treated with 10µl RNase (10mg/ml)

for 1 hour at 37˚C. It was thereafter centrifuged at 10,000 rpm for 10 min. The

aqueous phase was taken and 0.6 volumes of isopropanol added and stored at -

20˚C over night. Precipitated DNA was centrifuged at 10,000rpm for 20min.

Supernatant was decanted carefully and pellet washed with 70% ethanol. The

pellet was dried at 37˚C for 12min and dissolved in 30µl of 1XTE buffer.

3.4. QUALITY ASSESSMENT

DNA quantification and assessment of purity

The DNA yield per g fresh leaves was determined using a UV-VIS

spectrophotometer at 260nm and 280nm. The purity of DNA was determined

by calculating the ratio of absorbance at 260nm to at 280nm.

The concentration and purity of DNA was also determined by analyzing

the samples on 0.8% agarose gel. The known concentration of lambda DNA

(25, 50 and 100ng) was loaded along with the sample and visual quantification

was done based on the comparative intensities of the bands under UV

fluorescence. Quantification by visual comparison of the intensities of known

DNA concentration is a standard method of DNA quantification superior to

UV absorption method, as the purity of DNA can be assessed visually. The

presence of degraded DNA can be visualized only in agarose gels.

54

3.5. FINGER PRINTING OF WITHANIA SOMNIFERA COLLECTION

USING RAPD MARKERS

3.5.1. PCR AMPLIFICATION

Good quality DNA isolated from fresh leaves of Withania somnifera

was equalized for concentration and used for RAPD analysis using random

primers.

Thirty three random decamer primers (Operon Technologies, Inc.,

USA) were screened on template DNA from four cultivars as to identify those

giving good and scorable amplification products.

Thirty three oligonuclotide primers were finally selected for RAPD

analysis. Each reaction mixture (15µl) for PCR amplification consisted of 10X

Taq buffer, 10mM MgCl2, Taq polymerase, 2.5mM dNTPs, 0.5µM decamer

primer (Operon Technologies, Inc., USA) and approximately 50ng genomic

DNA template. The Thermocycler was programmed for an initial denaturation

step of 3 min at 94°C, followed by 30 cycles of 45 second at 94°C, annealing

step of 1min at 37°C, extension was carried out at 72°C for 1min and final

extension at 72°C for 7min and a hold temperature of 4°C at the end. PCR

products were loaded onto 2% agarose gel and stained with ethidium bromide.

Gels with amplified fragments were visualized and photographed under UV

light using Alpha Digidoc.

3.5. SOFTWARE ANALYSIS

3.5.1. DATA ANALYSIS

Data Scoring

Clearly resolved, unambiguous polymorphic bands were scored visually

for their presence or absence with each primer. The scores were obtained in

the form of a matrix with ‘1’ and ‘0’, which indicate the presence and absence

of bands in each genotype respectively.

55

3.5.2. CLUSTER ANALYSIS

The binary data scored was used to construct a dendrogram. The genetic

associations between varieties were evaluated by calculating the Dice

Similarity coefficient for Pair-wise comparisons based on the proportions of

shared bands produced by the primers (Nei and Li, 1972). Similarity matrix

was generated using the NTSYS-pc software, version 2.02 (Rohlf, 1998). The

similarity coefficients were used for cluster analysis and dendrogram was

constructed by the Unweighed Pair-Group Method for Arithmetic average

(UPGMA) (Sneath and Sokal, 1973).

56

RESULTS AND DISCUSSION

57

4.0. RESULTS AND DISCUSSION

The present study entitled "Assessment of Genetic diversity on Withania

somnifera using Random Amplified Polymorphic DNA (RAPD) Analysis" was

aimed to assess the genetic variation among Withania somnifera collections. The

results of the study are resented and discussed under the following headings.

