My thesis

GENETIC STUDY OF SEED DORMANCY IN RICE
VARIETIES OF NEPAL



A Project Report
Submitted for the partial fulfillment of the requirements of
The Bachelor’s Degree in Biotechnology.


By
Mukesh Maharjan


The Department of Biotechnology,
SANN International College, Purbanchal University.

August 2010
ii


COPYRIGHT

The author hereby declares that the work assembled herein is a genuine under the
supervision of the Dr. Jwala Bajracharya, Nepal Agricultural Research Council (NARC),
Seed Science and Technology Division, Khumaltar. The work presented here has not been
published or submitted elsewhere for the requirement of any degree program. Any
literatures, protocols, figures that are used are duly referenced.
The author has agreed that the SANN International College, Department of
Biotechnology, Gairhidhara may make this report freely available for inspection.
Moreover, the author has agreed that permission for copying of this project report for
scholarly purpose may be granted by the supervisor of this project recorded herein or, in
their absence, by the head of the department wherein the project report was done. It is
understood that the recognition will be given to the author of this report and to the SANN
International College, Department of Biotechnology, Gairhidhara in any use of the material
of this project report. Copying or publication or other use of this project report for
financial gain without approval of the Department of Biotechnology, Gairhidhara SANN
International College and author’s written permission is prohibited.
Request for permission to copy or to make any other use of the material in this
report in whole or in part should be addressed to:

Head
Department of Biotechnology
SANN International College.
Gairhidhara, Kathmandu.
Nepal.

iii



I Dr. Jwala Bajracharya hereby declare that the work assembled here in by Mr. Mukesh
Maharjan is doneunder my supervision at Seed Science and Technology Division, Nepal
Agricultural Research Council (NARC), Khumaltar, Lalitpur. I have read, and recommend
to the Department of Biotechnology, Purbanchal University for acceptance of this project
report, entitled “Genetic Study of Seed Dormancy in Rice Varieties of Nepal”, for the
partial fulfillment of the requirements for the degree of Bachelor in Science (B.Sc.) in
Biotechnology.
CERTIFICATE







Supervisor
Jwala Bajracharya, Ph.D.
(Senior Scientist)
Seed Science and Technology Division,
Nepal Agricultural Research Council (NARC).
Khumaltar, Lalitpur.



iv



Approved by
















Date: August 1, 2010.

Supervisor
Jwala Bajracharya, Ph.D.
(Senior Scientist)
Seed Science and Technology Division,
Nepal Agricultural Research Council (NARC).
Khumaltar, Lalitpur.

Head of Department
Mukunda Ranjit, Ph.D.
Department of Biotechnology,
SANN International College.
Gairhidhara, Kathmandu.
v


ACKNOWLEDGEMENTS


First and foremost, I express my sincere gratitude to my supervisor, Dr. Jwala Bajracharya,
who has supported me throughout my thesis with her patience and knowledge. Above all
and the most needed, she provided me constant encouragement and support in various
ways, which exceptionally inspired and enriched my growth as a student. I could not have
got a better or friendlier supervisor than her. I am indebted to her more than she knows.

It is my pleasure to pay tribute also to the National Agricultural Research Council
(NARC), specially seed testing laboratory and biotechnology laboratory for providing me
the permission to carry out my project work.

During my project, I have worked with a great number of people, whose
contribution in various ways to the research and the preparing the report deserves special
mention. It is a pleasure to convey my gratitude to them all in my humble
acknowledgment. I gratefully acknowledge Er. Sanjeev Maharjan for his crucial
contribution in providing me the access to almost all the research papers I was in need,
which made him a backbone of this project and so to this report. His involvement and
encouragement has triggered and nourished my intellectual maturity that I will benefit
from, for a long time to come.

I am much indebted to Mr. SarbottamPiya for his valuable advice in science
discussion, guidance in statistical analysis and furthermore, using his precious times to
read this report and gave his critical comments about it. I am equally thankful to Mrs.
SailejaShrestha for her amiable assistance throughout my laboratory works. She was
always there for me when I had a problem while working with microsatellite primers. I
gratefully thank Mr. Sanish Maharjan for his precious help throughout my project by
providing me many materials and suggestions. In addition, thank you to Hari Krishna
vi


Upreti, who provided me the information of the rice samples, and Dr. Uma Shankar shah,
for providing a computer access. I express my deep gratitude to Mrs. BinaDangol and
other staffs of NARC Agricultural Botany Division(ABD) and Biotechnology Unit, for
their cordial help and support.

I was also much benefited by the help of Mrs. AnjanaDevkota, who also provided
me with NTSYSpc software. It is my pleasure to co-work with my colleagues, Bijaya
Kumar Sharma, PremBhat, and ChandanKarmacharya, with the sharing of ideas, time and
precious views.

My sincere thank also goes to Dr. PromodAryal, for his advice and willingness to
share his bright thoughts with me, which were very commendable and provided me the
understanding of future prospects of my work.

I was very fortunate to have my report reviewed and edited by Mr. Mahesh Raj
Maharjan and Mr. Robin Maharjan, who pointed out many of the common mistakes I made
while writing and gave invaluable suggestions.

Lastly, I would like to express my deepest gratitude to my family members, friends
and all the staffs and lecturers of SANN International College. Finally, I would also
appreciate suggestion for the further improvement in future.

vii


Abstract

Seed dormancy in rice, Oryza sativa L., is an important trait related to the quality of seed
in rice production. This trait is valuable particularly in tropical and sub-tropical areas of
Nepal where rains frequently occur during the harvesting period and results pre-harvest
sprouting (PHS). Non-dormant varieties often germinate in situ under such conditions,
especially when the crop lodges into standing water. The traditional method of seed
selection by farmers in Nepal is generally based on qualitative traits of grains and not the
physiological traits selecting the dormant seeds. This study deals with the diversity and
molecular assay of the rice varieties for seed dormancy using the simple sequence repeat
(SSR) or microsatellite markers.
To study the genetic behavior of rice seed dormancy, eight microsatellite molecular
markers were analyzed in 46 rice varieties, which included 29 terai and 17 hill varieties. A
total of 41 alleles were identified with these eight SSR loci. The numbers of alleles varied
from 4 at one locus, to an intermediate value of 5 at five loci and to a high of 6 at two loci.
The number of alleles per locus therefore ranged from 4 to 6 with an average of 5.1. The
number of alleles detected at a locus was significantly correlated with the number of
simple sequence repeats in the targeted microsatellite DNA. All loci were polymorphic and
were informative with average PIC value 0.76 and the most informative among these was
RM128. The average PIC value was higher in the total varieties than in separate groups as
terai and hill varieties; and, as released, pipeline and local varieties. Released varieties, as
expected, had the highest PIC value of 0.72 amongst all the groups. This may be due to the
various genetic make-ups and breeding methods used during the improvement programs at
NARC. The cluster analysis and principle component analysis (PCA) showed consistency
in explaining the relationship among the rice varieties. The results showed that, in general,
the hill varieties were less dormant than the terai varieties. However, the landraces were
found to have intermediary character between the highly dormant and highly sprouting
trait. Pipeline varieties were found to possess high dormancy, based to these marker
viii


analyses. This study of rice seed dormancy could be used in breeding program, in
improvement of the rice varieties and in genetic diversity studies selecting the rice
genotypes for desirable level of dormancy. However, this marker study needs to be
correlated with the physiological study of seed dormancy using normal germination testing
and needs to be worked with many more markers.

ix


TABLE OF CONTENTS

Heading Page i
Copyright ii
Certificate iii
Approved by iv
Acknowledgements v
Abstract vii
Table of Contents ix
List of Figures xi
List of Tables xiii
Acronyms and abbreviation xiv


1. Introduction 1
1.1 Background: 1
1.2 Objective: 4
1.2.1 Main objective: 4
1.2.2 Specific Objectives: 4
2. Literature Review 5
2.1Biosystematics of rice plant: 5
2.1.1Taxonomy 7
2.2 The rice genome 7
2.3 Rice: The Model Monocot Plant 8
2.4 Seed dormancy: 10
2.5 Causes of dormancy 11
2.5.1 Primary dormancy: 13
2.5.1.1 Exogenous primary dormancy: 13
2.5.1.2 Endogenous primary dormancy: 15
2.5.2 Secondary dormancy: 16
2.6 Breaking the dormancy of seed: 16
2.6.1 Mechanical scarification: 16
2.6.2 Chemical scarification: 17
2.6.3 Dry After-ripening: 17
2.6.4 Pre-chilling: 18
2.6.5 Light: 18
2.6.6 Growth regulators: 18
2.6.7 Nitrate: 19
2.6.8 Sealed polyethylene envelops 19
2.7 Dormancy in rice: 19
2.8 Molecular markers: 21
x


2.8.1 Microsatellites DNA: 22
2.8.1.1Microsatellites as the molecular markers: 24
2.8.1.2 Microsatellite and other markers: 26
2.8.2 Seed dormancy study by Microsatellite markers in rice: 27

3. Materials and Methods 31
3.1 Materials: 31
3.1.1 Research site: 31
3.1.2 Plant material: 31
3.2 Methodology: 34
3.2.1 DNA extraction: 34
3.2.2 Microsatellite marker: 34
3.2.3 PCR amplification: 35
3.2.4 PCR product separation and microsatellites visualization: 35
3.2.5 Statistical analysis: 36
3.2.5.1Simpson index 36
3.2.5.2 Cluster Analysis 36
3.2.5.3 Principal Component Analysis (PCA) 37

4. Result 38
4.1 seed dormancy behavior shown by molecular marker analysis: 38
4.2 Microsatellite DNA polymorphism: 39
4.3 Cluster analysis: 43
4.4 Principal component analysis (PCA): 45

5. Discussion 48

6. Conclusion 50

References: 51
Appendix 58
Appendix A 59
Appendix B 60
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LIST OF FIGURES

Figure 2.1 Evolutionary pathway of cultivated rice……………………………………6
Figure 2.2 Gondwana supercontinent, showing various modern continents……….......6
Figure 2.3 Diagrammatic sketches of interactions between the envelopes and embryo
controlling seed dormancy and germination. ……………………………..14
Figure 2.4 (A) Examples of perfect microsatellites made up from mono-, di-, tri, tetra-,
penta-, and hexanucleotide repeats, respectively. (B) Examples of perfect,
imperfect, and compound microsatellites cloned from different genomic
compartments. …………………………………………………………….23
Figure 2.5 Diagram showing PCR amplification of microsatellite DNA.…………....24
Figure 2.6 Simple sequence repeats (SSR) linkage map and putative quantitative trait
loci (QTLs) for seed dormancy. …………………………………………28
Figure 4.1 An example of simple sequence repeat (SSR) polymorphism detected by the
primer pair RM 7. ........................................................................................41
Figure 4.2 Relationship between the number of simple sequence repeats in the targeted
microsatellite DNA and the number of alleles detected at the locus.
......………………………………………………………………………....43
Figure 4.3 Dendrogram showing genetic similarity between 46 rice varieties from pair
wise comparison of microsatellite markers, using Jaccard’s coefficients of
similarity and UPGMA clustering method (r=0.80;
P>0.01)…………………………………………………..………………...44
Figure 4.4 Dendrogram showing genetic similarity between 46 rice varieties from pair
wise comparison of microsatellite markers, using Simple matching
xii


coefficients of similarity and UPGMA clustering method (r=0.72;
P>0.01)………………………………………………………………….…45
Figure 4.5 Distribution of 46 rice varieties based on first and second principle
components accounting 28.59% of total variance calculated from 41 alleles
produced by 8 markers…………………………………………………….47

xiii


LIST OF TABLE

Table 2.1 Milestones in the molecular genetic analysis of rice…………………….….9

Table 2.2 A simplified classification of dormancy…..………………………………12

Table 3.1 Origin, parentage and recommendation domains of rice varieties under
study…………………………………………………………………….…31
Table 3.2 Markers used in the genetic analysis……………………………..………..34
Table 4.1 Banding pattern of rice varieties. The numbers in the third column
corresponds to the varieties as listed in the Table 3.1. ……………...….....38
Table 4.2 Summary of total alleles detected with 8 microsatellite loci in 46 rice
varieties………………………………………………………..……..……40
Table 4.3 Allelic data showing the number of varieties detected under each alleles at
each SSR locus………………………………………………...…………..40
Table 4.4 Number of alleles and diversity (PIC) values of different markers used in
rice varieties………………………………………………….……………42
Table 4.5 Matrix of Eigen values and vectors of principal components for 8
markers…………………………………………………….……………....46


xiv


ACRONYMS AND ABBREVIATION
A- Adenine
ABA- Abscisic acid
ABD- Agricultural Botany Division
AFLP-amplified fragment length polymorphism
BAC- Bacterial artificial chromosome
BC - Backcross
C- Cytosine
cDNA- Complimentary dna
CIM - Composite interval mapping
cM-centi Morgan
CTAB - Cetyltrimethylammonium bromide
CYP450- Cytochrome P450
DNA – deoxyribonucleic acid
EDTA- Ethylenediaminetetraacetic acid
EST- Expressed sequence tag
EtBr - Ethidium bromide
FAOSTAT- Food and Agriculture Organization Corporate Statistical Database
G- Guanine
GA- Gibberellins
GA20-oxidase - Gibberellic acid 20-oxidase
G-SSR - Genomic SSR
IAM - Infinite alleles model
xv


