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PATTERN OF GENETIC DIVERGENCE AND EXPLOITATION OF
SOMACLONAL VARIATIONS IN ADOPTED SUGARCANE
GENOTYPES (Saccharum officinarum L.)
MUHAMMAD SHAHZAD AHMED
(Regd. No. 2011-URTB-12808)
DEPARTMENT OF PLANT BREEDING & MOLECULAR GENETICS
FACULTY OF AGRICULTURE, RAWALAKOT
THE UNIVERSITY OF AZAD JAMMU AND KASHMIR
PATTERN OF GENETIC DIVERGENCE AND EXPLOITATION OF
SOMACLONAL VARIATIONS IN ADOPTED SUGARCANE
GENOTYPES (Saccharum officinarum L.)
By
Muhammad Shahzad Ahmed
2011-URTB-12808
M.Sc. (Hons.) Plant Breeding and Genetics
A thesis submitted in the partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
IN PLANT BREEDING AND MOLECULAR GENETICS
FACULTY OF AGRICULTURE, RAWALAKOT
THE UNIVERSITY OF AZAD JAMMU AND KASHMIR
i
ii
DECLARATION
I say publicly that, this thesis is entirely my own work and has not been
presented in any way for any degree to any other university.
04, May, 2017 Signature ___________________________
Muhammad Shahzad Ahmed
iii
DEDICATION
To my parents
iv
CONTENTS
Chapter Page
Acknowledgements xii
1 GENERAL INTRODUCTION 1
2 MORPHOLOGICAL STUDIES
2.1. INTRODUCTION
2.2. REVIEW OF LITERATURE
2.3. MATERIALS AND METHODS
2.3.1. Field Experiment
2.3.2. Data Collection
2.3.3. Statistical Analysis
2.4. RESULTS AND DISCUSSION
2.5. CONCLUSION AND RECOMMENDATIONS
16
3 MOLECULAR STUDIES
3.1. INTRODUCTION
3.2. REVIEW OF LITERATURE
3.3. MATERIALS AND METHODS
3.3.1. Plant Material
3.3.2. DNA extraction and quantification
3.3.3. Primer selection
3.3.4. PCR amplification
3.3.5. Electrophoreses and fragment analysis
3.3.6. Gel image analysis
3.3.7. Statistical analysis
3.4. RESULTS AND DISCUSSION
3.4.1. RESULTS
3.4.2. DISCUSSION
3.5. CONCLUSION AND RECOMMENDATIONS
50
4 SOMACLONAL VARIATIONS
4.1 INTRODUCTION
4.2 REVIEW OF LITERATURE
4.3 MATERIALS AND METHODS
4.3.2 Induction of somaclonal variation.
82
v
4.3.3 Somaclonal variation detection with SSR
markers.
4.3.4 Genetic integrity of candidate genes in
somaclones.
4.3.3.1. Database search and annotation of
candidate genes in sorghum and
maize
4.3.3.2. Database search and annotation of
candidate genes in sorghum and
maize.
4.3.3.3. Verification of candidate genes in
sugarcane.
4.3.3.4. Authentication amplified products
with reference sequences.
4.3.3.5. Silica based gel purification of
PCR products.
4.3.3.6. Quantification of purified PCR
product and sequencing.
4.3.3.7. Alignment of sequenced reads
with reference sequences for
conformation.
4.3.5 Screening of somaclones against red rot
(Colletotrichum falcatum L.).
4.3.6 Screening of somaclones against
sugarcane mosaic virus (SCMV).
4.3.7 Field performance of M0 generation of
somaclones.
4.3.8 Statistical analysis.
4.4 RESULTS AND DISCUSSION
4.5 CONCLUSION AND RECOMMENDATIONS
GENERAL CONCLUSION 163
GENERAL SUMMARY 164
5 LITERATURE CITED 167
vi
LIST OF TABLES
Table No. Title Page
Table 2.1 Sugarcane genotypes obtained from Sugarcane
Research Institute, AARI, Faisalabad Pakistan and
their names, nativity and parentage.
26
Table 2.2a Mean performance of morpho-physological traits of 20
sugarcane genotype from pooled data obtained during
the years 2013and 2014.
33
Table 2.2b Basic statistics for the estimated variables in
Sugarcane genotypes.
34
Table 2.3 Principal Components of Quantitative traits in 20
Sugarcane Genotypes.
36
Table 2.4 Analysis of the variance of quantitative traits in
sugarcane for cluster analysis.
44
Table 2.5 Non- Hierarchal Clusters and members in each cluster. 48
Table 3.1 A description of 49 sugarcane microsatellite markers
containing primer names, forward and reverse primer
sequences.
63
Table 3.2 A description of 49 sugarcane microsatellite markers
containing primer names, melting temperature, PCR
Product range (bp), No. of loci, Polymorphic loci, %
polymorphism, Polymorphic information contents
(PIC), Diversity Index (DI).
70
Table 3.3 Similarity coefficient matrix among 20 sugarcane
genotypes obtained by Jaccard’s similarity coefficient
using NTSYS-pc V 2.1.
75
Table 3.4 Principal Coordinate Analysis for 20 sugarcane
genotypes from SSR marker data.
77
Table 4.1 A description of 10 sugarcane microsatellite markers
containing primers names, forward and reverse primer
sequences.
104
Table 4.2 Average number of loci, average polymorphic loci and
average polymorphism percentage in somaclones of
each variety generated by 10 primers.
128
Table 4.3 A description of PCoA-1 and PCoA-2 eigenvalues,
percent variation and cumulative variation based on
binary data obtained from 10 SSR primers pairs
applied on parental clones and their somaclones.
132
Table 4.4 Candidate gene’s ID, putative functions, source
sequences of sequences, location on sorghum
chromosome, transcript name, exon(s), primer
sequences and product size.
135
Table 4.5 Total number of somaclones raised from parental
clones of six varieties inoculated with red rot spores
suspension culture and their response against red rot
148
vii
LIST OF FIGURES
Figure No. Title Page
Figure 1.1 Sugarcane production areas in the world. 2
Figure 1.2 Top 10 sugarcane producing countries in the world.
Source: Food and Agriculture Organisation (FAO).
6
Figure 1.3 Last five years sugarcane production status in
Pakistan.
7
Figure 1.4 Last 65 years sugarcane production status in
Pakistan.
8
Figure 2.1 Location of sugarcane sown at Arja Bagh, Azad
Kashmir (East 73.97°-42 minutes, North 33.97°- 21
minutes, Altitude 797m above sea level.). Figure
indicate the map of Pakistan (a), arrow showed the
satellite image of Arja near Arja bridge (b) and next
arrow indicate the site of experiment (c).
27
Figure 2.2 Scree plot diagram for quantitative traits of
sugarcane
36
Figure 2.3 Loading of PC1. 38
Figure 2.4 Loading of PC2. 38
Figure 2.5 Loading of PC3. 40
Figure 2.6 Loading of PC4. 40
Figure 2.7 Plot of (PC1) versus (PC2) for 10 Quantitative traits
and 20 Sugarcane genotypes.
42
Figure 2.8 Cluster Diagram of 20 Sugarcane Genotypes on the
bases of morpho-physological traits.
46
Figure 3.1 A hierarchical homology tree constructed by the
NTSYS pc (V2.0) software indicating the similarity
coefficient (%) among 20 sugarcane genotypes
(Saccharum officinarum L.).
76
Figure 3.2 Principal Coordinate Analysis (PCoA) of the first
two axes (PCoA1 and PCoA2) for 20 sugarcane
genotypes.
77
Figure 4.1 Schematic diagram of callus induction, sub-
culturing and irradiation callus for induction of
somaclonal variation, regeneration, shooting,
rooting, hardening and field transplantation in
sugarcane.
117
viii
Figure 4.2 Principal coordinate biplots of somaclones and their
parents on the bases of SSR score of primers used to
detect somaclonal variation. Where (a) = S-03-SP-
93, (b) =S-05-US-54, (c) = S-03-US-694, (d) = S-
06-US-300, (e) = HSF-240, (f) = SPF-213, (g) = S-
05-US-54 (10Gy).
133
Figure 4.3 Sequence annotations of sorghum candidate genes
searched from gene database Phytozome 9.1. where
(a) represents catalase isozyme 3 transcript
sequence, (b) sucrose phosphate synthase, (c)
Gibberellin 2 oxidase 4, (d) Teosinte branched1.
137
Figure 4.4 Pairwise sequence alignments of candidate genes
exon(s) regions, here (a) CAT1 sugarcane mRNA
gene bank accession (KF528830.1) and sugarcane
gDNA obtained sequence, (b) SPS sorghum
sequence (Sb04g005720) and sugarcane gDNA
obtained sequence, (c) Gibberellin2 oxidase 4
sorghum exon sequence and sugarcane GA2 oxidase
obtained sequence, (d) Teosinte branched1 sorghum
sequence and sugarcane obtained sequence.
138
Figure 4.5 Multiple alignment of CAT1 sequence reads
obtained from parental clone of S-03-SP-93 and its
5 somaclones; SC1, SC2, SC3, SC4 and SC5,
showed no SNPs.
142
Figure 4.6 Multiple alignment of CAT1 sequence reads
obtained from parental clone of S-05-US-54 (10Gy)
and its 5 somaclones; SC30, SC31, SC32, SC33 and
SC34, showed transversion of C into G at position
673 of parental clone’s read in SC32, SC33 and
SC34.
142
Figure 4.7 Multiple alignment of SPS exon-I sequence reads
obtained from parental clone of S-05-US-54 and its
5 somaclones; SC6, SC7, SC8, SC9 and SC10,
showed no SNPs.
143
Figure 4.8 Multiple alignment of exon-I sequence reads
obtained from parental clone of S-05-US-54 (10Gy)
and its 5 somaclones; SC30, SC31, SC32, SC33 and
SC34, showed transition of T into C at position 607
of parental clone’s read in SC30, SC32, SC33 and
SC34 while a transition of G into A at position 673
in SC30, SC31, SC32, SC33 and SC34.
143
Figure 4.9 Multiple alignment of SPS exon-II sequence reads
obtained from parental clone of S-03-US-694 and
its 5 somaclones; SC11, SC12, SC13, SC14 and
SC15, showed no SNPs.
144
Figure 4.10 Multiple alignment of GA2 oxidase 4 sequence
reads obtained from parental clone of S-06-US-300
and its 5 somaclones; SC16, SC17, SC18 and SC19,
showed no SNPs.
144
ix
Figure 4.11 Multiple alignment of GA2 oxidase 4 sequence
reads obtained from parental clone of HSF-240 and
its 5 somaclones; SC20, SC21, SC22, SC23
andSC24 showed no SNPs.
145
Figure 4.12 Multiple alignment of GA2 oxidase 4 sequence
reads obtained from parental clone of S-05-US-54
(10Gy) and its 5 somaclones; SC30, SC31, SC32,
SC33 and SC34, showed transition of T into C at
position 190 of parental clone’s read in SC30,
SC31, SC32, SC33 and SC34.
145
Figure 4.13 Multiple alignment of TB1 sequence reads obtained
from parental clone of SPF-213 and its 5
somaclones; SC25, SC26, SC27, SC28 and SC29,
showed no SNPs.
146
Figure 4.14 Multiple alignment of TB1 sequence reads obtained
from parental clone of S-05-US-54 (10Gy) and its 5
somaclones; SC30, SC31, SC32, SC33 and SC34,
raised from irradiated callus showed transversion of
G into T at position 170 of parental clone’s read in
somaclone SC32.
146
x
LIST OF PICTURES
Picture No. Title Page
Picture 3.1 Banding pattern of twenty adopted sugarcane
genotypes by using highly polymorphic SSR primer
pair P-90
72
Picture 3.2 Separation of PCR products of primer P-90 on PAGE
gel.
72
Picture 3.3 PCR products of primer mSSCIR43 on PAGE gel. 72
Picture 3.4 PCR products of primer P-89.
.
73
Picture 3.5 PCR products of primer P-100.
73
Picture 3.6 PCR products of primer P-101. 73
Picture 3.7 PCR products of primer P-137.
74
Picture 3.8 PCR products of primer SMs037.
74
Picture 3.9 PCR products of primer SMs009. 74
Picture 4.1 A view of crystalline compact and embryogenic calli
formed from young meristematic enfold leaves explant
after 24 days of inoculation in first subculture in
Murashige Skoog (MS) medium supplemented with
3mg/L 2,4-D. Where P1, P2, P3, P4, P5 and P6 are S-
03-SP-93, S-05-US-54, S-03-US-694, S-06-US-300,
HSF-240 and SPF-213 respectively.
120
Picture 4.2 Regeneration from calli after 70 days of inoculation in
third subculture in MS medium supplemented with
1mg/L BAP. Where a, b, c, d, e, f and g represent
regeneration of S-03-SP-93, S-05-US-54, S-03-US-
694, S-06-US-300, HSF-240 SPF-213 and S-05-US-54
(10Gy) respectively.
120
Picture 4.3 Shooting of four weeks old regeneration tissues in MS
medium supplemented with 1mg/L Kinetin. Where a,
b, c, d, e, f and g represents shooting of S-03-SP-93, S-
05-US-54, S-03-US-694, S-06-US-300, HSF-240 and
SPF-213 S-05-US-54 (10 GY)respectively.
122
Picture 4.4 Picture 4.4: Rooting of shootlets in half strength MS
medium supplemented with 1mg/L NAA. Where a, b,
c, d, e, f and g represent regeneration of S-03-SP-93,
S-05-US-54, S-03-US-694, S-06-US-300, HSF-240
and SPF-213 S-05-US-54 (10 GY) respectively.
122
Picture 4.5 SSR based detection of somaclonal variation in the
form of addition and deletion of short tandem repeats,
where (a) represent SP-93 and its somaclones banding
pattern with primer P-90, (b) represent S-05-US-54
129
xi
and its somaclones with primer P-89, (c) represent S-
03-US-694 and its somaclones using primer
MSSCIR58, (d) represent S-06-US-300 and its
somaclones with primer SMC119CG, (e) represent
HSF-240 and its somaclones with primer
SMC1604SA, (f) represent SPF-213 and its
somaclones with primer SMC1604SA and (g)
represent S-05-US-54 (10 Gy) and its somaclones with
primer MSSCIR58.
Picture 4.6 Combine picture of candidate genes with exon regions
gel purified PCR products amplified from sugarcane
gDNA samples, where (CAT1) is Catalase, (SPS)
Sucrose phosphate synthase gene, (GA 2-oxidase 4)
gibberellin 2-oxidase 4, and (TB1) Tillering gene.
138
Picture 4.7 Leaf samples of parental clone and somaclones. Where
(a) represents red rot infected leaf of one of the
representative parental clone while (b), (c), (d), (e), (f),
(g) and (h) represent red rot free somaclones leaf
samples of varieties i.e. S-03-SP-93, S-05-US-54, S-
03-US-694, S-06-US-300, HSF-240 SPF-213 and S-
05-US-54 (10Gy) respectively.
150
Picture 4.8 Response of somaclones against red rot after
inoculation. Where (a) represents highly susceptible
clone of S-05-US-54 (10Gy), (b) represents highly
susceptible clone of S-03-SP-93, (c) represents
resistant somaclone of S-03-SP-93 and (d) represents
highly resistant somaclone of S-03-SP-93.
150
Picture 4.9 Leaf samples of parental clone and somaclones. Where
(a) represents SCMV infected leaf of one of the
representative parental clone while (b), (c), (d), (e), (f),
(g) and (h) represent virus free somaclones leaf
samples of varieties i.e. S-03-SP-93, S-05-US-54, S-
03-US-694, S-06-US-300, HSF-240 SPF-213 and S-
05-US-54 (10Gy) respectively.
153
xii
LIST OF GRAPHS
Figure No. Title Page
Graph 4.1 Effect of different concentration levels of 2, 4 D on
callus induction and callus recovery percentage.
120
Graph 4.2 Number of somaclones raised, number of somaclones
survived after hardening and number of somaclones
survived after transplantation.
124
Graph 4.3 Somaclones survival %age after hardening and
survival percentage after transplantation.
124
Graph 4.4 A graphical description of 10 sugarcane
microsatellite markers containing primer ID, No. of
loci, Polymorphic loci and % polymorphism among
seven parental clones and their thirty four
somaclones.
128
Graph 4.5 Screening of somaclones against red rot by using 0-9
scale as described by Srinivasan and Bhat (1961).
148
Graph 4.6 Screening of somaclones against sugarcane mosaic
virus (SCMV).
153
Graph 4.7 Mean values of plant height of somaclones and their
parental clones.
156
Graph 4.8 Mean values of number of tillers per plant in
somaclones and their parental clones.
156
Graph 4.9 Mean values of stem diameter of somaclones and
their parental clones.
158
Graph 4.10 Mean values of number of internodes per plant of
somaclones and their parental clones.
158
Graph 4.11 Mean values of internodes length of somaclones and
their parental clones.
161
Graph 4.12 Mean values of brix percentage in somaclones and
their parental clones.
161
xiii
AKNOWLEDGEMENTS
I am thankful to Almighty Allah for His blessings that enabled me to
accomplish this work and His Prophet Muhammad (Peace be upon Him) who is a
tower of guidance for the humanity.
I would like to express my special gratitude and appreciation to Prof. Dr.
Syed Dilnawaz Ahmad Gardazi for providing me the opportunity to pursue my
education at The University of Azad Jammu and Kashmir and advising me
throughout my studies. I am highly indebted to the members of my supervisory
committee: to Prof. Dr. Sardar Ali Khan and Prof. Dr. Abdul Hamid for helping me
during my research. Humble thanks to my Co-Supervisor Dr. Muhammad Zaffar
Iqbal, Director Agricultural Biotechnology Research Institute, AARI, Faisalabad
for providing opportunity to work with his team for pursuing almost half of my
thesis research in his institute. I am would like to thank Prof. Dr. Jacqueline Batley
Centre of Integrative Legume Research, School of Agriculture and Food Sciences,
University of Queensland, Brisbane Australia and his team for providing me
opportunity to work in her lab with her team for 6 months, whose great expertise in
genetic stability analysis of candidate genes in somaclones made my project
possible to accomplish; her passion for science has made me change the way of
thinking about molecular genetics and bioinformatics.
I am thankful to the Higher Education Commission Pakistan for providing
me funding to travel abroad, accomplish my research work and gain additional
expertise. Special thanks to Dr. Shahid Iqbal Awan Lecturer Department of Plant
Breeding and Molecular Genetics, University of Poonch for technical support in
my research and guidelines. Many thanks to Aslam Javid Assistant Plant Virologist
and Dr. Shahid Nazir ARO, Agricultural Biotechnology Research Institute, AARI,
Faisalabad for providing me opportunity to work in their labs.
I am greatly obliged to my family members: particularly my father, mother,
brothers, sisters my spouse and beloved daughter Afsa for their continuous support
encouragement and love they extended with me. Help from the staff of PB&MG
lab, Faculty of Agriculture Rawalakot and everyone else in accomplishment of this
piece of work is greatly acknowledged.
Muhammad Shahzad Ahmed
xiv
ABBREVIATIONS
% Percentage
°C Degree Celsius
µg Microgram
µl Microliter
2, 4-D 2, 4-Dichlorophenoxyacetic acid
AARI Ayyub Agricultural Research Institute
AFLP Amplified Fragment Length Polymorphism
AGRF Australian Genome research Facility
APS Ammonium per sulphate
BAP 6-Benzylaminopurine
BLAST Basic local alignment search tool
BLASTn Basic local alignment search tool for nucleotides
bp Base pair
CDS Complementry DNA sequences
Chr Chromosome
CILR Center for Integrative Legume Research
cm Centimeters
CTAB Cetyl trimethylammonium bromide
d2H2O Double Distilled Water
DAP Diammonium Phosphate
DI Diversity index
DNA Deoxyribonucleic acid
ELISA Enzyme-linked immunosorbent assay
EST Expressed sequence tag
g Gram
GA Gibberellin
gDNA Genomic DNA
GDP Gross Domestic Product
GS Genetic similarity
IAA Indole Acetic Acid
Kbp Kilo base pair
Kg Kilogram
LA Leaf Area
MAS Marker Assisted Selection
mg/L Miligram per liter
MS Murashige and Skoog
NAA 1-Naphthaleneacetic acid
NCBI National Center for Biotechnology Information
ng Neno Gram
O.D Optical density
PAGE Polyacrylamide gel electrophoresis
PCA Principle Component Analysis
PCoA Principal Coordinate analysis
PCR Polymerase Chain Reaction
PIC Polymorphic information content
pNPP p-nitrophenyl phosphate
PVP Polyvinylpyrrolidone
xv
RAPD Randomly Amplified Polymorphic DNA
RFLP Restriction Fragment Length Polymorphism
SC Somaclone
SCMV Sugarcane Mosaic Virus
SNP Single nucleotide polymorphism
SPS Sucrose phosphate synthase
R Resistant
MR Moderatly resistant
MS Moderatly susceptible
S Susceptible
HS Highly susceptible
SSR Simple Sequence Repeats
TB1 Teosinte branched 1
TBE Tris Boric Ethylenediaminetetraacetic acid
TE Tris Ethylenediaminetetraaceticacid
TEMED N, N, N’, N’-Tetramethylethylenediamine
TILLING Targeting induced local leasion in genome
UPGMA Unweighted pair group method with arithmetic mean
UQ University of Queensland
V Volts
Σ Summation
Abstract
Present study was conducted to assess the genetic divergence and creation of
somaclonal variation in sugarcane. Phenotypic diversity of sugarcane genotypes was
estimated on the bases of some morpho-physiological traits and diversity on molecular
level was assessed with simple sequence repeat markers. For somaclonal variation tissue
culture following callus sub-culturing and irradiation with gamma (γ) rays were utilized.
Analysis of variance revealed highly significant differences among the morpho-
physological traits in genotypes. Principal Component Analysis depicted 54.63%
cumulative variance while SSR based genetic diversity analysis depicted 50.1%
variability in genotypes under study. Hierarchal and non-hierarchal cluster grouped
genotypes into five clusters and some diverse genotypes were identified with good
morphological traits. These genotypes can be used as parent for breeding program.
Six varieties were used for somaclonal variation that showed good response to
callus induction at 3mg/L 2, 4-D supplemented in MS media. Irradiation of callus
showed poor response to regeneration with maximum mortality and only few plants
from one variety was survived at 10 Gy level. Survival percentage of somaclones after
hardening and field transplantation was recorded 33.3% and 60%, respectively.
Somaclones showed considerable magnitude of SSR based polymorphism. Genetic
integrity assessment of candidate genes in somaclones revealed intact nucleotide
sequences, however few SNPs were detected in somaclones raised from irradiated
callus. Somaclones showed negligible sugarcane mosaic virus concentration with
mostly resistant reaction against red rot. Increase in number of internodes with reduced
length and high brix percentage was observed in somaclones as compare to their parental
clones. It is concluded that considerable magnitude of divergence observed in plant
material may be tested to initiate the breeding programme alternatively somaclonal
variation is a good source of variability in the sugarcane.
GENERAL INTRODUCTION
1
Chapter: 01
GENERAL INTRODUCTION
Agriculture occupies a vital status in the Economy of Pakistan. Its input to
GDP is 25.6%, generating 45% of the employment opportunities and is contributing
significantly to the other segments of the economic growth. Among agricultural
products sugarcane is the major source of sugar to meet the dietary requirements of
major population and also represents a vital position in agriculture policies devised
by the government (MNFS&R, 2013-14).
1.1. DOMESTICATION AND DISTRIBUTION OF SUGARCANE SPECIES
Sugarcane is grown in all tropical and subtropical regions of the world, on
both sides of the equator, up to approximately 35° N and 35° S (Dillewijn and Mass
1952; Cheavegatti-Gianotto, 2011). Sugarcane (S. officinarum L.) is a tropical
“noble” canes indigenous to New Guinea regions of south pacific (Fig. 1.1). This
species is no longer available wild and only found in cultivation in native gardens.
Plants are characterized by thick stems, soft rinds, high cane yield, low fibre and high
sucrose contents. It has been cultivated since prehistoric times (Sreenivasan et al.,
1987). It is generally believed that its centre of origin is Polynesia and that the species
was scattered throughout Southeast Asia, the modern centre of diversity was created
in Papua New Guinea and Java (Indonesia); from where the most of the samples
were collected in the last decades of 19th century (Daniels and Roach, 1987).
Sacccharum barberi and saccharum sinense are the north India and Chinese
sugarcanes, respectively indigenous to north India, Bangladash and Burma China
regions. The species probably originated by hybridization between S. officinarum
and S. spontanum. They have thick stem, great vigour, early maturity, wide
GENERAL INTRODUCTION
2
adoptability and comparatively resistant to biotic and abiotic stresses than S.
officinarum (Sleper and Poehlman, 2006).
The centre of diversity of S. spontaneum are temperate regions of subtropical
India. It is grown in a wide range of geographical regions (Fig. 1.1) ranging from
8°S to 40°N in three geographic zones: a) eastern zone, in the South Pacific Islands,
Philippines, Taiwan, Japan, China, Vietnam, Thailand, Malaysia and Myanmar; b)
central zone, in India, Nepal, Bangladesh, Sri Lanka, Pakistan, Afghanistan, Iran and
the Middle East; and c) western zone, in Egypt, Kenya, Sudan, Uganda, Tanzania,
and other Mediterranean countries (Daniels and Roach 1987).
Saccharum robustum is a wild species native to New Guinea. The species has
great vigour, wide adaptability, tall with medium thickness, high in fibre, low sucrose
contents and susceptible to mosaic disease. It has not been utilized extensively in the
breeding of commercial cultivars (Sleper and Poehlman, 2006).
Worldwide sugarcane production
Fig. 1.1: Sugarcane production areas in the world.
Source: FAOSTAT, 2014. Food and Agriculture Organization of the United
Nations, Statistics Division.
GENERAL INTRODUCTION
3
1.2.TAXONOMY OF SUGARCANE
According to the Carl Linnaeus (1707-1778) classification system sugarcane is
classified in the genus Saccharum, tribe Andropogoneae, family Gramineae. Within
genus Saccharum there are three species of cultivated sugarcane namely S.
officinarum L., S. barberi Jesw. and S. sinense Roxb., and two species of wild
sugarcane, S. robustum Brandes and Jeswiet ex Grassl, and S. spontaneum L. Present
day cultivated sugarcane clones are complex hybrids among these species and cannot
be classified as belonging to any specific species. S. edule Hassk., another species of
Saccharum, has an eatable inflorescence but has little or no sugar (Sleper and
Poehlman, 2006).
Kingdom Plantae
Subkingdom Tracheobionta
Superdivision Spermatophyta
Division Magnoliophyta
Class Lilliopsida
Subclass Commelinidae
Order Cyperales
Family Poaceae
Subfamily Panicoideae
Tribe Andropogoneae
Sub tribe Saccharinae
Genus Saccharum
Species Saccharum officinarum; Saccharum spontaneum;
Saccharum sinense; Saccharum barberi; Saccharum
robustum; Saccharum edule: Saccharum villosum and
Saccharum asperum.
1.3. PHYLOGENY OF SUGARCANE
Within the tribe Andropogoneae genus Saccharum is included, characterized by
having pedicellate spikelets. Clayton and Renvoize (1986) postulated that this was
the most primitive of the Andropogoneae, but this hypothesis has not been supported
by molecular phylogenetic data. The “Saccharum complex” was originally
categorized by Mukherjee (1957) by including genera i.e. Narenga, Sclerostachya,
GENERAL INTRODUCTION
4
Erianthus sect. Ripidium, and Saccharum. Most of the species in this complex have
tough main axis of the inflorescence and does not disintegrate at maturity; however,
the lateral branches separate between the spikelet pairs. Although awned lemmas are
common in this group, but absent in some species. Miscanthus was not included in
Saccharum group by Mukherjee (1957) in his original description, but it was later
added (Daniels and Daniels 1975).
Hodkinson et al., (2002) conducted the comprehensive molecular
phylogenetic study to investigate the “Sacrarium complex”. They included multiple
species of Saccharum and Miscanthus, as well as representatives of Erianthus,
Eulalia, Pogonatherum, Imperata, Narenga, and Spodiopogon in their studies and
concluded that with all other phylogenetic studies in the group, the relationships are
weak. Numerous other studies produced preliminary results that are consistent with
those of Hodkinson et al., (2002). Nair et al., (1999) used RAPD markers and found
a group corresponding to Saccharum, and another similar to Miscanthus. Besse et
al., (1997) used RFLP data to show that seven species of Erianthus were distinct
from two species of Saccharum, and Selvi et al., (2006) likewise found a clear
distinction between Saccharum species and Erianthus using AFLPs. Bacci et al.,
(2001) conducted ITS phylogeny of sugarcane and its relatives commonly
recognized six species are: S. officinarum, S. robustum, S. spontaneum, S. sinense,
S. barberi, and S. edule. Takahashi et al., (2005) studied the DNA sequences from
18 chloroplast regions and proposed that S. spontaneum is sister to the remaining
species. Few of the studies have used accepted phylogenetic methods, and none has
attempted to dissect the complex reticulate history of the Saccharum species using
multiple single copy nuclear genes. It is almost certain that the associations within
the genus Saccharum are not stringently different.