4.1. DIVERSITY ANALYSIS ON MORPHOLOGICAL

CHARACTERISTICS

4.1.1. Quantitative trait variability

4.1.2. Qualitative trait variability

4.1.3. Descriptive statistics

4.2. QUALITY ASSESSMENT

4.3. GENETIC DIVERSITY ANALYSIS USING RAPD MARKERS

4.4. CLUSTER ANALYSIS BASED ON MORPHOLOGICAL TRAITS

4.5. CLUSTER ANALYSIS BASED ON RAPD MARKERS

4.6. COMPARISON OF DISSIMILARITY MATRIX DERIVED FROM

MORPHOLOGICAL AND RAPD MARKER DATA

58

4.1. DIVERSITY ANALYSIS ON MORPHOLOGICAL TRAITS

The four varieties of W.somnifera collected from the different geographical

area were raised in the green house of Avinashilingam University during Rabi

– 2007- 2008 season. Therefore, observed variation could be largely genetic.

The evaluation of W.somnifera germplasm showed a large variation in the

quantitative (Table 4.1).

4.1.1. Quantitative trait variability

The mean values of 11 morphological traits for 4 varieties of Withania somnifera

are presented in table 4.1.

Plant height

The plant height ranged from 18.6cm (Poshita) to 21.7cm (Coimbatore). The

general mean of the variety was 20.95 and two varieties exceed the general

mean (Table 4.1).

Root length

The root length ranged from 4.7cm (Coimbatore) to 10cm (Nagori). The

general mean of the variety was 6.57 and one variety (Nagori) exceed the

general mean (Table 4.1).

Shoot length

The shoot length ranged from 13cm (Nagori) to 17cm (Coimbatore).

The general mean of the variety was 14.37 and one variety (Coimbatore)

exceed the general mean (Table 4.1).

Number of branches per plant:

The Jawahar variety had minimum 9 branches and Coimbatore had maximum

13 branches. The general mean of variety was 11 numbers and two varieties

exceed the general mean (Table 4.1).

59

Number of leaves per plant

The numbers of the leaves was lowest for Jawahar (10) and the highest

for Coimbatore (17). The general mean of variety was 13 numbers and two

varieties exceed the general mean (Table 4.1).

Leaf area

The Poshita had minimum leaf area (5.98cm2) and Jawahar had maximum leaf

area (11.2 cm2). The general mean of variety was 8.02 and two varieties

exceed the general mean (Table 4.1).

Number of lateral roots

The number of lateral root ranged from 2 (Nagori) to 6 (Coimbatore). The

general mean of the variety was 4 and one variety (Coimbatore) exceed the

general mean (Table 4.1).

Dry matter content

The total dry matter content was lowest for Coimbatore (0.22) and

highest for Poshita (0.25). The general mean of the variety was 0.235 and two

varieties exceed the general mean (Table 4.1).

Thousand Seed weight (g)

It ranged from 1.8 (Jawahar) to 2.0 (Poshita and Nagori), the two genotypes

Poshita and Nagori expressed significantly highest seed weight (Table 4.1).

60

Plate 4. 1 Withania somnifera plants used in the study

61

Table 4.1 Morphological Traits for the Four Varieties of

Withania Somnifera

MORPHOLOGICAL

TRAITS

COIMBATORE

(local)

JAWAHAR

NAGORI POSHITA

Plant height (cm) 21.7 20.5 23 18.6

Root length (cm) 4.7 6.5 10 5.1

Shoot length (cm) 17 14 13 13.5

No. of Branches 13 9 12 10

No. of Leaves 17 10 14 11

Leaf Area 6.4 11.2 8.5 5.98

No. of Lateral roots 6 4 2 4

Dry matter content 0.22 0.24 0.23 0.25

Thousand seed weight

1.9 1.8 2.0 2.0

Seed colour

1 2 3 2

Seed coat colour

1 2 1 1

Legend for table 4.1

QUALITATIVE

TRAITS

NUMBER NAME

62

Table 4.2 Descriptive statistics of quantitative traits

Seed colour 1

2

3

Yellowish orange

Light brown

Yellowish brown

Seed coat colour 1

2

Orange red

Orange

Plant

height

(cm)

Root

length

(cm)

Shoot

length

(cm)

No. of

Branches

No. of

Leaves

Leaf

Area

No. of

Lateral

roots

Dry

matter

content

Seed

weight/1000

Mean 20.95 6.57 14.37 11 13 8.02 4 0.23 1.92

Standard

Error

0.93 1.2 0.89 0.91 1.58 1.19 0.81 0.01 0.04

Standard

Deviation

1.87 2.41 1.79 1.82 3.16 2.38 1.63 0.01 0.09

Sample

Variance

3.50 5.8 3.22 3.33 10 5.7 2.66 0.0001 0.009

Range 4.4 5.3 4 4 7 5.22 4 0.03 0.2

Minimum 18.6 4.7 13 9 10 5.98 2 0.22 1.8

Maximum 23 10 17 13 17 11.2 6 0.25 2

63

4.1.2. Qualitative traits

All the four varieties of the Withania somnifera were evaluated for two

qualitative traits and are presented in table 4.1. The genotypes of Withania

exhibited significant degree of genetic variation for the traits were observed.