In- Inhibitor
IRAP - Inter-retrotransposon amplified polymorphism
PCA - Principal Component Analysis
PCR- Polymerase chain reaction
Pfr- Far red light photoreceptor phytochrome
PHS- pre harvest sprouting
PIC - Polymorphic information content
PPA- Percentage of Polymorphic Alleles
PPL- Percentage of Polymorphic Loci
QTL- Quantitative trait loci
RAPD- randomly amplified polymorphic DNA
RBIP - Retrotransposon-based insertion polymorphism
RFLP- restriction fragment length polymorphism
RM - Rice marker
SIM - Simple interval mapping
SMM - Stepwise mutation model
SNPs - Single nucleotide polymorphisms
SSLP- Simple sequence length polymorphisms
SSR- Simple sequence repeat
STMS - Sequence-tagged microsatellite sites
STRs - Short tandem repeats
T- Thiamine
TBE- Tris borate buffer
UPGMA - Unweighted Pair Group Method with Arithmetic Averages
xvi


UV- ultra violet
YAC- Yeast artificial chromosome

1

1. Introduction
1.1 Background:
Rice (Oryza sativa L.) is a monocot plant belonging to Poaceae family. It is the most
important and staple food for large part of the world population, especially in East, South,
Southeast Asia, the Middle East, Latin America, and the West Indies. It is the grain with
the second highest worldwide production, after maize
(http://faostat.fao.org/site/567/DesktopDefault.aspx#ancor ). Rice is probably the most
important grain concerning human nutrition and caloric intake and provides more than one
fifth of the calories consumed worldwide (http://en.wikipedia.org/wiki/Rice). Rice is
largely produced and consumed in Asia. About ninety-one percent of the total rice
production is in Asia (590 million ton per annum) (FAOSTAT, 2008 available at
http://beta.irri.org/solutions/index.php?option=com_content&task=view&id=250).
Rice is the staple food in Nepal and a mainstay for rural poor population.It is a key
source of food and a major employer and source of income of the poor farmers (Adhikari,
2004). Rice supplies 38.5% of the dietary energy, 29.4 percent of protein and 7.2 percent
of fat in Nepal (FAOSTAT, 2001 available at
http://beta.irri.org/solutions/index.php?option=com_content&task=view&id=250).
Preliminary estimate indicates that rice is grown in 1.55m ha (which is 0.92% of the world
and 10.3% of Asia) producing 4.5 million ton paddy with a productivity of 2.907t/ha in
2008 (MOAC, 2010). In Nepal rice grown under diverse soil and climatic conditions,
howeverthe production is low with total grain yield of 1.67%per annum, compared to the
rate of the population growth (2.25% per annum) (MOAC, 2010). It is therefore to fulfill
the food insufficiency, the statistics shows that, Nepal imported 60,000 tons of rice in 2008
and Nepal has become a net importing country with imports worth 2.73 billion rupees from
India during 2006 (USDA, 2009 available at
http://beta.irri.org/solutions/index.php?option=com_content&task=view&id=250).
2

Every plant generation starts with a seed, which usually contains a fully developed
embryo that can survive the period between seed maturation and germination.Seeds
generally have tendency to remain dormant, without germination, and wait for the suitable
condition to germinate. This property of seed is termed as dormancy. Hence, dormancy
can be defined as the failure of an intact viable seed to complete germination under
conditions that are otherwise favorable for germination. It is an adaptive trait optimizing
germination to the best suitable time that enables the seed to complete its life cycle
(Donohue, 2002 cited in Bentsink, 2007). In the evolutionary time scale, plant seeds were
desired to carry dormancy trait to overcome certain period of unfavorable conditions that
might be around the environment; without this there was the risk of existence of plant due
to untimely seedling. Seed dormancy is therefore, considered as an important trait in
agriculture that contributes to the adaptability in nature. Consequently, the weedy species
are persistent in soil which on favorable environment commencement, it germinates and
establishes.

Seeds of suitable dormancy were selected during the domestication of crop plants from
wild-plant species. Crop plants might have only low levels of dormancy that provide a
benefit for early and uniform seedling establishment. However, the low-dormancy has the
disadvantage of possible pre-harvest sprouting (PHS) i.e. germination before harvest,
which reduces the quality of the seed. This is a problem, especially for cereals when cool
and damp conditions occur prior to harvest (Holdsworthet al., 2006 cited in Bentsink,
2007). For example, in barley (Hordeumvulgare) for malting, low dormancy is desired
although this increases the risk of PHS. Therefore, a moderate dormancy just sufficient to
prevent PHS is usually desired for this trait in crop plants (Ullrichet al., 1997; Li et al.,
2003; Gubleret al., 2005 cited in Bentsink, 2007).

Nepal is diverse in climate, ranging from rainforest to dry lands. A considerable
number of rice varieties have been released suitable to these varied agro-ecosystems. These
varieties need specific and favorable conditions of temperature, moisture and level of
3

oxygen for its optimum growth and yield. Among many factors, rainfall and humidity are
the important ones that affect rice production and quality. One of the most important
properties of rice plant in its production and storage is seed dormancy, which is ultimately
affected by the climate. If the crop seed is dormant, its germination is restricted to a very
narrow range of micro-environmental conditions. Crops selected to have dormant seeds, or
artificially generated dormant seeds, could be sown at any favorable time. When seedling
establishment is desired, seed dormancy level could be lowered to produce synchronic
germination and seedling emergence by modifying the environment (i.e., changing the
light and thermal environment of the seeds), so that physiological changes could occur and
trigger germination. Nevertheless, the high level of seed dormancy results the inefficient
and non-uniform germination of the seeds. In addition to that, constrain of the low level of
seed dormancy in case of Nepal is that, seed germination could be naturally induced by
moist climate and humid environment prior to the harvest of plant.

Many molecular markers are used to analyze different traits of the plants. Among
themDNA based marker system is widelyused nowadays. One of the causes is that DNA
based markers are independent to the environmental changes. These marker systems
include restriction fragment length polymorphism (RFLP), random amplified
polymorphicDNA (RAPD), amplified fragment length polymorphism(AFLP) and simple
sequence repeat polymorphism (SSR or microsatellites). In understanding the dormancy
behavior of rice,SSR markers are found to be usedmore than any other conventional
molecular markers (McCouch et al., 1997; and Smykal et al., 2008). SSR markers are
codominant and locus specific PCR–based markers. This technique has been extensively
used in genetic diversity studies, QTL analysis, variety identification and mapping of rice
genome (Li et al., 2004; Chen et al., 1997; yang et al., 1994; wan et al., 2006; wan et al.,
2005; McCouch et al., 1997; Smykal et al., 2008; Akagi et al., 1996; and Wu et al., 1993).
Thus, by using such modern biotechnological tools we can understand the seed dormancy
character and promote seeds to be released from dormancy whenever it is desired.

4

1.2 Objective:

1.2.1 Main objective:
To study the genetic behaviors of dormancy in rice varieties using the simple sequence
repeat (SSR)markers associated with seed dormancy.
1.2.2 Specific Objectives:
1. To understand the germination behavior of rice and get knowledge on SSR
markers associated with seed dormancy in rice.
2. To learn the techniques of genomic DNA isolation and to be able to handle and
use the biotechnological tools like PCR, gel-electrophoresis,gel documentation
and molecular data generation.
3. To be able to analyze and interpret the physical and molecular data on seed
dormancy in rice varieties.









5

2. Literature Review

2.1 Biosystematics of rice plant:

Rice, an annual grass belongs to the genus Oryza of the family Poaceae.There are about
twenty-three species, out of which only two species have been known of their commercial
value. These two species are O. sativaL. (Asian rice) and O.glaberrimaSteud.(African
rice).O.sativa and O.glaberrimaare closely related to O.perennisTeud.
andO.breviligulataA. Chev. etRoehr, respectively. O.glaberrima and O.breriligulata are
endemic to Africa, while O.sativa and O.perennis are cosmopolitan
(http://www.nics.go.kr/R_Study/Rice/Eng/Introduction/Origin/evolution01.htm).
Moreover, these two series, perennis-sativa and breviligulata-glaberrima, are inter-sterile
and intra-fertile groups.

The O. sativa is the most commonly grown species throughout the world today,
while O. glaberrimais grown only in South Africa. O. sativais differentiated into three sub-
species based on geographical conditions viz., indica, japonica and javanica, as shown in
the evolutionary pathway of cultivated rice (Figure 2.1). The variety indica refers to the
tropical and sub-tropical varieties grown throughout South and South-East Asia and
Southern China. The variety japonicais grown in temperate areas of J apan, China and
Korea, while javanica varieties are grown alongside of indica in Indonesia
(http://agropedia.iitk.ac.in). However, primitively, the rice is supposed to originate from
the Gondwanasupercontinent that eventually broke up into Asia, Africa, the Latin America,
Australia and Antarctica (Figure 2.2). The Gondwana supercontinent then began to break
up in the early cretaceous period around 130 million years ago. Then, in each continents
rice began to evolve and get differentiated into various species (Chang, 2003).
6


Figure 2.1: Evolutionary pathway of cultivated rice.
(Source: http://www.nics.go.kr/R_Study/Rice/Eng/Introduction/Origin/evolution01.htm


Figure 2.2: Gondwana supercontinent, showing various modern continents. (Source: Chang, 1985 adapted from
Chang, 2003. Rice Origin, History, Technology, and Production)


)


7

2.1.1Taxonomy

Kingdom: Plantae – Plants
Subkingdom: Tracheobionta – Vascular plants
Super division: Spermatophyta – Seed plants
Division: Magnoliophyta – Flowering plants
Class: Liliopsida – Monocotyledons
Subclass: Commelinidae
Order: Cyperales
Family: Poaceae – Grass family
Genus: Oryza L. – rice
Species: Oryza sativa L. – rice
Oryzaglaberrima
(Source: http://plants.usda.gov/java/nameSearch
In last ten years, two high-density molecular linkage maps of rice containing about
3000 markers have been developed in the US and J apan, making the marker density in the
rice genome, on average, one marker per cM (200-300 kb) (Causseet al., 1994;
Harushimaet al., 1998 cited in Lopez-Gerena, 1993). Over 300,000 expressed sequence
)

2.2 The rice genome
Rice is a monocot plant with 2n(=24) chromosomes and it possesses very small units of
DNA than that of any crop plants (estimated at about 430 Mb) which is about three times
the size of the Arabidopsis thaliana genome (McCouch et al., 1997). The small genome of
rice comprises a huge percentage (ca. 75%) of single-copy DNA (McCouchet al., 1988
cited in Lopez-Gerena, 1993). A vast reservoir of germplasm (>200,000 accessions) of
both domestic and wild rice is available for genetic and breeding research (Hieiet al., 1994
cited in Lopez-Gerena, 1993). Rice has proven to be the most readily transformable cereal
crop (Hieiet al., 1994 cited in Lopez-Gerena, 1993).