GENERAL INTRODUCTION
5
1.4. ORIGIN OF SUGARCANE
Cultivated sugarcane had two geographic centres of origin, New Guinea and the
northern India-Burma-China region. S. officinarum, the large-barrelled, tropical
species, perhaps originated from S. robustum, the wild species, in the New Guinea
(NG) region. S. officinarum became modified through natural hybridization with
related genera when migrated outward from its centre of origin. S. sinenses and S.
barberi the north India-Burma-China sugarcanes, based on phenotype, probably
have one and possibly two unidentified species involved in their origin (Sleper and
Poehlman, 2006).
1.5. SUGARCANE GENETICS AND GENOME
Sugarcane (Saccharum officinarum L.) has ploidy level of 10 or more with the
total genome size 10 Tb (10,000 Mb) and 2n=15 than that of maize (5500 Mb,
2n=20), sorghum (1600 Mb, 2n=20) or rice (860Mb, 2n=24) representing high
polyploidy level of sugarcane cultivars (D’Hont and Glaszmann, 2001). The basic
chromosome numbers in sugarcane are 6, 8, and 10. S. officinarum, the noble cane
is an octaploid with a basic chromosome number of 10 and 2n number of 80 most
common. The wild species, S. robustum, has a basic chromosome number of 10, with
2n numbers of 60 and 80 most common existing. On the bases of chromosome
number, clones of S. barberi have been divided into four groups. S. spontaneum, the
wild species, contains one polyploid group with a basic chromosome number of 8,
and 2n numbers of 40, 48, 56, 64, 72, 80, 96, 104, 112, and 120; and a second
polyploid group with a basic chromosome number of 10 and 2n numbers of 40, 50,
60, 70, 80, 100, and 120. The number of chromosomes in commercial sugarcane
clones usually varies between 2n= 100 and 2n-130 (Sleper and Poehlman, 2006).
GENERAL INTRODUCTION
6
1.6.WORLD STATUS OF PAKISTAN IN SUGARCANE
A total of 246.5 million tonnes of sugarcane is produced all over the world, out
of which 63.7 million tonnes is produced in Pakistan. Pakistan ranks 5th in world
sugar cane production after Brazil, India, China and Thailand (FAOSTAT, 2013).
1.7. SUGARCANE GROWING COUNTRIES
Sugarcane is grown in 105 countries worldwide. Brazil is the top sugarcane
producer. Pakistan positions 5th in area, 14th in cane production and 60th in yield.
Although, Pakistan is 4th largest grower of sugarcane, however, it has the lowest
yield in as compare to other sugarcane producing contries in the world. Average yield
of sugarcane in the world is almost 65 metric tonnes per hectare. Pakistan is the
largest consumers of sugar in South Asia with 25.83 kg per capita consumption per
year, whereas in India it is 14 kg, Bangladesh 10 kg and China 11 kg, respectively
(FAOSTAT, 2013).
Fig.1.2: Top 10 sugarcane producing countries in the world.
Source: Food and Agriculture Organisation (FAO).
GENERAL INTRODUCTION
7
1.8. CURRENT SITUATION IN PAKISTAN
Sugarcane is high value cash crop of Pakistan. It is significantly important for
sugar and sugar related products. The sugar industry plays a vital role in the national
economy. Sugarcane accounts for 3.4 percent in the agriculture value addition and
0.7 percent in the GDP. During the year 2013-14, area put under cultivation was
1.173 million hectares that was 3.9 percent, more than the previous season
cultivation and the production was 66.5 million tonnes with an increase of 4.3 percent
compared to last year’s production which was 63.8 million tonnes. The increase in
production was due to more area sown, favourable weather conditions as well as
improvement in soil fertility resulting from the flood of 2010 and 2011 (MNFS&R,
2013-14).
Fig.1.3: Last five years sugarcane production status in Pakistan.
1.9. PRODUCTION TRENDS IN PAKISTAN
Pakistan has shown a remarkable increase in cane production from 6.9 million
tons in 1948-49 to 66.5 million tons during 2013-14. Sugarcane yield and sugar
recovery tendencies in Punjab, Sindh and Khyber Pakhtunkhwa provinces during the
years 1948-68 do not show significant progress. Cane yields have increased just by
50 to 60%, while sugar recoveries remained consistent in Sindh and Khyber
Pakhtunkhwa. Sugar mills recoveries in Punjab revealed a little rise. Taking into
GENERAL INTRODUCTION
8
consideration the existing yield and recoveries of Indian Punjab (9.60%) and
Karnataka (10.70%) the yield and recovery levels attained by Pak Punjab (8.9%) and
Sindh (33%). Pakistan could not make significant improvement in yield and recovery
during the past six decades. Low yields are due to non-adoption of improved
production technology and low recoveries are due to lesser area under quality
varieties and unavailability of improve local germplasm. The yield increased with
the increment of area under cultivation but the average acre yield remained almost
stagnant from last few decades (MNFS&R, 2014).
Fig.1.4: Last 65 years sugarcane production status in Pakistan. (Source:
Pakistan Sugar Mills Association)
1.10. SUGARCANE INDUSTRY IN PAKISTAN
The sugar industry in Pakistan is the second largest agro–based industries
comprising 81 sugar mills with annual crushing capacity of over 6.1 million tonnes.
Sugarcane farming and sugar manufacturing contribute significantly to the national
exchequer in the form of various taxes and levies. Sugar manufacturing and its by-
GENERAL INTRODUCTION
9
products have contributed significantly towards the foreign exchange resources
through import substitution. Sugar industry is mostly located in the rural areas of
Punjab and Sindh. A small percentage of total production is produced in the NWFP.
Previously, Punjab was partly dependent on supply of sugar from Sindh, but lately
the establishment of some large-scale units in Punjab has made the Province self-
sufficient in the commodity. Sugar production is seasonal activity. The mills, at an
average operate for 150 days, and supplies are made throughout the year.
1.11. HISTORY OF SUGARCANE BREEDING
In the last few decades of nineteenth century, plant breeders in java and India
started sugarcane breeding and conducted crosses between S. officinarum L. and S.
spontanium L. in order to induce vigour and resistance from wild S. spontaneum, and
recover cultivars with high sugar contents (Grivet and Arruda, 2002). The first
sugarcane breeding programme started in Java (Indonesia) in 1888 by using
previously selected genotypes that had viable seed at Barbados (West Indies) in 1858
(Stevenson, 1965). A key achievement in the early sugarcane breeding was the
production of hybrid namely; POJ2878, a “nobilized” cane in 1921 at Java.
Development of nobilized cane varieties in Java and India were present in the early
generations of modern sugarcane pedigree (Simmonds, 1976). As a result, modern
sugarcane cultivars were generated from these interspecific hybrized by repeated
undercrossing and selection. They are the anueploid hybrids with asymmetrical share
of genomes from S. officinarum (80-90 %) and S. spontaneum (10-20 %) and a little
contribution of recombinant chromosomes (Peperidis et al., 2000). Nobilized canes
were generated from Noble canes that are the adopted clones of S. officinarum L.
(X=10, 2n=70, 140) with thick stalk, high sucrose accumulation, and low percentage
of fibre contents (Irvine, 1999). After 1925 and thereafter nobilization breeding has
GENERAL INTRODUCTION
10
been used occasionally. The main breeding method was the crossing among
advanced clones for generating progeny for the selection of cultivars with
commercial value. Before partition sugar Breeding Institute Coimbatore, India
provided the viable seed (Fuzz) for evaluation and selection process at Punjab and
Sind. After partition no suitable agro-climatic conditions for viable fuzz production
in Pakistan was found, however some breeding efforts have been conducted at Thatta
Sindh and Murree, Punjab but success rate was not reasonable and only few
genotypes respond to flowering and viability percentage of fuzz was less.
1.12. PROSPECTS AND CHALLENGES OF CANE BREEDING IN
PAKISTAN
Pakistan has a vast setup of sugarcane industry, but no well established setup of
cane breeding to fulfil the demand of high yielding sugarcane varieties development.
There are possibilities to initiate the breeding work of sugarcane at certain areas of
area of Thatta, (Sind), Murree, Dargai (KPK) and Azad Kashmir, that have the
climate quite favourable for sugarcane flowering. Most of the sugarcane varieties
produced well established flowering arrow. However, seed viability is low but it can
be improved by providing glass house and has to be corrected under glass house
environments like most of the sugarcane breeding stations abroad. For variety
development, fuzz, the sugarcane true seed is imported from USA, Brazil, West
Indies and Sri Lanka but local environmental conditions not likely conducive for
exotic germplasm. Development of breeding facilities for introgression of important
traits in local germplasm for better adoptability and yield is necessary, for this
purpose search for diverse genotypes is prerequisite.
GENERAL INTRODUCTION
11
1.13. MORPHOLOGICAL BASED GENETIC DIVERSITY
Sugarcane (Saccharum officinarum L.) is the most important sugar and cash crop
not only in Pakistan but also in various parts of the world (Deho et al., 2002). It is
cultivated on mass scale in tropical and subtropical areas primarily for its capability
to accumulate high concentrations of sucrose in the internodes of the stem and raw
material for industrial products such as alcohol and ethanol as a biofuel (Martin et
al., 1982). Sugarcane is grown predominately in tropics and sub-tropics between 30˚
N and 35˚ S (Nazir et al., 1999) and accounts for approximately 75 percent of the
total world sugar production (Henry and Kole, 2010).
Genetic diversity assessment among cultivars is a robust tool for initiation of
plant breeding programme, it can give plant breeders with an opportunity for
analysing variability present in the germplasm, and this diversity provides sugarcane
breeders the means to identify more diverse germplasm for onward incorporation
into breeding programmes (Aitken and McNeil, 2010). To facilitate the appropriate
classification of genotypes and analysis of genetic diversity in sugarcane, several
methods have been utilized that include: on the basis of morphological data (Brown
et al., 2002), pedigree data (Lima et al., 2002) and data of agronomic attributes of a
crop (Skinner et al., 1987). For genetic diversity analysis and measurement of
genetic similarities between genotypes, individuals and population, various
statistical approaches are used depending on data set used. Multivariate data analysis
techniques are widely used in the sugarcane genetic diversity analysis by using
morphological and molecular data (Mohammadi and Prasanna, 2003). Among these
statistical tools Cluster analysis using hierarchical method (Sneath and Sokal, 1973)
and Principal Component Analysis (PCA) are, at present the most frequently used
approaches for sugarcane diversity assessment (Aitken et al., 2006).
GENERAL INTRODUCTION
12
PCA is a data reduction method, these procedures are used to reduce the number
of variables and to detect structure in the relationship between these variables and is
a unique mathematical solution for reduction of the data set to a few components, for
clustering purposes, and can be used to hypothesize that the most important
components are correlated with some other underlying variables (Acquaah, 2012).
Hierarchical clustering method have been mostly used coupled with Ward’s
method (Milligan, 1980). Even though hierarchical clustering method have been
widely adopted, but they have some disadvantages. Non-hierarchical clustering
methods also gained adoptability but few inadequacies affect their utility in various
applications (Hair et al., 2006). It has been suggested to use both methods
(hierarchical and non-hierarchical) to take the advantages of each clustering method
(Milligan, 1980 & Hair et al., 2006).
1.14. MOLECULAR BASE GENETIC DIVERSITY
Sugarcane (Saccharum spp.) is a tall, tropical, monocotyledonous, complex
aneu-polyploidy plant (2n = 8x or 10x = 100-130) that propagates asexually through
planting of vegetative cuttings (setts) of mature stalks. Modern sugarcane cultivars
are the hybrids between S. officinarum, S. spontaneum and S. robustum have narrow
genetic base. However, repeated utilization of sugarcane clones as a seed for
cultivation increase the narrowness of the genetic base of sugarcane cultivars, which
leads to the loss of some important characteristics (Acreneaux, 1967; D'hont et al.
1996; Roach, 1989; Tew, 2003).
Unlike morpho-physiological characters that are affected by environmental
fluctuations, molecular markers are considered stable and not influenced by
geographical region or seasonal changes. Microsatellite markers, also known as
simple sequence repeats (SSRs), are one of the most powerful genetic marker classes.
GENERAL INTRODUCTION
13
SSRs are repeated DNA sequences of simple sequence motifs, each motif ranging
from one to six nucleotides (Kalia et al., 2011). Microsatellite markers are
abundantly present in the genome of eukaryotic organisms, and are highly
polymorphic and co-dominant (Xu and Crouch, 2008; Chen et al., 2009). SSRs are
ubiquitous and highly polymorphic, owing to some of the spontaneous mutation
affecting the number of repeat units. The hyper variability of SSRs among related
organisms makes them an informative and excellent choice of markers for a wide
range of applications in sugarcane, which include high-density genetic mapping
(Chen et al., 2007), molecular tagging of genes (Singh et al., 2005), genotype
identification, genetic analysis of diversity (Cordeiro et al., 2003) and paternity
determination (Pan et al., 2010; and Tew. 2003). SSR markers are suitable for
sugarcane molecular genotyping (Pan et al., 2003) and genetic diversity estimation
(Cordeiro et al. 2001). Several studies have been conducted on sugarcane diversity
analysis using SSR markers (Cordeiro et al., 2001, 2002, 2003, 2007; Pan et al.,
2003; Chen et al., 2007; Singh et al., 2008; Chen et al., 2009; Glynn et al., 2009;
Chen et al., 2009; Creste et al., 2010; Mishra et al., 2010; Silva et al., 2011; Hameed
et al., 2012; Devarumath et al., 2012) reflecting the importance of SSR markers
utility for assessment of genetic diversity in sugarcane.
1.15. SOMACLONAL VARIATIONS
Variation generated and not from meiosis or normal sexual process known to as
somaclonal variation, while the variants are denoted to as somaclones. There two are
types of somaclonal variations, one may be transient or epigenetic while other are
heritable or genetic in origin. Epigenetic variations or unstable and cannot be
transmitted to next generation. Addition of auxin 2, 4-D in culture medium enhances
the probabilities of somaclonal variation induction (Acquaah, 2012). Improvement
GENERAL INTRODUCTION
14
of crops through somaclonal variation was first described by Heinz and Mee (1971).
Various factors responsible for somaclonal variation which include karyotype
changes, cryptic changes associated with chromosome rearrangement, transposable
elements, somatic gene rearrangements, gene amplification and depletion, somatic
crossing over and sister-chromatid exchanges.
Phenotypic variations among somaclones have been used as potential tools for
crop improvement. Such variations associated with changes in chromosome number
have led the breeders to exploit it in crop improvement programs (Rakesh et al.,
2011) as alternative method for improvement of existing genotypes (Shahid et al.,
2011). First in vitro raised somaclone of sugarcane, resistant to Fiji disease was
reported by Heinz, (1973). However, several studies have been reported the
improvement of commercially important crops via somaclonal variation. Gao et al.,
(2009) explained that somaclonal variation can be heritable in plant tissues raised in
vitro, and provides window of opportunity for plant breeders to produce novel
variants in sugarcane. Various authors (Shahid et al., 2011; Ali and Iqbal, 2012;
Seema et al., 2014 and Rastogi et al., 2015) reported the successful utilization of
somaclonal variation in sugarcane for genetic improvement of agronomic traits.
Rastogi et al., (2015) successfully utilized somaclonal variation for genetic
improvement in sugarcane against diseases (Red rot, Eye spot, downy mildew, Fiji
virus), drought tolerance, salt tolerance, sugar recovery, sugar contents and cane
yield. Red rot (Colletotrichum falcatum L.) and sugarcane mosaic virus (SCMV) are
very devastating sugarcane diseases in Pakistan. They cause very serious yield losses
in susceptible varieties.
Worldwide, Pakistan ranked 5th in cultivated area and 15th in cane yield
(FAOSTAT, 2014). There is a big gap between ranking in cultivated area and cane
GENERAL INTRODUCTION
15
yield therefore, it is inevitable to find a way to narrow down this gap. Unfavourable
geo-climatic conditions for sugarcane flowering and viable seed production has been
a major problem for sugarcane improvement in Pakistan. Therefore, genetic
improvement of sugarcane through conventional breeding is hindered by low
fertility. Hence, alternative methods such as In-vitro culture techniques for
somaclonal variation induction and induce mutations are being employed to create
the new genetic variability for the selection of the desired genotypes (Yasmin et al.,
2011).
Aims of this research work include:
To evaluate sugarcane genotypes on the basis of morphological
parameters of cane and sugar yield.
To assess molecular diversity among the genotypes using molecular
markers.
To exploit the somaclonal variations for the induction of variability.
Assessment of variability in mutants and their parent clones by using SSR
markers.
Genetic integrity assessment in important candidate genes.
MORPHOLOGICAL STUDIES
16
Chapter: 02
MORPHOLOGICAL STUDIES
2.1. INTRODUCTION
Sugarcane (Saccharum officinarum L.) is the most important sugar and cash
crop not only in Pakistan but also in various parts of the world (Deho et al., 2002).
It is cultivated on mass scale in tropical and subtropical areas primarily for its
capability to accumulate high concentrations of sucrose in the internodes of the stem
and raw material for industrial products such as alcohol and ethanol as a biofuel
(Martin et al., 1982). Sugarcane is grown predominately in tropics and sub-tropics
between 30˚ N and 35˚ S (Nazir et al., 1998) and accounts for approximately 75
percent of the total world sugar production (Henry and Kole, 2010).
Sugarcane production in Pakistan for the year 2013-14 was 66.5 million
tonnes with an area under cultivation of 1.173 million hectares. The resulting 4.3
percent increase as compare to 2012-2013 (63.8 million tonnes) attributed towards
more area brought under cultivation, conducive weather and improved soil fertility
due to effect of floods in 2010 and 2011 (MNF&RS, 2013). When this yield
scenario was compared with the last five year’s production, the change is enormous
(8%) as compared to year 2010-11 production (55.30 million tonnes). The countable
yield changes may be due to poor yielding varieties frequently used for cultivation
coupled with adverse climatic factors that hinders sugarcane yield in Pakistan.
Without adaptation of promising sugarcane varieties production cannot be
enhanced. Evaluation and assessment of genetic diversity in local and exotic
sugarcane germplasm in order to identify new avenues for genetic diversity to
MORPHOLOGICAL STUDIES
17
develop cultivars which can withstand biotic and abiotic stresses (Khalid et al.,
2014). Plant genetic resources provide raw material for development of new
varieties for suitable production system that have a better ability to cope with pests
and environmental influences (Sajid and Khan, 2009).
Genetic diversity assessment among cultivars is a robust tool for initiation of
plant breeding programme as it gives plant breeders with the opportunity for
analysing variability present in the germplasm, and this diversity provides
sugarcane breeders the means to identify more diverse germplasm to introduce
within their breeding programmes (Aitken and McNeil, 2010). To facilitate the
appropriate classification of genotypes and analysis of genetic diversity in
sugarcane several methods have been utilized that include: morphological data
(Brown et al., 2002), pedigree data (Lima et al., 2002) and data of agronomic
attributes of a crop (Skinner et al., 1987). For genetic diversity analysis and
measurement of genetic similarities between genotypes, individuals and
populations, various statistical approaches are used depending on data set used.
Multivariate data analysis techniques are widely used in the sugarcane genetic
diversity analysis by using morphological and molecular data (Mohammadi and
Prasanna, 2003). Among these statistical tools Cluster analysis using hierarchical
method (Sneath and Sokal, 1973) and Principal Component Analysis (PCA) are, at
present most frequently used approaches for sugarcane diversity assessment (Aitken
et al., 2006).
PCA is a data reduction method, these procedures are used to reduce the
number of variables and to detect structure in the relationship between these
MORPHOLOGICAL STUDIES
18
variables and is a unique mathematical solution for reduction of the data set to a few
components, for clustering purposes, and can be used to hypothesize that the most
important components are correlated with some other underlying variables
(Acquaah, 2012). Hierarchical clustering method have been mostly used coupled
with Ward’s method (Milligan, 1980). Non-hierarchical clustering methods is also
utilized in various applications (Hair et al., 2006). It has been suggested to use both
methods (hierarchical and non-hierarchical) to take the advantages of each
clustering method (Milligan, 1980 & Hair et al., 2006).
The aim of this research work was:
To assess the amount of genetic variability and interrelationships among the
adopted sugarcane genotypes.
To identify best parents to initiate a hybridization program.
MORPHOLOGICAL STUDIES
19
2.2 REVIEW OF LITERATURE
Balakrishnan et al., (2000) proposed a technique for characterization of S.
officinarum L. accessions based on their relative contributions to the total mean variance
of principal component score of a set of quantitative characteristics. The contribution of
total variance was computed on the bases of their cumulative proportion.
Bakshi and Hemaprabha (2005) evaluated fifty-three Saccharum officinarum
clones for genetic diversity, which flowered at Coimbatore and Cannanore, India.
Analysis of variance showed significant variation among genotypes for all traits studied.
They recorded data of 13 quantitative traits that were subjected to multivariate analysis
and genotypes were grouped into clusters. It was suggested that the use of parental
clones from different cluster with maximum divergence may enhance the chances of
exploration of heterosis for improving sugarcane yield.
GeMin et al., (2006) used ninety-four S. spontaneum genotypes for genetic
diversity analysis using Principal Component Analysis based on 7 quantitative
characters and obtained 3 principal components, with 82.47 % cumulative variation. By
doing cluster analysis they obtained 4 major clusters. Their results showed that cluster I
exhibited higher sugar content, plant height and number of tillers. Cluster II depicted
average of all characters, Cluster III revealed plant height, stalk diameter and less
number of tillers. On the bases of sugar contents the genotypes were grouped into 4
clusters with 22 genotypes included into Cluster I with 5.63 % sugar contents. Cluster
II contained 31 genotypes with 3.98 % sugar contents, following Cluster III having 18
genotypes with 4.64 % sugar contents and Cluster IV comprised 23 genotypes with a
mean sugar contents of 3.06%.
MORPHOLOGICAL STUDIES
20
Kashif and Khan (2007) determined genetic diversity among fourteen sugarcane
genotypes based on 12 quantitative characters by using Meteroglyph and divergence
analysis. Authors observed high genetic variation for all the characters under study and
obtained four clusters with four genotypes in each cluster. They observed that by doing
cluster analysis which grouped the genotypes based on genetic similarity for agronomic
traits, genotypes from same source or origin were grouped in the same cluster. They
reported that the genotypes with high index score can be used as a parent in crossing
programme.
Lopes et al., (2007) estimated the genetic diversity of 140 sugarcane genotypes
grown at three different locations by multivariate data analysis, using Mahalanobis
approach. They evaluated genotypes based on number of stalks per plant, brix
percentage and mass of ten stalks. They identified combinations of most divergent
clones with some post productive clones.
Ahmed and Obeid (2010) quantified the genetic diversity among twelve exotic
sugarcane genotypes on the bases of eleven cane yield and quality parameters namely:
plant height, stem diameter, number of internodes per plant and brix contents. Their
results indicated that genotypes were clustered into six groups based on genetic distance
calculated by using Mahalanobis’s approach. They noted higher distance between two
clusters (83.546) and concluded that genotypes within these two clusters had great
potential for breeding purposes.
Meenu et al., (2012) evaluated 41 genotypes of sorghum (Sorghum bicolor L.) by
using Principal Component Analysis (PCA). They collected data from mature plant
planted in randomized block design for some agronomic traits i.e., plant height, number
MORPHOLOGICAL STUDIES
21
of leaves per plant, leaf area, number of nodes per plant, internode length and stem
diameter. They obtained fourteen principal components. By using cluster analysis based
on principal component analysis forty one genotypes, scattered into five distinct groups
with maximum genetic distance between cluster number one and four. They concluded
that PCA provided convenient selection tool for various yield and quality contributing
traits.
Al-Sayed et al., (2012) estimated the degree of variation of different agronomic
traits by using multivariate data analysis techniques from two years data of sugar yield
and its components. They detected highly significant correlation coefficient between
sugar yield and number of internodes per plant and sucrose percentage. By doing factor
analysis they obtained three factors based on eight morphological traits and accounted
for 85.3 % variability. Factor I generated 34.89 % of total variability by including stalk
weight, stalk thickness and millable stalks per plant while Factor II comprised of soluble
solids contents (28.17 %). Last factor contained plant height, number of internodes per
plant and reducing sugar percentage that explained 22.25 % total variation. It was
concluded that high yielding genotypes would be obtained by selecting germplasm that
have high stalk weight and high percentage of sucrose.
Ajirlou et al. (2013) evaluated 20 sorghum varieties in a Randomized Complete
Block Design with four replications. Cluster analysis was used following Ward's
method. They found that all traits in local varieties were ranked as superior clusters.
They confirmed this grouping by detection function. By doing factor analysis, they
determined five factors which elucidated 86.24% of the total variability. They concluded
MORPHOLOGICAL STUDIES
22
that first main factor had 33.890 % of the total variation which they called as a
performance factor.
Tahir et al., (2013) evaluated genetic divergence of sugarcane germplasm
comprising 25 sugarcane genotypes (2008-09). They conducted Principal Component
Analysis (PCA) and obtained two principal components accounting for 88% of the total
variation in the tested breeding material that were named as “Vigor”, and “Quality”.
They also conducted Cluster analysis using Ward’s method on the newly created
variables using principal components which revealed 3 clusters at a linkage distance of
4.5. Cluster I and III had 11, and cluster II had 3 genotypes. Their analyses revealed that
there were two main components i.e. vigor, and quality accounting for maximum
variation in yield. They suggested that genotypes in cluster I and II could be utilized as
a source for future selection or hybridization program for the improvement of these
characters in sugarcane.
Kang et al., (2013) examined the genetic variability of 11 sugarcane varieties by
using morphological characters i.e.; plant height, number of tillers per plant, number of
leaves per plant, leaf area, stem diameter, sucrose contents and brix percentage. Their
results showed significant differences among varieties for all traits. Correlation among
various characters revealed that brix value has positive correlation with stem diameter,
leaf area, number of leaves and sucrose value. By using Cluster analysis genotypes were
partitioned into eight groups. They found that brix value had high contribution to genetic
divergence while stem diameter and sucrose contents had no significant contribution to
the total genetic variation among varieties.
MORPHOLOGICAL STUDIES
23
Smiullah et al., (2013) evaluated 10 sugarcane varieties for genetic diversity of
twelve agronomic traits by using Principal Component Analysis (PCA). They obtained
significant differences among the varieties for all the traits by using analysis of variance
(ANOVA). By doing PCA analysis they found greater extent of genetic diversity in case
of morphological traits i.e; plant height and internode length. The concluded that first
two PCs i.e. PC1 and PC2 have maximum contribution of variance from plant height
and internodal length, so parents can be selected for breeding program by keeping these
traits in mind
Sanjay and Devendra (2014) studied correlation among 15 traits in three hundred
and thirty-nine genotypes of sugarcane germplasm. They found that cane yield was
positively and significantly correlated with number of shoots, stalk diameter, stalk
length, number of internodes, length of internodes, and number of leaves whereas it was
negatively correlated with brix at all the stages.
Brasileiro et al., (2014) evaluated the genetic diversity of 77 sugarcane clones.
Based on morphological traits, Ward-Modified Location Model partitioned the clones
into three main groups comprising 37, 21 and 19 clones in each group respectively. The
diversity analysis of sugarcane clones by using Ward-Modified Location Model gave
clear discrimination among accessions while grouping.
Cardozo et al., (2014) evaluated eight sugarcane cultivars for ripening variation by
multivariate data analysis using traits related to the quality of raw sugarcane juice. The
statistical analysis by ANOVA, hierarchical and non-hierarchical (K mean) clustering
methods and Principal Component Analysis categorized cultivars into groups. They
found that the analysis of variance was significant for all sugarcane quality variables,
MORPHOLOGICAL STUDIES
24
while the non-hierarchical clustering (K mean) and Principal Component Analysis
approaches were good source for variability assessment.
James et al., (2014) phenotypically characterized the World Collection of
Sugarcane and representative core collection by 11 morphological traits using Principal
Component Analysis (PCA) and the data were clustered by Euclidian and unweighted
Neighbour Joining methods. They obtained 97.31 percent diversity of the World
Collection, although no species pattern was detected in the PCA whereas UNJ and
phenotypic diversity of World collection was almost completely represented by core
collection.
Sanghera et al., (2015) estimated the genetic divergence among 24 sugarcane
genotypes planted in a RCBD design containing three replications. They assessed the
genetic diversity based on 18 matric traits. The genotypes were grouped into five clusters
on the bases of genetic distance using Mahalanobis’s statistics. They estimated high
genetic distance between two clusters (89.66) and concluded that genotypes in these
clusters could be good parents for breeding programme.
