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Introduction
1. INTRODUCTION
1.1 Sesame
Sesame (Sesamum indicum L.), of family Pedaliaceae, is one of the oldest and most
nutritious oilseed crops known to humankind. It has been cultivated in Indian subcontinent since
1500 B.C. (Bedigian, 2003) and was a highly prized oilseed in the ancient world because of its
resistance to drought, the ease to extract oil from seeds and the high stability of the oil
(Langham & Wiemers, 2002).
1.1.1 Oil quality of sesame
In sesame oil, oleic (C18:1) and linoleic (C18:2) acids are predominant and make up
more than 80% of the total fatty acids. Linolenic acid (C 18:3) is found in traces in sesame oil.
The high levels of unsaturated (UFA) and polyunsaturated fatty acids (PUFAs) increase the
quality of oil for human consumption. Moreover, high level of PUFAs in sesame oil is claimed to
reduce blood cholesterol, high blood pressure and play an important role in preventing
atherosclerosis, heart diseases and cancers (Ghafoorunissa, 1994; Hibasami et al., 2000;
Miyahara et al., 2001). Among PUFAs, linolenic acid play very important roles in physiology,
especially during foetal and infant growth, in particular in the formation of central nervous
system and retina (Bourre, 2003; Bowen and Clandinin, 2005) and for the prevention of
cardiovascular diseases, being antithrombotic, anti-inflammatory, antiarhythmic and flavouring
plaque stabilization (Hu et al., 1999; SAS, 1999) . The nutritional value of this PUFA in human
diet is well recognized and increased consumption of this fatty acid has been recommended
(Department of health, 1994). As the demand for beneficial polyunsaturated fatty acids (PUFAs)
has drastically increased in recent years, there are increasing efforts to find plant sources of
PUFAs that are economical and sustainable, unlike animal sources. The amount of unsaturated
and polyunsaturated fatty acids, in a plant species, depends upon the efficiency with which the
process of desaturation and elongation takes place in the biosynthetic pathway. Therefore,
desaturation of fatty acids is also an important aspect in oil biochemistry as it determines the
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Introduction
level of unsaturation and the economic value of oil (Knutzon et al., 1992; Mikkilineni and
Rocheford, 2003).
1.2 Fatty acid biosynthetic pathway
A detailed knowledge of the metabolic pathways involved in the biosynthesis of fatty
acids is a prerequisite for genetic engineering of the seed fatty acid composition. Although
the pathway for sesame is not documented, the fatty acid profile suggests synthesis via the
known route common to most major oil crops. The fatty acid biosynthetic pathway is a primary
metabolic pathway because it is found in every cell of the plant and is essential to growth
(Ohlrogge and Browse, 1995). The synthesis of PUFA in plant cells are accomplished by
sequential desaturation of saturated fatty acids. Plant genetics and biochemistry have so far
identified over 10 genes involved in the fatty acid production (Ohlrogge and Browse, 1995). But
our present work was limited to genes involved directly in biosynthesis of linolenic acid as it is
an essential fatty acid but present in traces in sesame.
As an initial step for C18:3 fatty acid synthesis, first double bond is introduced by a
soluble stearoyl acyl carrier protein deasturase (sad) in stearic acid (C18:0). It is the chloroplastic
enzyme which catalyzes the conversion of C18:0 to oleic acid C 18:1. Hence their activity
primarily regulates the ratio of saturated to monounsaturated fatty acids (Ohlroggeav and
Browseb, 1995). Fatty acid desaturase 2 (fad2) encodes endoplasmic reticulum 18:1 desaturase
that controls the conversion of oleic C 18:1 to linoleic acid C18:2. Finally, linoleic acid C 18:2 is
converted to linolenic acid C 18:3 by omega 3 fatty acid desaturase (o3fad).
Stearic acid (a)
Oleic acid
(b)
Linoleic acid
(c)
Linolenic acid
(a) Stearoyl acyl desaturase (Sad)
(b) Fatty acid desaturase 2 (Fad2)
(c) Omega 3 fatty acid desaturase (O3fad)
The three enzymes involved in the biosynthesis of linolenic acid are encoded by the genes sad,
fad2 and o3fad, respectively.