8

tags (EST) have been deposited in the public database (Sasaki et al., 2005). The Rice
Genome Program of J apan collaborated with the international community to sequence the
rice genome with a high level of accuracy. With the completed sequence available from the
International Rice Genome Sequencing Project (2005), it is expected that the genome
sequence will facilitate pioneering research in functional and applied genomics. Integration
of the genome sequence with the genetic map will help development of new varieties
carrying agronomically important traits such as high yield potential and tolerance to both
biotic and abiotic stresses. In addition to genome sequencing, assortments of other
genomics projects have been initiated to produce important resources, which could serve as
crucial tools in clarifying the structure and role of the rice genome. The next phase of rice
genome research will focus on determining the function of approximately 35,000-40,000
predicted genes, which will advance both breeding and scientific discovery (Lopez, 1993).

2.3 Rice: The Model Monocot Plant

Rice is a member of the grass family and one of the three cereals on which the human
species largely subsists, along with wheat and corn. In the developing world, rice plant
alone provides 27 percent of dietary energy and 20 percent of dietary protein intake. Rice
was first cultured in Asia and now is cultivated in 113 countries and on all continents
except Antarctica (Lopez, 1993). It is grown in a large range of soil wetness regimes, from
deep flood to dry land, and in diverse soil conditions (Lopez, 1993). Two of 23 species
from the genus Oryzaare cultivated: O. sativa, which originated in the humid tropics of
Asia is also the more widely used, and O.glaberrima, from West Africa. Two main strains
of O. sativa are japonica and indica. The differences between these two evolved both
geographically and culturally over several thousand years as farming groups relocated to
diverse ecosystems. Over the millennia, different types of rice evolved under cultivation in
different conditions. Today, there are four general ecosystems under which rice is grown:
irrigated, rain-fed lowland, upland, and flood-prone (Lopez, 1993).

9

The first model plant species chosen was theArabidopsis, and its complete genome
sequence has been published (Kaul et al., 2000 cited in Mackill and McNally Kaul, 2004).
Rice is the second model plant species, and it is a representative of monocot plants.In
addition to its immense agricultural importance,rice has many practical advantages for use
in molecular genetics researches, which include its small genome size and relatively low
amount of repetitive DNA, its diploid nature, and its ease of manipulation in tissue
culture.Table 2.1 lists the major milestones in the development of rice as a model crop
species. The completion of a high-quality draft of the rice genome sequence by the
International Rice Genome Project was announced on 18 December 2002
(http://rgp.dna.affrc.go.jp/rgp/Dec18–NEWS.html
Milestone
).

Table 2.1: Milestones in the molecular genetic analysis of rice
References
First RFLP map McCouch et al. (1988)
Transgenic japonica rice Toriyama et al. (1988); Zhang et al. (1988);
Zhang and Wu(1988)
Transgenic indica rice Datta et al. (1988)
Major gene mapping Yu et al. (1991)
RAPD markers Zheng et al. (1991)
Microsatellite markers (SSR) Zhao and Kochert (1992, 1993); Wu and
Tanksley (1993)
QTL mapping Ahn et al. (1993); Wang et al. (1994)
Agrobacterium transformation Hiei et al. (1994)
Positional cloning Song et al. (1995)
AFLP markers Cho et al. (1996); Mackill et al. (1996)
Rice YAC library Umehara et al. (1996)
Rice BAC library J iang et al. (1995); Wang et al. (1995)
Rice genome draft Goff et al. (2002); Yu et al. (2002)
(Source: Mackill and McNally, 2004 in Biotechnology in agriculture and forestry, sec.I.3, p.40)





10

2.4 Seed dormancy:

Seeds are the basic and primary units of higher plants, which contain the complete genetic
information, enough to produce a new life, of same species. Seeds are generally able to
withstand long duration of unfavorable environmental conditions and remain viable; doing
so there is the possibility of maintaining the genetic diversity for long time. Therefore,
seeds generally have the tendency to remain dormant, without germination, and wait for
the suitable condition to germinate. This property of seed is termed as dormancy. Hence,
seed dormancy can be defined as the temporary inability of viable seed to germinate in the
otherwise favorable environmental conditions. Seed dormancy is the main problem in
breeding programs of cereal crops because it is associated with pre-harvest sprouting
(PHS) (Wan et al., 2005). In contrast, dormancy also helps seeds to avoid the germination
at wrong time and wrong place. Hence, dormancy maintains the genetic diversity of plant
through the seed dispersal and on-time germination. Breaking of seed dormancy can be
considered as the molecular process involving from integrated genetic regulations of
various genes to the complex embryological processes. Only after overcoming the
dormancy, seeds can germinate; germination being completely physical process involving
the protrusion of different organs (radical and plumule) out from seed coat. Seed dormancy
can be considered as the two-way sword as it has both good and bad aspects. We can see
dormancy also in the following terms:

Advantages:
Seed dormancy is a sort of survival mechanism of higher plants, it favors propagation and
spreading of plant populations and similarly-
• avoids germination at the wrong moment
• avoids germination at the wrong place
• distribution of germination in time, minimizes effects of “unfavorable event”
• favors spatial dispersion

11

Disadvantages:
In agriculture if seed dormancy is higher than the tolerable limit, it will mostly be a
problem. Followings are the disadvantages of seed dormancy:
• It is a problem for plant establishment and optimum harvest.
• It would be a problem in generation breeding programs.
• It is a problem in domestication of wild genotypes
• It is also a problem in seed evaluation and quality assessment. (Contreras, 2001)

The level of seed dormancy is checked physiologically by germination test. However,
for a better understanding of seed dormancy, it is important (but difficult) to distinguish
between dormancy, which is assumed to be induced during seed maturation on the mother
plant, and germination. These are two different physiological states or processes that
depend on each other. Germination can occur only after dormancy is released, and the
release of dormancy is visible only when germination takes place. In genetic terminology,
dormancy is epistatic to germination (Bentsink et al., 2007).Sometimes, even after the seed
has been released form dormancy the seed cannot geminate due to various factors like
(lack of water and light). This means, until we have clear markers that distinguish
dormancy (either embryo or coat-imposed) and germination potential as such, researchers
must mainly rely on germination tests for their analyses of dormancy, even though the test
is not specific to the dormancy (Bentsink et al., 2007).

2.5 Causes of dormancy

Dormancy is the characters of higher plants and is important for their genetic diversity
maintenance. Dormancy is an integrated and complex process of the seed and is the result
of genetic, environmental and physical interactions. Dormancy in seed is determined by the
co-action of the growth potential of the embryo and the restraints imposed by the tissue
surrounding it (Koornneef et al., 2002). Dormancy in rice seed is imposed by certain
physical and chemical factors associated with its covering structures, i.e. hull and pericarp.
12

The nature of these germination blocks, their mode of action, and processes regulating the
release of dormancy are not fully understood (Seshu and Dadlini, 1991). Dormancy is not
merely a resting state in the absence of suitable conditions for germination (which is more
correctly referred to as quiescence) (Copeland and McDonald, 2001 cited in Bennett and
Evans,n.d.). The mechanism, causes and detail analysis of dormancy in agricultural crop
seeds have been pointed out by Bennett and Evans (n.d.). Table 2.2 shows the
classification of seed dormancy in detail.

Table 2.2: A simplified classification of dormancy.
Primary dormancy Secondary dormancy
Exogenous Endogenous Combinatorial Endogenous
Location of
block
1.Maternal tissues (testa)
including perisperm or
endosperm enclosing
embryo
1. Immature embryo
(morphological
dormancy)
2. Metabolic blocks
(physiological
dormancy)
3. Morpho-
physiological
dormancy
(combined)

1. Combination of
exogenous
and endogenous
dormancy
1.Metabolic
blocks
Mechanism 1.Inhibition of water
uptake
(‘physical dormancy’)
2. Mechanical restraint
preventing embryo
expansion
(‘mechanical dormancy’)
3.Modification of gas
exchange
4. Prevention of leaching
of
1.Embryo in mature
seed has to
complete
development prior
to germination
2.Physiological
mechanisms
largely unknown
1.Physiological
mechanisms
largely
unknown
13

inhibitors from embryo
5.Supplying inhibitors to
embryo
and endosperm (‘chemical
dormancy’)
(Source: Hilhorst, 2007.Seed Development, Dormancy and Germination.p.51)

2.5.1 Primary dormancy:

Primary dormancy refers to the type of dormancy that occurs prior to dispersal and as part
of the seed developmental process. Primary seed dormancy is more common in nature than
secondary dormancy and can again be categorized into exogenous and endogenous
dormancy.

2.5.1.1 Exogenous primary dormancy:
This is due to the unavailability of essential inputs like water, light and temperature; as a
result, germination does not occur. However, this is affected by genetics and
environmental factor especially for the traits like hardseededness (Bennett and Evans,
n.d.). Exogenous primary dormancy can be further categorized as:

a. Dormancy due to physical barriers:
It includes dormancy due to physical barriers such as – hull, seed (fruit) coat, perisperm
(endosperm lining), pericarp etc. However, the influence of hull in imposing dormancy is
stronger and more prolonged than that of pericarp (Seshu and Dadlini, 1991). These hinder
the permeability to water and/or gases (Figure 2.3). Due to these physical factors,
following effects will occur on the tissue surrounding the embryo.
 Interference with water uptake
 Mechanical restraint to radical protrusion
 Interference with gas exchange, particularly oxygen and carbon dioxide
 Prevention of inhibitor leakage from the embryo
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14

 Supply of inhibitors to the embryo; and
 Light filtration.



Figure 2.3: Diagrammatic sketch of interactions between the envelopes and embryo controlling seed
dormancy and germination. Radicle protrusion occurs when embryo growth potential overcomes the
constraints imposed bythe envelopes. The main mechanisms through which the testa can influence embryo
growth potential are mentioned in boxes. Full lines represent an action, and dashed lines indicate diffusion or
leakage. Sharp and blunt arrows stand for promotive and inhibitory actions, respectively.
Abbreviations:ABA, abscisic acid; GAs, gibberellins; In, inhibitor; Pfr, far-red light photoreceptor
phytochrome. (Source: Debeaujon et al., 2007.Seed Development, Dormancy and Germination.Blackwell publishing.)





15

b. Dormancy due to chemical barriers:
It includes the inhibitors of germination present in seed coat (ABA, phenolic compounds--
flavonoids and other chemicals like mucilage, cutin, and callose) (Debeaujon et al., 2007).
c. Mechanical
For many species where exists hard seeds, it is classified as mechanical dormancy
(hardseededness) (Hilhorst, 2007). It is prevalent in legume with the significance in seed
and food values.

2.5.1.2 Endogenous primary dormancy:
This dormancy is due to the internal defect on the seed. This defect may be due to the
genetic inability, and it may also be influenced by the environmental factors during the
seed development and maturation.Itis also grouped into morphological and physiological
dormancy (Hilhorst, 2007).

1. Morphological:
Seed(fruit) position in plant or in inflorescence, age of mother plant, moisture content of
the seed/fruit or the plant etc. are the morphological characters that could be the cause for
dormancy. Plant species having the rudimentary embryo also have the morphological
dormancy (Bennett and Evans, n.d.).
2. Physiological:
Matured embryos show physiological dormancy. It is reversible unlike the coat imposed
dormancy. This dormancy is linked to seed metabolic rates, presence of growth
promoters/inhibitors (phenolics, cyanogenic compounds, ABA, GAs, cytokininesetc) in
seed. The high sugar and salt level also act as physiological factor for the dormancy as it
prevents full imbibition, thereby preventing or slowing germination (Copeland and
McDonald, 2001 cited in Bennett and Evans,n.d.).