MORPHOLOGICAL STUDIES
25
2.3. MATERIAL AND METHODS
Sugarcane germplasm containing twenty adopted varieties/genotypes (Table.
2.1) were collected from Ayub Agricultural Research Institute Faisalabad, Pakistan and
were sown in March 2013 at Arja (District Bagh-30 Km from Rawalakot, East 73.97°-
42 minutes, North 33.97°- 21 minutes, Altitude 797m above sea level, Average Annual
Temperature 20.2°C and Average Annual Rainfall 1051mm) in three replications.
Germplasm comprised commercial varieties, local adopted varieties and exotic
genotypes.
2.3.1. Field Experiment
The experiment was conducted for two years under irrigated conditions. The
field was ploughed two times and then beds were prepared. The experiment was
conducted in three replications with Randomized Complete Block Design. Borders rows
of the experimental field was covered with non-experimental line. Four meter long rows
of each entry were sown. Stem Setts of almost 1.5 ft from each sugarcane genotype were
placed in furrows prepared in beds 2 ft apart. DAP at the rate of 100 kg per hectare
spread with broadcast method. Later, setts were covered with soil and light irrigation
was applied. After almost 25 days of germination hoeing and earthing up of plant were
carried out followed by irrigation. Frequent weeding and hoeing was carried out
throughout crop season. During second season ratoon crop was raised from crop grown
in the previous season by earthing up the stubbles. Urea and DAP at the rate or 100 kg
per hectare were spread by broadcast method. Half of the dose of urea was applied after
two months of crop raising. Frequent irrigations were applied and all agronomic
practices were carried out with the plants raised to maturity.
MORPHOLOGICAL STUDIES
26
2.3.2. Data Collection
Data were recorded from 5 guarded selected plants at maturity for two years
during 2013 and 2014. Parameters recorded at maturity included; plant height, number
of tillers per plant, stem girth, number of nodes, inter-nodes length, number of leaves,
leaf area, brix percentage, reducing sugar and non-reducing sugar. Details of each
parameter recorded as follows:
Table 2.1: Sugarcane genotypes obtained from Sugarcane Research Institute,
AARI, Faisalabad Pakistan and their names, nativity and parentage.
S. NO Variety/line Nativity Parentage
Female parent Pollen parent
1 HSF-242 Sindh, Pakistan SPHS- 89-2085 Poly cross
2 SPF-213 Sao Paulo, Brazil SP -70-1006 Unknown
3 CPF-237 Canal Point, America 86P-19 CP 70-1133
4 BF-162 Barbados, West Indies Co 1001 Unknown
5 S-03-US-694 Canal Point, America CP87-1628 CP84-1198
6 S-06-SP-321 Sao Paulo, Brazil Unknown Unknown
7 S-05-FSD-307 Murree, Pakistan Unknown Unknown
8 S-05-US-54 Canal Point, America CP92-1167 CP93-1634
9 S-06-US-300 Canal Point, America Not known Not known
10 S-03-SP-93 Sao Paulo, Brazil Not known Not known
11 S-06-US-272 Canal Point, America Not known Not known
12 S-03-US-127 Canal Point, America CP89-879 CP90-956
13 S-06-US-658 Canal Point, America Not known Not known
14 S-03-US-778 Canal Point, America CP -43-33 Unknown
15 S-05-FSD-317 Murree, Pakistan Not known Not known
16 SPF-232 Sao Paulo, Brazil Not known Not known
17 LHO-83153 Not known Not known Not known
18 S-08-FSD-23 Murree, Pakistan Not known Not known
19 S-08-FSD-19 Murree, Pakistan Not known Not known
20 HSF-240 Sindh, Pakistan CP -43-33 open
pollination
MORPHOLOGICAL STUDIES
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Figure. 2.1: Location of sugarcane sown at Arja Bagh, Azad Kashmir (East 73.97°-42 minutes, North 33.97°- 21 minutes,
Altitude 797m above sea level.). Figure indicate the map of Pakistan (a), arrow showed the satellite image of Arja near
Arja bridge (b) and next arrow indicate the site of experiment (c).
Source: Google Maps
MORPHOLOGICAL STUDIES
28
2.3.2.1. Plant Height (cm)
Plant height was recorded at maturity stage in centimetres from five randomly
selected plants of each genotype from each replication and average data was obtained.
2.3.2.2. Number of tillers per plant
Number of tillers was recorded from five randomly selected plants and average
data was taken.
2.3.2.3. Stem girth (cm)
Diameter of mother stem at three places (base, middle and upper portion) of five
randomly selected plants from each replication was recorded by using Varner calliper in
centemeter and average was obtained.
2.3.2.4. Number of Nodes
Number of nodes of randomly selected five plants from each genotype was
recorded from each replication and average of the data was obtained.
2.3.2.5. Inter-nodal length (cm)
Inter-nodal length was recorded from five inter nodes of each five randomly
selected plants and average data from three replications was taken for each genotype.
2.3.2.6. Number of Leaves
Number of leaves from five selected plants were counted and average data taken.
2.3.2.7. Leaf Area (cm2)
Leaf area of five selected plants from each replication was recorded in
centimetres from three places for width (cm) and average was then multiplied with
length and then with factor 0.72 according to Sinclair et al. (2004).
Leaf Area = (length x width from three places) x 0.72
MORPHOLOGICAL STUDIES
29
2.3.2.8. Brix %age
Brix percentage was estimated from the juice extracted for each genotype at maturity by
using the digital refractometer by putting a 2 to 3 drops of juice on the lens of
refractometer.
2.3.2.9. Reducing Sugar contents
Reducing sugar was estimated by using Benedict’s method (A.O.A.C. 1990).
Two gram of anhydrous sodium carbonate was added to 5 ml of Benedict solution in
250 ml flask. Mixture was shaked well and gently warmed at 100ºC and finally titrated
against the sugarcane juice drop by drop through burette until colour was changed to
bricks read. Volume of sample solution was recorded in duplicate. Final calculations
were based as follows.
1 ml of juice used in titration = 2 mg of reducing sugar.
2.3.2.10. Non-Reducing Sugar contents
Non-reducing sugar was determined by using Benedict’s method (A.O.A.C.
1990). In this method sugarcane juice sample of 20 ml was taken in a beaker and 5 ml
of 2% HCl was added and boiled for 30 minutes in a water bath. It was cooled down
and its pH was brought to 7.0 with NaOH (0.1N). Then it was titrated against the 5 ml
boiled Benedict’s reagent containing 2 gram anhydrous sodium carbonate drop by drop
through burette and shaked until the colour was changed to brick red. Volume of juice
used in titration was recorded and finally calculations were recorded as follows:
1 ml of juice used in titration = 2 mg of non-reducing sugar.
MORPHOLOGICAL STUDIES
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2.3.3. STATISTICAL ANALYSIS
Data collected from above mentioned parameters was subjected to some basic
statistics i.e. mean, standard deviation and analysis of variance. The explanation of
statistics are concluded by following equations:
2.3.3.1. Mean
=𝚺𝐗
𝐍
Where:
= Symbol for the mean.
= Symbol for summation.
X = Symbol for scores.
N = number of samples.
2.3.3.2. Standard deviation
Where:
S = Standard deviation for samples
= Sum of samples
= Samples mean
n = number of samples
MORPHOLOGICAL STUDIES
31
2.3.3.3 Analysis of variance (ANOVA)
Analysis of variance was performed according to the Steel and Torrie (1980).
2.3.3.4. Principal Component Analysis
Principal Component Analysis (PCA) was performed by using PAST Statistical
software, version 2.17c (Hammer et al., 2001). As measuring units of various parameters
were not same mean data were standardized according to the Hair et al. (2006).
2.3.3.5. Cluster Analysis
Cluster analysis based on Ward's method using Euclidian distance (Kumar et al.,
2009) was performed using the statistical software STATISTICA version 5.0. To
calculate cluster analysis a number of variables from each sample were employed. To
standardized, Euclidian distance and m-space a matrix was used by following formula.
m
XX
d
m
k
jkik
ij
1
2
Where Xik is the measurement of variable k on sample i and Xjk is the amount of
variable k on sample j, dij is distance between the 02 samples. For properly normalizing
the distance matrix it can be observed like,
A B C D E F
A 1
B dAB 1
C dAC dBC 1
D dAD dBD dDC 1
E dAE dBE dCE dDE 1
F dAF dBF dCF dDF dEF 1
MORPHOLOGICAL STUDIES
32
2.4. RESULTS AND DISCUSSION
Twenty sugarcane genotypes were used to quantify the genetic divergence by
using various quantitative traits. Basic statistics for various morphological traits are
presented in Table 2.2. Analysis of variance revealed highly significant differences
among the traits studied. Bakshi and Hemaprabha (2005) and Cardozo et al., (2014)
compared various traits among Saccharum officinarum L. genotypes and also found
differences among them.
Basic statistics for various morphological traits are presented in Table 2.2a.
Maximum mean values for plant height (202 cm) showed by genotype S-03-US-127 and
minimum showed by the genotype S-08-FSD-23 (139 cm), Number of tillers recorded
in the range from 3.7 to 7 cm, maximum tillers recorded from genotype S-08-FSD-19.
Average 2.5 cm stem girth was recorded in all the genotypes ranged from 2 to 2.8 cm.
average 11 internodes per plant were recorded followed by 13.6 cm average inter-nodal
length. Average 11 leaves per plant with leaf area 535 cm2 were recorded per plant. The
genotype HSF-242 revealed maximum value (19.9) for brix percentage and reducing
sugar contents while genotype SPF-213 showed maximum values for maximum value
for non-reducing sugar but minimum value for brix percentage. HSF-242 showed
maximum value for reducing sugar contents while minimum value for number of tillers,
internode length and number of leaves, S-03-US-778 showed maximum leaf area but
minimum plant height. The genotypes S-03-US-127 and S-06-US-321 were found batter
on the bases of mean performance for most of the important agronomic characters.
MORPHOLOGICAL STUDIES
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Table 2.2a: Mean performance of morpho-physological traits of 20 sugarcane genotype from pooled data obtained during the
years 2013and 2014. (LSD = 5% α)
S.
NO
Variety/
Genotype
Plant
height
Tillers/
Plant
Stem
Girth
(cm)
No. of
nodes
Inter-
nodes
length
(cm)
No. of
leaves
Leaf
area
(cm2)
Brix
%age
Reducing
sugar
(mg/ml)
Non-
reducing
sugar
(mg/ml)
1 HSF-242 180abcde 6.3abc 2.58abcd 12.3abc 15.6a 17.7ab 560bcde 19.9a 10a 8.0b
2 SPF-213 195 ab 5.7abcd 2.43abcd 9.3cd 14.8ab 17.3ab 642abc 12.3k 7.0e 9.1a
3 CPF-237 190abcd 6.7ab 2.22cd 12.7ab 14.8ab 18.7ab 450ef 19.1b 5.0i 3.7j
4 BF-162 180bcde 3.7f 2.54abcd 11.3abcd 14.7ab 19.0ab 410f 15.7i 5.3h 2.3l
5 S-03-US-694 192abc 4.3def 2.47abcd 12.0abcd 14.6ab 20.3a 556bcde 19.2b 5.0i 4.7g
6 S-06-SP-321 178abcde 5.3bcde 2.68abc 10.7abcd 14.3ab 18.7ab 672ab 18.2de 6.0g 6.1e
7 S-05-FSD-307 202a 6.0abc 2.67abcd 13.0a 14.3ab 19.0ab 508def 14.9j 4.9i 4.9g
8 S-05-US-54 164bcdef 6.0abc 2.43abcd 10.7abcd 14.1ab 18.3ab 468def 17.9ef 3.3k 7.0d
9 S-06-US-300 172abcde 6.7ab 2.26bcd 11.7abcd 14.0ab 16.0b 481def 17.9ef 3.9j 4.1h
10 S-03-SP-93 160cdef 5.7abcd 2.18d 9.7bcd 14.0ab 18.0ab 568abcde 16.1h 6.0g 6.3e
11 S-06-US-272 175abcde 4.0ef 2.83a 11.0abcd 13.4ab 17.3ab 479def 16.0h 2.3l 7.3c
12 S-03-US-127 153ef 3.7f 2.46abcd 11.0abcd 13.3ab 17.3ab 502def 19.7a 2.3l 6.3e
13 S-06-US-658 158def 5.7abcd 2.43abcd 9.0d 13.2ab 15.7b 540cde 18.7c 9.7b 9.0a
14 S-03-US-778 153ef 6.7ab 2.30bcd 11.3abcd 13.2ab 18.3ab 688a 19.8a 6.3f 3.9ij
15 S-05-FSD-317 175abcde 5.0cdef 2.43abcd 11.7abcd 13.1ab 18.7ab 466def 18.3d 4.0j 2.3l
16 SPF-232 182abcde 4.0ef 2.54abcd 11.0abcd 12.9ab 18.0ab 658abc 12.1k 7.7d 5.3f
17 LHO-83153 179abcde 5.7abcd 2.57abcd 11.0abcd 12.7ab 15.7b 577abcd 17.1g 5.0i 4.0hi
18 S-08-FSD-23 139f 5.0cdef 2.75ab 11.0bcd 12.5ab 18.0ab 509def 19.3b 10a 2.9k
19 S-08-FSD-19 176abcde 7.0a 2.33bcd 11.3bcd 11.9b 19.7ab 481def 19.3b 9.0c 2.1l
20 HSF-240 175abcde 6.3abc 2.47abcd 10.7abcd 11.9b 17.3ab 493def 17.7f 4.8i 2.2l
Grand mean 173.95 5.46 2.48 11.12 13.66 11.54 535.55 17.45 5.87 5.07
Standard
Error
11.41 1.86 0.25 1.51 1.55 1.69 93.84 0.15 0.12 0.12
MORPHOLOGICAL STUDIES
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Table 2.2b: Basic statistics for the estimated variables in 20 sugarcane genotypes
Parameters Minimum
value
Maximum
value
Standard
deviation
Analysis of variance
(F. value)
PH 128.83 230 23.63 139.8**
NT 4.67 10.17 2.18 11.98**
SG 1.80 3.14 0.31 124.23**
ND 10 16 1.86 71.21**
INDL 11 19.6 1.85 106.15**
NL 15 21 2.08 153**
LA 476 729 118 49.90**
Brix% 14 20.6 2.3 780**
RS 2.4 10 2.35 132.9**
NRS 2.2 9.2 2.23 291**
** Highly Significant at 1% level significance, * Significant at 5% level of significance.
Where,
PH; Plant Height, NT ; Number of Tillers, SG; Stem Girth, ND; Number of Nodes,
INDL; Inter Nodal Length, NL; Number of Leaves, LA; Leaf Area, Brix %; Brix
Percentage, RS; Reducing Sugar, NRS; Non Reducing Sugar
2.4.1. PRINCIPAL COMPONENT ANALYSIS
Principal component analysis was performed to assess the variability among 20
sugarcane genotypes, using quantitative traits. The primary purpose of PCA was to
define the underlying structure in a data. As a data reduction or exploratory methods,
these procedures were used to reduce the number of variables and to detect structural
relationship between these variables. PCA is a technique for finding putative variables
which gives interpretation for as much of the variables in a multivariate data as possible.
PCA is a unique mathematical solution; it performs simple reduction of the data set to a
few components, for plotting and clustering purposes, and can be used to assume that
the most essential components have association with some other underlying variables
(Acquaah, 2012).
A data matrix was constructed using the determined quantitative traits as
columns and the sugarcane genotypes as rows. Principal components analysis was
MORPHOLOGICAL STUDIES
35
performed on auto-scaled data. The first four principal components (Jolliffe cut off value
= 0.7) were chosen for modeling the data, which communally accounted for 79.75% of
the variation (Tab.2.3). The remaining variance of other principal components did not
have significant eigenvalues. First four principal components (PCs) have significant
eigenvalues for all 10 quantitative traits compared, hence they all included in the model.
PC1 contributed maximum variance (32.672%) in the data set followed by the PC2
(21.9%) while the PC3 has generated variance of 12.9% followed by the PC4 that
produced 12.1% variance in the data set. Scree plot diagram in the (Fig.2.1) showed
that after the PC4 curve for the eigenvalue % age becomes straight forward, which
provided the indications that, the first four components generate maximum variability
for the data set under study while rest of other PCs were considered to be non-significant.
Gemain et al., (2006) obtained three Principal Components with 82 percent
cumulative variance in S. Spontaneum L. while studying 7 quantitative traits. Al-Sayed
et al., (2010) computed 85 percent variance by doing Factor analysis on morphological
traits of sugarcane with maximum variability generated by Factor I was 34 percent.
Ajirlou et al., (2013) conducted Factor Analysis in sorghum genotypes and elucidated
86% total variability with first main Factor contained 33 percent total variability. Tahir
et al., (2013) obtained two Principal components with cumulative variability of 88
percent. James et al., (2014) found 97 percent total variance in sugarcane germplasm
evaluated by doing PCA analysis. Our results were nearly similar to the findings of
previous reports except Tahir et al., (2013) and James et al., (2014), they reported to
only first few components.
MORPHOLOGICAL STUDIES
36
Table. 2.3: Principal Components of Quantitative traits in 20 Sugarcane Genotypes
PC Eigenvalue % variance Cumulative variance
%age
1 3.26715* 32.67 32.67
2 2.19* 21.95 54.63
3 1.29* 12.94 67.57
4 1.21* 12.17 79.75
5 0.61 NS 6.14 85.89
6 0.56 NS 5.68 91.58
7 0.31 NS 3.18 94.76
8 0.29 NS 2.97 97.74
9 0.12 NS 1.26 99.00
10 0.10 NS 1.00 100.00
*Significant at Jolliffe cut off value =0.7,
NS Non-significant
Fig. 2.2: Scree plot diagram for quantitative traits of 20 sugarcane genotypes.
MORPHOLOGICAL STUDIES
37
2.4.2. LOADINGS OF PCS FOR QUANTITATIVE TRAITS
2.4.2.1. Loadings of PC1
Loading of first principal component (PC1) are presented in the Fig.2.3 which
depicted that number of nodes per plant showed maximum positive loadings (0.461)
followed by the plant height (0.414) and number of leaves per plant (0.422).
Reducing sugar showed minimum loadings (-0.38) followed by stem girth (-0.322).
From the results it can be inferred that plant height, number of nodes per plant and
number of leaves per plant have positive correlation among themselves while these
parameters have negative correlation with stem girth and reducing sugar. With the
increase in plant height and number of nodes there is decrease in reducing sugar and
stem girth.
2.4.2.2. Loading of PC2
Loadings of the PC2 are presented in the Fig.2.4. Brix percentage has
maximum loading (0.45) in this PC which means that its contribution in the
generation of variance is more in this PC followed by the number of tillers per plant
and leaf area with the loadings 0.43 and 0.3, respectively. Non-reducing sugar
showed minimum loadings (-0.3567), followed by the plant height (-0.33) and stem
girth (-0.30). Plant height, leaf area and brix percentage have negative correlation
with number of tillers per plant, stem girth and non-reducing sugar. Sanjay and
Devendra (2014) found that yield was significantly correlated with number of tillers,
stem diameter, plant height, number of inter nodes, intermodal length and number of
leaves. These results do not match totally with our findings, which may be due to
different germplasm used, environmental factors or interaction of both.
MORPHOLOGICAL STUDIES
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Fig 2.3: Loading of PC1.
Fig 2.4: Loading of PC2s.
MORPHOLOGICAL STUDIES
39
2.4.2.3. Loadings of PC3
Loading of third principal component (PC3) as depicted in the Fig. 2.5
indicated that the inter-nodes length has maximum positive loadings (0.677)
followed by the non-reducing sugar (0.5707). Number of tillers showed minimum
loadings (-0.183) followed by number of leaves per plant (-0.1657).
It can be concluded from the above finding that inter-node length has positive
correlation with non-reducing sugar. Number of tillers per plant and number of
leaves per plant has negative correlation among themselves as well as negative
correlation with inter-nodes length and non-reducing sugar.
2.4.2.4. Loadings of PC4
Loadings of the PC4 is presented in the Fig.2.6. From the figure the number
of tillers per plant has maximum loadings (0. 5278) followed by the leaf area
(0.4916) and number of leaves per plant (0.4), which means that its contribution in
the generation of variance was aparent in this PC. Brix percentage showed minimum
loadings (-0.3345) followed by the inter-nodal length (-0.192).
Number of tillers per plant depicted maximum negative correlation with brix
percentage. The results indicated that an increase in number of tillers per plant
decreased the brix percentage in the genotypes under study. So, the careful selection
of genotype should be made for number of tillers per plant because increased number
of tillers brings the drastic change in the decreased brix percentage which is a metric
trait in case of sugarcane.
MORPHOLOGICAL STUDIES
40
Fig 2.5: Loading of PC3.
Fig 2.6: Loading of PC4.
MORPHOLOGICAL STUDIES
41
2.4.2.5. PC1 VERSUS PC2 BIPLOT FOR 10 QUANTITATIVE TRAITS OF 20
SUGARCANE GENOTYPES
The first two PCs; i.e. PC1 and PC2 genetared 54.63 percent of the total
variance (Table.2.3) among the 20 genotypes for the 10 quantitative traits under
study and is resperented in the Fig.2.7. Plant height, number of nodes per plant and
number of leaves falls on opposite axis with respect to leaf area and reducing sugar
in the biplot diagram which means that these parameters have negative correlation.
This association was confirmed from the loading of the PC1 in Fig.2.3. Brix
percentage, inter-nodes length number of tillers per plant have negative correlation
with stem girth and non-reducing sugar while plant height has negaticve correlation
with leaf area. These results are very much in accordance with the loadings of the
PC2 (Fig.2.3).
Biplot diagram of 20 genotypes for 10 quantitative traits shows that five
genotypes; i.e. S-08-FSD-19, S-03-US-778, HSF-241, S-06-272 and S-03-US-127
fall outside the range of the center of axis as compared to the rest of other genotypes
hence, these genotypes are considered to be outliers, which means that these
genotypes are morphologically more divergent as compared to other genotypes under
study.
Biplot diagram detpected that S-03-US-778 has maximum leaf area, S-08-
FSD-19 has maximum value for brix percentage, number of tillers per plant and
inter-nodes length, S-03-US-127 and S-06-US- 272 have maximum plant height,
number of nodes and leaf area while HSF-242 has maximum stem girth and non-
reducing sugar. Contribution of these parameters in the generation of variance was
high, therefore during selection these parameters must be given due consideration.
MORPHOLOGICAL STUDIES
42
It can further be inferred for the Biplot diagram that almost 75 percent of the
genotypes used in this study showed less divergence for the quantitative traits under
study and fell near the center of origen in the different axis and made three groups.
First group comprised genotypes; S-06-US-658, S-03-SP-93, LHO-83153, HSF-240,
SPF-232 and SPF-213. Second group consisted of genotypes; S-06-US-300, S-03-
US-694, S-05-FSD-317, S-05-FSD-307, CPF-237 and BF-162. Third group
comprised genotypes; S-08-FSD-23 and S-06-SP-321. These three groups indicated
less divergence for most of the traits compared.
Fig.2.7: Plot of (PC1) versus (PC2) for 10 Quantitative traits and 20 Sugarcane
genotypes.
MORPHOLOGICAL STUDIES
43
2.4.3. CLUSTER ANALYSIS
Cluster analysis can be used by two ways; one is hierarchical or graphical
approach while the second approach is non-hierarchal, K-mean clustering or
numerical approach. For authentication of results it is generally suggested that these
two approaches can be used in combination.
Analysis of variance was performed using statistical software package
STATISTICA 0.5. Plant height and reducing sugar were highly significant traits
(Table.2.3). Number of leaves per plant were significant followed by leaf area while
all other traits; i.e. number of tillers per plant, stem girth, number of nodes, inter-
nodal length, brix percentage, reducing sugar and non-reducing sugar were non-
significant. Bakshi and Hemaprabha (2005) and Cardozo et al. (2014) found
significant difference for all the traits considered. However, present studies varied
from the reports where all traits were not found significantly variable.
2.4.3.1. HIERARCHAL CLUSTER
Data was subjected to the cluster analysis that generated five clusters at
Euclidean distance of 7 by following Ward’s method. Range of linkage distance were
between 0-12, as detailed below. Analysis of variance for quantitative traits showed
highly significant differences (Table 2.4) in plant height and reducing sugar,
significant differences in number of leaves per plant and leaf area while number of
tillers per plant, stem girth, internodes length brix percentage and non-reducing sugar
were non-significant. Plant height, leaves per plant, leaf area and reducing sugar were
important characters in the variance generation, hence selection of genotypes by
keeping view on these character would be beneficial.
MORPHOLOGICAL STUDIES
44
2.4.3.1.1. Cluster I
Cluster I contained only one genotype; HSF-242 which is an outlier in the cluster
diagram. This genotype is also an outlier in a biplot diagram (Fig.2.7) of PC1 and
PC2.
2.4.3.1.2. Cluster II
Cluster II comprised eight genotypes; SPF-213, S-05-FSD-307, S-06-US-300, S-
03-SP-93, SPF-232, LHO-83153, HSF-240 and S-06-US-658. SPF-213 and S-06-
US-658 are the outliers in this cluster. Biplot diagram (Fig.2.7) also showed almost
same genotypes in the group one. It means that these genotypes have close
association among themselves.
Table.2.4: Analysis of variance for quantitative traits in 20 sugarcane genotypes
for cluster analysis.
** Highly significant
* Significant
NS Non-Significant
S.O.V Between Within F Probability
SS d.f SS d.f
Plant Height (cm)
9.37 1 9.6 18 17.51 0.001**
No. Tillers/Plant
0.04 1 19.0 18 0.04 0.845NS
Stem Girth (cm)
1.00 1 18.0 18 1.00 0.329NS
No. of internodes (cm)
12.90 1 6.1 18 38.07 7.961NS
Internodes Length (cm)
0.17 1 18.8 18 0.16 0.691NS
No. of Leaves per plant
4.43 1 14.6 18 5.47 0.031*
Leaf Area
4.62 1 14.4 18 5.79 0.027*
Brix %age
1.84 1 17.2 18 1.93 0.181NS
Reducing sugar
8.07 1 10.9 18 13.28 0.001**
Non-Reducing sugar
0.20 1 18.8 18 0.19 0.668NS
MORPHOLOGICAL STUDIES
45
2.4.3.1.3. Cluster III
This cluster was composed of three genotypes; S-03-US-778, S-08-FSD-23 and
S-08-FSD-19. Two of these genotypes S-03-US-778 and S-08-FSD-23 are the
outliers in the biplot diagram and also form a separate group along with S-08-FSD-
19.
2.4.3.1.4. Cluster IV
Five genotypes; CPF-237, BF-162, S-03-US-694, S-05-FSD-317 and S-05-US-
54 are included in cluster number four. These genotypes have close association with
the genotypes included in the cluster V and cluster III. Biplot of PC1 and PC2 also
showed same genotypes in the second group. These genotypes have association with
genotypes of cluster V but much divergent as compared to the genotypes of cluster
I, cluster II and cluster III.
2.4.3.1.5. Cluster V
Only three genotypes (S-06-SP-321, S-06-US-272 and S-03-US-127) were
included in this cluster. S-03-US-127 is an outlier in this group which can be
confirmed from the biplot diagram of PC1 versus PC2 where S-06-US-272 and S-
03-US-127 are the outliers. It clearly depicts that these genotypes are more divergent
in the overall genotypes compared and can be used for future crop improvement
program.
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46
Fig.2.8: Cluster Diagram of 20 Sugarcane Genotypes on the basis of morpho-
physological traits.
MORPHOLOGICAL STUDIES
47
2.4.3.2. NON- HIERARCHAL CLUSTER (K MEAN CLUSTERING)
K-mean clustering was performed among 20 sugarcane genotypes on the basis
of 10 quantitative traits (Table 2.5).
2.4.3.2.1. Cluster I
This cluster has only one genotype; HSF-242. Hierarchal cluster also has one
member HSF-242.
2.4.3.2.2. Cluster II
This cluster has eight genotypes; SPF-213, S-05-FSD-307, S-06-US-300, S-
03-SP-93, S-06-US-658, SPF-232, LHO-83153 and HSF-240. Hierarchal cluster has
same genotypes in the cluster II.
2.4.3.2.3. Cluster III
Cluster III has four genotypes; S-06-SP-321, S-03-US-778, S-08-FSD-23
and S-08-FSD-19. Hierarchal cluster also has same genotypes in the cluster III
except S-06-SP-321.
2.4.3.2.4. Cluster IV
Cluster IV comprised five genotypes; CPF-237, BF-162, S-03-US-694, S-05-
US-54 and S-05-FSD-317. Hierarchal cluster has same genotypes in the cluster IV.