In the case of seed colour two varieties were found to possess light brown

colour and remaining were found to possess yellowish orange and yellowish

brown. Likewise, three varieties of Withania found to possess orange red

colour seed coat and one variety found to possess orange colour seed coat.

A graphical representation of morphological variation among Withania

in figure 4.2.The highest variation for plant height was observed for Nagori and

Poshita. For the root length, maximum variation was observed between Nagori

and Coimbatore as compared to other varieties. The variation in shoot length

character between Coimbatore and Nagori was high as compared to other

varieties. Variation between Coimbatore and Jawahar was relatively high for

total number of branches and number of leaves as compared to other varieties.

For leaf area highest variation was observed between Jawahar and Nagori. For

lateral roots variation was shown between Coimbatore and Nagori as compared

to other varieties. For seed colour variation was shown between Nagori and

Coimbatore as compared to other varieties.

4.1.4. Descriptive statistics

The data recorded on nine quantitative characters were subjected to descriptive

statistics of quantitative traits such as mean, and measure of dispersion (Range,

64

0

5

10

15

20

25

Plant height Root length Shoot length Number of

branches

Number of

leaves

Leaf area Number of

lateral roots

Dry matter

content

Seed weight Seed colour Seed coat

colour

Fig. 4.1 Morphological traits for four varieties of Withania somnifera

Coimbatore Jawahar Nagori Poshita

variance, standard deviation, standard error and coefficient of variation). The

descriptive statistics of the quantitative traits is presented in table 4.2.

Mean

Among all the characters the highest mean value was recorded by plant height

(20.95) and the least value by total dry matter content (0.23).

Range

The highest range was exhibited by number of leaves (7) and the least value by

total dry matter content (0.03).

Variance

The maximum value of variance was shown by number of leaves (10) and the

least value by total dry matter content (0.0001).

65

4.2. DNA ISOLATION

The extraction of DNA carried out as described in experimental procedure was

found to be satisfactory. DNA recovery varied widely with varying of leaves.

DNA obtained from recently matured leaves was high quality. Amplifiable

DNA was isolated from 200mg of leaf sample using 1ml of 2% extraction

buffer, 4% PVP, this resulted in good quality, high molecular weight DNA.

4.3. QUALITY ASSESSMENT

DNA quantification and assessment of purity

DNA samples were quantified in spectrophotometer at 260nm.The A 260/280

ratio ranged from 1.62 to 1.7. A ratio less than 1.8 indicates high purity DNA.

Presence of proteins or RNA might give a value >1.8 (Sambrook et al., 1989).

The use of pooled samples has been proved efficient in genetic variation

studies. Total DNA isolation from fresh leaves and dried powders of fruits of

E. officinalis, T. belerica, and T. chebula was carried out and the isolated DNA

had normal spectra in which the A 260/280 ratios were 1.7 indicates insignificant

levels of contaminating proteins and polysaccharides (Warude et al., 2003).

Table 4.3 DNA RATIOS

280nm 260nm SAMPLE

0.140 0.240 Coimbatore

0.109 0.174 Jawahar

0.420 0.720 Nagori

0.200 0.324 Poshita

66

The total DNA isolated from fresh leaves of Withania somnifera was

quantified by means of agarose gel electrophoresis (0.8%).Fig 4.2 shows W1

and W4 have quantity of DNA compared to W2 and W3 comparable to 100ng

and 25ng of standard DNA respectively.

Fig. 4.2 DNA quantification of Withania somnifera samples

4.4. GENETIC DIVERSITY ANALYSIS USING MOLECULAR

MARKER

In the present study, four varieties were evaluated for genetic diversity using

RAPD markers.