16

2.5.2 Secondary dormancy:

Secondary dormancy is imposed only after the seed is released from the primary dormancy
and it may be the result of the prolonged inhibition of germination (Hilhorst, 2007). The
inhibition may be due to factors like endogenous ABA, secondary metabolites or lack of
proper conditions for germination (Gulden et al., 2004). Primary and secondary dormancy
differ significantly to each other (Cadman et al., 2006 cited in Hilhorst, 2007).
Thermodormancy, skotodormancy and photodormancyare considered as the kinds of
secondary dormancy.

2.6 Breaking the dormancy of seed:

Microbial actions, freeze-thaw cycle in nature and ingestion through the gut of the animals
break the dormancy of seeds in the nature. This allows the water and oxygen to enter into
the embryo. Roberts (1962) also showed the importance of oxygen in dormancy release.
Sometimes, even pre-soaking and pre-washing can promote the seeds to geminate and the
effect was more pronouncing in low temperature (3
0
C) conditions (Roberts, 1962).
Similarly, for many species only dry storage for short period is enough to break the seed
dormancy. However, for many other species special treatments are needed for the effective
release of seed dormancy. In rice, dormancy is completely released in all cultivars by
subjecting the seeds to moist heat treatment, by removing the hull and pericarp, and by
applying GA
3
after dehulling (Seshu and Dedlini, 1991). Following are the techniques of
breaking dormancy of seed in seed testing laboratory for their germination assessments.

2.6.1 Mechanical scarification:
Careful piercing, chipping, filing or sand scarification of the seed coat may be sufficient to
break the dormancy. Scarification results the rupture on seed coat that helps in water intake
and swelling of seeds. In case of dormancy due to hardseedednessof seed coat, these
techniques are used.
17

2.6.2 Chemical scarification:
In some species, digestion in concentrated sulphuric acid (H
2
SO
4
) is effective. The seeds
are soaked in the acid until the seed coat becomes pitted. But in case of the O. sativa
soaking the seed in one normal nitric acid (HNO
3
) for 24 hours (after preheating at 50
0
It is found that seeds in spring/summer, whose seedlings emerge in autumn, face a period
of, prolong desiccation which often leads to a loss of primary dormancy that is present
when mature seeds are shed. Intact seeds of red rice (Oryza sativa) were non-dormant
(greater than 90% germination at 30
C)
is performed. This method is also used for the germination of hard seeds (hardseededness)
(Seed Science and Technology: Rules, 1999).

2.6.3 Dry after-ripening:
0
C) after dry storage at 20
0
or 30
0
C for 4 weeks after
harvest (Cohn and Hughes, 1981). For most of the rice varieties, temperature treatment of
50
0
C for 4 to 5 days gave germination of about 80% or more (J ennings and J esus, 1964).
More intensely dormant varieties required additional time of treatment in some cases
extending up to7 to 10 days (J ennings and J esus, 1964). However, Roberts (1962)
suggested that not only higher temperature caused loss of dormancy but also led to loss of
viability, at the higher moisture contents. Although, Leubner-Metzger (2005) have
claimed that both transcription and translation could take place in air dry seeds and were
involved in after- ripening, there is not clear understanding in the mechanism (Leubner-
Metzger, 2005 cited in Allen et al., 2007). Under natural conditions dry after ripening
mayoccur, in winter annuals, in which dormancy is released by high summer temperatures
in order to make the seeds germinable in the fall. Similarly, for summer annuals dry after
ripening may occur during cold winter months to release dormancy (Hilhorst, 2007).The
seed sensitivity to Gasand light increased further during after ripening, which indicated
dormancy release. Moreover, decrease in ABA content of Arabidopsis seeds occurred
during dry after ripening (Ali-Rachedi et al., 2004 cited in Hilhorst, 2007). In laboratory,
the replicates for the germination are heated at a temperature not exceeding 30-35
0
C with
18

free air circulation conditions. However, for some species like Oryza sativa (50
0
C) higher
temperature is required. (Seed Science and Technology: Rules, 1999).

2.6.4 Pre-chilling:
It is also known as stratification or moist chilling or cold after-ripening. After pre-chilling,
the seed sensitivity towards the environmental factors, like light and nitrate, and also to
exogenously applied GAs increases (Hilhorst, 2007). Le Page-Degivry, (1997) as cited in
Debeaujon (2007), suggested that the cold treatments decreased the ABA biosynthesis
capacity at the optimal germination temperature, which resulted in a change of the
equilibrium from biosynthesis to catabolism. In laboratory, the replicates for germination
are placed in contact with the moist substrate and kept at a low temperature for an initial
period before they are moved to the suitable temperature (agricultural, vegetable, and
flower, spice, herb and medicinal seeds temperature of between 5
0
C and 10
0
In species like lettuce, light and growth regulator GAs promote the degradation of ABA
(Toyomasu et al., 1994 cited in Hilhorst, 2007), and light has the additional effect to
promote GA synthesis by induction of a GA 3-oxidase gene (Toyomasu et al., 1994 cited
C is
maintained up to seven days). In some seeds, a long period of pre-chilling is required
(more than two months) (Seed Science and Technology: Rules, 1999).

2.6.5 Light:
It is needed for germination of seeds. Some seeds require illumination to germinate (for
example, horticultural species germinate only in the presence of light) but, it is not the
exact cause of dormancy. It is therefore in seed testing, the seed plates are exposed to
illumination and the cycles of day and night temperature are maintained. In laboratory, the
test is illuminated during at least 8 hours in every 24 hours cycle and during the high
temperature period when the seeds are germinated at alternating temperatures. The light
intensity of approximately 750-1250 lux is provided from cool white lamps (Seed Science
and Technology: Rules, 1999).
2.6.6 Growth regulators:
19

in Hilhorst, 2007) in seed during imbibition.The author suggested that, decline of the ABA
is due to the catabolism through oxidative degradation to 8’-hydroxy-ABA (J acobsen et
al., 2002; Toyomasu et al., 1994 cited in Hilhorst, 2007). More strong evidence can be seen
by the studies of GA mutants like tomato (gib1) and Arabidopsis (ga1) which require the
exogenous GA to complete the germination (Koornneef and van der veen, 1980 cited in
Hilhorst, 2007). In laboratory, the substrate is moistened with 0.05% solution of GA
3,

prepared by dissolving 500mg GA
3
in one liter of water, and if the concentration higher
than 0.08% is required then phosphate buffer solution is required as the solvent (seed
science and technology: rules, 1999).

2.6.7 Nitrate:
Instead of water, 0.2% KNO
3
solution, prepared by dissolving 2g KNO
3
There are significant studies on the genetics of seed dormancy and their causes. Various
studies indicates that there are many genes or the genetic loci which govern the properties
of seed dormancy and pre-harvest sprouting (PHS) in rice (Cai and Morishima, 2000;
Dong et al., 2003; Lin et al., 1998; Miura et al., 2002). However, it is also found that many
of these loci are in similar positions of chromosomal locations of various cereal crops.
Cereals especially rice, wheat and barley were found to share synteny with the
in one liter of
water, is used to saturate the germination substrate at the beginning of the test. Water is
used for moistening thereafter (seed science and technology: rules, 1999).

2.6.8 Sealed polyethylene envelops:
Where a high proportion of fresh ungerminated seeds are found at the end of the standard
test, retesting in a sealed polyethylene envelop of just sufficient size to hold the test
satisfactorily, will usually induced these seeds to germinate (seed science and technology:
rules, 1999).

2.7 Dormancy in rice:

20

chromosomal regions that were related in seed dormancy and pre-harvest sprouting
(PHS).Li et al. (2004) found from the sequence alignment that GA-20-oxidase gene in
wheat shared 77% similarity with rice and 98% with barley. Li et al. (2004) found that
several genes in the rice genome as possibly being involved in seed dormancy including
several transcription factors, cytochrome P450 (CYP450) and gibberellic acid 20-oxidase
(GA20-oxidase). The GA-20 oxidase gene expression was accompanied with dormancy
release when using heat shock treatment on the dormant embryo (Li et al., 2004). This
gene catalyses GA53, GA44, GA19 and GA20 in the GA synthesis pathway (Li et al.,
2004).The contents of GA3 and GA20 in seeds with high germination rate were twice and
five times higher, respectively, than those from seeds with a low germination rate,
indicating a possible role of gibberellins in dormancy release (Fernandez et al., 2002 cited
in Li et al., 2004). Similarly, both map location and expression pattern supported GA 20-
oxidase as a candidate gene contributing to the seed dormancy/PHS quantitative trait loci
(QTL) (Li et al., 2004). Moreover, the gene is also linked with the alpha-amylase activity
and early seedling vigor. Based on these evidences Li et al. (2004) propose that GA20-
oxidase on barley chromosome 5H is intimately involved in controlling seed dormancy
release and PHS.

Mutant analysis on the rice varieties, other cereal crops and the model plant
Arabidopsis have elucidated the clear involvement of different genes in development of
seed dormancy (Koornneef et al., 2002; Bentsink et al., 2007). The isolation of a Tos17-
transposon-induced viviparous (non-dormant) mutant in rice, which was shown to be
defective in a zeaxanthinepoxidase gene (encoding one of the enzymes of the ABA-
synthetic pathway), showed that ABA is also important in dormancy control in cereals
(Agrawal et al., 2001). Studies of gibberellic acid (GA)-deficient, abscisic acid (ABA)-
deficient and signaling mutants in Arabidopsis and tomato have identified the crucial role
of ABA in seed dormancy and requirement for GA for germination (Koornneef et al.,
2002). Similarly, manipulation of seed ABA content by genetic modification of tobacco
has shown that overexpression of zeaxanthinepoxidase results in increased dormancy,
21

whereas ‘knocking out’ the gene encoding this enzyme by antisense techniques yields
phenotypes that are less dormant (Frey et al.,1999 cited in Hilhorst, 2007).

2.8 Molecular markers:

There has been a long history for the development of markers. The earliest genetic markers
studied by biologists are phenotypic markers. In 1913, based on analysis for several
phenotypic traits such as eye colour, wing shape, body size and colour of the fruit fly,
Alfred Sturtevant, an undergraduate student of Morgan, constructed the first linkage map
in Drosophila (Yu, 2005can be found in http://sundoc.bibliothek.uni-halle.de/diss-
online/05/05H169/t4.pdf
One of the earliest typesof DNA-based molecular markers, restriction fragment
length polymorphisms (RFLPs), was based around the detection of variation in restriction
fragment length detected by Southern hybridization. The types of sequence variation
detected by this procedure could be caused by single base changes that led to the creation
or removal of a restriction endonuclease recognitionsite or through insertions or deletions
of sufficient size to lead to a detectable shift in fragment size (Langridge and Chalmers,
). Since then, a lot of different phenotypic markers have been
identified in several important crops and they have been used extensively as tools in
genetic studies.
Molecular markers have been taken, in recent years, as reference on the assays that
allow the detection of specific sequence differences between two or more individuals.
However, it should be recognized that iso-enzyme and other protein-based marker systems
also represent molecular markers and were in wide use long before DNA markers became
popular. The reliability of the DNA marker is higher than the conventional markers (non-
DNA markers-protein based, phenotypic, morphological markers etc.) (Langridge et al.,
2004). In the DNA based marker the main advantage is that the information content is in
the sequence level (whether differ by the nucleotide sequence or the size of the
sequence)(Langridge et al., 2004).

22

2005). This technique has been largely superseded by microsatelliteor simple-sequence
repeat (SSR) markers and is now rarely used inscreening material for breeding programs,
but it remains an importantresearch tool. SSR markers detect variation in the number of
short repeatsequences, usually two or three base repeats. The number of such repeat
unitshas been found to change at a high frequency and allows the detection ofmultiple
alleles.

Even more sophisticated tool is now being used to detect the polymorphism at the
single nucleotide level. The large expansion of DNA, particularly expressed sequence tags
(EST), sequencedatabases has now opened the opportunity for the identification of single
nucleotide polymorphisms(SNPs). These occur at varying frequencies, depending on the
species and genome region being considered. SNPs are widelyseen as providing the key
advantage of multiple detection systems many ofwhich, such as mass spectroscopy, offer
high throughput at low detectioncost.