2.4.3.2.5. Cluster V
This cluster has two genotypes; S-06-US-272 and S-03-US-127. These
genotypes are also present in the hierarchal cluster V. Bakshi and Hemaprabha
(2005) conducted cluster analysis on sugarcane genotypes containing 13 traits and
grouped genotypes into 9 clusters. Gemin et al. (2006) obtained 4 clusters on the
basis of sugar contents by doing cluster analysis. Kashif and Khan (2007) determined
genetic diversity in fourteen sugarcane genotypes on the basis of 12 quantitative
characters and obtained 4 clusters while Ahmed and Obeid (2010) found genotypes
MORPHOLOGICAL STUDIES
48
clustered into six groups with higher genetic distance between two clusters being 83
percent. Meenu et al., (2012) evaluated 41 genotypes on the bases of quantitative
traits and obtained five groups of genotypes. Tahir et al., (2013) conducted cluster
analysis using Ward’s method to distinguish sugarcane genotypes and revealed 3
clusters with linkage distance of 4.5 while Kang et al., (2013) partitioned sugarcane
genotypes into eight clusters. Sanghera et al., (2015) assessed genetic diversity by
using cluster analysis in sugarcane based on eighteen quantitative traits and found
genotypes grouped into five clusters with maximum genetic distance between two
clusters as much as 89.
Above studies supports the authentication of our findings. Our results are in
accordance with the findings of Gemin et al., (2006), Kashif and Khan (2007),
Ahmed and Obeid (2010), Tahir et al., (2013) and Sanghera et al., (2015) while the
results of Bakshi and Hemaprabha (2005) and Sanghera et al., (2015) do not match
with our results.
Table.2.5: Non- Hierarchal Clusters and members in each cluster.
Clusters Members
Cluster I HSF-242
Cluster II SPF-213, S-05-FSD-307, S-06-US-300, S-03-SP-93, S-
06-US-658
SPF-232, LHO-83153 and HSF-240
Cluster III S-06-SP-321, S-03-US-778, S-08-FSD-23 and S-08-FSD-
19
Cluster IV CPF-237, BF-162, S-03-US-694, S-05-US-54 and S-05-
FSD-317
Cluster V S-06-US-272 and S-03-US-127
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49
2.5 CONCLUSION AND RECOMMENDATIONS
Analysis of variance revealed highly significant differences among the
parameters compared. Cumulative variance percentage in genotypes was recorded
54.63% in first two PCs on the basis of Principal Component Analysis. Hierarchal
and non-hierarchal cluster and biplot diagram for PC1 and PC2 grouped genotypes
in a similar pattern. Genotype HSF-242 from cluster I and genotype S-03-US-127
from Cluster V showed maximum genetic distance (8). Genotype S-05-US-307 from
Cluster II and from Cluster IV genotypes S-03-US-694 and S-05-FSD-revealed
Euclidian Distance 5. These genotypes can be used for hybridization program.
Hence, assessment of divergence on the basis of morphological parameters is not
sufficient for accurate genotyping of sugarcane. A meticulous observation on
phenotypic traits along with application of modern molecular markers (i.e SSR and
SNPs) can give precise genetic discrimination among genotypes.
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Chapter: 3
MOLECULAR STUDIES
3.1. INTRODUCTION
Sugarcane (Saccharum spp.) is a tall, tropical, monocotyledonous, complex
aneu-polyploid plant (2n = 8x or 10x = 100-130) that propagates asexually through
planting of vegetative cuttings (setts) of mature stalks. It is one of the important
commercial sugar producing crops and a major source of approximately 50% sugar
and ethanol in the world. More than 1,000 million tons of sugarcane is harvested
each year. It is the source of most of the sugar produced in the world, greatly
exceeding sugar beet (Cordeiro et al., 2001). Sugarcane is the second major cash
crop of Pakistan and is used as a raw material for the production of sugar, gur and
ethanol. Its share in agriculture and GDP is 3.7 and 0.8 percent, respectively.
Sugarcane was cultivated on an area of 10.46 million hectares with the cane
production of 58.0 million tons, for the year 2011-12 (MNFSR, 2012).
An essential first step in any varietal development program is to come up
with germplasm that has sufficient genetic variability reflected on morphological
basis. Accurate assessment of genetic diversity is very important in crop breeding as
it helps in the selection of desirable genotypes, identifying diverse parental
combinations for further improvement through selection in segregating populations,
and introgression of desirable genes from diverse germplasm into the available
genetic base (Mohammadi et al., 2003). Therefore, genetically diverse germplasm is
essential in breeding programs to enhance the productivity and diversity of cultivars.
In case of the non-availability of diverse germplasm, utilization of introduced
germplasm with full knowledge of its genetic base and genetic remoteness also help
in crop improvement program (Malik et al., 2010).
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51
The efficiency of genetic introgression in sugarcane has been low, due to the
sporadic flowering behaviour, barriers in natural hybridization, self-incompatibility,
technical difficulties in artificial crossing, prolonged selection and evaluation
processes. Due to all these factors, the genetic base of Pakistani sugarcane cultivars
is considered narrow. Therefore, extensive breeding strategies are required to
enhance the genetic base of cultivars and close the gap between current cane yield
and actual yield potential. Breeder’s aim to select superior sugarcane clones with
broad genetic base for hybridization and selection and to attain this, assessment of
genetic distinction in the available germplasm is a prerequisite. To understand the
extent of natural variation on a molecular basis it is important to set up new strategies
for sugarcane improvement program. Molecular markers such as microsatellites have
been used for this purpose. Morphological evaluation of sugarcane genotypes to
know the extent of variability on the basis of some important matric traits under agro-
climatic condition is essential to assess the genotype x environmental (G x E)
interaction, biotic and abiotic stress response of genotypes, vegetative and
reproductive phase response of genotypes in a particular environment. Unlike
morpho-physiological characters that are affected by environmental fluctuations,
molecular markers are considered stable and not influenced by geographical region
or seasonal changes. Microsatellite markers, also known as simple sequence repeats
(SSRs), are one of the most powerful genetic marker classes. The SSRs are repeated
DNA sequences of simple sequence motifs, each motif ranging from one to six
nucleotides (Kalia et al., 2011). Microsatellite markers are abundantly present in the
genome of eukaryotic organisms, and are highly polymorphic and co-dominant (Xu
and Crouch, 2008; Chen et al., 2009). The SSRs are ubiquitous and highly
polymorphic, owing to some of the spontaneous mutation affecting the number of
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52
repeat units. The hyper variability of SSRs among related organisms makes them an
informative and excellent choice of markers for a wide range of applications in
sugarcane, which include high-density genetic mapping (Chen et al., 2007),
molecular tagging of genes (Singh et al., 2005), genotype identification, genetic
analysis of diversity (Cordeiro et al., 2003) and paternity determination (Pan et al.,
2010; and Tew. 2003). SSR markers are suitable for sugarcane molecular genotyping
(Pan et al., 2003) and genetic diversity estimation (Cordeiro et al. (2001). Several
studies have been conducted on sugarcane diversity analysis using SSR markers
(Cordeiro et al., 2001, 2002, 2003, 2007; Pan et al., 2003; Chen et al., 2007; Singh
et al., 2008; Chen et al., 2009; Glynn et al., 2009; Chen et al., 2009; Creste et al.,
2010; Mishra et al., 2010; Silva et al., 2011; Hameed et al., 2012; Devarumath et al.,
2012) reflecting their importance for assessment of genetic diversity in sugarcane.
Aim of this research work include:
Determine the molecular diversity of adopted local and exotic
sugarcane genotypes in Pakistan using SSR markers
Select genotypes with a diverse genetic base for future hybridization
programmes
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53
3.2. REVIEW OF LITERATURE
Cordeiro et al., (2003) utilized SSR markers to determine the extent of
genetic diversity among S. officinarum, S. spontanum, S. sinenses Old world
Erianthus, North American S. giganteum, sorghum and Miscanthus. They tested 66
accessions by using six SSR markers and generated 187 alleles and compared the
available results against already published data from other molecular markers i.e.
AFLPs, RFLPs RAPDs, and 5S rRNA intergenic spacers. They reported that the
genetic similarity coefficient and cluster analysis revealed same genetic relationship
for Saccharum spp and Erianthus sect. Ripidium as previously recognized using
other molecular marker system. It was concluded that microsatellite markers were
an ideal tool to assess the genetic constitution of modern sugarcane cultivars that
have interspecific origins.
Singh et al., (2008) evaluated the polymorphic potential of microsatellite
markers for their polymorphism, genetic diversity analysis and comparative linkage
mapping in 20 sugarcane varieties. They found 158 SSR markers abundantly
polymorphic with PIC values range from 0.51 % to 0.84 %. They were ranged from
2 to 11 with a mean of 5 alleles per locus while a total of 977 polymorphic DNA
bands were detected with fragment size of 20 to 1380 bp. The studies concluded that
microsatellite markers were unique source for sugarcane germplasm evaluation and
marker assisted breeding approaches.
Chen et al., (2009) conducted an experiment for molecular genotyping of 35
sugarcane genotypes by using 20 polymorphic SSR primers and identified a total of
251 alleles, of which 248 depicting polymorphism while only three were
monomorphic. A total number of alleles by each primer pair ranged from 7 to 18
with an average of 12.5 alleles per primer, while diversity index (DI) ranged from
0.71 to 0.91 with an average of 0.83. They identified 10 SSR markers that were much
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54
informative for characterization of 40 genotypes. Cluster analysis grouped the
genotypes into five main groups based on similarity coefficient values. In accordance
to their experiment they concluded that SSR markers were useful in progeny
selection and allele transmission in sugarcane.
Singh et al., (2010) characterized the sugarcane germplasm by using 7
sugarcane cDNA derived microsatellite markers, 9 gemonic microsatellite and 16
unigene sugarcene SSR markers. They assessed the genetic diversity among 83
accessions of S. officinarum, S. barbary and S. spontanium using SSR markers and
found amplified number of alleles ranged from 4 to 14 indicatig high level of
heterozygosity and polymorphism in sugarcane genotypes. Based on cluster analysis
followed by UPGMA genotypes were grouped into 10 distinct clusters. They
concluded that diverse genotypes with desirable agronomic attributes should be used
as a proginator for clutivar development with broad genetic base.
Duarte Filho et al., (2010) analysed the genetic similarity in commercial
sugarcane cultivars of using eighteen SSR markers. The SSRs amplified an average
3.2 alleles per primer pair with polymorphic information content ranging from 0.34
to 0.78. The results revealed genotypes with high genetic similarity could decrease
genetic gain in breeding programme.
Banumathi et al., (2010) utilized 40 primers to study the genetic diversity in
a set of 48 sugarcane clones and generated 147 alleles with average polymorphic
information content (PIC) value of 0.665. Based on UPGMA cluster analysis by
using sugarcane SSR markers data they found significant variation among clones and
concluded that SSR markers have unique discriminating power for characterization
of sugarcane genotypes.
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55
Pan (2010) used 21 highly polymorphic SSR markers to evaluate the genetic
diversity among 1025 sugarcane clones and amplified 144 DNA fragments. He
constructed molecular identity database on the basis of presence (A) and absence (C)
and continued updating database annually by SSR based genotyping newly assigned
sugarcane clones. He suggested that this database provide molecular description for
novel genotype registration that provided information to identify ambiguous
sugarcane genotypes in crossing programmes, it also determined the paternity of
cross progeny and confirm the preferred genotypes that were grown in farmers’
fields.
Liu et al., (2011) evaluated 152 sugarcane SSR markers developed for
germplasm transferability characterization. They selected and utilized 23 sugarcane
SSR primers and amplified 200 PCR fragments, of which 199 were polymorphic
with an average of 8.7 polymorphic alleles per primer pair with size ranging from
100 to 505 bp. Polymorphic information content (PIC) value estimated varied from
0.42 to 0.90. The study was suggested as a good reference source for sugarcane
breeders for identification of local germplasm used in other countries
Devarumath et al., (2012) studied the genetic diversity within and among
Saccharum species and commercial hybrids using Inter Simple Sequence Repeat
(ISSR) and Simple Sequence Repeats (SSR) markers. They used total 13 ISSR
primers to characterize 81 sugarcane genotypes and amplified 65 fragments, among
them 63 (96.3 %) were polymorphic with mean PIC value of 0.28 and average
genetic similarity coefficient of 0.59. By using 28 SSR primers they obtained 79
alleles, among them 76 were polymorphic (92.2 %) with PIC value ranging from
0.06 to 0.55 with mean PIC value 0.17. They calculated genetic similarity by
Jaccard’s similarity coefficient which ranged from 0.11 to 0.91 with an average value
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56
of 0.51. On the basis of dendroram constructed by suing cluster analysis following
UPGMA, it was concluded that low level of genetic association was found between
genetic similarities based on pedigree.
Perera et al., (2012) stated that for identification of genotypes and
assessment of genetic diversity in sugarcane on the basis of morphological and
molecular markers, the general approach for data set should be diverse. They
evaluated sugarcane genotypes in Argentina for diversity analysis by using SSR
markers and morphological traits and found that local genotypes attained same group
in cluster with no genetic difference among local and USA sugarcane genotypes,
which may be due to frequent exchange of germplasm for breeding purposes. It was
suggested that these markers should be used for sugarcane variety protection and
genetic similarities assessed from molecular markers, as it provide more precise
information to plant breeders as compared to pedigree method when determining
genetic inheritance of sugarcane.
Dos Santos et al., (2012) illustrated that reassessment of genetic diversity
available to breeder is necessary in order to develop modern varieties, for this
purpose some methodologies based on morphological and genealogical data have
been utilized but morphological traits are influenced by the environmental factors
and genealogical data can mislead for biased information. They suggested that SSR
markers were reliable to distinguish between closely associated individuals. They
analysed 47 varieties and generated 124 polymorphic alleles with sizes ranged from
81 to 340 bp. They categorized 22 alleles as a rare and 12 others considered common.
The genetic similarities estimated among main progenitors were low which may be
due to high level ploidy and heterozygosity of sugarcane. It was concluded that by
using cluster analysis following UPGMA little divergence within varieties was
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57
observed to separate them in distinguishable groups because these varieties may be
taken from same parents.
Hameed et al., (2012) utilized simple sequence repeat (SSR) based markers
system to detect the genetic relationship between sugarcane cultivars resistant and
susceptible to red rot. They used twenty one polymorphic SSR markers for genetic
diversity analysis of 20 sugarcane cultivars. About 144 alleles, with range of 3 to 11
alleles per marker and mean value of 6.8 were detected. Three SSR primers were
able to differentiate among 20 genotypes. By generating homology tree genetic
diversity among the genotypes was analysed and that all cultivars shared 58 percent
genetic similarity whereas, SSR derived markers were found to be the reliable
marker system to identify red rot resistant and susceptible cultivars.
Smiullah et al., (2013) detected polymorphism in seventeen sugarcane
accessions by using 30 simple sequence repeat primer pairs. They amplified 62 DNA
fragments by using 30 SSR primers with a mean of 2.14 bands per primer. Genetic
similarity coefficient ranged from 62.90 to 90.30 percent by construction
dendrogram based on relationship among accessions using cluster analysis presented
90.30% genetic similarity between two genotypes. Their studies indicated that SSR
markers were the best approach to explore the genetic diversity in sugarcane.
You et al., (2013) characterized 115 sugarcane genotypes used for
hybridization based on five genomic simple sequence repeat markers (gSSR) and
detected 88 polymorphic alleles with high genetic variability (90.5%) in
intrapopulation as compared to inter population (9.5%). The genotypes were
characterized into three groups based on cluster analysis. It was reported that
information gained from their study could be useful for future breeding programme
by selecting genotypes with higher genetic divergence.
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58
Diola et al., (2014) assessed the genotypes and phenotypes association in
sugarcane genotypes by using EST SSR markers obtained from nine selected genes
for agronomic traits and amplified a total of 210 amplicons of which 115 were
polymorphic with an average 23.2 alleles in each primer pair. Polymorphic
information content (PIC) value found was ranging from 0.48 to 0.69. Genotypes
were grouped into five major groups with genetic distance approximately 0.8
between groups. It was reported that SSR was the best approach for marker assisted
selection in sugarcane breeding.
Que et al., (2014) used 20 Start codon Targeted (SCoT) marker primers for
the assessment of genetic divergence of sugarcane accession from local germplasm
collection in China and amplified 176 DNA fragments by doing PCR, among them
163 were polymorphic. The polymorphic information contents (PIC) value ranged
from 0.78 to 0.9 with an average of 0.8 percent. Six clusters were obtained by using
UPGMA cluster analysis of SCoT marker’s data of 107 sugarcane genotypes at 0.67
genetic similarity coefficient level. Relative abundance of genetic diversity among
three genotypes was observed which were cultivated on about 80 percent sugarcane
growing area in china. They partitioned 107 genotypes into two major groups viz;
Domestic group and Introduced group and concluded that the knowledge of genetic
diversity among sugarcane germplasm provide apprehension while handling
sugarcane germplasm.
Manish et al., (2014) estimated genetic diversity by using SSR markers.
Twenty SSR primers were used to assess the genetic diversity among 40 sugarcane
genotypes and their parents. They separated PCR fragments with an average 2.3
alleles per loci and identified 10 polymorphic primers with PIC value ranging from
0.15 to 0.67. By using cluster analysis of available data from 20 SSR primers they
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59
estimated the genetic relationship among genotypes following Unweighted Paired
Grouped Method of Arithmetic Mean (UPGMA) and concluded that genotypes have
considerable extent of genetic variability which can be utilized for the selection of
parent for future hybridization programme.
Chandra et al., (2014) used florescent labelled SSR markers for genetic
evaluation of twenty-four sugarcane cultivars, 12 each from USA and India through
capillary electrophoresis (CE). Out of 213 alleles amplified 161 were common to
both US and Indian cultivars, of which 27 were detected only in US genotypes and
25 were only found in Indian genotypes. High level of genetic diversity in both US
(91.1%) and Indian (82.4%) cultivars with average PIC value ranged from 0.66 to
0.77. Genotypes were separated using cluster analysis following UPGMA into three
clusters at genetic similarity level of 59 percent. The potential utility of six cultivar
specific SSR alleles in sugarcane breeding was proposed for varietal purity test,
fidelity assessments, and genetic similarity coefficient among species of the genus
Saccahrum and associated genera.
Tena et al., (2014) studied the genetic relationship and genetic variation of
90 sugarcane accessions by using 22 microsatellite markers and amplified a total 260
alleles of which 230 were polymorphic with an average of 10.45 alleles. They
calculated a range of 4 to 22 alleles per primer with 60.51 percent polymorphic loci.
The PIC value with a range of 0.231 to 0.375 containing average value 0.303 was
estimated. By using UPGMA cluster analysis on SSR alleles data they separated
genotypes into three major cluster containing 11 distinct groups and concluded that
sugarcane accessions from different countries grouped together provide indication
of exchange of germplasm between countries.
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60
Costa et al., (2014) used SSR markers as a molecular tool for the
confirmation of true self-pollinated derived clones in sugarcane. They amplified 62
polymorphic alleles by doing PCR with eight SSR primers pairs, with a mean of
seven polymorphic loci across the genotypes tested. Three informative bands were
detected and were used to assess the extent of selfing in sugarcane S1 families,
similarities in families ranged from 71.7 to 97.6 percent. It was concluded that SSR
loci provide a reliable and authentic tool as a selection strategy in breeding
programme of sugarcane.
Xavier et al., (2014) identified the parental clones in sugarcane by using 10
microsatellite markers and amplified DNA fragments ranging from 102 to 120 with
a mean of 113.25 alleles per SSR marker. They detected 45.9 percent genetic
similarity among the parental clones involved in polycrosses. It was reported that
SSR marker technology was useful for the identification and confirmation of male
parent selection with high performance in breeding programme.
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3.3. MATERIAL AND METHODS
3.3.1. PLANT MATERIAL
Twenty sugarcane cultivars used in this study were collected as setts from the
germplasm collection at the Sugarcane Research Institute, AARI Faisalabad,
Pakistan. The germplasm collection contained local and exotic (Canal Point, USA,
Sao Paulo, Brazil and Barbados, West Indies) material evaluated for improved
cultivars to be grown throughout sugarcane growing areas of Punjab, Pakistan. These
vegetative sets of the cultivars were sown at Arja, Bagh, Azad Kashmir, Pakistan
under field conditions and leaf samples were collected for DNA isolation from one
month old seedlings. Leaf samples were immediately put into isotherm bucket
contained ice gel pads and brought to laboratory of Plant Breeding and Molecular
Genetics, Faculty of Agriculture Rawalakot where samples were stored at -80°C
freezer.
3.3.2. DNA EXTRACTION AND QUANTIFICATION
DNA was extracted from 0.5 gm fresh young leaves according to the CTAB
procedure of Doyle (1991) with modifications. One gram of leaf sample was
macerated in a pre-autoclaved mortar and pestle containing liquid nitrogen. Fine
powdered leaf tissue was transferred to 15 ml Falcon™ tubes and 2.5 ml 2X CTAB
buffer (CTAB powder 20gm, 100mM Tris-HCl pH 8.0, 0.5 mM EDTA pH 8.0, 1.4
M NaCl, PVP 40 SIGMA-ALDRICH™. 10 gm, β-Mercaptoethanol 10 ml, H2O up
to 1000 ml) was added to each tube. The contents were mixed and placed in a 65°C
water bath for 30 min with the tubes shaken after 10 min. An equal volume of
chloroform: isoamylalcohol (24:1, v/v) was added to each tube and the contents
mixed gently by inversion and then incubated at room temperature for 5 min. Tubes
were centrifuged at 6000g for 15 min and the aqueous upper layer supernatant was
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62
transferred into fresh tubes. An equal volume of ice chilled iso-propanol was added
and the tubes were inverted 4-5 times to mix the contents. Tubes were centrifuged at
6000g for 10 min to collect the precipitated nucleic acid at the bottom of the tube.
The nucleic acid pellet was washed with 70 % ethanol and air dried. The nucleic acid
was resuspended in 200 µl Milli Q water and transferred to 1.5 ml microfuge tubes
and incubated at 37°C for an hour after adding 5 µl RNAse (10mg/mL) Thermo
Scientific™ to digest RNA. DNA quantification was carried out at Agricultural
Biotechnology Research Institute, Faisalabad Pakistan using a NanoDrop® ND-
1000 Spectrophotometer. From 200 ul DNA stock 1 µl was used to measure the
concentration at 260 nm wavelength and 20 ng/µl final concentration of DNA for
each sample was adjusted for PCR amplification.
3.3.3. PRIMER SELECTION
A total of 49 primer pairs primers were selected for this study. Among them
20 primer pairs were synthesised from already published sugarcane SSR primers,
namely mSSCIR3, SMC18SA, SMC1604SA, SMC7CUQ, SMC24DUQ,
SMC36BUQ, SMC119CG, SMC278CS, SMC334BS, SMC569CS, mSSCIR66,
mSSCIR43, SMC703BS, SMC851MS, SMC1751CL, SMC597, mSSCIR78,
mSSCIR58, mSSCIR17 and mSSCIR24 (Chen et al. 2009). The remaining SSR
primers were designed and developed based on the microsatellite containing
sequences of sugarcane by the International Consortium of Sugarcane Biotechnology
(ICSB).
3.3.4. PCR AMPLIFICATION
PCRs were conducted following a procedure described by reagents
manufacturer (Thermo Scientific™) with little modifications. PCR reaction volume
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Table 3.1. A description of 49 sugarcane microsatellite markers containing
primer names, forward and reverse primer sequences.
S. No Primer Name Forward Primer (5’→3’)
Reverse Primer (3’→5’)
1 P-86 CTGTCCATTCCCATCCTC
GCACCGATTCTCTTCTGG
2 P-89 AGAGAGAAAGAGAGGCGG
CTTCACGGAGCGAGAGAC
3 P-90 CTTCCACAACCAGAGCAG
GGAGACAGAGGCGAACAG
4 P-92 CTGGCTCTCCTGGTTTCC
CTGCTGTTGTTCCTGCTC
5 P-94 ATTCTTGTCTATGGCGGG
GCTATCCCTTCACTCTCCTC
6 P-99 GTCTGTCTCCTTCCTGCTC
TGTCTCCCTGCTGTTGTT
7 P-100 AACGCCTCCGACAGTGAG
CCGAGACCAACCAAGCAG
8 P-101 AGGAAATGGATTGCTCGG
CTTGTGGATTGGATTGGAT
9 P-105 TGATACACCATTGTTGATGC
ACACCACTCACATCCACTTG
10 P-108 TGCTTCTAAGTCAACCAAA
TGGTCTACTGAATTCGTG
11 P-111 GCCTTCTTTTGTTTTCCTC
CGTCTCTATGCACCCTATC
12 P-114 CAGGTTGCGTCTTCCACCT
AGCGATGGGTGCTGACAT
13 P-126 CCATAGCAACTACATACAGCATCT
TTACTAAAGGCACAACAAGAAC
14 P-127 CATGCCAACTTCCAATACAGACT
AGTGCCAATCCATCTCACAGA
15 P-128 GGATGAGCTTGATTGCGAATG
CAATTCTGACCGTGCAAAGAT
16 P-129 GCCAGAGAGAGAGAGAGTAGG
ATCGGCTTACATTCAGGTT
17 P-132 GAAATTCCTCCCAGGATTA
CCAACTTGAGAATTGAGATTCG
18 P-133 GTTGTTTATGGAATGGTGAGGA
GCCTTTCTCCAAACCAATTAGT
19 P-137 TGCCAGAAGTGGTTGTCCTCA
TTAAGAGACCCGCCTTTGGAA
20 P-139 CCAATCGTGCCACTGTAGTAAG
ACGCTTGCGTGCTCCATT
21 P-141 CTTCCCTCCCTCTCCTCT
AGCCTTCTAAACTATCTGCT
22 P-142 TAAGAATCGTTCGCTCCAGC
TTACTGGCTGGGTTTTGTTC
23 P-143 AGCTCTATCAGTTGAAACCGA
GCCAAAGCAAGGGTCACTAGA
24 SMC851 CGTGAGCCCACATATCATGC
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ACTAAAATGGCAAGGGTGGT
25 SMC 18SA ATTCGGCTCGACCTCGGGATAT
AGTCGAAAGGTAGCGTGGTGTTAC
26 SMC1604SA AGGGAAAGGTAGCCTTGG
TTCCAACAGACTTGGGTGG
27 SMC7CUQ GCCAAAGCAAGGGTCACTAGA
AGCTCTATCAGTTGAAACCGA
28 SMC703BS GCCTTTCTCCAAACCAATTAGT
GTTGTTATGGAATGGTGAGGA
29 SMC24DUQ CGCAACGACTTATACACTTCGG
CGACATCACGGAGCAATCAGT
30 SMC36BUQ GGGTTT CATCTCTAGCCT ACC
TCAGTAGCAGAGTCAGACGCTT
31 SMC119CG AGCAGCCATTTACCCAGGA
TTCTCTCTAGCCTACCCCAA
32 SMC278CS TTCTAGTGCCAATCCATCTCAGA
CATGCCAACTTCCAAACAGACT
33 SMC334BS CAATTCTGACCGTGCAAAGAT
CGATGAGCTTGATTGCGAATG
34 SMC569CS GCGATGGTTCCTATGCAACTT
TTCGTGGCTGAGATTCACACTA
35 SMC597 GCACACCACTCGAATAACGGAT
AGCTGAATCGTGGTGAACAA
36 SMC851MS ACTAAAATGGCAAGGGTGGT
CGTGAGCCCACTATCATGC
37 SMC1751CL GCCATGCCCATGCTAAAGAT
ACGTTGGTCCCGGAACCG
38 mSSCIR-3 ATAGCTCCCACACCAAATGC
GGACTACTCCACAATGATGC
39 mSSCIR17 AGTTCTTTTCGTTCTCTGG
AGCATAGTTTTTGTGGAC
40 mSSCIR24 TTACTCCGCCTCTTTACT
AGATGAACCCAAAAACTTA
41 mSSCIR-43 AACCTAGCAATTTACAAGAG
ATTCAACGATTTTCACGAG
42 mSSCIR58 TGGTCTATCACTTAATCAGCAC
AGGCTACATGCTTACAGCCAT
43 mSSCIR-66 AGGTGATTTAGCAGCATA
CACAAATAAACCCAATGA
44 mSSCIR78 GCAACCGCGTCCTCATAC
CAGGTTCGTCTTCCAGCT
45 SMs009 TCATACAAGCAGCAAGGATAG
GAGCCGCAAGGAAGCGAC
46 SMs012 AAGGAGATGCTGATGGAGA
AAATGTCTTCGCACTAACC
47 SMs016 TCTGTCCTCTGGTAATCCTG
AGCACGGCACGCAATCAC
48 SMs032 AGATGGAAGAAGGAGAATG
CGACGAGAGCCTGACGAG
49 SMs037 AGTTGTAAGTCGTTCTGGTTT
TTTGGGCAGTCGTTTATC
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was 20 µl containing reagents (Thermo Scientific™) 10X Taq Buffer 2.0 µl, 25 mM
MgCl2, dNTP’s mix 2.5mM, 10 mM forward and reverse primers each, Taq DNA
polymerase 1 U/µL, 20ng/µl DNA from each genotype and MilliQ H2O 5.8 µl. PCR
amplification reactions were conducted in a Mini Opticon Real-Time PCR System
BIO RAD™ under the programme of 105°C pre heating lid, 95°C for 5 min initial
denaturation, 35 cycle of (94°C for 30 sec, annealing ranging 48-68°C depending on
primer length for 45 sec, and extension 72°C 1 min) and final extension at 72°C for
10 min and hold at 4°C.