4.4.1. RAPD Analysis

All the thirty three RAPD markers that were employed in the present study to

detect the genetic relationship within the Withania genotypes fail to generate

amplification product. Instead 9 RAPD primers i.e., OPO 13, OPR13, OPO20,

W1 W2 W3 W4

λ1 - 25ng DNA W1 - Coimbatore (local)

λ2 - 50ng DNA W2 - Jawahar

λ3 - 100ng DNA W3 - Nagori

W4 - Poshita

λ1 λ2 λ3 W1 W2 W3 W4

67

OPO09, OPO08, OPO10, OPB04, OPE09, OPM02 were found to be resulted

with amplification products.

Analysis of four varieties of Withania somnifera revealed 74.37% of

polymorphism as presented in Table 4.5. A total of 67 bands were scored for

the nine RAPD primers out of which 57 bands are polymorphic with number of

bands ranging from 3 to 11, corresponding to an average of 7.4 bands per

primer. Percentage of polymorphic bands ranged from 60 to 87.5%. The

primer with maximum number of polymorphic bands is OPO 20 (11alleles)

and minimum with OPO 13, OPO 09 and OPE 09 (3 allele). The dendrogram

was drawn, based on the Genetic Distance from RAPD data.

The average percentage of polymorphisms i.e., 74.37% was found to be

relatively higher when compared to the other endangered species, stating that it

should be able to adapt to the environmental variations.