2.8.1 Microsatellites DNA:
Microsatellites also termed as simple sequence repeats (SSRs), short tandem repeats
(STRs) or sequence-tagged microsatellite sites (STMS), consist of varying numbers of
tandem repeat units (1 to 6 base pairs each) (Mohler and Schwarz, 2004). Microsatellites
represent a class of repetitive DNA that is commonly found in eukaryotic genomes (Tautz
and Renz, 1984) and well distributed throughout the rice genome. The most abundant
motifs found in mammalian genomes proved to be (A)
n
and (CA)
n
as well as their
complements, whereas (A)
n
, (AT)
n
, (GA)
n
,and (GAA)
s
repeats are the most frequent
motifs in plants. Mononucleotiderepeats consisting of A/T tracts are also present in
chloroplast genomes(Weising et al., 2005). As a rule, trinucleotide repeats are the
predominant type of microsatellites found in exons, whereas repeats consisting of
multiples of one, two, four, and five base pairs are rare in genes (Weising et al., 2005).
They are characterized by great abundance, high variability, and even distribution
throughout the genomes in many species. Microsatellites are typically multi-allelic loci,
23

and loci with more than five alleles are commonly observed in plants and animals
(McCouch et al., 1997).

Weber (1990 cited in Weising, 2005) categorized microsatellites, based on the
perfectness of the array, into three classes. It comprised (1) perfect repeats, which consist
of a single, uninterrupted array of a particular motif; (2) imperfect repeats, in which one or
several out-of-frame bases interrupt the array; and (3) compound repeats, with
intermingled perfect or imperfect arrays of several motifs (Figure 2.4).

A
Mononucleotide repeats: ...AAAAAAAAAAAAAAAAAAAAAAAA...
Dinucleotide repeats: ...CACACACACACACACACACACACACA...
Trinucleotide repeats: ...CGTCGTCGTCGTCGTCGTCGTCGT...
Tetranucleotide repeats: ...CAGACAGACAGACAGACAGACAGA...
Pentanucleotide repeats: ...AAATTAAATTAAATTAAATTAAATT...
Hexanucleotide repeats: ...CTTTAACTTTAACTTTAACTTTAA...
B
Perfect repeats: ... (AG)
32
...
... (TAT)
25
...
...(CAA)
7
...
Imperfect repeats: ...(TC)
6
A(TC)
13
...
...(AG)
12
GG(AG)
3
...
Compound repeats: ...(AT)
6
(GT)
42
AT(GT)
5
(GT)
10
...
...(AT)
14
(AG)
8
...
...(GAA)
21
...(TA)
23
...


Figure 2.4: (A) Examples of perfect microsatellites made up from mono-, di-, tri, tetra-, penta-, and
hexanucleotide repeats, respectively. (B) Examples of perfect, imperfect, and compound microsatellites
cloned from different genomic compartments. (Source:DNA Fingerprinting in Plants: Principles, Methods, and Applications,
Second Edition. P.9)


24

2.8.1.1Microsatellites as the molecular markers:
One of the most important attributes of microsatellite loci is their high level of allelic
diversity, making them valuable as genetic markers. The unique sequences bordering the
SSR motifs provide templates for specific primers to amplify the SSR alleles via the
polymerase chain reaction (PCR) (Weber et al., 1989 cited in McCouch et al., 1997). The
polymorphism shown by SSR primers is referred to as simple sequence length
polymorphisms (SSLP) and is in the form of allelic differences, which are usually the
results of variable numbers of repeat units within the microsatellite structure (McCouch et
al., 1997). SSLPs can readily be analyzed via PCR (Figure 2.5). They are easily detected
on high resolutionagarose or polyacrylamide gels, and behave as co- dominant markers.


Figure 2.5: Diagram showingPCR amplification of microsatellite DNA. Primer pairs (depicted as shaded
bars) are designed to specifically target the 5′ - and 3′-flanking region of a microsatellite(symbolized by a row
of circles; each circle represents a single repeat unit). Like RFLPs, microsatellite markers areco-dominant,
i.e., both alleles of a diploid organism are detected (lanes [C] and [D]), and homo- and heterozygotes can
therefore be distinguished.(Source:DNA Fingerprinting in Plants: Principles, Methods, and Applications, Second Edition. p.41)
25


Microsatellite sequence markers or SSR-markers are generally derived from the
two processes. The first, and traditional method, is from genomic library. In developing
genomicSSR (G-SSR) marker, first whole genome of the organism is digested and
sequences are cloned in the vectors and ultimately transformed in the suitable host cells.
Then, the clones are sought for the desired microsatellite (mono-, di-, tri-, tetra-, penta- or
hexa-) repeats, by the colony hybridization technique. After that, possible SSR-markers are
developed (Trojanowska and Bolibok, 2004). Second method is, constructing the SSR-
marker from the existing expressed sequence tag (EST) database. In this method, the
cDNA database is searched for the desired SSR sequences suitable for the marker
development. As the EST database does not include introns or non-coding sequences, it
displays slightly less polymorphisms than G-SSRs (54.0% vs. 83.8%, in rice), which is
also explained by the pressure for sequence conservation in coding regions (Trojanowska
and Bolibok, 2004; Scott, 2001 cited in Mohler and Schwarz, 2004).

Microsatellites have been exploited as tools to measure genetic distance and
diversity in evolutionary studies. Their power for these analyses comes from their
characteristically high allelic diversity, which in turn is a product of their high rate of
stepwise mutation due to replication slippage. For this reason, several measures of genetic
distance have been developed for microsatellites on the basis of the stepwise mutation
model (SMM; Kimura and Crow, 1964 cited in Matsuoka et al., 2002). The SMM assumes
that alleles mutate back and forth by small numbers of repeats, and thus the same allelic
states are created repeatedly over time. The SMM-based genetic distances for
microsatellites have successfully been applied in evolutionary studies in animals. An
alternative model is the infinite alleles model (IAM; Ohta and Kimura, 1973 cited in
Matsuoka et al., 2002), which assumes that each mutation creates a new allele in the
population(Matsuoka et al., 2002).

2.8.1.2 Microsatellite andother markers:
26


Many studies have been carried out to find which marker will best define the
polymorphism and other information content in organism (Smykal et al., 2008; Wuand
Tanksley, 1993; yang et al., 1994; McCouch et al., 1997). Smykal et al. (2008) studied the
potential of DNA based and non DNA based molecular marker techniques for the
discrimination of varieties. They demonstrated a high potential and resolving power of
DNA based methods. SSR markers were found to be superior in terms of high information
content and discrimination power, owing to high allelic variation, when compared among
isozyme markers, microsatellite markers, inter-retrotransposon amplified polymorphism
[IRAP] and retrotransposon-based insertion polymorphism [RBIP]. In terms of
polymorphic information content (PIC) values also SSR marker system proved to be the
most informative, given by the allelic richness. The only limitation in using the SSR
marker system is the necessity of accurate length reading, which is influenced by analytical
system (Smykal et al., 2008).

Wu and Tanksley (1993) also found the similar result in comparing the SSR and
RFLP markers. In their work, in all possible combinations between japonica and indica
subspecies, only six out of eighteen RFLP markers were informative. On the other hand,
all the microsatellite markers were informative within japonica, within indica and between
japonica and indica. They found out that, microsatellite markers had higher heterozygosity
values in all categories in comparison to RFLP. Panaud et al. (1997 cited in McCouch et
al., 1997) also found PIC values of 0.69 for SSLPs compared to 0.39 for RFLPs. Unlike
RFLPs, SSLP markers generate enough allelic diversity to differentiate cultivars within a
subspecies or ecotype, making it possible to analyzegermplasm commonly used in rice
breeding programs (McCouch et al., 1997 cited in Mackill et al., 1997; Yang et al., 1994).



2.8.2 Seed dormancy study by microsatellite markers in rice:
27


Significant efforts have been made to identify the quantitative trait loci (QTLs) controlling
and involving the seed dormancy and pre-harvest sprouting tolerance in rice (Cai and
Morishima, 2000; Dong et al., 2003; Lin et al., 1998; Miura et al., 2002; Wan et al., 2005,
2006).The substantial influence of environmental effects on expression of germination
characteristics and the involvement of many genes make dormancy a typical quantitative
trait (Koornneef et al., 2002).In a study done by wan et al. (2006), five quantitative trait
loci (QTLs) were found to be associated with the seed dormancy. In his study he derived
three simple sequence repeat (SSR) based linkage maps from two backcross (BC)1-type
populations of Nanjing35 (a japonica non-dormant breeding line)/N22//Nanjing35
(population I, abbreviated as PI) and USSR5 (non-dormant japonica cultivar)/N22//USSR5
(PII), and one F2 population of USSR5/N22 (PIII), were constructed to detect genes
controlling seed dormancy. The QTLS for seed dormancy, i.e., qSdn-1, qSdnj-3, qSdn-5,
qSdn-7 and qSdn-11, were identified on chromosomes 1, 3, 5, 7 and 11, respectively. The
mean germination rates for the cultivars N22, Nanjing35 and USSR5 were 0, 97.7, and
99.0%, respectively, indicating that N22 has a high level of seed dormancy while
Nanjing35 and USSR5 produce virtually non-dormant seeds. Hence, he concluded to the
point that the qSdn-1, qSdn-5, qSdn-7 and qSdn-11 QTLs detected in this study were
contributed by the highly dormant parent, N22 (Wan et al., 2006).


28



Figure 2.6: Simple sequence repeats (SSR) linkage map and putative quantitative trait loci (QTLs) for seed dormancy.(Source: Wan et al., 2005. P 713)



29

The major QTL on chromosome 1, qSdn-1, detected in three populations,
confirmed the distinctness of this gene from osVP1 genes for dormancy. According to the
study of Bailey et al., one orthologous Vp1 gene for the dormancy related maize
transcription factor VIVIPAROUS-1 was detected on rice chromosome 1. Vp1-
orthologous loci were detected on the long arms of wheat chromosomes 3A, 3B, and 3D,
and maize chromosome 3, in line with previous evidence of synteny between these regions
of the rice and wheat genomes and chromosome 3 of maize. The Vp1 gene was located
between the markers C86 and C112 on rice chromosome 1corresponding to the region of
RM104, around 20 cM far away from qSdn-1(Wan et al., 2006).Similarly, in the study
done by wan et al. (2005) (creating the population from a three way cross
IR52/Tatsumimochi//Miyukimoch; IR50 being indica dormancy donor and other japonica
species being non-dormant) the QTL qsd-1 was detected only in F
1
Cai et al. (2000) concluded that seed dormancy in rice is controlled by a large
number of genes as pointed out in many other species. All chromosomes except for
chromosome 4 and 10 harbor seed dormancy genes. Chromosome 3,5,6,9 and 11 seemed
generation, similar to
the results of Wan et al. (1997 cited in Wan et al., 2006), who reported that dormancy
controlled by one QTL on chromosome 7 was easily broken during storage, suggesting it
to be a minor QTL for seed dormancy. The genetic map created by Wan et al. (2005) is
shown in Figure 2.6.

These findings are also related to the study done by Cai et al. (2000). According to
the study done by Cai et al. (2000) non-shattering of the seeds (the property of seed to be
shattered to expose the viable seed to the environment and germinate) and reduced seed
dormancy were selected consciously and unconsciously during the domestication of rice,
as in other cereals. Both traits are quantitative and their genetic bases are not fully
elucidated, though several genes with relatively large effects have been identified. A total
of 147 markers were mapped on 12 rice chromosome. QTL analysis was performed by
simple interval mapping (SIM) and composite interval mapping (CIM).

30

to carry more than two independent loci. They also inferred that the loci which were
significant only in intact seeds and not significant in de-hulled seeds, qDOR-3-1, qDOR-3-
3, qDOR-5-1, qDOR-8 and qDOR-11-6, might control hull-imposed dormancy. On the
other hand, the loci significant in de-hulled seeds, qDOR-9-2, qDOR-11-2 and qDOR-11-4,
are probably responsible for kernel dormancy.