3.3.5. ELECTROPHORESES AND FRAGMENT ANALYSIS
Ten microliters of PCR products mixed with 2 µl 6X loading dye (Thermo
Scientific™) were analysed by electrophoresis on a 2 % (w/v) agarose gel in TBE
Gel images were captured under gel documentation system (UV tech™).
SSR fragments were normally in the range of 50 bp to 600 bp, so they did not resolve
well on agarose gels. Polyacrylamide gels were used to clearly separate the SSR
fragments. The procedure for PAGE was used as described by Anderson et al. (2013)
with modifications. Following gel composition was used; 0.5X TBE buffer, 10 %
APS (Ammonium persulphate), TEMED (Tetramethylethylenediamine Sigma
Aldrich®), PAGE gel solutions (Rotiphorese® Gel 30). PCR products volume 1 µl
diluted in 3 µl 6X loading dye was used to run on gel at 80 volts/cm for two hours.
The banding pattern of amplified fragments was compared by running 1 µl of 50bp
DNA ladder (Thermo Scientific™). Gel was dipped in the fixative solution (10%
ethanol 80 ml, 10% acetic acid 40 ml, d3H2O 680 ml) for 15-20 min with gentle
shaking then stained silver nitrate solution (AgNO3 1.6 gm, d3H2O 800 ml) for 10-
12 min with gentle shaking at electric shaker. The gel was washed twice with
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deionised double distilled H2O and put in the developing solution (NaOH 12gm,
formaldehyde 8ml and d3H2O 800 ml) till the appearance of bands.
3.3.6. GEL IMAGE ANALYSIS
Gel images were taken under gel documentation system (UV Tech™)
containing NTSYS SPc 2.2 software and saved in JPEG mode. Totallab Quant ID
gel image processing software (Totallab™) was used for band detection.
3.2.7. STATISTICAL ANALYSIS
Polymorphic SSR marker’s alleles were scored as a binary data: presence (1)
and absence (0) in MS Office 2010® Excel Sheet. Only unambiguous and clearly
resolved bands were used in the analysis. The genetic similarity coefficient was
estimated by using NTSYS-pc v. 2.1 software (Rohlf et al., 2000). A dandrogram
for cluster analysis was constructed on NTSYS-pc v.2.1 software by using
Unweighted Pair Group Method with Arithmetic Mean (UPGMA) as described by
Sneath and Sokal (1973). To estimate the genetic association among genotypes
Principal Coordinate analysis (PCoA) of the SSR data was performed by using the
Simpson similarity index with PAST statistical software (Hammer et al., 2001).
Polymorphic information content (PIC) was calculated a 1-p2-q2, where p is the
presence of band frequency and q is the absence of band frequency as described by
the (Mondal et al., 2009). Diversity index (DI) values were calculated by the formula
given by (Simpson, 1949).
DI =1 −∑ 𝑃𝑖2𝑠
𝑖=1
Where Pi represents the frequency of the ith allele.
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3.4. RESULTS AND DISCUSSION
3.4.1. RESULTS
The study was conducted at Laboratory of Plant Breeding and Molecular
Genetics, Faculty of Agriculture Rawalakot, University of Azad Jammu & Kashmir,
Pakistan. A total of 20 adopted sugarcane genotypes that are cultivated in most part
of sugarcane growing areas of Pakistan were used for selection of some diverse
genotypes for future breeding programme by using SSR markers. To test the general
utility of 49 SSR primer pairs; genetic similarity coefficient, number of alleles. PIC
value, polymorphism percentage and diversity index (DI) were calculated. Cluster
analysis following UPGMA was conducted to access the genetic similarity (GS)
among genotypes while Principal Coordinate Analysis was conducted to estimate the
genetic variation and confirmation of results generated with cluster analysis. Data
obtained for each marker and genotype are presented in (Table 3.2). PCR products
generated from 49 SSR primer pairs ranged from 50 bp to 600 bp. In total, 420 SSR
alleles were identified, of which 60 were monomorphic while remaining 380 were
polymorphic. The total number of alleles generated by any single SSR primer pair
ranged from 3 to 22. Three SSR primers namely; P-89, P-90 and P-100 showed
higher polymorphism by generating more than 15 alleles (Fig.2abc). Fourteen
primers showed moderate polymorphism by producing 10 to 14 alleles. Eighteen
SSR primer pairs produced polymorphic alleles between 7 and 9, The remaining 17
primers generated less than 7 alleles and showed lower level of polymorphism.
The mean diversity index (DI) value of 49 SSR markers ranged from 0.60 to
0.95. The SSR markers with higher DI value lead to lower allelic frequency. Most
likely, a marker is more useful to detect polymorphism if it generates large number
of alleles with high DI value. P-90 showed higher DI value and 20 polymorphic loci
out of 21, followed by P-100 with 15 detectable alleles out of 15, P-137 with 10
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polymorphic alleles out of 10 and mSSCIR58 with 11 polymorphic alleles out of 14.
These SSR markers generated large number of polymorphic alleles.
Polymorphic information content (PIC) value of 49 SSR primer pairs tested
ranged from 0.174 (P-114) to 0.728 (P-89) with a mean of 0.33. Only one marker, P-
89, showed a greater PIC value (0.728). Nine markers showed PIC values of almost
0.4 and the other markers generated PIC values of 0.3 or less. The markers that
revealed greater PIC values and generated large number of polymorphic alleles
differentiated a large number of genotypes than SSR markers with higher PIC values
but that generates fewer polymorphic alleles. Out of 9 markers that showed PIC
values of almost 0.4, only four markers viz; P-101, mSSCIR43, mSSCIR66 and
SMs009 generated more than 90% polymorphic alleles.
Cluster analysis grouped twenty adopted sugarcane genotypes into four main
clusters (I, II, III and IV) at 70% homology level (Fig. 3.1). Pairwise similarity
coefficient values ranged from 64% (S-03-SP-93) to 88% (S-08-FSD-19 and HSF-
240). Cluster-I contained nine genotypes. Cluster-I can be further partitioned into
three sub-groups i.e., (Ia), (Ib) and (Ic). Sub-cluster (Ia) contained four genotypes
viz; HSF-242, SPF-213, CPF-237 and BF-162 at 73% homology. Sub-group (Ib)
included three genotypes viz; S-03-US-694 and S-05-FSD-307 at a level of 75%
similarity. Sub-cluster (Ic) consisted of only two genotypes at a level of 74%
similarity. Cluster-II included genotypes four genotypes namely; S-06-US-272, S-
03-US-127, S-06-US-658 and S-03-US-778. Cluster-III contained six genotypes.
This cluster can be further grouped into three sub-clusters i.e, (IIIa), (IIIb) and (IIIc).
Sub-cluster (IIIa) consisted of only one genotype (S-05-FSD-317) at 70% similarity
index. Sub-cluster (IIIb) had two genotypes (SPF-232 and LHO-83153) and they
share 75% similarity. Sub-cluster (IIIc) contained three genotypes viz; S-08-FSD-
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23, S-08-FSD-19 and HSF-240 at almost 78% similarity, while within the same
cluster two genotypes S-08-FSD-19 and HSF-240 shared 88% similarity. Cluster-IV
contained only a single genotype, S-03-SP-93.
The data generated from 20 sugarcane genotypes on the basis of SSR
polymorphic loci was also subjected to Principal Coordinate Analysis (PCoA) for
conformation of results generated from cluster analysis (Fig.3.2). The first four
PCoA showed eigenvalues >0.1 (Table. 3.4) following the Simpson similarity index.
Eigenvalue >0.1 is considered as significant. First four coordinates; generated total
50.1% variability, to which PCoA-1 and PCoA-2 accounted 31% variability while
PCoA-3 and PCoA-4 generated 16% variability. Principal coordinate divided the 20
genotypes into 4 groups in a similar pattern as grouped in cluster analysis diagram
(Fig.1).
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Table 3.2: A description of 49 sugarcane microsatellite markers containing
primer names, melting temperature, PCR Product range (bp), No. of loci,
Polymorphic loci, % polymorphism, Polymorphic information contents (PIC),
Diversity Index (DI). S
. N
o
Pri
mer
Nam
e
Tm
(°C
)
PC
R P
rod
uct
ran
ge
(bp
)
No. of
loci
Poly
morp
hic
loci
Poly
morp
his
m (
%)
PIC
Div
ersi
ty I
nd
ex
(DI)
1 P-86 57 200-300 6 5 83.3 0.290 0.79
2 P-89 55 140-600 15 13 86.67 0.728 0.91
3 P-90 55 100-600 22 21 95.45 0.328 0.95
4 P-92 53 190-400 10 10 100 0.289 0.85
5 P-94 53 100-400 5 4 80 0.265 0.69
6 P-99 54 230-450 4 3 75 0.257 0.68
7 P-100 54 50-500 15 15 93.33 0.333 0.91
8 P-101 53 130-400 11 11 100 0.405 0.90
9 P-105 59 220-500 6 6 100 0.201 0.71
10 P-108 51 110-250 8 8 100 0.241 0.77
11 P-111 53 200-270 7 6 85.71 0.222 0.67
12 P-114 54 100-220 9 9 100 0.174 0.87
13 P-126 57 150-210 7 7 100 0.331 0.84
14 P-127 57 150-300 12 12 100 0.310 0.88
15 P-128 58 90-160 8 8 100 0.405 0.86
16 P-129 58 130-200 8 8 100 0.325 0.86
17 P-132 60 180-200 3 2 66.67 0.370 0.67
18 P-133 61 120-200 10 8 80.0 0.402 0.89
19 P-137 61 130-300 14 10 71.43 0.343 0.91
20 P-139 59 180-250 6 4 66.67 0.381 0.81
21 P-141 63 90-160 8 7 87.5 0.416 0.90
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22 P-142 60 120-250 11 11 100.0 0.421 0.91
23 P-143 62 160-210 5 4 80.0 0.364 0.77
24 SMC851 58 80-150 11 10 90.91 0.397 0.88
25 SMC 18SA 62 140-200 6 4 66.67 0.404 0.82
26 SMC1604SA 62 130-200 8 8 100.0 0.343 0.87
27 SMC7CUQ 60 175-300 6 6 100.0 0.268 0.77
28 SMC703BS 62 210-250 5 4 80.0 0.344 0.79
29 SMC24DUQ 64 120-200 9 8 88.89 0.272 0.87
30 SMC36BUQ 64 110-250 7 6 85.71 0.359 0.80
31 SMC119CG 58 140-220 9 8 88.89 0.389 0.86
32 SMC278CS 64 140-250 10 10 100.0 0.362 0.88
33 SMC334BS 64 120-250 10 9 90.0 0.234 0.84
34 SMC569CS 62 160-200 4 2 50.0 0.375 0.69
35 SMC597 64 150-200 6 6 100.0 0.322 0.79
36 SMC851MS 58 130-220 8 7 87.5 0.346 0.83
37 SMC1751CL 60 130-180 6 6 100.0 0.320 0.84
38 mSSCIR-3 60 170-300 9 9 100.0 0.328 0.85
39 mSSCIR17 60 230-350 8 7 87.5 0.306 0.83
40 mSSCIR24 59 250-380 6 5 83.33 0.399 0.77
41 mSSCIR-43 53 120-410 13 13 100.0 0.406 0.92
42 mSSCIR58 61 110-250 14 11 78.57 0.343 0.91
43 mSSCIR-66 58 125-180 6 6 100 0.446 0.83
44 mSSCIR78 54 100-220 7 6 85.71 0.353 0.83
45 SMs009 51 100-300 12 9 75.0 0.435 0.91
46 SMs012 58 150-800 7 6 85.7 0.200 0.60
47 SMs016 65 100-175 6 6 100 0.322 0.77
48 SMs032 53 100-500 11 10 90.9 0.224 0.80
49 SMs037 64 200-400 6 6 100 0.000 0.91
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Picture.3.1: Banding pattern of twenty adopted sugarcane genotypes by using
highly polymorphic SSR primer pair P-90
Note: PCR products were run on 2 % agarose gel. Number represents individual
sugarcane genotype as represented in Table 1.
Picture.3.2: Separation of PCR products of primer P-90 on PAGE gel.
Picture.3.3: PCR products of primer mSSCIR43 on PAGE gel.
Where,
1. HSF-242; 2. SPF-213; 3. CPF-237; 4. BF-162; 5. S-03-US-694; 6. S-06-SP-321;
7. S-05-FSD-307; 8. S-05-US-54; 9. S-06-US-300; 10. S-03-SP-93; 11. S-06-US-
272; 12. S-03-US-127; 13. S-06-US-658; 14. S-03-US-778; 15. S-05-FSD-317; 16.
SPF-232; 17. LHO-83153; 18. S-08-FSD-23; 19. S-08-FSD-20. HSF-240.
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Picture.3.4: PCR products of primer P-89.
Picture.3.5: PCR products of primer P-100.
Picture.3.6: PCR products of primer P-101.
Where,
1. HSF-242; 2. SPF-213; 3. CPF-237; 4. BF-162; 5. S-03-US-694; 6. S-06-SP-321;
7. S-05-FSD-307; 8. S-05-US-54; 9. S-06-US-300; 10. S-03-SP-93; 11. S-06-US-
272; 12. S-03-US-127; 13. S-06-US-658; 14. S-03-US-778; 15. S-05-FSD-317; 16.
SPF-232; 17. LHO-83153; 18. S-08-FSD-23; 19. S-08-FSD-20. HSF-240.
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Picture.3.7: PCR products of primer P-137.
Picture.3.8: PCR products of primer SMs037.
Picture.3.9: PCR products of primer SMs009.
Where,
1. HSF-242; 2. SPF-213; 3. CPF-237; 4. BF-162; 5. S-03-US-694; 6. S-06-SP-321;
7. S-05-FSD-307; 8. S-05-US-54; 9. S-06-US-300; 10. S-03-SP-93; 11. S-06-US-
272; 12. S-03-US-127; 13. S-06-US-658; 14. S-03-US-778; 15. S-05-FSD-317; 16.
SPF-232; 17. LHO-83153; 18. S-08-FSD-23; 19. S-08-FSD-20. HSF-240.
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Table. 3.3: Similarity coefficient matrix among 20 sugarcane genotypes obtained by Jaccard’s similarity coefficient using
NTSYS-pc V 2.1.
HSF-2
42
SPF-213
CPF-237
BF-162
S-03-U
S-694
S-06-S
P-321
S-05-F
SD-307
S-05-U
S-54
S-06-U
S-300
S-03-S
P-93
S-06-U
S-272
S-03-U
S-127
S-06-U
S-658
S-03-U
S-778
S-05-F
SD-317
SPF-232
LHO-8
3153
S-08-F
SD-23
S-08-F
SD-19
HSF-2
40
HSF-242 1.00
SPF-213 0.78 1.00
CPF-237 0.73 0.76 1.00
BF-162 0.71 0.74 0.79 1.00
S-03-US-694 0.70 0.73 0.73 0.74 1.00
S-06-SP-321 0.67 0.69 0.74 0.74 0.76 1.00
S-05-FSD-307 0.69 0.70 0.70 0.71 0.74 0.77 1.00
S-05-US-54 0.74 0.74 0.75 0.71 0.71 0.71 0.72 1.00
S-06-US-300 0.68 0.67 0.68 0.69 0.69 0.69 0.72 0.74 1.00
S-03-SP-93 0.64 0.60 0.63 0.65 0.63 0.63 0.67 0.66 0.70 1.00
S-06-US-272 0.72 0.69 0.68 0.69 0.69 0.71 0.72 0.70 0.73 0.68 1.00
S-03-US-127 0.69 0.66 0.66 0.67 0.64 0.68 0.71 0.66 0.70 0.66 0.77 1.00
S-06-US-658 0.69 0.70 0.70 0.69 0.67 0.71 0.69 0.69 0.69 0.65 0.76 0.76 1.00
S-03-US-778 0.70 0.68 0.72 0.69 0.67 0.72 0.70 0.69 0.69 0.66 0.72 0.70 0.76 1.00
S-05-FSD-317 0.68 0.67 0.68 0.69 0.65 0.68 0.69 0.70 0.66 0.61 0.70 0.66 0.71 0.73 1.00
SPF-232 0.68 0.67 0.70 0.67 0.69 0.69 0.71 0.68 0.67 0.62 0.77 0.69 0.72 0.73 0.73 1.00
LHO -83153 0.66 0.68 0.68 0.69 0.70 0.67 0.69 0.68 0.69 0.65 0.73 0.66 0.71 0.70 0.70 0.76 1.00
S-08-FSD-23 0.63 0.64 0.64 0.66 0.67 0.63 0.71 0.65 0.65 0.61 0.69 0.64 0.64 0.66 0.67 0.73 0.76 1.00
S-08-FSD-19 0.68 0.68 0.68 0.67 0.68 0.68 0.73 0.70 0.64 0.62 0.71 0.65 0.69 0.65 0.68 0.71 0.75 0.79 1.00
HSF-240 0.69 0.70 0.68 0.70 0.70 0.69 0.74 0.70 0.65 0.61 0.69 0.65 0.70 0.66 0.72 0.70 0.75 0.77 0.88 1.00
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Fig. 3.1: A hierarchical homology tree constructed by the NTSYSpc (V2.0)
software indicating the similarity coefficient (%) among 20 sugarcane
genotypes (Saccharum officinarum L.).
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Table. 3.4: Principal Coordinate Analysis for 20 sugarcane genotypes from
SSR marker data.
Axis Eigenvalues Variance percentage Cumulative percentage
1 0.21* 17.78 17.78
2 0.16* 13.63 31.40
3 0.12* 10.24 41.64
4 0.10* 8.77 50.42
5 0.09NS 7.29 57.71
6 0.07 NS 6.31 64.02
7 0.06 NS 5.51 69.53
8 0.06 NS 4.94 74.47
9 0.06 NS 4.86 79.32
10 0.05 NS 3.86 83.18
11 0.04 NS 3.09 86.28
12 0.03 NS 2.75 89.02
13 0.03 NS 2.23 91.25
14 0.02 NS 2.02 93.27
15 0.02 NS 1.41 94.68
16 0.01 NS 0.85 95.53
17 0.01 NS 0.43 95.96
18 0.00 NS 0.11 96.07
19 0.00 NS 0.00 96.07
20 0.00 NS 0.00 96.07
*Significant NS Non-significant
Fig.3.2: Principal Coordinate Analysis (PCoA) diagram of the first two axes
(PCoA1 and PCoA2) for 20 sugarcane genotypes.
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3.4.2. DISCUSSION
Intention of this discussion is to evaluate the suitability of SSR markers used
and identification of genetically diverse genotypes from the material under survey.
3.4.2.1. POLYMORPHISM PERCENTAGE AND SSR LOCI
A total of 420 SSR alleles were identified with a mean polymorphism of
89.12% estimated for all markers. A range of loci from 50 to 280 were obtained by
Cardeiro et al., (2003); Glynn et al., (2009); Mishra et al., (2010); Silva et al., (2012);
Devarumath et al., (2012) and Hameed et al., (2012) by using SSR markers. Our
results are in comparison with the overall findings of (Cardeiro et al., 2003; Glynn
et al., 2009; Silva et al., 2012; Hameed et al., 2012) with respect to average number
of alleles generated by individual markers. SSR primer pairs viz; P-89, P-90 and P-
100 generated more than 15 polymorphic alleles and found best for genotyping
sugarcane clones.
3.4.2.2. DIVERSITY INDEX (DI)
Diversity index (DI) values indicated allelic frequency of SSR microsatellite
alleles. If the DI value is low it means polymorphic alleles only exists in fewer
genotypes and vice versa. Most probably, a marker is more feasible to identify in a
genotype if it generates large numbers of alleles with high diversity index (Chen et
al., 2009). Number of alleles and DI value play an important role in the molecular
distinctiveness of any genotype. DI values ranged from 0.60 to 0.95 were clculated.
Eleven primers, namely P-89, P-90, P-100, P-101, P-137, P-141, P-142, mSSCIR43,
mSSCIR58, SMc009 and SMs037 revealed DI values more than 0.9 (Table 3). This
reflects the general usefulness of 11 SSR markers.
3.4.2.3. POLYMORPHIC INFORMATION CONTENT (PIC)
Polymorphic information content (PIC) is a measure of the relative
information content of a marker that indicates whether markers are useful in
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determining polymorphism in germplasm (Cordeiro et al., 2003). The term
polymorphism information content (PIC) term was originally introduced into human
genetics by Botstein et al., (1980) which refers to the value of a marker system that
detects polymorphism(s) within a population. It generates information about the
number of identifiable alleles and the distribution of their occurrence (Ni et al.,
2002). PIC measures the extent of a marker system to differentiate among genotypes
(Weir 1990). PIC values of SSR markers used in our study ranged from 0.174 to as
high as 0.728. The work of several scientists indicated that PIC values varied for
SSR markers used in sugarcane, (Cordeiro et al., 2000; Singh et al., 2008; Creste et
al., 2010) recorded PIC values ranged from 0.55-0.88. Cordeiro et al., (2000) and
Creste et al., (2010) reported a very little value for PIC. These differences are might
be due to the type of germplasm used, small set of genotypes as well as the method
of detection. Irrespective of the coincidence, PIC values for any SSR marker are not
static but give the reference for the capacity to detect variation.
3.4.2.4. CLUSTER AND PRINCIPAL COORDINATE ANALYSIS
Cluster analysis grouped 20 genotypes into 4 clusters at 70% homology level
(Fig.1). Cardeiro et al., (2003) grouped sugarcane genotypes into two clusters at 37%
genetic similarity index by using SSR markers. Our results are similar to the findings
of Chen et al., (2009); Glynm et al., (2009); Singh et al., (2010); Hameed et al.,
(2012) and Devarumath et al., (2012). However, Cardeiro et al., (2003) and Silva et
al., (2012) reported less genetic similarity. Sugarcane share many of the same
genomic regions (Cordeiro et al., 2001; Pinto et al., 2006; Glynn et al., 2009; Duarte
et al., 2010), which may affect the efficiency of molecular markers to differentiate
genotypes. The presence of genetic similarity (GS) or homology in the germplasm
means less genetic diversity and vice versa. However, due to the occurrence of very
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80
unique patterns of sexual reproduction, sporadic flowering responses in different
agro-climatic conditions, self-incompatibility mechanisms, less chance of
transgressive segregation, clonal propagation and evolution of Saccharum
officinarum L. from few common ancestors are the common factors that lead
cultivated sugarcane to have less genetic divergence. Cluster-VI contains only single
genotype S-03-SP-93 with 64% genetic similarity as compared to the other
genotypes tested. This is an outlier with broad genetic background and can be used
for hybridization programme. Unfortunately, this genotype did not flower at our
experimental site (Arja, Azad Kashmir, East 73.97°-42 minutes, North 33.97°- 21
minutes, Altitude 797m above sea level) while genotypes S-08-FSD-19 and HSF-
240 showed 88% homology. Genotypes derived from their respective region grouped
in the same clusters due to their common genetic base. In general it can be suggested
here that genotypes grouped in Cluster-I (CPF-237 and BF-162) and Cluster-III (S-
05-FSD-317, S-08-FSD-19 and HSF-240) have higher genetic distance and
relatively less homology and these genotypes can be used for future hybridization
programmes but unfortunately genotypes in Cluster-I (CPF-237 and BF-162) did not
flower under local natural conditions according to author’s personal assessment.
Fortunately, couple of genotypes from Cluster-I (S-05-FSD-307 and S-03-US-694)
and Cluster-III (S-05-FSD-317, S-08-FSD-19 and HSF-240) respond flowering at
Arja, Azad Kashmir. From Cluster-I genotype S-03-US-694 has high genetic
distance with S-08-FSD-19 and HSF-240 While S-05-FSD-307 has high genetic
distance with S-08-FSD-19 and HSF-240. These genotypes can be successfully
exploited for hybridization programme by automation of synchronization problems
in some genotypes under natural conditions.
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Principal coordinate analysis divided 20 genotypes into 4 groups almost in a
similar pattern as grouped in cluster analysis. Group-I contained 7 genotypes viz;
SPF-213, BF-162, S-03-US-694, S-06-SP-321, S-05-FSD-307 and S-05-US-54.
Most of these genotypes were the introduction from Sao Paulo Brazil and Canal
Point Florida USA, Group-II comprised 7 genotypes; HSF-242, S-06-US-300, S-03-
SP-93, S-06-US-272, S-03-US-127, S-06-US-658 and S-03-US-778. Group-III
consist of three genotypes; S-05-FSD-317, SPF-232 and LHO-83153 while Group-
IV have three genotypes; S-08-FSD-23, S-08-FSD-19 and HSF-240 and these
genotypes are adopted to Pakistan and made separate group having maximum
genetic distance with genotypes like S-03-US-694 and S-05-FSD-307 from Group-
I. Although, genotypes from Group-II and Group-I have high genetic distance but
genotypes from Group-1 did not respond flowering under local conditions. Principal
coordinate Analysis validated the results generated from cluster analysis.
3.5 CONCLUSION AND RECOMMENDATIONS
It can be concluded here that this study revealed SSR markers as reliable tool
for genotyping and diversity analysis in sugarcane. A considerable genetic diversity
obtained from material under surveyed by using SSR markers. Hierarchical cluster
analysis grouped genotypes into clusters. Principal Coordinate Analysis depicted
50.1% variability in tested genotypes. Four diverse genotypes S-03-US-694, S-05-
FSD-307, S-08-FSD-19, S-08-FSD-23 and HSF-240) were identified that may
provide valuable breeding stock for future hybridization programme and pyramiding
beneficial genes in new sugarcane cultivars while retaining genetic diversity.
SOMACLONAL VARIATION
82
Chapter: 4
SOMACLONAL VARIATIONS
4.1 INTRODUCTION
Sugarcane is a highly polyploid crop with chromosome numbers in somatic
cells (2n) ranging from 80 to 124 in cultivated varieties and 48 to 150 in wild types
(Garcia et al., 2006). It is important industrial crop being used for energy production
(Tew and Cobill, 2008) in addition to sugar production. It is a photo-thermal
sensitive crop and flowering takes place at 5 to 23° latitude whereas Pakistan is
situated at 24 to 37° latitude. Other conditions required for changing the vegetative
to reproductive phase are; (1) Temperature range of 25 to 33°C for 70 days. (2) 70
to 80% humidity for 70 days. (3) Day length of 11.5 to 12.5 h for 70 days. For
breeding purposes, fuzz is imported from abroad because Pakistani breeders do not
have the ideal conditions for crossing and hybridization for varietal improvement
(Khan et al., 2004).
Worldwide, Pakistan ranks 5th in cultivated area and 15th in cane yield
(FAOSTAT, 2014). There is a big gap between ranking in cultivated area and cane
yield therefore, it is inevitable to find a way to narrow down this gap. Unfavorable
geo-climatic conditions for sugarcane flowering and viable seed production has been
a problem in Pakistan. Therefore, genetic improvement of sugarcane through
conventional breeding is hindered by low fertility. There are some biotechnological
tools such as genetic transformation and induction of somaclonal variations. By
genetic transformation we can improve qualitative or oligo-genic traits. Apart from
these, there are some biosafety rules and regulations related to anti-cis technology.
Hence, an alternative method such as In-vitro culture techniques for somaclonal
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variation induction and induced mutations are being employed to create the new
genetic variability for the selection of the desired genotypes (Yasmin et al., 2011).
Clones, are exact copies of the genotype from which its source tissue had
been obtained. Clonal propagation is done through tissue culture environment,
produces plant materials that are not exact copies of the original plant used to initiate
the culture. Such variation, which generated not from meiosis or normal sexual
process but from the culture of somatic tissue, is known to as somaclonal variation,
while the variants are denoted to as somaclones. Variation obtained through in-vitro
propagation are of two types one may be transient or epigenetic while other are
heritable or genetic in origin. Epigenetic variations or unstable and cannot be
transmitted to next generation. These changes are not due to alteration in DNA
sequences but may be suppression of regulatory sequences of a genes or masking of
open reading frame of a gene with chemicals used in tissue culture or by other
mechanisms. Tissue culture medium components may determine the chance for
heritable changes in the callus. Addition of auxin 2, 4-D in culture medium enhances
the probabilities of somaclonal variation induction (Acquaah, 2012). Improvement
of crops through somaclonal variation was first described by Heinz and Mee (1971).