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Introduction
1.3 Modification of fatty acid composition in plantstorage oils
Development of crop varieties producing oils, with quality appropriate for specific market
needs, presents a better alternative to chemical modification of vegetable oils and a means to
circumvent the short-comings associated with the technology. One way to achieve this is by
domesticating wild plants that accumulate oil with characteristics of interest. However, the long
time scale (of over 20 years) needed to adapt them to cultivation and the requirement for remodelling of agricultural machinery and processing equipment becomes a major limitation to
development of novel oil crops.
Induced mutagenesis has been used to create additional diversity in seed fatty acid
composition, as was done when developing high linoleic acid linseed (Linola) from a high
linolenic acid variety (Green, 1986). However, induced mutagenesis is disadvantageous as it
lacks precision, generating many plants with defects and entails extensive screening of lines to
eliminate the bulk of abnormal ones. Undesirable traits such as late flowering, reduced vigour
and low seed yield are obtained alongside the phenotype of interest in mutant lines. This method
is therefore unreliable for creating variants in which only one locus influencing synthesis of a
specific fatty acid is disrupted.
Current research effort is directed towards creating plant oils having diverse fatty acid
composition by genetic engineering. This approach is superior to those previously used owing to
its precision and applicability across taxa. By using molecular techniques, it is possible to modify
specifically the seed oil quality while keeping the rest of the genetic background of the plant
intact.
1.3.1 Molecular aspect of modifying seed oil composition
Marker-assisted selection (or molecular-assisted), MAS breeding can provide a dramatic
improvement in the efficiency with which breeders can select plants with desirable combinations
of genes. MAS is gaining considerable importance as it would improve the efficiency of plant
breeding through precise transfer of genomic regions of interest (foreground selection) and
accelerate the recovery of the recurrent parent genome (background selection). They can be used
to monitor DNA sequence variation in and among the species and create new sources of genetic
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Introduction
variation by introducing new and favourable traits from landraces, wild relatives and related
species. This will help to fasten the time taken in conventional breeding, germplasm
characterization, genetic mapping, gene tagging and gene introgression from exotic and wild
species. For successful MAS, a molecular breeder needs a lot of information like: position of the
markers, details of candidate gene, mapping of those markers alongwith the phenotypic data and
domestication history of the candidate gene beside other minor information of the crop
germplasm.
1.4 Molecular markers
Molecular markers are now widely used to track loci and genome regions in several cropbreeding programmes, as molecular markers tightly linked with a large number of agronomic and
disease resistance traits are available in major crop species (Phillips and Vasil, 2001; Jain et al.,
2002; Gupta and Varshney, 2004). These molecular markers include: (i) hybridization-based
markers such as restriction fragment length polymorphism (RFLP), (ii) PCR-based markers:
random amplification of polymorphic DNA (RAPD), amplified fragment length polymorphism
(AFLP) and microsatellite or simple sequence repeat (SSR), and (iii) sequence-based markers:
single nucleotide polymorphism (SNP). The majority of these molecular markers has been
developed either from genomic DNA libraries (e.g. RFLPs and SSRs) or from random PCR
amplification of genomic DNA (e.g. RAPDs) or both (e.g. AFLPs). These DNA markers can be
generated in large numbers and can prove to be very useful for a variety of purposes relevant to
crop improvement. Amongst all the markers, the third generation molecular marker with highest
frequency is SNP.