Fig. 4.3 RAPD profile using primer OPO 13

OPO 13 1300bp

OPO 13 800bp

1Kb ladder W1 W2 W3 W4

68

Fig. 4.4 RAPD profile using primer OPR 13

Fig. 4.5 RAPD profile using primer OPO 20

OPO 20 500bp

1Kb ladder W1 W2 W3 W4

OPO 20 700bp

OPR 13 1000bp

OPR 13 900bp

1Kb ladder W1 W2 W3 W4

69

Fig. 4.6 RAPD profile using primer OPO 08

Fig. 4.7 RAPD profile using primer OPO 09

1Kb ladder W1 W2 W3 W4

OPO 08 1000bp

OPO 08 700bp

1Kb ladder W1 W2 W3 W4

OPO 09 1500bp

OPO 09 900bp

70

Fig. 4.8 RAPD profile using primer OPO 10

Fig. 4.9 RAPD profile using primer OPB 04

1Kb ladder W1 W2 W3 W4

OPO 10 1000bp

OPO 10 700bp

OPB 04 190bp

1Kb Ladder W1 W2 W3 W4

71

Fig. 4.10 RAPD profile using primer OPE 09

Fig. 4.11 RAPD profile using primer OPM 02

1Kb ladder W1 W2 W3 W4

OPE 09 100bp

1Kb ladder W1 W2 W3 W4

OPM 02 140

72

Table 4.4 Data Matrix

OPO 13 W1 W2 W3 W4

OPO 13 1 1 1 1

OPO 13 1 0 1 1

OPO 13 1 1 1 1

OPO 13 0 1 0 0

OPO 13 1 1 0 0

OPR 13 1 1 0 1

OPR 13 1 0 0 0

OPR 13 1 1 1 1

OPR 13 1 0 1 1

OPR 13 1 1 0 0

OPR 13 0 0 1 1

OPR 13 1 1 1 1

OPR 13 1 1 1 1

OPR 13 1 1 1 0

OPO 20 1 0 0 1

OPO 20 1 1 0 0

OPO 20 1 1 0 1

OPO 20 1 1 1 1

OPO 20 0 0 0 1

OPO 20 0 1 0 0

OPO 20 1 0 0 1

OPO 20 0 1 0 0

OPO 20 1 0 1 1

73

OPO 20 1 0 0 0

OPO 20 1 1 1 1

OPO 20 1 1 0 1

OPO 20 1 1 0 1

OPO 08 1 1 1 1

OPO 08 0 0 1 0

OPO 08 1 1 0 1

OPO 08 1 1 0 0

OPO 08 1 1 1 1

OPO 08 1 1 0 0

OPO 08 1 1 0 0

OPO 08 0 0 1 0

OPO 08 0 1 0 0

OPO 09 1 1 0 0

OPO 09 1 1 1 1

OPO 09 0 0 1 1

OPO 09 1 0 1 1

OPO 10 0 0 0 1

OPO 10 1 1 0 0

OPO 10 1 1 1 1

OPO 10 0 0 1 0

OPO 10 1 1 0 0

OPB 04 1 1 1 1

OPB 04 0 0 1 1

OPB 04 0 1 1 0

OPB 04 0 0 1 0

OPB 04 1 1 0 0

74

OPB 04 0 1 0 0

OPB 04 0 1 1 1

OPB 04 0 1 1 1

OPE 09 0 1 1 1

OPE 09 0 1 1 1

OPE 09 0 1 1 0

OPE 09 1 1 1 1

OPE 09 1 1 1 1

OPM 02 1 1 1 1

OPM 02 1 1 1 1

OPM 02 1 1 1 0

OPM 02 1 0 0 0

OPM 02 1 1 1 0

OPM 02 1 1 1 0

OPM 02 1 0 1 0

OPM 02 1 0 1 0

OPM 02 0 0 1 0

Table 4.5 Polymorphism in Withania Somnifera Using nine

RAPD Markers

Polymorphism

(%)

No. Of

Polymorphic

Bands

No. Of

Bands 5' To 3' Code S.No

60.00 3 5 GTCAGACTCC OPO 13 1

66.66 6 9 GGACAACGAG OPR 13 2

84.62 11 13 ACACACGCTG OPO 20 3

75

77.77 7 9 CCTCCAGTGT OPO 08 4

75.00 3 4 TCCCACGCAA OPO 09 5

80.00 4 5 TCAGAGCGCC OPO 10 6

87.50 7 8 GGACTGGAGT OPB 04 7

60.00 3 5 CCAAGCTTCC OPE 09 8

77.77 7 9 ACAACGCCTC OPM 02 9

4.5. CLUSTER ANALYSIS BASED ON MORPHOLOGICAL TRAITS

4.5.1 Dissimilarity Index

The Euclidean distances computed for the morphological traits are

presented in the table 4.6. The dissimilarity coefficients based on

morphological traits ranged from 1.81 to 3.12. Among the 4 varieties the

highest dissimilarity index (3.12) was observed between Coimbatore (local)

and Jawahar and the lowest dissimilarity index (1.81) was observed between

Poshita and Jawahar.

4.5.2 Clusters based on Dendrogram

Agglomerative hierarchical clustering performed on the Euclidean

distance matrix utilizing the Ward’s linkage method and the resulting

dendrogram is presented in Fig 4.10. The two clusters along with the varieties

included are presented in Table 4.7. The maximum number of varieties was

included in cluster II having 3 varieties and the minimum number in cluster I.

The cluster I consisted of Coimbatore. The cluster II consisted of Jawahar,

Poshita, and Nagori. The cluster pattern revealed that the cultivated varieties

have minimum divergence indicating their close relationship. The second

cluster include all the three cultivated varieties conclude that there is no

relationship between genetic divergence and geographical origin, supporting

the report presented by earlier workers (Stebbins, 1960., Rao et al., 1980).

76

4.6. CLUSTER ANALYSIS BASED ON RAPD MARKER

4.6.1 Similarity Index

The binary data from the polymorphic primers were used for computing

Jaccard’s similarity indices. The similarity index values obtained for each pair

wise comparison among the 4 varieties and presented in the Table. 4.8. The

similarity coefficients based on 9 RAPD markers ranged from 0.43 to 0.61.

Among the 4 varieties the highest similarity index (0.61) was observed

between Coimbatore and Jawahar and the lowest similarity index (0.43) was

observed between Nagori Vs Coimbatore and Nagori Vs Jawahar.

4.6.2 Clusters based on Dendrogram

The similarity values obtained for each pair wise comparison of 9

RAPD markers among the 4 Withania somnifera varieties were used to

construct dendrogram based on Jaccard’s coefficient and the results are

presented in Fig. 4.11. The 4 varieties formed 2 clusters at nearly 61%

similarity levels. The cluster I consisted of Coimbatore and Jawahar. The

cluster II consisted of Nagori and Poshita. There is a nearly close similarity of

61% between Coimbatore and Jawahar which clearly depict that genetically

they are more or less similar and might share a few genetic traits amongst

others. It can be inferred that Nagori and Poshita exhibited a genetic similarity

of 55% showing less similarity among them.