Somaclonal variation can provide an alternative for improvement of existing
genotypes (Shahid et al., 2011). Various factors are responsible for somaclonal
variation which include karyotype changes, cryptic changes associated with
chromosome rearrangement, transposable elements, somatic gene rearrangements,
gene amplification and depletion, somatic crossing over and sister-chromatid
exchanges. Phenotypic variations among somaclones have been used as potential
tools for crop improvement. Such variations associated with changes in chromosome
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number have led the breeders to exploit it in crop improvement programs (Rakesh et
al., 2011).
First in-vitro raised somaclone of sugarcane, resistant to Fiji disease was
reported by Heinz, (1973). However, several studies have been reported the
improvement of commercially important crops via somaclonal variation. Gao et al.,
(2009) elaborated that somaclonal variation can be heritable in plant tissues raised
in-vitro, and provides window of opportunity for plant breeders to produce novel
variants in sugarcane. Various authors like (Shahid et al., 2011; Ali and Iqbal, 2012;
Seema et al., 2014 and Rastogi et al., 2015) reported the successful utilization of
somaclonal variation in sugarcane for genetic improvement of agronomic traits.
Patade et al. (2006) exploited somaclonal variation in sugarcane to develop
somaclones tolerant to higher salt stress. Wagih et al., (2004) regenerated
somaclones from embryogenic callus of sugarcane resistant to drought. Rastogi et
al., (2015) elaborated that somaclonal variation was successfully used for genetic
improvement in sugarcane against diseases (Red rot, Eye spot, downy mildew, Fiji
virus), drought tolerance, salt tolerance, sugar recovery, sugar contents and cane
yield etc. Red rot (Colletotrichum falcatum L.) and sugarcane mosaic virus (SCMV)
are very devastating sugarcane diseases in Pakistan. They cause very serious yield
losses in susceptible varieties. Somaclonal variation is a rapid and robust genetic tool
to improve the resistance mechanism of sugarcane against red rot and sugarcane
mosaic virus. Singh et al., (2000); (Acquaah, 2012); and Kumar et al., (2012)
reported the development of somaclones in sugarcane with improved agronomic
traits and resistant to red rot. Oropeza and Garcia (1996); Gaur et al., (2002) and
Smiullah et al., (2012) reported development of sugarcane mosaic virus free
somaclones.
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Assessment of genetic variability in tissue culture derived somaclonal
variants are helpful for plant breeders to select appropriate material for their breeding
program. Simple sequence repeat (SSR) markers are the most commonly used
molecular techniques to study polymorphism in sugarcane (Nair et al., 2002). For
this purpose, a range of statistical procedures following the molecular data are used
to assess the genetic distance and discrimination among genotypes. Principal
Coordinate Analysis (PCoA) of simple sequence repeats (SSR) data is instrumental
to find out genetic relationship among populations for breeding purposes (Reif et al.,
2003). Reif et al., (2003) successfully identified genetically identical germplasm by
using molecular markers data and suggested that PCoA is economical and solid
method for making breeding decisions. Polymerase chain reaction (PCR) based
molecular markers like RAPD, ISSR and SSR have been widely used marker system
for detection of somaclonal variation in various crops like sweet potato (Veasey et
al., 2008), rice (Gao et al., 2009), stone pine Pinus pinea L. (Cuesta et al., 2010),
Plantago ovata L. (Mahmood et al., 2012), Prunus. spp (Gargaro et al., 2012),
banana (Emma et al. 2014) and sugarcane (Seema et al., 2014).
Induction of somaclonal variation is a hit and trial method, along with
beneficial mutations, as there are equal chances of being conceiving deleterious
nucleotide changes in important growth and development candidate genes. Genetic
integrity of candidate genes is important to perform important metabolic pathways
for normal growth and development processes. Various molecular techniques are
routinely utilized for the detection of genetic integrity of somaclones like randomly
amplified polymorphic DNA (RAPD), simple sequence repeats (SSR), amplified
fragment length polymorphism (AFLP), restriction fragment length polymorphism
(RFLP) and methylation-sensitive amplified polymorphism (MSAP) (Coste et al.,
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2015). Several reports are available for the genetic fidelity of somaclones by using
molecular markers. Peyvandi et al., (2013) and Jagesh et al., (2013) reported the
utilization of ISSR and SSR marker to check the genetic stability of olive and potato
somaclones, respectively. Only few reports are available on nucleotide sequence
integrity of candidate genes in somaclones. Coste et al., (2015) reported the integrity
of lycopene gene’s nucleotide sequence in tomato somaclones and find a single
nucleotide change. Sugarcane (Saccharum officinarum L.) is a complex hybrid
contained chromosomes 2n=8X=80 making its genome more sophisticated. Various
efforts have been made to sequence its genome but multiple haplotype sequences
due to its various chromosome sets gathered from its various others species make it
difficult. So, its high ploidy level and heterozygosity nature is a challenge for modern
day high throughput short-read genome sequence technologies like Illumina Miseq
and Hiseq Sequencing. Express Sequence Taq (EST) is a good source of sugarcane
gene search, while sequence annotation of Sorghum bicolor’s genome, which is
closest diploid relative of sugarcane (S. spontaneum L.) that served as a key source
of sugarcane genomic studies (Zhang et al., 2013). However, PCR amplified 1kb
genomic DNA fragments can also be sequenced by using Sanger sequencing (Rizzo
and Buck, 2012).
Keeping in view of above mentioned studies an experiment was designed
with following objectives.
To create variability in sugarcane varieties by using somaclonal variations.
To assess the variability in somaclones with respect to their parent clones by
using SSR markers.
To assess the genetic integrity of candidate gene(s) in somaclones.
Field evaluation of S0 generation of somaclones under field condition for
agronomic traits and screening against sugarcane mosaic virus and red rot.
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4.3. REVIEW OF LITERATURE
Oropeza and Garc (1996) illustrated that sugarcane mosaic virus causes
severe yield losses to sugarcane. Resistant varieties developed by using conventional
methods takes between 10 and 15 years. Improvement of sugarcane by tissue culture
techniques are used as an aid for disease resistance. They developed two resistant
somaclones against Sugarcane Mosaic Virus by somatic embryogenesis from
susceptible sugarcane cultivars. They used indirect enzyme linked immunosorbent
assay (ELISA) to evaluate somaclones for the presence of the viral particles, and
reported that the leaves of resistant somaclones did not contain viral particles. It was
concluded that field performance of somaclones was similar to the mother plants.
Huber and Huber (1996) described that sucrose-phosphate synthase (SPS) is
the plant enzyme that play a vital role in sucrose biosynthesis. SPS is controlled by
metabolites and by reversible protein phosphorylation in photosynthetic and non-
photosynthetic tissues. They argued that regulation of the enzymatic action of SPS
seems to contain calcium, metabolites, and control of the protein phosphatase that
activates SPS. They also suggested that activation of SPS also happens during
osmotic stress in darkness that facilitate sucrose formation for osmoregulation.
Finally, they concluded that in vivo expression of manipulated SPS confirmed the
role of this enzyme in sucrose biosynthesis.
Singh et al., (2000) regenerated sugarcane somaclones using callus cultures
that showed broad variations for red rot resistance against four isolates of red rot
(Colletotrichum falcatum L.) Went. They tested 42 somaclones, out of which three
were found moderately resistant by using plug inoculation method. Rest of the
somaclones showed varying degrees of susceptibility. Most of the somaclones
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showed susceptibility against red rot pathogen when treated with red rot culture
suspension.
Sakamoto et al., (2001) isolated and characterized GA 2-oxidase 1 from rice
(Oryza sativa L.) and observed that expression of the OsGA2ox1 in transgenic rice
inhibited stem elongation and curtailed the development of reproductive organs.
They inferred from their results that OsGA2ox1 encodes a GA 2-oxidase that was
functional not only in-vitro but also in vivo as it was expressed in shoot tips and roots
but not in leaves and stems. They concluded that OsGA2ox1 controls bioactive GAs
in the shoot apex, so, decrease in its expression may lead to the early development
of the inflorescence.
Gaur et al., (2002) reported that sugarcane mosaic (SCMV) causes inter-
veinal chlorotic streaks on young leaves and thus affect sugarcane crop. They used
DAC-ELISA (direct antigen coating enzyme linked immunosorbent assay) for virus
detection in juice samples of infected cane stalk. Their results showed O.D values at
405 nm of leaf samples ranged from 0.016 to 1.24 while in juice samples O.D values
ranged from 0.059 to 1.083 were observed. They suggested that cane stalk juice was
equally suitable as virus infected leaf samples for screening of sugarcane samples
against sugarcane mosaic virus.
Wang et al., (2003) used central leaves of sugar cane for callus culture on MS
media fortified with different concentration of 2, 4-D like 1.5, 2.5, 3.5, 4.5, 5.5 and
6.5mg/L, respectively. Finally, they obtained best callus induction at MS medium
supplemented with 2.4-D at the rate of 2.5mg/L.
Ngezahayo et al., (2007) detected somaclonal variation in rice (Oryza sativa
L.) at the nucleotide sequence level by using Random Amplified Polymorphic DNA
(RAPD) and Inter-Simple Sequence Repeat (ISSR) followed by sequencing of
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selected bands that were responsible for genomic variability. They analysed calli and
their regenerated plantlets with 24 RAPD and 20 ISSR primers that depicted 20.83%
and 17.04% variability, respectively). They obtained two distinct groups by
conducting UPGMA cluster analysis on the basis of ISSR bands score derived from
somaclones. They concluded that sequence analysis designated a low level of
variation with single-base-pair (SNP) substitutions on selected PCR amplified
fragments.
Khan et al., (2007) used induced somatic mutation in sugarcane vegetative
setts using irradiation doses of 0, 10, 20, 30, and 40 Gy. They utilized RAPD markers
for variability assessment among mutants and found most similar (85%) sugarcane
mutants at 20 Gy, while most of the mutants that were raised from setts exposed to
30 Gy and their Parent showed less genetic similarity (38%).
Badawy et al., (2008) carried out an experiment to study the response of
sugarcane for callus induction on Murashige and Skoog (MS) media augmented with
3 mg/L 2,4 Dichlorophenoxyacetic acid (2, 4 D) and obtained best callus induction.
They obtained 82 to 100% callus induction recovery among sugarcane varieties used.
Veasey et al., (2008) used simple sequence repeat (SSR) markers to assess the
genetic diversity of 78 sweet potato (Ipomoea batatas L.) accessions and identified
eight SSR loci using polyacrylamide gels stained with silver nitrate. They subjected
the binary data (0 and 1) to principal coordinate analyses (PCoA) for genetic
dissimilarity analysis and recorded 58.2% variability within accessions.
Suprasanna et al., (2008) applied partial desiccation treatment to improve
plant regeneration response in irradiated in-vitro cultures. They exposed
embryogenic callus cultures of sugarcane to different doses of gamma radiation (0–
80 Gy) and radiation effect was evaluated in terms of post-irradiation callus
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recovery, growth and regeneration of plants. They found LD50 to be around 20–30
Gy and at higher doses, poor regeneration frequency was observed after 4–6 weeks
of post-irradiation culture. To stimulate regeneration response, they subjected
irradiated cultures to partial desiccation for 6 h and the treatment resulted in
enhanced plant regeneration.
Behera and Sahoo (2009) standardized protocol for induction of callus and
regeneration of plantlets through in-vitro culture using young meristem of Sugarcane
(Saccharum officinarum L. cv- Nayana) as an explant. They observed multiple shoot
regeneration at various frequencies by using different concentration and combination
of growth regulators. They found that highest percentage of callus induction in MS
medium supplemented with 2.5 mg/l, 2-4 D. The response was obtained in terms of
multiple shoot induction on MS medium with BAP 2.0 mg/l + NAA 0.5 mg/l.
Profuse rooting was obtained by inoculating in-vitro shootlets on the half-strength
MS basal media supplemented with 3.0 mg/l NAA. Their results showed that
transplanted rooted shoots in the green house for hardening and their survival rate
was 90% in the field condition.
Rashid et al., (2009) optimized protocol for callus induction and regeneration
in sugarcane cultivar HSF-240. They took shoot tip as explant for callus induction
with 2. 4 D concentrations i.e. 2 mg/L and 3 mg/L supplemented in MS medium and
obtained maximum (80-82%) calli for both 2 mg/L and 3 mg/L. They used 1.0 mg/l
GA3 and 0.5 mg/L Kinetin to obtain optimum shoots length while maximum roots
length (3.5 mm) was obtained by using 1.0 mg/L IBA in MS media,
Gao et al., (2009) elaborated that somaclonal variation can be heritable in plant
tissues raised in-vitro, and provides window of opportunity for plant breeders to
produce novel variants. In their study they utilised 120 SSR markers in rice to analyse
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eight somaclonal mutants derived from seven different cultivars. Their results
depicted that some SSR markers in the rice genome detected higher number of
polymorphisms. They concluded that these results suggest multiple molecular
mechanisms being responsible for somaclonal variation in rice mutants derived from
tissue culture.
Kaur and Gosal (2009) applied gamma radiation on sugarcane callus for
creating mutation. They applied different levels of gamma radiation like 20Gy,
40Gy, 60Gy and 80Gy with the dose rate of 2500Gy/h for a range of time viz; 1 min
20 sec, 2 min 20 sec, 4 min 20 sec and 5 min 20 sec respectively. Later they
regenerated callus on MS + 4 mg/L 2, 4-D + 0.5 mg/L BAP in medium. Shoots were
regenerated from two-month-old calli on MS media containing BAP at the rate of
0.5 mg/L. They recorded percent shoot regeneration from calli irradiated with
gamma rays in the three varieties that were ranged from 90 to 93.8% at 20 Gy level,
83.3 to 87.5% at 40 Gy level, 30 to 36.4 % at 60 Gy level and 0 at 80 % Gy level.
Zhang et al., (2009) utilized the Inter Simple Sequence Repeat (ISSR) markers
to investigate the genetic stability of a medicinal plant Jewel Orchids (Anoectochilu
formosanus) propagated in-vitro. They performed cluster analysis to assess genetic
similarity that was recorded more than 94% and the polymorphism of 2.76%. They
concluded that A. formosanus clones showed high genetic fidelity after in-vitro
propagation.
Mhamdi et al., (2010) described the plant catalase genes and their function in
Arabidopsis. They presented original data on Arabidopsis catalase single and double
mutants as model to examine the consequences of increase in intracellular H2O2.
They used catalase-deficient plants to investigate the metabolizing pathways of
reductive H2O2. They also observed the high pathogenesis response in catalase
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deficient lines. It was concluded that variations in catalase activities in plants
affected plant responses to variations in biotic or abiotic challenges.
Gopitha et al., (2010) conducted micropropagation studies on callus induction
of sugarcane and used various concentration of 2, 4-D, auxin, cytokinin, sucrose at
different pH level in MS media. They observed best callus induction at 3.0mg/L 2,
4-D with 10% coconut milk, regeneration of shoot on MS medium supplemented
with IBA 0.5mg/L and BAP 1 mg/L while roots were obtained on MS media fortified
with 3 mg/L NAA and 5% sucrose.
Tarique et al., (2010) conducted an experiment to develop protocol for
micropropagation of sugarcane. They used leaf sheath as explant for callus formation
and shoot development. They used Murashige and Skooge (MS) fortified with
different concentration of NAA and 2, 4-D. They observed best callus induction from
two sugarcane varieties at 4.0 mg/L 2, 4-D and one variety at 3.0 mg/L of 2, 4-D
contained in MS media while shoot initiation and multiplication was done best at 1.0
mg/L BAP plus 0.5 mg/L NAA. NAA showed better root initiation than IBA. They
successfully transferred plantlets to soil with 80 to 90 percent survival rate.
Cuesta et al., (2010) applied Inter Simple Sequence Repeat (ISSR) and
randomly amplified polymorphic DNA (RAPD) for detection of somaclonal
variation in micropropagated plantlets of stone pine (Pinus pinea L.). They tested
130 primers and amplified 178 bands ranged from 2.47 (ISSR). They detected almost
no somaclonal variation within the clones and they concluded ISSR showed
monomorphic banding pattern, while RAPD markers showed some extent of
variability.
Shahid et al., (2011) developed somaclones from sugarcane. They used two
types of explants, leaf and pith, and two growth hormones 2, 4-D and IAA. Their
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findings showed that leaves as explants with 3.0 mg/L 2,4-D supplemented in MS
media gave the best results for callus induction and proliferation while half-strength
Murashige and Skoog medium with 1.5 mg/L IAA proved to be the best media for
rooting. They assessed genetic variability in somaclones using SSR marker detected
67% polymorphism while polymorphic information content (PIC) value ranged from
0.06-0.47. They concluded that somaclonal variation of sugarcane varieties is
adequate to conduct selection.
Studer et al., (2011) transferred a transposable element (Hopscotch) in a
regulatory region of teosinte branched1 (TB1) in maize that acts as an enhancer of
gene expression and observed increased apical dominance in maize as compared to
its progenitor, teosinte.
Suo et al., (2012) explained that gibberellic acids (GAs) are plant hormones
that play major roles in processes of plant growth and developmental. They produced
transgenic soybean plants containing Arabidopsis DREB1A gene driven by the
CaMV 35S promoter and showed that the transgenic soybean plants revealed as GA-
deficient mutants with severe dwarfism, small and dark-green leaves, and late
flowering compared to wild type plants. They recovered phenotype with normal
stature by the application of exogenous GA3 once in a week. They performed
quantitative PCR analysis and revealed that the transcription levels of the GA
synthase genes were high in the transgenic soybean plants as compared to controls.
Ali and Iqbal (2012) worked with sugarcane cultivar HSF-240 for callus
induction and proliferation to different factors effecting callus cultures and found
that leaf disc segments of 1.0-2.0 mm thickness produced more amount of
embryogenic callus as compared to 3.0 mm or more thick discs. They studied that
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temperature range from 24°C to 30oC had been found to make no difference in callus
induction and particularly callus proliferation.
Smiullah et al., (2012) performed Enzyme linked immunosorbent assay
(ELISA) to evaluated somaclones regenerated from sugarcane variety HSF-240
against sugarcane mosaic virus (SCMV). They evaluated a total of 26 parental plants
and 64 somaclones. They isolated ten (10) somaclones with positive reaction to the
SCMV, 9 somaclones with mild reaction to virus and 45 somaclones were resistant
to virus.
Mahmood et al., (2012) used callus DNA to assess the somaclonal variations
in Plantago ovata L with the Random Amplification of Polymorphic DNA (RAPD)
markers. The maximum callus growth was observed in Murashige and Skoog (MS)
medium containing 4 mg/L 2, 4-D for shoot initiation and 2 mg/L for roots. They
observed maximum genetic variability in the DNA samples of callus at the
concentration of 2 mg/L 2, 4-D for all explants. Cluster analysis was based on
similarity coefficient and Numerical Taxonomy and Multivariate Analysis System
(NTSYS) PC version 2.01. They concluded that Random Amplified Polymorphic
DNAs was successful to assess polymorphism among callus and this study was
useful for the production of callus from Plantago ovata and estimation of genetic
variability due to tissue culture. Finally, they inferred that new genetic variability in
somaclones can bring vital insight for plant improvement.
Gargaro et al., (2012) determined somaclonal variation in Prunus. spp using
RAPD and SSR markers from one-year old plants leaves in comparison to the in vivo
maintained parental plant. They score reproducible PCR fragments to determine
genetic similarity on the basis of Dice similarity index by using UPGMA clustering
method. They obtained genetic variability among the somaclones from each variety.
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Kumar et al., (2012) studied the Red rot behaviour of 50 sugarcane
somaclones by inoculation using four strains of red rot (Colletotrichum falcatum L.).
The four somaclones were found moderately resistant (MR) according to 0–9 scale
method of scoring disease reaction. They concluded that the somaclones developed
were higher in resistance against red rot than the donor clones.
Abdullah (2013) utilized molecular markers for assessment of somaclonal
variation in sugarcane were somaclones. They amplified thirty (30) DNA fragments
with fifteen (15) SSR primer pairs among the sugarcane somaclones and their
parental clones. They found eleven (11) polymorphic bands and nineteen (19)
monomorphic bands. It was concluded that SSRs were useful molecular tools for
identification of somaclonal variation and the association between parents and their
somaclones.
Srinath and Jabeen (2013) developed a protocol for callus induction and
regeneration in sugarcane. Callus induction was done from leaf sheath explants
raised on MS medium containing different hormones viz, 2, 4-D, BAP and NAA.
They obtained callus on MS media containing 1 mg/L 2, 4-D, 2% sucrose and 300
mg/L PVP. Regeneration of calli were done on MS medium supplemented with
2mg/L Kinetin and 1mg/L BAP and recovered 100% calli regeneration. They
initiated root by using 5 mg/L, transferred plant to polythene bags filled with a
mixture of sterilized black soil and sand (1:1) for hardening. After hardening they
shifted plats to greenhouse and recorded 90% survival percentage.
Yadav and Ahmad (2013) standardized the protocol for callus induction and
shoot regeneration in sugarcane. They obtained best callus induction at 3.0 mg/L of
2, 4-D supplemented in MS media. They found best shoot formation response on
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MS medium containing 0.5 mg/L Kinetin, BAP and NAA each. They used half
strength MS media supplemented with 3mg/L NAA.
Peyvandi et al., (2013) checked the genetic stability of olive somaclones by
using 6 microsatellite markers (SSR) and detected total 14 alleles with an average
number of 2.33 alleles per locus. By doing UPGMA cluster analysis they obtained
variability between two cultivars but when they applied different concentrations of
Cu the micropropagated plants of each cultivar showed genetic stability and that
were similar to the parental plant.
Jagesh et al., (2013) studied the genetic stability of in-vitro generated potato
microtubers by using simple sequence repeat (SSR). During their study they used 12
SSR and produce 96 SSR bands. By doing cluster analysis they revealed 100 %
genetic similarity among parental plant and its somaclones within the clusters by
SSR. For confirmation of these results they performed Principal Component
Analysis (PCA) that also plotted parental plant and somaclones together in plot. They
concluded that SSR markers were reliable to detect genetic stability of in-vitro
conserved potato microtubers.
Seema et al., (2014) created genetic variability in sugarcane by doing tissue
culture in MS media supplemented with 2,4 D. They raised embryogenic calli in MS
media containing MS basal media + Kinetin (2mg/L) + IBA (2mg/L) + IAA (2mg/L).
After shooting and rooting, hardening and acclimatization of somaclones in the field
they isolated DNA from leaves and RAPD primers were applied to detect the genetic
variation between parents and somaclones. They obtained highest similarity between
BL4 parent and BL4 somaclone (96%) and minimum similarity between NIA-98
parent and AEC82-1026 somaclone (69%).
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Viehmannova et al., (2014) investigated somaclonal variation in 6
somaclones of yacon (Smallanthus sonchifolius L.) raised from in-vitro somatic
embryogenesis by using simple sequence repeat (ISSR) markers. They obtained
number of bands for each primer ranging 3 to 10 with an average of 6.95 bands per
ISSR primer. They identified eight primers that were polymorphic in nature and
generated 10 polymorphic bands having 7.19% mean polymorphism. They recorded
genetic distance according to Jaccard's similarity coefficient ranging from 0.020 to
0.163. They concluded that somatic embryogenesis was best approach to widen
genetic variability and improvement of yacon especially when normal sexual
reproduction hinders conventional methods of breeding.
Emma et al., (2014) created somaclonal variation in banana by
supplementing 2, 4-D in MS media. They utilised molecular markers (SSR) to
detect somaclonal variation. They suggested that somaclonal variation was in
fact, due to frequent subculture and high level of 2, 4-D concentration. By using
simple sequence repeats (SSR), one can obtain considerable amount of
polymorphism in somaclones. They concluded that SSR can be a key tool to find
out somaclonal variation.
Nayak et al., (2014) performed an experiment to screen two group of
sugarcane S. officinarun L. and S. spontaneum L. accessions with 36 microsatellite
markers and recorded 209 alleles. They recorded that genetic diversity ranged from
0 to 0.5 with an average of 0.304. By performing principal coordinate analysis
(PCoA) they revealed three clusters with all S. spontaneum genotypes in one cluster,
S. officinarum and Saccharum hybrids in another cluster while mostly non-
Saccharum spp. in the third cluster.
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Lee et al., (2014) described that gibberellin (GA), a plant hormone, is
responsible in many aspects in vegetative and reproductive phases of plant growth
and development. Gibberellin (GA2-oxidase) performs a vital role in the gibberellin
catabolic pathway to reduce bioactive gibberellins. They synthesized transgenic
Arabidopsis plants expressing GA2-oxidase 4 (AtGA2ox4) and found that transgenic
plants showed a dominant semi-dwarf stature with a reduction of bioactive GA up to
two-times as compared to control plants. By application of bioactive GA3 they
recorded increased shoot length that indicated that the GA signalling pathway were
functioned normally in transgenic plants.
Su et al., (2014) reported that Catalase avoid oxidative damage by scavenging
reactive oxygen species (ROS) to avoid oxidative damage. In sugarcane, they
suggested that catalase enzyme have a positive correlation with biotic and abiotic
stresses. They used cDNA sequence of Gene Bank Accession No. KF664183 to
come to know the function of catalase, from S. scitamineum infected sugarcane. They
predicted that ScCAT1 encode 492 amino acid residues and high expression of
ScCAT1 in recombinant E. coli cells under salt stresses showed high tolerance. They
obtained high relative expression of CAT1 in sugarcane buds and moderate in stem
epidermis in S. scitamineum tolerant plants. Finally, they concluded that ScCAT1 in
involved in the defence mechanism of sugarcane against reactive oxygen species and
positive response to biotic stresses like S. scitamineum.
Vandenbroucke et al., (2015) conducted an experiment to assess genetic
variation in Kava (Piper methysticum) which is a major cash crop in the Pacific using
SSRs. They determined genetic structure using principal coordinate analyses
(PCoA). They found thirteen SSR primers were polymorphic with genetic distances
ranged from 0 to 0.65 with an average of 0.24 using SSRs. They revealed from
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molecular data that all noble cultivars were evolved by clonal selection and
represented distinguishing morphological traits. They finally concluded that SSR
markers were useful for kava diversity analyses.
Rastogi et al., (2015) described that plant micropropagation is a rapid multiplication
of new cultivars in short time. By using conventional techniques crop improvement
in sugarcane is difficult task due to obstacles in normal sexual reproduction and its
narrow genetic base. Somaclonal variations play a vital role in sugarcane genetic
improvement program. They deliberated that these variations are heritable like
mutation breeding and serve as genetic tool for improving a cultivar. They concluded
that somaclones were successfully used for improvement of qualitative and
quantitative parameters and molecular markers like SSR etc. are frequently used for
molecular genotyping of sugarcane.
Liu et al., (2015) illustrated that catalases (CAT) have important roles in the
defence mechanisms of plants like stress response, delay in aging and cellular redox
balance. They cloned CAT gene from sugarcane (S. officinarum L.) by designing
pair of specific primers by utilizing probe of sorghum cDNA sequence of catalase
gene (XM 002437586.1). They obtained two new sequences of CAT genes sequence
length 3816 bp, 3814 contained eight exons and seven introns, respectively. They
obtained 1532 bp cDNA length. They concluded that the proteins encoded by these
CDS showed high similarity with those of corn, rice and sorghum CAT cDNA
protein products.
Coste et al., (2015) conducted an experiment to study the genetic integrity of
tomato (Lycopersicon esculentum Mill.) genotypes by following amplified fragment
length polymorphism (AFLP) by utilising 4 primers and sequencing of lycopene β-
cyclase gene (LCY-B) assays from leaves. They inferred from AFLP data that
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100
genetic dissimilarities between in-vitro derived somaclones from cryopreserved
tissues were similar as compared with the non-cryopreserved controls. They
identified single nucleotide polymorphism (SNP) G→T transversion. It was
concluded that sequencing of LCY-B gene from leaves showed no genetic change
after in-vitro regeneration.
Nikam et al., (2015) used gamma ray (10 to 80 Gy) at a dose rate of 9.6 Gy/min
on sugarcane embryogenic callus cultures. They observed 50–60% regeneration of
irradiated callus under salt (NaCl) stress, and later they acclimatized somaclones in
the greenhouse, recorded 80–85% survival. They raised a total of 138 irradiated and
salt-selected somaclones, grown to maturity and their agronomic attributes were
evaluated, of which 18 mutant somaclones were selected on the basis of different
agro-morphological characters. They observed that some somaclones exhibited
improved sugar yield and brix percentage. They concluded that radiation-induced
mutagenesis offers an efficient way to bring genetic variation in sugarcane.
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4.3. MATERIAL AND METHODS
4.3.1. INDUCTION OF SOMACLONAL VARIATION
4.3.1.1. PLANT MATERIAL
Plant material was collected from sugarcane field germplasm repository of
Sugarcane Research Institute; Ayub Agricultural Research Institute, Faisalabad
Pakistan. Six obsolete sugarcane varieties (S-03-SP-93, S-05-US-54, S-03-US-694,
S-06-US-300, HSF-240 and SPF-213) were selected. Tops of these varieties were
collected from mature plants during December-January 2012-13.