1.4.1 SNP
In the simplest form, a single nucleotide polymorphism (SNP) is an individual nucleotide base
difference between two DNA sequences. SNPs can be categorized according to nucleotide
substitution as either transitions (C/T or G/A) or transversions (C/G, A/T, C/A, or T/G). As a
nucleotide base is the smallest unit of inheritance, SNPs provide the ultimate form of molecular
genetic marker. They also represent the most frequent type of genetic polymorphism, and the
potential number of such markers is enormous in comparison with any but the most closely
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Introduction
related genotypes within a given species (Rafalski, 2002). They can occur in any position within
or outside of genes and accordingly can have very different effects. SNPs present within the
protein encoding regions of a gene may result in incorporation of an alternative amino acid in the
protein for which the gene serves as the blueprint, or template. Depending on where this occurs
within the protein and to what extent the alternative amino acid differs from the normally
incorporated one; such an amino acid exchange can have a profound influence on the function of
the protein.
1.4.1.1 SNP: advantages and uses
The main advantages of SNPs are: they are very common and evenly-distributed in the
genome, and secondly, methods of detecting (or "assaying") SNPs can be easily automated. This
ease of automation is what makes SNPs "high- throughput" markers. It can be applied to various
purposes including rapid identification of crop cultivars, construction of ultra-high density
genetic maps and association with genetic disorders (in humans and livestock) and agronomic
traits (in crop plants).
1.4.1.2 SNP discovery in plants
The two main strategies which can be followed for SNP searching to obtain genetic
correlation data are whole-genome scans and candidate gene-based approaches.
1.4.1.2.1 Whole genome scan
This requires scanning the whole-genome with a very large number of genetic loci (in the region
of 10,000–100,000 or higher). This objective is difficult to achieve as it requires an extremely
detailed knowledge of the genome under consideration, the availability of a large number of
independent SNP markers, and a high throughput detection method that can ideally be
multiplexed on a very large-scale. For plant species, in which genomes can be relatively
complex, for which linkage disequilibrium may only extend over short molecular distances
because of the influence of reproductive systems, and for which SNP frequencies may be low
(Rafalski and Morgante, 2004), this approach can be difficult to apply.
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Introduction
1.4.1.2.2 Candidate gene approach
This approach consists of the characterization of SNPs present in a subset of specific genes
identified using various strategies such as bioinformatics-based data mining, QTL analysis and
linkage mapping, expression studies, transgenic modification by antisense RNA expression or
RNA interference (RNAi), or positional cloning and physical mapping. The idea is to find the
single base polymorphism that is directly causal of functional variation in the trait of interest
(which is often termed the qualitative or quantitative trait nucleotide, QTN), or at least to find a
SNP located within the functional gene or at a small physical distance from the gene. This
strategy provides a good solution to the problems raised by the rapid decline of linkage
disequilibrium observed in plant genomes (Rafalski and Morgante, 2004), as the chances that
linkage disequilibrium may be dissipated by a recombination event are extremely low in
generational time (c. 10 6per meiosis) when assaying a SNP located in a candidate gene,
compared with much higher probabilities when using a more distant marker in a low-resolution
genome scan. This numerically discrete strategy may consequently be applied to a large number
of individuals (such as those present within germplasm collections).
1.5. Mapping
Two of the most commonly used tools for dissecting complex traits are Quantitative trait loci
(QTL) mapping and association mapping (Risch and Merikangas, 1996; Mackay, 2001).
1.5.1 QTL mapping
The acronym QTL refers to Quantitative Trait Locus. Quantitative traits refer to
phenotypes (characteristics) that vary in degree and can be attributed to polygenic effects, i.e.,
product of two or more genes, and their environment. Quantitative trait loci (QTLs) are stretches
of DNA containing or linked to the genes that underlie a quantitative trait. Mapping regions of
the genome that contain genes involved in specifying a quantitative trait is done using molecular
tags such as AFLP or, more commonly SNPs. This is an early step in identifying and sequencing
the actual genes underlying trait variation. QTLs are detected through QTL mapping
experiments. In crop plants, these experiments utilize experimental pedigrees, usually produced
from crossing two inbred lines.