The QTL qSdn-5was also identified on the region near RM26 between marker
RM421 and RM334 on the long arm of chromosomes 5 in PI, PIII (Wan et al., 2005). This
QTL appeared to correspond to the QTL qDOR-5-2 reported by Cai et al. (2000). Their
study showed that the expression of the qSdn-1 effect on seed dormancy was highly
repeatable under the different genetic combination of N22 and Nanjing35 or USSR5. If it
is proven that this QTL is a beneficial gene in marker assisted selection for seed dormancy,
specific molecular markers that are easy to handle and very useful for rice breeders should
be developed. However, the deduced position of qSdn-1 varied somewhat between gene
structure, being between RM488-RM237 and RM1297 in PI, and between RM237-RM128
and RM265 in PII, PIII. Thus, more investigations are needed to dissect this QTL,
particularly to determine its precise position via linkage to molecular markers. Supporting
to the study by Wan et al. (2005), Gu et al. (2004 cited in wan et al., 2006) also suggested
that N22 most probably possesses two pairs of major genes together with a few major
genes, suggesting that it can be used as a donor genotype for the improvement of
dormancy in rice breeding programs.

31

3. Materials and Methods

3.1 Materials:
3.1.1 Research site:
The whole laboratory research works were carried out in seed testing laboratory and
biotechnology laboratory in Nepal Agricultural Research Council (NARC), Khumaltar,
Lalitpur, Nepal, in 2066.
3.1.2 Plant material:
Materials used in this study consisted of 46 rice varieties comprised of 34 released
varieties, 4 landraces and 8 pipeline varieties (Table 1) (however, out of 57 accessions, 11
accessions whose amplification products in many primers were missing were excluded
from the analysis.). Varieties namely, J anaki and CH-45 were the test samples used as
checks for most dormant and sprouting varieties in this study respectively. These seeds
were procured from National Rice Research Program (NRRP), Hardinath,Dhamsaand
ABD, Khumaltar. J anaki was highly dormant and CH-45 was non-dormant variety. The
parentage, origin and recommended domains of the rice varieties are shown in Table
3.1.For the genetic analysis,bulk DNA was isolated from the young seedlings of each of
the varieties grown in the normal room temperature and light conditions in normal rice
season.
Table 3.1: Origin, parentage and recommendation domains of rice varieties under study.
S.N. Rice varieties Parentage Origin Recommended domain
1 Rampur Mansuli Lalnakanda/IR30 India Terai, Inner Terai and Foot
Hills in CDR and WDR (upto
900 masl.) (Released)
2 Loktantra Mahasuri/IR4547-6-2-2 Nepal Terai, Inner Terai, Low hills
and
32

Mid hills (Released)
3 Chaite -4 BG34-8/IR28//IR2071-625-1-
252
IRRI Terai, Inner Terai(Released)
4 C.H.-45 Selection at IRRI IRRI Terai, Inner Terai (Released)
5 Mithila Fortuna//Miltor 6*2/Azucena Bangaladesh Terai, Inner Terai (Released)
6 Hardinath-1 BG 95///79-3348/H4//BW228-
1-3
srilanka Terai, Inner Terai (Released)
7 Radha-12 TN1/T141//Annapurna IRRI Eastern Terai
(Irrigated/unirrigated low land)
(Released)
8 SetoBasmati Terai (Landrace)
9 Radha-4 BG 34-8/IR 2071-625-1 IRRI Mid and Far-Western Terai
(Released)
10 Mansuli MayangEbos
80*2/Taichung 65
Malaysia Terai, Inner Terai (Released)
11 TundaNavayeko
Basmati
local Terai (Landrace)
12 Chaite-2 BG34-8/IR2061-522-6-9 IRRI Terai, Inner Terai (Released)
13 Kalanamak Local Terai (Landrace)
14 IR-58115 Hill (Pipeline)
15 Barkhe-3004 Kalinga-3/ IR 36 Nepal Terai and Inner Terai
(Released)
16 Sabitri IR 1561-228-1/IR
1737//CR94-13
IRRI Terai, Inner Terai (Released)
17 KanchhiMansuli Local Terai (Landrace)
18 IR-670115 Hill (Pipeline)
19 Radha-9 IR 42/Masuli Nepal Terai, Inner Terai (Irrigated
area) (Released)
20 SunauloSugandha Terai (Released)
21 Radha-32 Terai (Released)
22 Radha-7 J anaki/Masuli Nepal Terai, Inner Terai (Rainfed,
Lowland area (Released)
23 NR-1190 Terai (Pipeline)
24 Pusa-834 Terai (Pipeline)
25 Makawanpur-1 Ob678/IR20//H4 Sri Lanka Terai, Inner Terai (Pipeline)
33

26 NR-1488 Hill (Pipeline)
27 IR-51656 Hill (Pipeline)
28 Radha-17 Terai (Released)
29 Gahiya-2 MTU/W.Kakaiku India Terai, Inner Terai (Released)
30 J anaki Peta 3/TN1//Ramadja Sir Lanka Terai, Inner Terai (Released)
31 Ram Dhan Mahasuri//IR30 India Central terai, Siwalik Valley
32 Radha-11 Local selection in India IRRI Central-Terai (Rainfed area)
33 IR-51656-212 Hill (Pipeline)
34 IR-51672 Hill (Pipeline)
35 Bindeshwari TN 1/Co29 India Terai, Inner Terai (Released)
36 Khumal-8 J umliMarsi/IR-36 Nepal Tar, Foot-hills to Mid-hills
(Released)
37 Khumal-11 Akudaka/Barkat Nepal Kathmandu valley (Released)
38 Chaining-242 Hsingchio 4/Taichung
150//Taipe 17/T 45
Taiwan Mid Hill & Valley (Released)
39 Khumal-4 IR 28/ PokhreliMasino Nepal Mid Hill (Released)
40 Chandannath-3 Selection from Yunlen-1 China J umla valley and similar high
hills (2300 masl.) (Released)
41 Manjushree-2 Fuji 102/NR10157 (J umli
Marsi/IR 9129-159-3//kn-lb-
361-1-8-6-3)
Nepal Kathmandu valley (Released)
42 Chandannath -1 Selection from J ingling 78-
102
China J umla valley and similar high
hills (2300 masl.) (Released)
43 Machhapuchhre-3 Fuji 102/ChhomroongDhan Nepal Mid to High Hills with
coolclimate (1300-2000 m)
(Released)
44 Khumal-6 IR 13146-45-2-3/IR7492-18-
6-1-1-3-3
Nepal Kathmandu Valley and
similarareas (Released)
45 Chhomrong Selection from Ghandruk
Local
Nepal High Hills of Eastern &
Western
region (1400-2000 m), Mid
Hills in cold water region
(Released)
46 Palung-2 BG 94-2/PokhreliMasino Nepal High Hill (Released)

34

3.2 Methodology:
3.2.1 DNA extraction:
For the marker analysis, 10-15 seeds were raised for seedlings in individual pots at normal
room temperature and light condition for extraction of DNA. Bulk DNA of 10-15
individuals of each varieties was isolated from the young seedlings at 3-4 leaf stage. The
leaf material was weighted out to make about 3g for DNA extraction. The DNA was
extracted by the Cetyltrimethylammonium bromide (CTAB) method (protocol given in the
Annex A). The extracted DNA was then run in 0.8% normal agarose gel in 1xTBE buffer
(0.09 M Tris-borate and 0.5 M EDTA) at 80V for one and a half hour with ethidium
bromide (EtBr) staining and concentration of the DNA was estimated by comparing with
the known concentration of lambda DNA.
3.2.2 Microsatellite marker:
A total of 8 microsatellites markers were used. The selection of the markers was done on
the basis of the reviews of earlier marker works on genetics of dormancy in rice.
Information of these seed dormancy primers was taken from the published literatures and
database (http://www.gramene.org).In this experiment, mainly the primerslinked to QTLs
for dormancy on the chromosome 1, 3, 5 and 7 were analyzed in the rice varieties (Wan et
al., 2006).
Table 3.2: SSR Markers used in the genetic analysis.
Primer Primer sequence (5’-3’) Repeat
Motif
PCR
Produc
t (bp)
Linkage Reference
RM 7 TTC GCC ATG AAG TCT CTC G
CCT CCCATCATT TCG TTG TT
(GA) 180
19
Chr.3 Panaud et al., 1996
RM 10 TTG TCA AGA GGA GGC ATC G
CAG AAT GGG AAA TGG GTC C
(GA) 159
15
Chr.7 Panaud et al., 1996
RM 11 TCT CCT CTT CCC CCG ATC
ATA GCG GGC GAG GCT TAG
(GA) 140
17
Chr.7 Panaud et al., 1996
RM 128 AGC TTG GGT GAT TTC TTG GAA GCG
(GAA) 157
9
Chr.1 Akagi et al., 1996
35

ACG ACG AGG AGT CGC CGT GCA G
RM 231 CCA GAT TAT TTC CTG AGG TC
CAC TTG CAT AGT TCT GCA TTG
(CT) 182
16
Chr.3 Chen et al., 1997
RM 315 GAG GTA CTT CCT CCG TTT CAC
AGT CAG CTC ACT GTG CAG TG
(AT)
4

(GT)
133
10

Chr.1 Temnykh et al., 2000
RM 421 AGC TCA GGT GAA ACA TCC AC
ATC CAG AAT CCA TTG ACC CC
(AGAT) 234
6
Chr.5 Temnykh et al., 2000;
2001
RM 480 GCT CAA GCA TTC TGC AGT TG
GCG CTT CTG CTT ATT GGA AG
(AC) 225
30
Chr.5 Temnykh et al., 2000;
2001

3.2.3 PCR amplification:
SSR rice primers used in the study were supplied by Promega (Promega Corporation,
Madison, WI, USA). PCR reaction was conducted in the 25µl volume (4ng of genomic
DNA, 20µM each primer, 12.5µl of Master Mix [Promega Corporation, Madison, WI,
USA]).PCR mixture was amplified in aMJ Research PTC-100
TM
Programmable Thermal
Controller (MJ Research, Inc, watertown, MA, USA.) holding 96x 0.2ml microfuge tubes
or one 96 well ‘V’ bottom plate.The temperature cycle conditions programmed for
amplification of the DNA was touchdown PCR (Bajracharya, 2003). It is as follows:
5 minutes of 94
0
C followed by 2 cycle of 94
0
C for 1 minute, 65
0
C for 1 minute and 72
0
C
for 2 minutes; then, 6 cycles of 94
0
C for 1 minute, 62
0
C for 1 minute and72
0
C for 2
minutes; then, 10 cycles of 94
0
C for 1 minute, 59
0
C for 1 minute and 72
0
C for 2 minutes;
followed by 14 cycles of 94
0
C for 1 minute, 57
0
C for 1 minute and 72
0
C for 2 minutes and
finally 72
0
C for 5 minutes and then hold at 4
0
PCR products after amplification were separated in horizontal agarose gel electrophoresis
of 2.5% of low EEO agarose (GENE I, Bangalore GENE I Pvt. Ltd., India) in 1x TAE
(0.11% (v/v) Glacial Acetic acid, 0.5M EDTA and 0.04M Tris base) buffer solution
stained with 3.5µl of 10 mg/ml EtBr (electrophoresis grade, Fisher Scientific UK Limited,
UK). Volume of 12.5µl of the PCR product was loaded for the gel electrophoresis. Then
C.
3.2.4 PCR product separation and microsatellites visualization:
36

after, the gel was run in 90V (2.5V/cm) for 4 hours. A PCR marker ladder (Promega
Corporation, Madison, WI, USA) of 0.06µg/µl concentration was used for the molecular
weight estimation of PCR product size. The gel was then visualized under UV gel
documentation chamber (VilberLourmat, Marne-La-Valleen, France.).
3.2.5 Statistical analysis:
The amplified products were scored as bands on visualization on gel on UV
illuminator.Only the reliable bands were included in the analysis. These scored bands were
computed into a binary matrix. The presence of the band was scored as ‘1’, absence as ‘0’
and missing as ‘9’. The respective statistical analyses were carried using NTSYS and
Excel software. The following diversity and relationship analysis werecarriedout to
interpret the data obtained from the experiment.
3.2.5.1Simpson index
The Simpson index also known as Polymorphic Information Content (PIC) is defined as:

Where, p
i
is the proportion of entries in the i
th
Cluster analysis, a method for displaying the similarity or differences between pairs of
subjects in a set (Piya, 2010 unpublished, with personal contact) was employed for
grouping together genotypes that showed similarity in the microsatellite patterns. All the
data were processed with NTSYSpc version 2.11 software. Cluster analysis was conducted
on similarity estimates, by using the Un-weighted Pair Group Method with Arithmetic
Averages (UPGMA). A similarity matrix was created using the J accard’s Coefficient of
similarity. A dendrogramwas constructed using cophenetic correlation values. The
class of an n class trait. PIC value was also
calculated for each marker. Simpson’s index is the function of gene frequencies (allelic
evenness).
3.2.5.2 Cluster Analysis
37

comparison of similarity matrices was made by application of Mantel’s Z-statistics
computed by the MXCOMP procedure.
3.2.5.3 Principal Component Analysis (PCA)
Principal component analysis of molecular data was performed using NTSYSpc version
2.11 to know the relationship of the dormancy linked SSR primers.
