4.3.1.2. CALLUS INDUCTION
Experiment was conducted at Biotechnology Research Institute, AARI
Faisalabad. Explant were prepared in pre sterilized and disinfected laminar air flow
hood cabin by peeling off older leaves of tops and small round shaped meristem were
excised with heat sterilized surgical blade and immediately transferred to the test
tubes containing pre cool and autoclaved (120°C for 30 min) MS media (Murashige
and Skoog, 1962) with following composition; MS media (Phytochemicals™) 4.43
g, Gel Grow (Phytochemicals™) 1.75 g, 30 g sucrose, Iron 10 ml (100mg/100ml),
2, 4 D (100mg/100ml) 1 ml/L, 3 ml/L, 5 ml/L and control without 2, 4 D (2,4-
Dichlorophenoxyacetic acid) separately, d3H2O (deionized double distilled) water up
to 1000ml and pH 5.75. Sets of tubes containing different level of 2, 4 D
supplemented in media were wrapped with paper and kept at dark for 19 days at
incubation room contained 27°C temperature. All varieties responded for callus
induction at 2, 4 D level 3ml/L, calli were sub-cultured twice with the interval of
three weeks for somaclonal variation induction.
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4.3.1.3. REGENERATION AND PROLIFERATION
Embryogenic calli were transferred to test tubes containing regeneration
media; MS media (Phytochemicals™) 4.43 g, Gel Grow (Phytochemicals™) 1.75 g,
30 g sucrose, Iron 10 ml (100mg/100ml), 1 ml/L IBA (Indole-3-butyric acid
100mg/100ml), d3H2O up to 1000 ml and pH 5.75. Then tubes were kept in
incubation room at temperature 27°C and light intensity 1200 lux.
4.3.1.4. SHOOTING AND MULTIPLICATION
After 4 weeks regenerated tissues were transferred to shooting media
supplemented with Kinetin 1m/L instead of IBA for shoot initiation and
multiplication under similar condition as for regeneration and proliferation.
4.3.1.5. ROOTING AND HARDENING
Regenerated plantlets were then transferred to rooting media composed with
half strength MS media 2.21g, Iron 5 ml/L, sucrose 30g, Gel Grow 1.75 g, NAA
(naphthalene acetic acid 100mg/100ml) 1ml/L, d3H2O up to 1000 ml and pH 5.75.
Roots were initiated within five to six weeks. After root initiation plantlets were
transferred to polythene bags filled with canal silt and sand and kept under shade of
tree for hardening.
4.3.1.6. FIELD TRANSPLANTATION
Field was well prepared with tractor and then leveled with leveller, tranches
were made with trencher. Plant to plant distance was maintained 50 cm and line
spacing was kept 1 m. After six to eight weeks of hardening 224 survived
somaclones were transplanted in the field by cutting bottom and sides of polythene
bags during last week of March, 2014 at experimental area of Agricultural
Biotechnology Research Institute, AARI Faisalabad. Five sets of parental clone (six
inches long containing one node) of each variety from which somaclones were
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generated were also cultivated. Sides of field was covered by sowing setts of non-
experimental sugarcane plants. Urea was applied by broad cast method in the field
at the rate of 120 kg per hectare before field levelling. First irrigation was applied
immediately after transplantation. After one and half months of transplantation
hoeing was done. All the necessary cultural practices were done till the end of
maturity. No insecticide, fungicide or weedicide was applied.
4.3.2. SOMACLONAL VARIATION DETECTION WITH SSR MARKERS
Leaf samples were collected from two month old plantlets for DNA isolation
by using 0.5 g fresh young leaves according to the CTAB procedure of Doyle (1991)
with modifications at Genomic Lab of Agricultural Biotechnology Research Institute
Faisalabad (ABRI). Quantification of DNA was done by using a Nano Drop® ND-
1000 Spectrophotometer. From 300 µl stock DNA 1 µl was used to measure the
concentration at 260 nm wavelength and 20 ng/µl final concentration of DNA for
each sample was made for PCR amplification. Ten highly polymorphic SSR primer
pairs were selected for polymorphism and somaclonal variation detection (Table.
4.1). Polymerase chain reaction (PCR), agarose and polyacrylamide gel
electrophoreses were performed according to the procedures as mentioned in
material and methods of chapter 3. Gradient PCR were performed by using a range
of temperature for identification of optimum annealing temperature for each primer.
After finding appropriate annealing temperature for each primer pair PCR
amplification was done containing parental DNA samples and their somaclones and
then amplified fragments were run on agarose gel for separation. If any sample was
not amplified, repeated the PCR amplification for that sample and then PAGE gel
were performed for separation of smaller amplified fragments. Scoring of bands were
done by using 1 for presence of band and 0 was used for absence of band.
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Table 4.1: A description of 10 sugarcane microsatellite markers containing
primers names, forward and reverse primer sequences.
S. No Primer Name Forward Primer (5’→3’)
Reverse Primer (3’→5’)
1 P-89 AGAGAGAAAGAGAGGCGG
CTTCACGGAGCGAGAGAC
2 P-90 CTTCCACAACCAGAGCAG
GGAGACAGAGGCGAACAG
3 P-100 AACGCCTCCGACAGTGAG
CCGAGACCAACCAAGCAG
4 P-137 TGCCAGAAGTGGTTGTCCTCA
TTAAGAGACCCGCCTTTGGAA
5 SMC1604SA AGGGAAAGGTAGCCTTGG
TTCCAACAGACTTGGGTGG
6 SMC119CG AGCAGCCATTTACCCAGGA
TTCTCTCTAGCCTACCCCAA
7 SMC334BS CAATTCTGACCGTGCAAAGAT
CGATGAGCTTGATTGCGAATG
8 mSSCIR58 TGGTCTATCACTTAATCAGCAC
AGGCTACATGCTTACAGCCAT
9 mSSCIR-66 AGGTGATTTAGCAGCATA
CACAAATAAACCCAATGA
10 SMs009 TCATACAAGCAGCAAGGATAG
GAGCCGCAAGGAAGCGAC
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4.3.3. GENETIC INTEGRITY OF CANDIDATE GENES IN SOMACLONES.
This study was conducted at Centre of Integrative Legume Research (CILR),
School of Agriculture and Food Sciences (SAFS), University of Queensland (UQ)
St. Lucia campus, Brisbane Australia.
4.3.3.1. DATABASE SEARCH AND ANNOTATION OF CANDIDATE
GENES IN SORGHUM AND MAIZE
Sequences (sucrose phosphate synthase, GA2 oxidase, Catalase1 and
Cellulose synthase) from sorghum (Sorghum bicolor L.) and TB1 from Maize sub
spp. Teosinte were used to identify the exon regions of these genes in sugarcane
(Saccharum officinarum L.) BLASTn search at NCBI
(http://www.ncbi.nlm.nih.gov) and Phytozome 9.1 (http://www.phytozome.net)
were performed to find out similar sequences in sorghum genome against full length
CDS (complementary DNA sequences) sequences and ESTs sequences from
sugarcane at NCBI database.
4.3.3.2. VERIFICATION OF CANDIDATE GENES IN SUGARCANE
From genomic sequences of sorghum and maize selected candidate genes
intron and exon boundaries were identified and primers were designed from selected
larger exon region by using Primer 3.0 software and NCBI primer BLAST. Genomic
DNA of parental lines and their somaclones was isolated at Genomic Lab of
Agricultural Biotechnology Research Institute Faisalabad, Pakistan and taken to
CILR, SAFS University of Queensland Australia in pallet form contained in
centrifuge tubes where DNA was resuspended in ultra-pure water then Qubit
quantification was done for DNA concentration estimation. PCR reactions were
conducted in a total volume of 25 µl containing 20 ng template DNA, 0.5 µl of 10
mM forward and reverse primer each, Mango Taq™ polymerase 0.5 µl (1U/µl), 0.5
SOMACLONAL VARIATION
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µl reaction buffer provided with, Mango Taq™ polymerase kit, 50 mM MgCl2 2 µl,
25 mM dNTPs 0.5 µl, ultra-pure water 14.5 µl. PCR conditions were; 5 min at 95°C
followed by 35 cycles of 30 seconds at 94°C, 30 seconds annealing temperature
(50°C-68°C), 45 seconds at 72°C for extension and final extension after 35 cycle at
72°C for 6 min.
4.3.3.3. VERIFICATION OF PCR AMPLIFIED PRODUCTS
Amplified PCR products were run on 2% agarose (Sigma Aldrich™) gel.
Two different molecular size DNA ladders i.e. 100bp and 1kb (Thermo Scientific™)
were also run alongside PCR products to compare the band size with desired known
molecular weight for actual product identification. Sometimes gradient PCR was
conducted with a range of temperatures to find out appropriate annealing temperature
that produce clear and unambiguous band with ample quantity of desirable product.
4.3.3.4. AUTHENTICATION AMPLIFIED PRODUCTS WITH REFERENCE
SEQUENCES
After identification of desirable PCR fragment by comparison with molecular
weight marker desired bands were cut from agarose gel and eluted out by exposing
gel at low index UV trans illuminator in dark room. PCR products were then purified
using Silica gel PCR product clean-up system as described by (Boyle et al. (1995)
as described below.
4.3.3.5. SILICA BASED GEL PURIFICATION OF PCR PRODUCTS
Desirable bands of PCR products were cleaned up and purified by using the Silica
based protocol as described by Boyle et al., (1995) with few modifications.
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Components
1. Silica
Silica dioxide (Sigma S-5631)100 mg was mixed in 1 ml of d3H2O in a
centrifuge tube and left to settle overnight. Supernatant was removed and repeated
the process over two hours. Contents were stored at room temperature.
2. 6M Sodium Iodide (NaI)
To make 10 ml of 6M Sodium Iodide 9 gm sodium iodide powder was mixed
in 15ml falcon tube and then d3H2O was added to 10 ml line. Falcon tube was
wrapped and in tin foil and stored at 4°C.
3. Wash Buffer
For washing wash buffer was used that contained the following constituents;
a) 50mM Sodium Chloride (from 5M stock solution)
b) 10mM Tris HCl pH 7.5 (from 1M stock solution)
c) 2.5 mM EDTA (from stock 0.5M)
d) 50 % V/V Ethanol (Absolute molecular biology grade)
e) To make 50 ml wash buffer following recipe was used;
f) 0.5ml 5M NaCl
g) 0.5ml 1 M Tris HCl pH 7.5
h) 0.25 ml 0.5M EDTA
i) 25 ml ethanol (Absolute)
j) 23.75ml H2O
k) Contents were stored at -20 °C.
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PROCEDURE
a. PCR products were run through TAE agarose gel (pH 7.8).
b. Bands were excise from gel by using long wavelength UV light and placed
in sterile pre-weighed 1.5 ml microcentrifuge tube.
c. Added about 3X 6M sodium iodide to the gel slice and incubate at 50 °C for
5 minutes with hand shaking and mixing after every 2 minutes.
d. Silica was completely shaken and re-suspended before use then 15 µl silica
was added into each tube, mixed by hand and incubated at 50 °C for 5-10
minutes with gentle hand mixing after every 2 minutes.
e. Contents were centrifuged at 13000 rpm for 30 seconds.
f. Supernatant was removed completely.
g. Added 500 µl of ice chilled wash buffer. Pellet was broken up by pipetting
and pellet was completely re-suspended.
h. Centrifuged at 13000 rpm for 30 second and all wash buffer was removed.
i. Steps 7 and 8 were repeated for recovering DNA with sharp band.
j. To ensure the complete removal of wash buffer tubes were spun again and
pipette any remaining liquid off and tubes were left for air try for 10-15
minutes, but did not over dry.
k. Then 25 µl ultra-pure water was added in each tube and vortex to broken up
pellets and incubated at 50 °C for 5 minutes.
l. Contents were centrifuge for 5 minutes and supernatant containing purified
DNA bands were used for downstream applications.
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4.3.3.6. QUANTIFICATION OF PURIFIED PCR PRODUCT AND
SEQUENCING
Purified products were then DNA quantified by using 1 µl purified product
at Qubit™ fluorometry method. To reconfirm the actual band size, quality and single
allele of purified PCR product 5 µl purified samples were again run of 2% agarose
gel along with DNA ladders. If the purified product showed single allele with clear
bright and sharp band then sample were prepared for sequencing according to the
standard protocols of AGRF (Australian Genome Research Facility) Sanger
Sequencing. Sequencing samples containing 1 µl of forward primer (10mM) for
forward direction sequencing and ultra-pure water and purified PCR sample after
calculation with 12 µl final volume were put into 96 well plate and submitted to
AGRF for sequencing.
4.3.3.7. ALIGNMENT OF SEQUENCED READS WITH REFERENCE
SEQUENCES FOR CONFORMATION
Resulting sequenced reads were compared with reference sequences of sorghum
and maize by doing pairwise alignment using Geneious 6.1 software. Reads matched
with reference sequences were confirmed and primers for these sequences were used
for PCR amplification of our somaclone genetic integrity in comparisons with their
parental clone’s analysis.
4.3.4. SCREENING OF SOMACLONES AGAINST RED ROT (Colletotrichum
falcatum)
A total of 134 somaclones from six varieties were evaluated against red rot
in field by inoculation of red rot suspension culture. Potato dextrose agar (PDA)
containing 20 g agar, 20 g dextrose and 1 litter d3H2O medium was used to grow a
culture of red rot for inoculation. Inoculum was collected from infected plants stem
SOMACLONAL VARIATION
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and small pieces of stem cutting were spread over petri plate containing PDA
medium. After one week of infection spores of red rot pathogen were collected and
spread over the PDA culture medium for reaeration of red rot spores in large quantity.
Culture was suspended in 1 L distilled water shake well and then purified in a flask.
Inoculum containing 5 ml of red rot cell suspension was injected via syringe in 6
month old plants in the central stem of each in the middle of the internode. Scoring
of plant was done according to the scale from 0-9 given by Srinivasan and Bhat
(1961). Scale contained scoring (0-2.0) Resistant, (2.1-4.0) moderately resistant,
(4.1-6.0) moderately susceptible, (6.1-8.0) susceptible and (above 8.0) highly
susceptible.
4.3.5. SCREENING OF SOMACLONES AGAINST SUGARCANE MOSAIC
VIRUS (SCMV)
Serological examination of somaclones along with their parental clones were
conducted against sugarcane mosaic virus (SMCV) by using double antibody
sandwich, enzyme linked immunosorbent essay (DAS-ELISA) according to
procedure as described by Clark and Adam (1977). Reagents kit of DAS-ELISA a
product of Martin-Luther University, Germany with trade mark BIOREBA™ was
used for the detection of sugarcane mosaic virus (SCMV) that contained the
following components:
a) IgG
b) Conjugate
c) Positive control
d) Negative control
e) Extraction buffer (10X)
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f) Coating buffer
g) Conjugate buffer (10X)
h) Substrate buffer (5X)
i) Washing buffer
j) Substrate (pNPP)
k) Microtiter plate
4.2.5.1. BUFFERS FORMULATION
Ingredients provided in kit for making different buffers were utilized
according to following procedures.
a) Coating Buffer
One tablet provided in kit for making coating buffer was dissolved in 100 ml of
distilled water resulting in 50 mM carbonate-bicarbonate buffer (pH 9.6) containing
0.02% NaN3.
b) Washing Buffer
One pouched provided in kit for making wash buffer was dissolved in 500 ml of
double distilled water. The resulting buffer was a 10 mM phosphate buffer (pH 7.4)
containing 3 mM KCl, 140 mM NaCl and 0.05% Tween 20 (PBST) free from NaN3.
c) Extraction Buffer
A volume of 100 ml 10X concentrate extraction of buffer provided in kit was
made up to 1000 ml with double distilled water, resulted 20 mM Tris buffer (pH 7.4
at 25ºC), 3 mM KCl, 137 mM NaCl, 2% PVP, 0.05% Tween 20 and 0.02% NaN3.
d) Conjugate Buffer
A volume of 10 ml of 10X concentrate of conjugate buffer provided in kit was
made up to 100 ml with double distilled water resulted in 20 mM Tris buffer (7.4 at
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112
25ºC), 137 mM NaCl, 1 mM MgCl2, 3 mM KCl, 0.05% Tween 20, 2% PVP, 0.2%
BSA, and 0.02% NaN3.
e) Substrate Buffer
A volume of 20 ml of 5X concentrate of substrate buffer provide in kit was made
up to 100 ml with double distilled resulted in 1 M diethanolamine pH 9.8, containing
0.02% NaN3. Add one pNPP tablet (20 mg) per 20 ml buffer 15 min before use.
f) Substrate (pNPP)
Tablet containing 20 mg of pNPP (p-nitro-phenyl-phosphate) was used. One
tablet per 20 ml of substrate buffer is used to obtain a solution of 1 mg/ml.
4.2.5.2. PROCEDURE
Following steps were adopted for detection of sugarcane mosaic virus
(SCMV) in samples of somaclones and their parental clones.
a) Coating:
Specific antibody (lgG) that can adsorb to the surface of the microtiter plate
wells was diluted 1000 X in coating buffer; (i.e. 40 µl in 40 ml buffer, and 200 µl)
was added in each well of microtiter plate. Plate was covered tightly and was placed
in a humid box and then incubated at 4ºC overnight. After that wells were emptied
and washed 3-4 times with washing buffer, liquid was removed by blotting the plates
on tissue paper.
b) Extraction of plant extract
One gram of leaf sample was taken from leaf samples collected from five selected
somaclones generated from each six varieties along with one parental clone at
juvenile stage of plants and ground with mortar and pastel along with 1 ml extraction
buffer until leaf material converted into fine homogenize mixture and added in to
Eppendorf tube. Plant extracts were stored in refrigerator.
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c) Antigen: Incubation of plant extract.
Homogenize test samples were loaded in duplicate in the microtiter plate at the
rate of 200µl in each well. Positive and negative control of SCMV provided in kit
were also loaded. Plate was tightly covered and placed for incubation at 4ºC
overnight. After 24 hours, plate was washed with wash buffer 3-4 times.
d) Conjugate: Incubation of enzyme-labeled antibody.
Enzyme conjugate was diluted in 1000 x in conjugate buffer and 200µl was
added in each well in microtiter plate. Then plate was covered tightly and was
incubated at 30ºC for 5 hours. After that plate was washed 3-4 times with wash
buffer.
e) Substrate: Color reaction indicates infected samples.
p-nitrophenyl phosphate (pNPP) was dissolved at the rate of 1 mg/ml on substrate
buffer and 200 µl was added in each well. Then plate was incubated at room
temperature in dark and reaction was observed and read when yellow color was
developed after 2 hours. After that reading was taken at optical density (O.D) 405nm
on ELISA reader machine attached with computer and data was collected and export
in an Excel sheet. Mean of two replicates was calculated and mean graph was plotted
for samples comparisons.
4.3.6. FIELD PERFORMANCE OF M0 GENERATION OF SOMACLONES
After transplantation 134 plants were survived, of which 35 somaclones from
variety S-03-SP-93, 13 from S-05-US-54, 16 from S-03-US-694, 4 from S-06-US-
300, 28 from HSF-240, 25 from SPF-213 and 13 from S-05-US-54 (10 GY).
4.3.6.1. Data Collection
Data were recorded from five selected somaclones from each variety along
with their mother clones on the basis of following traits; plant height, number of
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tilers per plant, stem diameter, number of nodes, intermodal length, leaf area, brix
percentage and non-reducing sugar. Details of each parameter recorded as follows:
4.3.6.2. Plant Height (cm)
Plant height was recorded at maturity stage in centimetres from 5 selected
somaclones from each variety and their parental clones. Height of five tillers were
recorded from each somaclone and parental clone and average data was recorded.
4.3.6.3. Number of tillers per plant
Number of tillers were recorded from five somaclones from each variety and
their parental clones.
4.3.6.4. Stem girth (cm)
Diameter of mother stem at three places (base, middle and upper portion) five
tillers of each selected somaclone and their mother clones were recorded and average
was obtained.
4.3.6.5. Number of Nodes
Number of nodes of five tillers from each somaclones and their parental clones
was recorded and average was estimated.
4.3.6.6. Inter-nodal length (cm)
Inter-nodal length was recorded from five inter nodes of each five tillers of
selected plants and average data was taken.
4.3.6.7. Leaf Area (cm2)
Leaf area of five tillers of each selected plant was recorded in centimetre from three
places for width (cm) and average was then multiplied with length and then with
factor 0.72 according to (Sinclair et al. 2004).
Leaf Area = (length x width from three places) x 0.72
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4.3.6.8. Brix %age
Brix percentage was estimated from the juice extracted for each selected
plant at maturity by using the digital refractometer by putting a 2 to 3 drops of juice
on the lens of refractometer.
2.3.2.10. Non-Reducing Sugar contents
Non-reducing sugar was determined by using Benedict’s method (A.O.A.C.
1990). In this method sugarcane juice sample of 20 ml was taken in a beaker and 5
ml of 2% HCl was added and boiled for 30 minutes in a water bath. It was cooled
down and its pH was brought to 7.0 with NaOH (0.1N). Then it was titrated against
the 5 ml boiled Benedict’s reagent containing 2 g anhydrous sodium carbonate drop
by drop through burette and shaked until the colour was changed to brick red.
Volume of juice used in titration was recorded and finally calculations were
recorded as follows:
1 ml of juice used in titration = 2 mg of non-reducing sugar.
4.3.7. STATISTICAL ANALYSIS
Principal coordinates analysis (PCoA) of the SSR data obtained on the basis
of 1 for presence of band and 0 for absence of band was performed by using the
Simpson similarity index with PAST statistical software (Hammer et al., 2001).
Sequence alignments of candidate genes exon region of parental and somaclonal
lines were done by using Geneious® 6.0.6 software (Biomatters Ltd.).
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Chapter: 4
4.4. RESULTS AND DISCUSSION
4.4.1. DEVELOPMENT OF SOMACLONES
Present study was conducted to develop somaclones from 6 sugarcane
obsolete varieties namely; S-03-SP-93, S-05-US-54, S-03-US-694, S-06-US-300,
HSF-240 and SPF-213 (Fig.4.1). Calli induction of these varieties were done by
subjecting young meristem as an explant into Ms media supplemented with different
concentrations levels of 2, 4 D like; 0mg/L, 1mg/L, 3mg/L, 5mg/L and 7mg/L to find
out the most suitable 2, 4 D concentration for callus induction. A set of 20
contamination free test tubes containing explant in MS media supplemented with
above mentioned concertation kept at incubator in dark for 19 days to test the callus
induction responses and recovery percentage. Control showed no callus response
(Graph. 4.1) while callus induced at 1mg/L 2, 4 D concentration level showed callus
recovery percentage ranging from 10-20 percent for plant material used. At 3mg/L
2, 4 D concentration level, all varieties showed good callus response which ranged
from 70-90 percent. Three varieties; S-03-SP-93, S-06-US-300 and HSF-240
depicted 90 percent while S-05-US-54, S-03-US-694 and SPF-213 accounted 70%,
80% and 85% callus recovery, respectively. At 5mg/L 2, 4 D concentration level
callus recovery percentage ranged from 45 to 65 percent while for 7mg/L 2, 4 D
concentration level callus recovery percentage ranged from 20 to 55 percent. All
varieties used in this study showed excellent callus response and recovery percentage
on MS media supplemented with 3mg/L 2, 4 D. For induction of somaclonal
variations, two sets of calli from each variety were used, of which one set was sub-
cultured three times on MS media contained 3mg/L 2, 4 D and one set was subjected
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Fig 4.1: Schematic diagram of callus induction, sub-culturing and irradiation
callus for induction of somaclonal variation, regeneration, shooting, rooting,
hardening and field transplantation in sugarcane.
Explant selection
Six sugarcane varieties i.e S-03-SP-93, S-05-US-54, S-03-US-694, S-06-US-300, HSF-240, SPF-213
Callus induction by using different levels of 2,4 D in MS media
Control
1mg/L3mg/
L
Excellent callus response at 2,4 D level 3mg/L
Making two sets of calli from each variety
Gamma rays
10 Gy
100% mortality
S-05-US-54
survived
20 Gy
100% mortality
30 Gy
100% mortality
40 Gy 83.33%
mortality
Sub-culturing of calli with 3mg/L 2,4 D
First Sub-culture
Second sub-culture
Regeration with 1mg/L BAP
Shooting and multiplication with
1mg/L Kinetin
Rooting with 1mg/L NAA
Transfered plantlets in polythene bags
contaning river bank's soil
Hardening under tree shade
Transplantationin field
5mg/L 7mg/L
SOMACLONAL VARIATION
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to four gamma rays level like; 10Gy, 20Gy, 30Gy and 40Gy. Both sets of calli were
transferred to MS media containing 1 mg/L BAP for regeneration. Calli sub-cultured
at 3mg/L 2, 4 D showed good response for regeneration while gamma rays treated
callus showed 100% mortality except calli treated with 40Gy and depicted 87.5%
mortality where calli from variety S-05-US-54 were survived.
Several studies have been conducted to find out the most suitable callus
induction protocol by using different 2, 4 D concentration on MS media. Behera and
Sahoo (2009) obtained sugarcane callus at 2, 4 D concentration 2.5 gm/L
supplemented in MS basal media. Rashid et al., (2009) obtained 80 to 82 percent
callus recovery in sugarcane by using 2 mg/L and 3 mg/L 2, 4 D in MS media.
Several authors like (Wang et al., 2003; Badawy et al., 2008; Gopitha et al., 2010;
Tarique et al., 2010; Lawan et al., 2012 and Yadav and Ahmad, 2013) reported the
best callus induction at 3 gm/L 2, 4 D supplemented in MS media form sugarcane.
These results are very much in accordance with our findings. However, Srinath and
Jabeen, (2013) reported callus induction on MS media containing 1mg/L 2,4 D along
with coconut water and PVP. This difference may be due to supplementation of
coconut water and PVP (Polyvinylpyrrolidone). Coconut water enhance callus
induction but cannot induce callus and somaclonal variation in alone. Badawy et al.,
(2008) and Rashid et al., (2009) obtained 82% callus recovery percentage at 3 mg/L
2, 4 D in MS media. These results are similar to our findings. Tarique et al., (2010)
recorded 80 to 90 percent survival rate after transferred plantlets to soil. These results
were not matching with our results where the survival percentage after hardening
was 33.3%. This may be due to subsequent sub-culturing of callus on 2, 4 D that lead
to lethal somaclonal variation in regenerated plantlets.
SOMACLONAL VARIATION
119
Khan et al., (2007) applied gamma radiation on vegetative sets at the rate of
0, 10, 20, 30 and 40 Gy, gamma rays, respectively and they observed no such
mortality. This difference was due to type of plant material exposed to irradiation.
Callus is a delicate and soft aggregate of cells and penetration of ionizing radiations
is very easy that may cause heavy genetic change, so the survival rate is very low
due to lethal mutations in case of callus as compared to vegetative sets. Suprasanna
et al., (2008) exposed embryogenic callus of sugarcane to gamma radiation (0–80
Gy) and found LD50 to be around 20–30 Gy while at higher doses, they observed
poor regeneration frequency after 4–6 weeks. These finding somewhat match with
our results, however time length of callus exposure to irradiation and source of
irradiation and rate of irradiation also affect the mutation rate. Khan et al., (2007)
applied gamma radiation from Cesium 137 source at the rate of 30.86Gy/minute on
sugarcane vegetative tissues, Kaur and Gosal (2009) used gamma radiation (20Gy
to 80Gy) source 60Co callus with dose rate 2500Gy/h for 5 minutes and they observed
regeneration percent recovery in calli ranged from 30-90% while 100% mortality at
80Gy. In case of our study we applied 30Gy/min for 10 min. Nikam et al., (2015)
used gamma ray (10 to 80 Gy) at a dose rate of 9.6 Gy/min on sugarcane
embryogenic callus cultures. In case of our study we applied gamma rays source
from Cobalt 60 at the rate of 30Gy/minute for 10 min. High mortality in callus
regeneration might be due to rate of irradiation exposure. It is suggested that gamma
rays exposure of callus at the rate of 30Gy/minute was lethal for mutation induction
in sugarcane.
Callus regeneration was done on MS media supplemented with 1.0 mg/L
BAP and all varieties showed good callus regeneration except callus treated with
gamma radiations in 4 to 6 weeks. Shoot initiation and multiplication was done with
SOMACLONAL VARIATION
120
Picture 4.1: A view of crystalline compact and embryogenic calli formed from
young meristematic enfold leaves explant after 24 days of inoculation in first
subculture in Murashige Skoog (MS) medium supplemented with 3mg/L 2,4-D.
Where P1, P2, P3, P4, P5 and P6 are S-03-SP-93, S-05-US-54, S-03-US-694, S-
06-US-300, HSF-240 and SPF-213 respectively.