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Introduction
1.5.2 Association mapping
In association mapping, the genetic markers usually must lie within (or directly upstream
or downstream of) candidate genes suspected to contribute to the variation in that trait, and the
goal is to identify the actual genes affecting that trait, rather than just (relatively large)
chromosomal segments. In contrast to QTL mapping, which is performed in the context of a
pedigree, association mapping is performed at the population level: the genotypes of the
candidate gene markers and the phenotypes of the corresponding trait are determined in a set of
unrelated or distantly-related individuals sampled from a population. Association mapping relies
on linkage disequilibrium (LD) between the candidate gene markers and the actual causative
polymorphism in that gene (i.e., the actual polymorphism that causes the differences in the
phenotypic trait). Hence association mapping is also referred to as 'LD mapping'.
Although the goal of both association mapping and linkage mapping is to find
associations between phenotypes and genes (or molecular markers), there are some important
differences. Linkage mapping, is usually done in the context of closely related individuals having
known relationships, such as the offspring of a controlled cross or the members of a family
where the pedigree is known. Since the number of recombination events in these cases is
relatively small, genes or quantitative traits are mapped to large chromosomal blocks, and the
resolution is low (Mb scale). On the other hand, association mapping is done using distantly
related individuals with unknown relationships, randomly chosen from a natural population. If
the population has a long history of inbreeding, LD will decay slowly and the resolution of the
association mapping study will be quite low.
1.6 SNP genotyping
SNP genotyping is the measurement of genetic variations of single nucleotide polymorphisms
(SNPs) between members of a species. Several methods are employed to study SNP genotyping
like which fall under two categories broadly, hybridization based methods and enzyme based
methods.
Several applications have been developed that interrogate SNPs by hybridizing
complementary DNA probes to the SNP site. The challenge of this approach is reducing crosshybridization between the allele-specific probes. This challenge is generally overcome by
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Introduction
manipulating the hybridization stringency conditions (Rapley and Harbron, 2004). In enzyme
based
techniques
a
broad
range
of
enzymes
including DNA
ligase, DNA
polymerase and nucleases are employed to generate high-fidelity SNP genotyping methods.
PCR based method falls under enzyme based genotyping. It employs two pairs of primers
to amplify two alleles in one PCR reaction. The primers are designed such that the two primer
pairs overlap at a SNP location but each match perfectly to only one of the possible SNPs. As a
result, if a given allele is present in the PCR reaction, the primer pair specific to that allele will
produce product but not to the alternative allele with a different SNP. The two primer pairs are
also designed such that their PCR products are of a significantly different length allowing for
easily distinguishable bands by gel electrophoresis. In examining the results, if a genomic sample
is homozygous, then the PCR products that result will be from the primer which matches the
SNP location to the outer, opposite strand primer as well from the two opposite, outer primers. If
the genomic sample is heterozygous, then products will result from the primer of each allele to
their respective outer primer counterparts as well as from the two opposite, outer primers. It is
also called allele-specific (AS) Polymerase Chain Reaction, and is a convenient and inexpensive
method for genotyping SNPs and mutations. It is applied in many recent studies including
population genetics, molecular genetics and pharmacogenomics.
The present study
The aim of this study was to develop conventional and biotechnological tools that could be used
in sesame improvement programs towards diversifying the fatty acid composition of the seed oil.
Such work would help expand the market niche for sesame oil, thereby contributing to increased
cultivation of the crop. In addition, a better market competitiveness would translate to having a
sure source of income for sesame farmers, thereby improving their livelihood. From a long-term
perspective the present work, through development of SNP markers those are currently lacking
and their association mapping to the fatty acid composition will help in future for marker assisted
selection. Moreover domestication history of the trait of interest will help plant breeders in the
discovery and utilization of rare but potentially important alleles present in the genetic resources.
Till date, no such work has been reported not only in Indian germplasm of sesame but also
worldwide. Moreover, there is insufficient variability in the fatty acid composition of sesame oil.
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Introduction
This study will identify cultivars with high linolenic acid content and a composition different
from the rest that will later be developed further by genetic modification for the production of
novel oils. Genetic transformation of sesame with certain genes involved in fatty acid synthesis
will provide a means to effect changes in oil composition.
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