In the banding pattern of Withania somnifera in primer OPO 13, Fig 4.3

Coimbatore and Jawahar varieties showed the allele OPO 13 800 was present

and was not found in other two varieties Nagori and Poshita.Likewise, in

primer OPR 13900 W3 and W4 (Nagori and Poshita) were showing higher

variation at 900bps which were not found in other two varieties (Coimbatore

and Jawahar). Also, in the primer OPO 20, the W2 (Jawahar) was showing

higher variation at OPO 13 700bp which were not found in other varieties from

other species up to OPO 13 200bp.

77

The banding pattern of the plant in primer OPO 08, the W2 (Jawahar) was

showing higher variation at OPO 08 700 allele was not amplified in other

varieties. And also, in primer OPO 09, the W2 (Jawahar) was showing higher

variation at OPO 09 1500 which was not amplified in other varieties. In the

primer OPO 10, the W2 (Jawahar) was showing higher variation at OPO 10 700

which was not found in other three varieties.

The percentage of polymorphism was found to be 49.61% for eight

varieties of O.indicum stated that the genetic difference among the varieties is

due to the result of biotic or climatic and biotic factors (Jayaram and Prasad,

2008). They also show that the species genetic diversity among this O.

indicum by itself is low, but relatively higher when compared to other

endangered species and it should be able to adapt to the environmental

variation.

Table 4.6 Dissimilarity index computed for the morphological

traits

POSHITA NAGORI JAWAHAR COIMBATORE

0 COIMBATORE

0 3.12 JAWAHAR

0 2.29 2.7 NAGORI

0 2.29 1.81 2.56 POSHITA

Table 4.7 Clusters Based On Morphological Traits Dendrogram

CLUSTER

NO.

NO. OF

VARIETIES

LIST OF VARIETIES

INCLUDED

I 1 Coimbatore

II 3 Nagori, Poshita and Jawahar

78

Fig 4.12 Dendrogram of withania somnifera genotypes based

Morphological traits

Similarity Coefficient

2.09 2.38 2.66 2.95 3.23

COIMBATORE

JAWAHAR

POSHITA

NAGORI

Table 4.8 Similarity index computed for the RAPD markers

COIMBATORE JAWAHAR NAGORI POSHITA

COIMBATORE 1

JAWAHAR 0.61 1

NAGORI 0.43 0.43 1

POSHITA 0.49 0.44 0.55 1

79

Table 4.9 Custer analysis based on RAPD markers

Dendrogram

CLUSTER

NO.

NO. OF

VARIETIES

LIST OF VARIETIES

INCLUDED

I 2 Coimbatore, Jawahar

II 2 Nagori, Poshita

Fig 4.13 Dendrogram of withania somnifera genotypes based on

the RAPD markers

Coefficient

0.45 0.49 0.53 0.57 0.61

Coimbatore

Jawahar

Nagori

Poshita

80

4.7. COMPARISON OF DISSIMILARITY MATRIX DERIVED FROM

MORPHOLOGICAL AND RAPD MARKER DATA

The product- moment correlation (r) and the Mantel test statistic (Z) were

calculated to measure the degree of relationship between the dissimilarity

matrixes generated from morphological and RAPD marker data. The matrix

correlation value ‘r’ was 0.68977 for morphological and RAPD data and

Mantel t value 1.6543.

The extent of agreement between the dendrograms derived from morphological

and RAPD data was analyzed using Mantel matrix correspondence test. In the

present investigation, the correspondence between the dissimilarity matrix

generated by RAPD data and morphological data was evaluated by calculating

product-moment correlation (Mantel’s test). There was no close

correspondence between the dissimilarity matrix of RAPD and morphological

data. There was very low correlation (r=0.68977(p<0.9510)). A similar

disparity has been reported in rye grass (Roldan-Ruiz et al., 2001) and taro

(Okpul et al., 2006). The lower agreement between phenotypic and molecular

distances may be due to the fact that the variation observed at RAPD level

might have not been expressed at phenotypic level. Limited numbers of

markers were analyzed in this study and the distribution of the markers studied

was enough to cover the whole genome of Withania as well as there is a

considerable effect of environment on morphological traits, thus there is less

agreement between the diversity pattern of phenotypic traits and molecular

markers.