38

4.Result

4.1 seed dormancy behavior and molecular markers:
The PCR products, amplified with rice primers related to seed dormancy, were visualized
in the UV-illuminator chamber and the banding patterns were scored and photographed.
The amplified products, observed as bands, were compared with the dormant and non-
dormant checks varieties. The Table 4.1 shows the grouping of the varieties based on the
size of alleles and their banding pattern.
Table 4.1: Banding pattern of rice varieties. The numbers in the third column corresponds to the varieties as
listed in the Table 3.1. [Inclined varieties are pipeline varieties, bold varieties are landraces and others are
released varieties.]
S.
N.
Primers Allele sizes as that of
J anaki CH-45 Different alleles
1 RM7 26,27,28
(3)
5,6,7,8,9,10,13,17,23
,34,35 (11)
3,12,15,16,18,20,21,22,24,25,29,31,32,3
3,36,37,40,41,42,43,44,45,46
2 RM10 1,2,3,6,7,8,9,10, 15,16,17, 20,22,
24,25,26,33,36,38,41
3 RM11 2,5,6,25,29,34,46 (7) 2,5,6,29,34,46,25
(7)
3,7,8,12,13,14,15,
20,22,23,37,38,40,42,43,45,35,39,41,44,
36,28,
4 RM128 13,6,7,8,9,11,
18,16,22,23,24, 27,
46 (13)
3,20, 15,35,36,41,44,42,40,43,45
5 RM231 8,9,10,13, 12,16,
18,20,21,22,23,24,29,31,32,33,25,26,34,
36,35,37,38
6 RM315 1,2,5,6,7,8,10,27,29,31
,32 (11)
1,2,5,6,7,8,10,29,31,
32,27 (11)
9,11,12,13,14,15,17,18,19,21,22,23,25,3
5,41,37,40,42,43,44,45,46
39

7 RM421 1,2,3,6,7,8,9,12,35,3
7,38,40,41,42,43,45
(17)
5,10,11,13,14,
15,16,17,18,19,20,21,23,24,26,27,28,29,
31,33,34,39,44,46
8 RM480 3,19,20,21,22,23,24,25
,26,28,31,32,33,34
(14)
1,5,6,7,8,37,38
(7)
9,11,10,12,14 ,13,15,16,17,18, 35,36,39
(N.B. - The numbers indicated follows the Table 3.1)
Both the check varieties were terai varieties, so more of the terai varieties were
seen to be closely related to both the check varieties. For the loci RM7 and RM480 Radha-
17, Radha-9, Sugandha, Radha-32, Radha-7, Pusa-834, IR-51656-212 and NR-1488
possessed the alleles of check for highly dormant variety, J anaki. Likewise, for RM315
and RM11 Lokatantra, Mithila,Hardinath-1, Ghaiya-2,Rampur Mansuli, Radha-12, Seto-
Basmati, Mansuli, IR-51656, Ghaiya-2, Ram Dhan, Radha-11, Makawanpur-1, IR-51671
and Phalung-2 possessed the alleles of both J anaki and CH45. Whereas, marker RM7,
RM128, RM421 and RM480 showed that varieties Khumal-11, Khumal-242,
Chandannath-1, Machhapuchhre-3, Chandannath-3, Khumal-6 and Bindeshwari possessed
alleles as that of non-dormant check variety CH45. Other varieties and varieties amplified
by rice markers RM231 and RM10 did not possess alleles as that of any check varieties.
4.2 Microsatellite DNA polymorphism:
All the SSR markers amplified the product in all 46 rice varieties. The rice SSR markers
revealed 41 alleles in the 46 varieties, with 5.1 alleles per locus, and all the loci were 100%
polymorphic, except for the pipeline varieties (95.7%) and landraces (81.25%) (Table 4.2).
The highest numbers of 6 alleles were identified at each of two loci, RM7 and RM480; 5
alleles were identified at each of five loci, RM10, RM11, RM128, RM231 and RM315;
and 4 alleles at one locus, RM421 (Table 4.3). All primers tested were polymorphic.
However, RM128 was monomorphic (87.5%) in pipeline varieties, and RM7, RM128 and
RM 231 were monomorphic (62.5%) in landraces. Example of the SSR alleles, as resolved
with the PCR assay, is shown in Fig 4.1.

40

Table 4.2: Summary of allelic diversity measured for8 microsatellite loci in 46 rice varieties.
Diversity parameters All
varieties
Terai
varieties
Hill
varieties
Released
varieties
Pipeline
varieties

Landraces
Total number of varieties 46 29 17 34 8 4
Total number of alleles 41 35 33 40 23 16
Total SSR markers (loci) 8 8 8 8 8 8
Average number of alleles
per locus
5.1 4.38 4.1 5 2.9 2
Number of polymorphic loci 8 8 8 8 7 5
Percentage polymorphic loci 100% 100% 100% 100% 87.5% 62.5%
Percentage polymorphic
alleles
100% 100% 100% 100% 95.7% 81.25%

Table 4.3: Allelic data showing the number of varieties detected under each alleles at each SSR locus.










Locus

Alleles (no of rice varieties)
a b c d e f
RM7 4 6 12 6 7 4
RM10 2 4 11 1 2 -
RM11 8 4 9 9 1 -
RM128 4 2 2 14 3 -
RM231 3 5 8 5 2 -
RM315 13 5 5 6 6 -
RM421 3 16 17 5 - -
RM480 1 5 15 6 8 1
41

a)

b)

Figure 4.1: An example of simple sequence repeat (SSR) polymorphism detected by the primer pair RM 7.
Genomic sequences containing (GA)
n

repeats were amplified by PCR in the presence of deoxynucleotides,
separated in gel containing EtBr, and detected by UV-illumination. a) Shows half of the rice varieties in 30
wells and b) shows another half of the rice varieties. (The numbers indicates the varieties consistent to table
3.1 in materials and method.In figure, the numbers 12, 16, 17, 22, 26, 40, 42, 43, 44, 47 and 48 indicate
discarded varieties.)
The diversity value as polymorphic information content (PIC), over the total
sample varied drastically from one locus to another (Table 4.4). The number of alleles
ranged from 4 to 6 with an average of 5.1 for whole sample and PIC ranged from 0.00 to
0.94 with an average of 0.76. In comparison to the number of alleles per locus, the
diversity value is more varied. As shown in Table 4.4, PIC ranged from 0.64 (RM10) to
0.94 (RM128), with an average of 0.76. This shows that all the markers were informative
and the most informative among these was RM128. The average PIC value was higher
(0.76) in the total varieties, and it was 0.64 for terai and 0.68 for hill varieties; and, 0.72 for
released varieties, 0.5 for pipeline varieties and 0.34 for local varieties.

42

Table 4.4: Number of alleles and diversity (PIC) values of different markers used in rice varieties.
S.No. locus Terai (29) Hill (17) Released
varieties(34)
Pipeline
varieties(8)
Landraces (4) Total (46)
No. of
alleles
PIC No. of
alleles
PIC No. of
alleles
PIC No. of
alleles
PIC No. of
alleles
PIC No. of
alleles
PIC
1 RM7 5 0.71 6 0.76 6 0.81 4 0.73 1 0.00 6 0.80
2 RM10 3 0.55 3 0.64 5 0.65 2 0.44 2 0.50 5 0.64
3 RM11 5 0.73 4 0.71 5 0.74 3 0.66 2 0.50 5 0.75
4 RM128 4 0.44 5 0.76 5 0.75 1 0.00 1 0.00 5 0.94
5 RM231 4 0.68 4 0.69 5 0.77 4 0.72 1 0.00 5 0.77
6 RM315 4 0.67 4 0.60 5 0.74 4 0.75 3 0.62 5 0.76
7 RM421 4 0.66 3 0.62 4 0.60 2 0.38 2 0.38 4 0.66
8 RM480 6 0.71 4 0.72 5 0.72 3 0.45 4 0.75 6 0.74

Mean 4.375 0.64 4.125 0.68 5 0.72 2.88 0.50 2 0.34 5.12 0.76

Comparatively, similar number of alleles were found in both terai and hill rice
varieties. In total of 29 terai varieties and 17 hill varieties, average of 4.4 and 4.1 alleles
were detected. The difference in diversity values was also not statistically significant in
terai and hill varieties, as determined by the paired t-test (p-value: 0.346).
There was a very good linear relationship between the number of alleles detected at
a locus and the total number of simple sequence repeats within the targeted microsatellite
DNA (Figure 4.2). The Pearson Correlation Coefficient was found to be 0.9, which is
significant at the 0.01 probability level. Thus, it was observed that, the higher the repeat
numbers of the microsatellite DNA, the higher the number of alleles detected.
43


Figure 4.2: Relationship between the number of simple sequence repeats in the targeted microsatellite DNA
and the number of alleles detected at the locus. The correlation is significant at the 0.01 probability level.
4.3 Cluster analysis:
Similarity and dissimilarity matrices were calculated among 46 rice varieties, using
J accard’s coefficient, simple matching coefficient; and Nei’s distance, respectively.
Dendrogramswere then constructed with Un-weighted Pair Group Method with Arithmetic
Averages (UPGMA) cluster analysis using the similarity and distance matrices (Figure 4.3
and 4.4). Landraces Kalanamak, Kanchhimasuli and TundaNabhayeko Basmati were
clustered together along with some pipeline and released varieties but Seto Basmati was
found to be clustered along with highly sprouting check variety CH45. Most of the hill
varieties, as expected, were clustered in one group (II). Likewise, the varieties Rampur,
Loktantra, Radha-12, Mithila, Seto Basmati, Mansuli and Chaite-4 were grouped with the
highly sprouting check variety CH-45. Similarly, the pipeline varieties like IR-51656-212,
IR-51656, NR-1488, IR-51672 and IR-670115 were grouped with the highly dormant
check variety J anaki along with some terai varieties, except Palung-2.
Mantel Test was done to check the goodness of fit of dendrograms with the
similarity or distance matrices. The cophenetic correlation was found to be 0.8, 0.7 and 0.4
for J accard’s similarity, Simple Matching similarity and Nei’s distance, respectively at
0.01 probability level. This indicates that J accard’s similarity and simple matching
R² = 0.770
0
2
4
6
8
0 10 20 30 40
N
u
m
b
e
r

o
f

a
l
l
e
l
e
s

p
e
r

l
o
c
u
s
Number of simple sequence repeats
44

matrices fitted well and Nei’s distance was poor in cluster analysis (Rohlf and Fisher,
1968).


Figure 4.3: Dendrogram showing genetic similarity between 46 rice varieties from pair wise comparison of
microsatellite markers, using J accard’s coefficients of similarity and UPGMA clustering method (r=0.80;
P>0.01).
45


Figure 4.4: Dendrogram showing genetic similarity between 46 rice varieties from pair wise comparison of
microsatellite markers, using Simple matching coefficients of similarity and UPGMA clustering method
(r=0.72; P>0.01).
4.4 Principal component analysis (PCA):
Principal component analysis was also performed on 41 observed alleles using NTSYSpc
(version 2.11x). The results supported the clustering patterns using J accard’s and simple
matching similarity matrices. First three Eigen vectors, which accounted 15.7, 12.9 and
11.5% variation that explained up to 40% of the total variation (Table 4.5). The projection
vectors shown in the PCA chart shows the relatedness of the varieties not only by the
distance but also by the angle between them, i.e. lesser angle will show more relatedness.
The principal component analysis supported relatedness within the hill and terai varieties,
SimplematchingCoefficient
0.67 0.75 0.84 0.92 1.00
machhhapuchhre3MW
rampur
loktantra
ch45
hardinath1
radha12
setobasmati
mithila
mansuli
radha4
chaite4
khumal11
chainung242
machhhapuchhre3
chandannath1
chandannath3
chhomrong
bindeswari
manjushree2
khumal8
khumal4
khumal6
tundanabhayeko
kalanamak
chaite2
barkhe3004
IR58115
sabitri
kanchhimasuli
IR670115
radha9
sugandha
radha32
palung2
makawanpur1
IR51672
NR1488
IR51656
radha17
janaki
ghaiya2
ramdhan
radha11
IR51656212
radha7
NR1190
pusa834
46

seen as grouped together (Figure 4.5). Hill varieties like Chhomrong, Chandannath-1,
Chandannath-3, Machhapuchhre-3, Chainung-242 and Manjushree-2 were closely related
to each other. PCA showed the close relationships of the varieties of the clusters I, II and
IV shown in the tree (Figure 4.3 and 4.5); varieties of cluster III and V were not found to
be distributed uniformly as other clusters. The distribution of landraces in dendrogramwas
also supported by the component analysis, landraces Kalanamak, TundaNabhayeko
Basmati and Kanchhimasuli were grouped together with less projection angle but Seto
Basmati was grouped together with non-dormant check variety CH45.
Table 4.5: Matrix of Eigen values and vectors of principal components for 8 markers.
S.N. Eigen value Percent Cumulative
1 6.43752777 15.7013 15.7013
2 5.28663113 12.8942 28.5955
3 4.69944013 11.4620 40.0576
4 3.89025990 9.4884 49.5460
5 3.54179991 8.6385 58.1845
6 3.00973834 7.3408 65.5254
7 2.26985696 5.5362 71.0616
8 2.20114794 5.3687 76.4302
9 1.96328848 4.7885 81.2188
10 1.84611813 4.5027 85.7215
11 1.66805311 4.0684 89.7899
12 1.37937789 3.3643 93.1542
13 1.32062830 3.2210 96.3753
14 1.19194500 2.9072 99.2825
15 1.04735491 2.5545 >100%
47

Figure 4.5: Distribution of 46 rice varieties based on first and second principal components accounting 28.59%
of total variance calculated from 41 alleles produced by 8 markers. The lines in the figure represent the
projection vectors for the varieties from the origin.


48

5. Discussion
All SSR markers related to seed dormancy in rice detected variations at each locus with
alleles varying from 4-6 per locus. The number of alleles per locus detected was more than
that reported by Bajracharya (2003). Bajracharya (2003) reported 95 alleles with an
average of 2.9 alleles per locus, using 33 rice markers on 24 rice landraces. However,
Yang et al. (1994) detected much more alleles in rice using rice markers. He reported 9.3
alleles per locus from 10 rice markers, reporting up to 25 alleles at one locus (RM 163).
Maroof et al. (1994) detected 28 alleles by a microsatellite HVM3 in barley. Yang et al.
(1994) found much larger number of alleles in landraces than in cultivars. However, this
result was in contrast to Yang et al. (1994). The main factor in this deviated result may be
the less number of landraces taken (only 4 landraces were taken in this study).
According to the J accard’s similarity matrix, the closest (J accard’s coefficient-1.00)
varieties to J anaki were Lokatantra, NR-1488 and IR-51656; and the furthest (J accard’s
coefficient-0.00) were almost all the hill varieties and some of the terai varieties like
Radha-4, Chaite-4, Barkhe-3004, Sabitri, KanchhiMasuli, Bindeshwari, TundaNabhayeko
Basmati and IR-670115. Likewise, the varieties closest (J accard’s coefficient-1.00) to CH-
45 were Rampur Mansuli, Lokatantra and Hardinath-1; and the furthest were Radha-9,
Radha-32 and Radha-17, SunauloSugandha, Barkhe-3004, IR-58115, IR-516562 and
Khumal-4 and Khumal-6. Here, the occurrence of the variety Lokatantra closest to both
J anaki and CH-45 was also shown by the allelic data (Table 4.1), and this may be due to
the lack of suitable SSR marker that can distinguish the variety in the study or this can be
explained as the presence of the dormancy related QTLs relating to both J anaki (dormant)
and CH-45 (highly sprouting). Actually, markers RM11 and RM315 were responsible in
showing Lokatantra as related to both dormant and highly sprouting variety. This
ambiguity in the result would not have been seen, if a single gene had guided the dormancy
character. The polygenic nature of the dormancy trait is the main reason behind this.
49

The UPGMA cluster analysis of 46 rice varieties led to grouping into 5 clusters. A
distinct group of rice cultivars for hill environment was seen in the cluster analysis using
J accard’s similarity coefficient and simple matching coefficient (Figure 4.3 and 4.4). The
group comprised Chainung-242, Machhapuchhre-3, chandannath-1, Chandannath-2,
Chhomrong, Khumal-8, Khumal-4, Khumal-6, Khumal-11, Bindeshwari and Manjushree-
2, in which the former 5 varieties were cold tolerant (Annual report, 2007/2008. ABD,
NARC). This entire cluster was at the average distance 0.13 from the non- dormant check
variety CH-45, and with average distance of 0.001 from the dormant check variety J anaki.
Distribution in PC plot with the first and second principle components also supported the
sub groupings of the hill rice varieties (Figure 4.5). This showed that these hill varieties are
non-dormant. In the clusters analyzed using J accard’s coefficient and Simple Matching
coefficient, the highly sprouting check variety (CH-45) grouped with Rampur Mansuli,
Lokatantra, Hardinath-1, Radha-12, Seto Basmati, Mithila, Mansuli, Radha-4, Chite-4 and
Khumal-11, suggesting these to be non-dormant varieties. Similarly, the dormant check
variety (J anaki) grouped with IR-51656-212, Radha-11, Ramdhan, Ghaiya-2, Radha-17,
IR-51656, NR-1488, IR-51672, Makwanpur-1, Palung-2, Radha-32, Sugandha, Radha-9
and IR-670115, suggesting that these could be dormant varieties. This result suggests that,
these varieties have the similar expression of the dormancy QTLs as analyzed by the
markers, and could have similar genetic background. These findingswere also supported by
the Principal component analysis (Figure 4.5).
Bajracharya (2003) found that all the landraces from J umla clustered together and
formed the distinct group. The study done here also showed the similar result, except the
Seto Basmati, all the landraces were clustered in same group. However, the landraces were
not grouped, as expected, with the dormant check variety J anaki.

50

6. Conclusion
With the help of SSR marker technology the genetic analysis of terai and hill rice varieties
were carried out. The study showed that more of the terai varieties were genetically related
to the dormant check variety J anaki and most of the hill varieties were genetically similar
to sprouting check variety CH45. However, pipeline varieties did not show the relatedness
with sprouting check variety and landraces also did not showed the relatedness with
dormant check variety as expected. The unexpected results were attributed to the
insufficient number of markers analyzed and unsuitable marker choice. However, this
study is expected to be helpful for the rice plant breeders in planning the selection strategy
to improve the trait, particularly seed dormancy in this case, in breeding programs. This
study also revealed that the greater resolving power of the SSR assay could provide more
informative data than other techniques. In comparison to the physiological markers the
DNA based molecular markers are more reliable as it is independent to reference material
and the external environments. SSR, particularly, are more superior because of the high
PIC values, its technical simplicity, co-dominant nature, small amount of starting DNA
requirement, relatively low cost and rapidity of the process. On the other hand, to get a full
potential, precise SSR band scoring is required, which is eventually affected by the
analytical system. Moreover, the precision of SSR in this study could have been increased
by increasing the number of the SSR markers (loci). It is therefore suggested for further
analysis with more SSR markers and relate these information with the physical testing of
seed dormancy. Nepal is lacking much more in these areas of researches. Study in much
deeper level should be encouraged in this field. Moreover, in depth study up to
transcriptome level, as promoter assays, could really increase the horizon of the field.



51

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58





Appendix
59

A) Protocol for the extraction of the rice DNA by CTAB method:

1. Fresh sample (seedling, adult leaves) weight: 3g
2. Put it in the paper envelops and dry in the oven (60
0
3. Grind it fine in a crusher or the mortar (if necessary, use quartz sand).
C). For rice plant; 2-3 hours.
4. Put it in a 15ml centrifuge tube and add 6ml
2
5. Incubate it for 30 minutes at 55
of 1xCTAB. Then mix well.
0
6. Add 6ml of chloroform/isoamylalcohol and mix gently (for about 30 minutes).
C.
7. Centrifuge it at 2400rpm for 15minutes.
8. Pour the supernatant fluid to a new tube and add 105 CTAB to the fluid in the
proportions of 1:10 and 6ml of chloroform/isoamylalcohol. Then, mix gently (for
about 30 minutes).
9. Centrifuge in at 2400rpm for 15 minutes.
10. Pour the supernatant fluid to a new tube and precipitation buffer more than there
was of the fluid. Then, mix gently. DNA will be precipitated.
11. Leave it for 30 minutes.
12. Centrifuge it at 2400rpm for 5 minutes.
13. Remove the supernatant fluid and add 1ml of 1M NaCl-TE with RNase (1l
RNase/ml).
14. Incubate t for more than 2 hours at 55
0
15. Add 1 ml of 2-propanol and mix gently, and DNA will be precipitated.
C.
16. Centrifuge it at 2400rpm for 5 minutes and remove the supernatant fluid.
17. Add 1ml of 70% ethanol and wash the inside wall of the tube (twice).
18. Invert the tube to evaporate ethanol (for 30 minutes to 1 hour).
19. Add 0.3 ml of 0.1 x TE and cool-store it.
60

B) Stock solutions for SSR (microsatellite) analysis:

1. 1MTris – 121 g of Tris was dissolved in 800 ml water and adjusted to pH 8.5 with
concentrated HCl and made up to 1 l with water and autoclaved.
2. 5MNaCl – 292 g of NaCl was dissolved in 750 ml water and made up to 1 l with
water and autoclaved.
3. 0.5M EDTA – 186 g of Na
2
EDTA.2H
2
4. 100 x TE – 121 g Tris and 37.2 g Na
O was dissolved in 800 ml water and
adjusted to pH 8.0 with NaOH pellets and made up to 1 l with water and
autoclaved.
2
EDTA 2H
2
5. 1 x TE – 5 ml of 100 X TE was added to 495 ml of water and autoclaved.
O was dissolved in 800 ml water,
adjusted to pH 8.0 with concentrated HCl, made up to 1 l and autoclaved.
6. 50 x TAE – 242 g Tris was dissolved in 500 ml water. 100 ml 0.5M EDTA and
57.1 ml glacial acetic acid added and made upto 1 l.
7. 1 x TAE – 200 ml of 50 x TAE was added to 9.8 l water in a 10 l bottle.
8. 50 x TBE – 270 g Tris (base), 138 g boric acid dissolved in 500 ml water. 100 ml
0.5 M EDTA added and made upto 1 l.
9. 1 x TBE – 200 ml of 50 x TBE was added to 9.8 l water in a 10 l bottle.
10. Gel loading buffer – 100 mg bromophenol blue and 372 mg Na
2
EDTA.2H
2



O
dissolved in 100 ml glycerol and 10 ml of water was added to this and stored in
fridge.