81

SUMMARY AND CONCLUSION

82

5.0. SUMMARY AND CONCLUSION

Genetic diversity is essential for the continued progress in breeding as well

as adaptation to future environmental challenges. Assessment of genetic

diversity and identification of superior genotypes are important prerequisites

for a successful crop improvement program. Genetic diversity in crop plants

can be measured using various tools such as morphological, biochemical and

DNA based markers. The present study was conducted with an objective to

assess the genetic diversity and marker association study among four Withania

somnifera varieties using morphological as well as RAPD markers.

1. A wide range of variation was noticed for nine quantitative and two

qualitative traits and this indicated the existence of morphological

diversity in the selected varieties.

2. Four varieties were grouped into two clusters based on morphological

traits using PCA and hierarchical cluster analysis.

3. Genetic diversity was assessed using a set of nine primers. RAPD

primers used in this study produced 57 percentage of polymorphism.

4. Dendrogram was constructed using Jaccard's similarity coefficient and

the selected varieties were grouped into two clusters based on RAPD

markers.

5. Mantel statistics indicated the lack of correspondence r=0.68977

between the dissimilarity matrices of RAPD and morphological data.

6. Significant geographical patterns of variation were found in this work.

7. The clustering pattern of varieties also indicates that there was a wide

genetic diversity between the different Withania somnifera varieties.

83

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APPENDICES

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APPENDIX I

• Extraction buffer /CTAB buffer

2% CTAB

100 mM Tris HCl pH 8

20 mM EDTA disodium salt

1.4M NaCl

4 % PVP

β-Mercaptoethanol – 2µl

• ‘WET ‘ Chloroform :

Chloroform: Isoamyl alcohol (24:1)

• RNAse:

10mg/ml was prepared, kept in water bath for 15 min and then

stored at -20°C.

• Wash buffer:

10mM Ammonium acetate

76% Ethanol.

• TE Buffer:

10mM Tris Hcl pH 7.4

1mM EDTA (disodium salt)

• 5X TBE:

53.9 g Tris base

27.6 g Boric acid

9.3 g EDTA

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APPENDIX II

DNA ELECTROPHORESIS IN AGAROSE GEL ELECTROPHORESIS

(Maniatis et al., 1982)

DNA can be checked for size, intactness, homogeneity and purity by this

technique.

Principle

Agarose forms a gel by hydrogen bonding and the gel pore size depends

on the agarose concentration. The DNA molecules are separated by

electrophoresis on the basis of their size, shape and magnitude of net charge on

the molecules. The dye ethidium bromide intercalates between the bases of

RNA and DNA and fluorescence orange when irradiated with UV light. Low

concentration agarose gels with large pore permit fractionation of high

molecular weight molecules and vice versa.

TBE Buffer:

Tris Borate buffer (TBE) – 1X

0.9 M Tris HCl

0.025M EDTA (disodium salt)

0.9M Boric acid

Agarose:

Agarose - 0.8 % w/v in TBE 1X

Tracking dye:

10mM Tris HCl (pH 7.6)

0.03% Bromophenol blue

0.03% Xylene cyanol FF

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60mM EDTA

60% Glycerol

Ethidium Bromide (0.1mg/ml)

PROCEDURE

• The agarose gel is prepared by dissolving 2.0g in 100ml of 1X TBE

buffer and was kept in oven until it is completely dissolved (3 min).

• When the temperature was around 60˚C, 50µl of EtBr was added

to the solution and mixed well.

• The gel was poured to the cleaned and sealed gel template

arranged with the suitable comb. Air bubbles were removed if

formed. The gel was allowed to polymerize.

• The gel along with the template and seal removed was placed in

the electrophoresis tank which was previously filled with 1X TBE

buffer.

• About 3µl of the genomic DNA with 2µl of loading dye was

loaded into the wells.

• Hind III digest/ λ DNA marker is added to the lane parallel to the

unknown samples. The bands observed can be compared to those

of the unknown in order to determine their size. The distance a

band travels is approximately inversely proportional to the

logarithm of the size of the molecule.

• The gel was allowed to run at 5V/cm for 45 min. It was then

documented under UV Transilluminator.

95

96