Picture 4.2: Regeneration from calli after 70 days of inoculation in third
subculture in MS medium supplemented with 1mg/L BAP. Where a, b, c, d, e, f
and g represent regeneration of S-03-SP-93, S-05-US-54, S-03-US-694, S-06-US-
300, HSF-240 SPF-213 and S-05-US-54 (10 Gy)* respectively.
*where (10 Gy) represents callus treated with 10Gy gamma radiation.
Graph 4.1: Effect of different concentration levels of 2, 4 D on callus induction
and callus recovery percentage.
1020 25
10 15 15
9080
70
90 90 85
5545
6050 55
65
25 20
45
25
55
30
0
20
40
60
80
100
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213Ca
llu
s re
cov
ery
% a
ge
Varieties
Callus induction wtih 2,4 D
Control 1mg/L 3mg/L 5mg/L 7mg/L2, 4 D levels
SOMACLONAL VARIATION
121
MS media supplemented with 1.0 mg/L kinetin that showed excellent shoot
formation in all varieties in 4 to 6 weeks. Rooting was done with half strength MS
media contained 1mg/L NAA that showed excellent root formation in all varieties
after 3 weeks. Several studies have been conducted to find out the most appropriate
regeneration, shoot and root initiation in sugarcane. Behera and Sahoo (2009)
initated multiple shoot induction on MS medium with BAP 2.0 mg/L + NAA 0.5
mg/L while rooting on the half-strength MS basal media supplemented with 3.0 mg/l
NAA. Rashid et al., (2009) used 1.0 mg/L GA3 and 0.5 mg/L Kinetin to obtain
optimum shoots length while they used 1.0 mg/L IBA in MS media for roots
initiation. Gopitha et al., (2010) used IBA at the rate of 0.5mg/L and BAP 1 mg/L
for shoot induction while 3 mg/L NAA and 5% sucrose for successful roots initiation.
These finding are somewhat different from our results. These variations in results
may be due to difference in experimental conditions and plant material used. Naz et
al., (2008); Tarique et al., (2010); Shahid et al., (2012); Srinath and Jabeen (2013);
Yadav and Ahmad (2013) reported 1.0 mg/L BAP for calli regeneration and 0.5 gm/L
kinetin for shoot initiation and multiplication with 100% regeneration recovery,
while Tarique et al., (2010) reported best root initiation using NAA at the rate of 0.5
mg/L supplemented in MS media. These finding are very much in accordance with
our results. It is concluded that 1 mg/L BAP for callus regeneration, 1 mg/L Kinetin
is for shooting while 1 mg/L NAA for rooting proved to be best supplement.
A total of 671 somaclones were developed from six varieties (Graph.4.2), of
which 110 somaclones were raised from variety S-03-SP-93, from S-05-US-54, 84
from S-03-US-694, 74 from S-06-US-300, 112 from HSF-240, 106 from SPF-213
and 90 from S-05-US-54 (10 GY, radiation treated callus). After hardening 224
somaclones survived, of which 45 plants from variety S-03-SP-93, 26 from
SOMACLONAL VARIATION
122
Picture 4.3: Shooting of four weeks old regeneration tissues in MS medium
supplemented with 1mg/L Kinetin. Where a, b, c, d, e, f and g represents
shooting of S-03-SP-93, S-05-US-54, S-03-US-694, S-06-US-300, HSF-240 and
SPF-213 S-05-US-54 (10 GY)respectively.
Picture 4.4: Rooting of shootlets in half strength MS medium supplemented
with 1mg/L NAA. Where a, b, c, d, e, f and g represent regeneration of S-03-SP-
93, S-05-US-54, S-03-US-694, S-06-US-300, HSF-240 and SPF-213 S-05-US-54
(10 GY) respectively.
SOMACLONAL VARIATION
123
S-05-US-54, 29 from S-03-US-694, 19 from S-06-US-300, 42 from HSF-240, 46
from SPF-213 and 23 from S-05-US-54 (10 GY).
After transplantation 134 plants were survived, comprising 35 somaclones
from variety S-03-SP-93, 13 from S-05-US-54, 16 from S-03-US-694, 4 from S-06-
US-300, 28 from HSF-240, 25 from SPF-213 and 13 from S-05-US-54 (10 GY). The
overall survival percentage of somaclones after hardening was 33.3% (Graph.4.3)
with maximum survival percentage 40.9 in S-03-SP-93 while minimum 25.5% from
S-05-US-54. Survival percentage after field transplantation was 60% with maximum
37% somaclones survived from SPF-213 and minimum 5.4% survival rate was
recorded from S-06-US-300.
Behera and Sahoo, (2009) observed 90 percent survival rate of somaclones
after greenhouse and field transplantation while Srinath and Jabeen, (2013) recorded
90 percent survival percentage after transplantation of somaclones in greenhouse.
These results do not match with our findings, where the survival rate was 60 percent
after field transplantation. These differences may be due to seasonal changes,
environmental differences, temperature variations, field conditions, soil type and
irrigation water. Our experimental sight has irrigation water with generally high salt
concentrations, this may be the cause of low survival percent. Nikam et al., (2015)
reported survival of 18 somaclones out of a total of 138 irradiated and salt-selected
somaclones grown to maturity for their agronomic attributes with improved sugar
yield and brix percentage. These results are similar to our findings.
SOMACLONAL VARIATION
124
Graph 4.2: Number of somaclones raised, number of somaclones survived after
hardening and number of somaclones survived after transplantation.
Graph 4.3: Somaclones survival %age after hardening and survival percentage
after transplantation.
110
9584
74
112106
90
45
26 2919
42 40
2335
13 16
4
28 25
13
-20
0
20
40
60
80
100
120
140
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(10Gy)
No
. o
f p
lan
ts
Somaclone's parentage
No. of somaclones raisedNo. of somaclones survived after hardeningNo. of somaclones survived after transplantation
40.9
27.3
34.5
25.6
37.5 37.7
25.5
31
13
19
5.4
25
37
14
0
5
10
15
20
25
30
35
40
45
50
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(10Gy)
Su
rviv
al
%a
ge
Somaclones
Survival %age after hardening Survival %age after transplantation
SOMACLONAL VARIATION
125
4.4.2. DETECTION OF SOMACLONAL VARIATION
For detection of somaclonal variations, ten highly polymorphic SSR primers
were utilized (Graph 4.4). A set of five somaclones were randomly selected along
with their parental clones for comparison on the basis of banding pattern generated
through PCR amplification. In case of somaclones generated from variety S-03-SP-
93 and their parental clone, a total of 397 bands were amplified of which 158 were
polymorphic with an average 39 bands per primer. An average 35.3% polymorphism
was generated by 10 primers. Higher number of bands generated by primer P-90
were 100 while average number of bands generated by any single primer was
estimated to be 15.8. In case of somaclones generated from variety S-05-US-54 and
parental clone, a total of 438 bands were amplified. Among these 209 were
polymorphic with an average total polymorphism estimated being 39.7%. Maximum
172 bands were generated by primer P-90. In case of S-03-US-694 and its five
somaclones a total of 434 bands were generated, of which 161 were polymorphic
with average polymorphism estimated was 34.6%. Maximum 97 bands were
generated by primer pair P-90 while average individual primer generated 34 bands.
In S-06-US-300 and its four somaclones 10 selected SSR primers generated a total
of 345 bands. Among these 104 were polymorphic with average total polymorphism
estimated being 25.4%. An average 10 bands were generated by each primer. In
variety HSF-240 and its parental clone and five somaclones produced total 400
bands, among them 188 were polymorphic with average total polymorphism
generating by all primers was estimated to be 51.2%. Primer P-90 produced
maximum 79 bands while minimum 25 bands being generated by primer P-89. A
total of 390 bands were generated in parental clones and five somaclones of variety
SPF-213, among them 152 being polymorphic with average total poly morphism
SOMACLONAL VARIATION
126
40.6%. Maximum 88 bands were generated by primer P-90 while minimum 18 bands
were produced by primer SMC119CG. Somaclones generated from callus of S-05-
US-54 irradiated with gamma rays (10Gy), 10 selected SSR primer generated a total
of 433 bands of which 125 were polymorphic with an average 29.1% expressing
polymorphism.
Simple sequence repeat (SSR) markers are the most commonly used
molecular techniques to study polymorphism in sugarcane (Nair et al., 2002).
Microsatellite markers are useful for discriminating the genotypes and evaluation of
genetic relationships due to their reproducibility, multiallelic and codominant nature
(Wong et al., 2009). There are several reports about the successful detection of
somaclonal variation in many agriculturally important crops by using PCR based
molecular techniques. Khoddamzadeh et al., (2010) detected somaclonal variation
in Phalaenopsis bellina (Rchb.f.) a Christenson orchid species by using RAPD
markers and observed 17% polymorphism in somaclones. Shahid et al., (2011);
Shahid et al., (2012) and Abdullah et al., (2013) used SSR marker to detect
polymorphism in sugarcane somaclones and estimated 67%, 64% and 81%
polymorphism, respectively. Seema et al., (2014) tested somaclonal variations in
sugarcane by using RAPD markers and estimated 60% polymorphism among
somaclones.
Overall polymorphism percentage in somaclones was estimated in the range
from 29 to 51 percent (Table 4.2) with somaclones raised from varieties HSF-240
and SPF-213 showing high polymorphism (51.2% and 40.6%, respectively) than rest
of the other varieties. Similar findings were reported by (Khan et al., 2007; Cuesta
et al., 2010; Shahid et al., 2011; Seema et al., 2014 and Emma et al., 2014).
Somaclones developed from varieties S-03-SP-93, S-05-US-54 and S-03-US-694
SOMACLONAL VARIATION
127
showed 35.3, 39.7 and 34.6 percent polymorphism, respectively, while somaclones
from S06-US-300 and S-05-US-54 (10Gy) depicted 25.4 and 29.1 percent
polymorphism respectively. Similar results have been reported earlier (Ngezahayo
et al., 2007; Gao et al., 2009; Fusheng Zhang, 2009 and Viehmannova et al., 2014).
It can be suggested here that SSR markers are the valuable molecular tools
to detect somaclonal variation and polymorphism in somaclones representing
somaclonal variation on the basis of addition and deletion of tandem repeats of
nucleotide sequences. If the addition and deletion of repeated nucleotides fall in the
coding sequences or exon regions of genome, regulatory sequences regions of genes
and binding sites of transposons definitely will affect the genotype of an individual
(Lodish et al., 2000).
4.4.3. PRINCIPAL COORDINATE ANALYSIS (PCoA)
Principal coordinated analysis was done to estimate the genetic variance and
genetic distance among somaclones and their parental clones. Principal Coordinate
Analysis (PCoA) of simple sequence repeats (SSR) data is instrumental to find out
genetic relationship among populations for breeding purposes (Reif et al., 2003). It
is a synthesis and interpretation of multivariate data with some fundamental linear
structure. Reif et al., (2003) successfully identified genetically identical germplasm
by using molecular markers data and suggested that PCoA is economical and solid
method for making breeding decisions. Principal Coordinate Analysis is ordinate or
scaling procedure that starts with a matrix of similarities or dissimilarities between
individuals on multidimensional graphical plot and recommended over PCA when
there is missing data and when there are less individuals than characters (Rohlf,
1972).
SOMACLONAL VARIATION
128
Graph 4.4: A Graphical description of 10 sugarcane microsatellite markers containing primer ID, No. of loci, Polymorphic loci
and % polymorphism among seven parental clones and their thirty four somaclones.
Table 4.2: Average number of loci, average polymorphic loci and average polymorphism percentage in somaclones of each
variety gerated by 10 primers.
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(40Gy) No.
loci
Poly.
loci
%
poly
No.
loci
Pol.
loci
%
pol
No.
loci
Pol.
loci
%
pol
No.
loci
Pol.
loci
%
pol
No.
loci
Pol.
loci
%
pol
No.
loci
Pol.
loci
%
pol
No.
loci
Pol.
loci
%
pol
40 16 35 44 21 40 43 16 35 35 10 25 40 19 51 39 15 41 43 13 29
0
10
20
30
40
50
60
70
80
90
100
110
120
130
`No. loci Poly.
loci
% poly. `No. loci Pol. loci % pol. `No. loci Pol. loci % pol. `No. loci Pol. loci % pol. `No. loci Pol. loci % pol. `No. loci Pol. loci % pol. `No. loci Pol. loci % pol.
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54 (40Gy)
Somaclones and their parental clonesP-89 P-90 P-100 P-137 SMs009 mSSCIR58 SMC1604SA SMC334BS mSSCIR66 SMC119CG
SSR primers
SOMACLONAL VARIATION
129
Picture 4.5: SSR based detection of somaclonal variation in the form of addition and deletion of short tandem repeats, where (a)
represent SP-93 and its somaclones banding pattern with primer P-90, (b) represent S-05-US-54 and its somaclones with primer
P-89, (c) represent S-03-US-694 and its somaclones using primer MSSCIR58, (d) represent S-06-US-300 and its somaclones with
primer SMC119CG, (e) represent HSF-240 and its somaclones with primer SMC1604SA, (f) represent SPF-213 and its
somaclones with primer SMC1604SA and (g) represent S-05-US-54 (10 Gy) and its somaclones with primer MSSCIR58.
SOMACLONAL VARIATION
130
Analysis was performed on the basis of differences of alleles generated with
10 polymorphic SSR markers (Graph 4.4) from 7 varieties as parent [S-05-SP-93, S-
05-US-54, S-03-US-694, S-06-US-300, HSF-240, SPF-213 and S-05-US-54
(10Gy)] and their 34 somaclones. In case of S-05-SP-93 and its somaclones SC1,
SC2, SC3, SC4 and SC5 SSR data generated by using 10 primers was subjected to
principal coordinate analysis, the first two dimensions of principal coordinate
generated 71.12% cumulative variance, of which PCoA-1 and PCoA-2 contributed
54.4% and 16.7%, respectively. Biplot of PCoA-1 and PCoA-2 (Fig 4.2a and Table
4.3) shows dispersion of somaclones from parental clone depicting large genetic
distance. Parental clone of variety S-05-US-54 and its somaclones SC6, SC7, SC8,
SC9, and SC10 accounted for 75.73% of the total variance, to which PCoA-1 and
PCoA-2 generated 60.7% and 14.9%, variability, respectively. Biplot diagram of fist
two PCoA (Fig 4.2b) illustrated close association between parental clone S-05-US-
54 and its somaclones SC8, SC9 and SC10 while SC6 and SC7 showed maximum
genetic distance with respect to their parental clones. First two PCoA of S-03-US-
694 and its somaclones generated 76.34% cumulative variance, to which PCoA-1
and PCoA-2 contributed 61.61% and 14.7% respectively. Biplot of first two PCoA
(Fig 4.2c) shows clear dispersion of parental clone and its somaclones, where SC11
showed close association with parental clone S-03-US-694 while rest of other
somaclones having maximum genetic distance with respect to their parental clone.
Principal coordinate analysis of parental clone of variety S-06-US-300 and its
somaclones SC16, SC17, SC18 and SC19 accounted for 91.2% of the total
variability, where PCoA-1 and PCoA-2 added 82% and 9.2% genetic variability
respectively, while the biplot of fist two PCoA (Fig 4.2 d) presented close association
between somaclone i.e. SC17 and its parental clone S-06-US-300. In case of variety
SOMACLONAL VARIATION
131
HSF-240 and its somaclones PCoA produced 80.89% of the total variance, of which
PCoA-1 and PCoA-2 contributed 69.49% and 11.3% variability respectively. Biplot
of first two PCoA (Fig 4.2e) illustrated genetic similarity between parental clone of
variety HSF-240 and its somaclones SC20 and SC23, while SC21 showed maximum
genetic distance with respect to its parental clone. Principal Coordinate Analysis of
parental clone of variety SPF-213 and its somaclones generated 82.5% total variance
where as PCoA-1 and PCoA-2 contributed 60.2% and 22.3% variability,
respectively. Biplot diagram of first two PCoA (Fig 4.2f) depicted maximum genetic
distance between parental clone and its somaclones, but somaclones i.e. SC25, SC26
and SC27 showed close association among them. PCoA of somaclones generated
from callus treated with gamma radiation (10Gy) from variety S-05-US-54
accounted for 76.31% variance, to which PCoA-1 and PCoA-2 contributed 44.5%
and 31.7% genetic variability, while biplot of first to PCoA (Fig 4.2g) illustrated
clear dispersion of somaclones and their parental clones.
Principal Coordinate Analysis (PCoA) of simple sequence repeats (SSR) data
is instrumental to find out genetic relationship among populations for breeding
purposes (Reif et al., 2003). It is data reduction technique and mostly utilized on
molecular data when there are less individuals than characters and it works with
matrix of similarities or dissimilarities between individuals on multidimensional
Graphical plot (Rohlf, 1972). Individual close on biplot Graph or having small
distance show more genetic similarity and less genetic variability and vice versa. The
overall variance in somaclones and their parental clones from all varieties ranged
from 71 to 91 percent. Maximum cumulative variance was observed in somaclones
and parental clones of variety S-06-US-300 while minimum cumulative variance was
estimated in somaclones and parental clone of variety S-03-SP-93. Similar findings
SOMACLONAL VARIATION
132
were reported by Nayak et al., (2014) and Karaca et al., (2015). Only few somaclones
showed less genetic distance with respect to their parental clones like somaclones
SC9 and SC10 in S-03-SP-93, SC17 in S-06-US-300, SC20 and SC23 in HSF-240,
while SC26 and SC25 in SPF-213. It can be concluded that in-vitro generated
somaclones have reasonable extant of genetic variability, so selection can be made
on succeeding generations.
Table 4.3: A description of PCoA-1 and PCoA-2 eigenvalues, percent variation
and cumulative variation based on binary data obtained from 10 SSR primers
pairs applied on parental clones and their somaclones.
S.
No
Parents and somaclones
PCoA
Axis
Eigen
value
Percent
variation
Cumulative
Percentage
variation
1. S-05-SP-93 + somaclones PCoA-1 0.039 54.413 71.12
PCoA-2 0.012 16.707
2 S-05-US-54 + somaclones PCoA-1 0.034 60.78 75.73
PCoA-2 0.008 14.953
3 S-03-US-694 + somaclones PCoA-1 0.018 61.616 76.34
PCoA-2 0.004 14.729
4 S-06-US-300 + somaclones PCoA-1 0.045 82.002 91.21
PCoA-2 0.005 09.211
5 HSF-240 + somaclones PCoA-1 0.038 69.494 80.89
PCoA-2 0.006 11.399
6 SPF-213 + somaclones PCoA-1 0.021 60.204 82.50
PCoA-2 0.008 22.300
7 S-05-US-54 (10 Gy) +
somaclones
PCoA-1 0.010 44.567 76.31
PCoA-2 0.007 31.747
SOMACLONAL VARIATION
133
Fig 4.2: Principal coordinate biplots of somaclones and their parents on the basis of SSR score of primers used to detect
somaclonal variation. Where (a) = S-03-SP-93, (b) =S-05-US-54, (c) = S-03-US-694, (d) = S-06-US-300, (e) = HSF-240, (f) = SPF-
213, (g) = S-05-US-54 (10Gy).
SOMACLONAL VARIATION
134
4.4.4. GENETIC INTEGRITY OF CANDIDATE GENES
4.4.4.1. IN SLICO CANDIDATE GENE IDENTIFICATION
We used in our study four well annotated candidate genes in sorghum
responsible for growth and development to find out their corresponding homologous
genes exon regions in sugarcane. The candidate genes responsible for enzymes
included catalase, sucrose phosphate synthase, gibberellin 2-oxide 4 and teosinte
branched1 (referred here as CAT1, SPS, GA 2-oxidase 4 and TB1). Nucleotide
sequences of these genes were searched as on sorghum gene database (Phytozome
database version 9.0. www.http://phytozome.jgi.doe.gov). Annotation sequences of
these genes exons and introns are listed in (Fig 4.3), while their function, location on
chromosome, transcript name and Gene Bank accession number/Phytozome ID are
listed in (Table 4.4). Intron and exon boundaries of these sequences were identified
and only exon, the coding sequences were used for primer synthesized with
maximum coverage and then PCR amplification was done on sugarcane genomic
DNA and expected band size were amplified and gel purified and then sequenced.
Pairwise alignment was made with sorghum candidate genes sequences. Gel purified
bands of putative homologues of sorghum from sugarcane gDNA are presented in
(Picture 4.6), whereas sequence alignments of gel purified bands of sugarcane and
their sorghum sequences are presented in (Fig 4.4).
These candidate genes have a very vital role in the plant defence mechanism
against biotic and abiotic stresses, sugar production, growth and development and
increase number of tillering in sugarcane. Catalase avoid oxidative damage by
scavenging reactive oxygen species (ROS) to avoid oxidative damage (Su et al.,
2014). Catalases (CAT) also have an important role in the defence mechanisms of
SOMACLONAL VARIATION
135
Table 4.4: Candidate gene’s ID, putative functions, source of sequences, location on sorghum chromosome, transcript name,
exon(s), primer sequences and product size.
S. No
Gene ID Putative function
Source of
sequences
Location on
sorghum
Chromosome
Transcript Name Gene Bank
/Phytozome
ID and
Accession
number Exon
Primer sequences
(5’-3’)
(3’-5’)
Product
size (bp)
1
(CAT1)
Catalase
Catalytic activity
in cell specially
conversion
reactive oxygen
species i.e, H2O2
to H2O and O2
response to
oxidative stress
Sugarcane
/Sorghum
Chr04 Sobic.004G011500.1
KF528830.1/S
b04g001130
F: GGCTTCTTCGAGTGCACCCAC
R: CGCCATCACTCACATGTTTGGC
1275
2
(SPS) Sucrose
phosphate
synthase gene
Sugar metabolism
pathway, sucrose
biosynthesis
Sugarcane
/Sorghum
Chr04 Sobic.004G068400.1
AB001338.1/
Sb04g005720
Exon-I F: TCCTGGAGTTTACCGGGTT
R: TACATCTTGCACTAATTGCCTA
740
3 Chr04 Sobic.004G068400.1 Exon-II F: TGCGGATGCACTATATAAACTT
R: AAGGAATGCACAATGCACG
722
4
(GA 2-oxidase
4) gibberellin
2-oxidase 4
Oxidoreductase
activity, control
the stem
elongation in
plants Sorghum
Chr09 Sobic.009G196300.1
Sb09g025470
F: TCGTCCTCGCGAAGCCACC
R: TGATTGGTTACCGCACCGCAG
422
5
(TB1)
Tillering gene
Control tillering in
most of the
species of family Gramineae
Zea mays
sub.spp
teosinte/
Sorghum
Chr01 Sobic.001G121600.1
AF377743.1/
Sb01g010690
F: TCCTTTCTGTGATTCCTCAAGCC
R: TCAGTAGAAGCGTGAGTTCTGC
1143
SOMACLONAL VARIATION
136
plants like stress response, delay in aging and cellular redox balance (Liu et al.,
2015). Sucrose-phosphate synthase (SPS) is the plant enzyme that play a vital role
in sucrose biosynthesis. SPS is controlled by metabolites and by reversible protein
phosphorylation in photosynthetic and non-photosynthetic tissues (Huber and Huber
1996). Gibberellin 2-oxidase controls shoot apex and height of the plants (Sakamoto
et al., 2001). Teosinte branched1 gene control the tillering in members of family
poaceae.
4.4.4.2. AUTHENTICATION OF CANDIDATE GENES EXON REGION(S)
IN SUGARCANE
In case of catalase (CAT1), sugarcane mRNA sequence with NCBI Gene
bank (http://www.ncbi.nlm.nih.gov) accession number KF52883601 was used as a
reference sequence with 1275 bp (Table 4.4). Almost similar sized band was
obtained by PCR amplification in sugarcane (Fig. 4.4). Sequencing of gel purified
band, almost 1180 bp product obtained whereas pairwise alignment of with NCBI,
Gene Bank accession CAT1 sugarcane mRNA (KF52883601) showed almost 100%
similarity. (Su et al., 2014) identified similar cDNA sequence with Gene Bank
Accession No. KF664183 while Liu et al., (2015) also clone CAT gene from
sugarcane (S. officinarum L.) with specific primers by utilizing probe of sorghum
cDNA sequence of Catalase gene (XM 002437586.1) contained 1532 bp cDNA.
Sucrose phosphate synthase (SPS), sorghum sequence with Phytozome
(http://www.phytozome.net/) ID Sb04g005720 was used as a reference sequence
with two larger exons (Fig 4.3) with Exon-I 740 bp and exon-II 722 bp (Table 4.4).
Almost similar sized PCR amplification products were isolated from sugarcane
genomic DNA (Picture 4.6). Sequencing of the gel purified PCR product were almost
same size as sorghum SPS exons were obtained, while pairwise sequence alignment
SOMACLONAL VARIATION
137
Fig 4.3: Sequence annotations of sorghum candidate genes searched from gene
database Phytozome 9.1. where (a) represents catalase isozyme 3 transcript
sequence, (b) sucrose phosphate synthase, (c) gibbriline 2-oxidase 4, (d) Teosinte
branched1.
SOMACLONAL VARIATION
138
Picture 4.6: Combined picture of candidate genes with exon regions gel purified
PCR products amplified from sugarcane gDNA samples, where (CAT1) is
Catalase, (SPS) Sucrose phosphate synthase gene, (GA 2-oxidase 4) gibberellin 2-
oxidase 4, and (TB1) Tillering gene.
Fig 4.4. Pairwise sequence alignments of candidate genes exon(s) regions, here (a)
CAT1 sugarcane mRNA gene bank accession (KF528830.1) and sugarcane gDNA
obtained sequence, (b) SPS sorghum sequence (Sb04g005720) and sugarcane
gDNA obtained sequence, (c) Gibberellin2 oxidase 4 sorghum exon sequence and
sugarcane GA2 oxidase obtained sequence, (d) Teosinte branched1 sorghum
sequence and sugarcane obtained sequence.
SOMACLONAL VARIATION
139
with sorghum homologue showed almost 100% similarity in both the exons. The first
time sucrose phosphate synthase gene cloned was reported by Worrall et al., (1991) in
maize (Zea mays L.). McIntyre et al., (2006) cloned gene family of sucrose phosphate
synthase in sugarcane with 400 bp sequence. Verma et al., (2010) also utilized similar
sequence with (Gene Bank accession no. GI161176315) for sucrose phosphate
synthase expression analysis. Komatsu et al., (2002) reported the similar sequences
for sucrose phosphate synthase in sugar beet, Arabidopsis, carrot, barley, wheat and
citrus.
In case of gibberellin 2 oxidase 4 (GA 2-oxidase 4), we used sorghum sequence
with Phytozome (http://www.phytozome.net/) ID Sb04g005720 as a reference
sequence with three small exon regions (Fig 4.3), Two exons were obtained by PCR
amplification in sugarcane, of which only one was truly sequenced with size of 422 bp
(Fig. 4.4) and other smaller exons had multiple haplotypes so, they had strong GC rich
regions hence could not sequence fully. Sequencing of gel purified band, almost 400
bp product showed 100% similarity with its homologue of sorghum by doing pairwise
alignment. Tillering branched1 gene was searched in sorghum Phytozome gene
database with gene ID Sb01g010690 and CDS sequence 1143 bp (Table 4.4).
Polymerase chain reaction amplification of this sequence generated similar sized band
in sugarcane. Gel purification of PCR product in sugarcane was sequenced in forward
as well as reverse direction due to strong GC region in the centre of the product that
block the reaction by self-pairing and making hairpin loops. Reverse direction
sequencing gave true read until the CG rich region. Almost 900 bp true sequence was
aligned with sorghum sequence that showed similar sequence pattern.
4.4.4.3. CANDIDATE GENE INTEGRITY ASSESSMENT OF SOMACLONES
After confirmation of target sequences of candidate genes in sugarcane with their
SOMACLONAL VARIATION
140
reference sequences, PCR amplification of exon regions of candidate were done by
using gDNA of somaclones and their parental (control) clones. By doing sequencing
of each candidate gene exon(s) from gel purified products of each candidate gene
parental clone and its five somaclones from six varieties, the sequence reads were
aligned and single nucleotide sequence (SNPs) changes were examined.
In case of CAT1 no possible SNPs were observed in all the somaclones
generated from callus culture (2, 4 D 3mg/L) based induced somaclonal variation in
six varieties (S-03-SP-93, S-05-US-54, S-03-US-694, S-06-US-300, HSF-240 and
SPF-213), while the SNPs were observed in somaclones raised from callus irradiated
with 40 Gy gamma radiations in variety S-05-US-54. A Transversion of C into G was
detected in somaclones SC32, SC33 and SC34 at position 673 bp.
Alignment of sequence reads of SPS exon-I and exon-II obtained from
somaclones and their parental clones in all varieties showed no SNPs changes while
in case of somaclones raised from irradiated callus showed transition of nucleotide
based. A transition of in T into A in exon-I position 607 of parental clone sequence in
somaclones SC30, SC32, SC33 and SC34 was detected while transition G into A in
somaclones SC30, SC31, SC32, SC33 and SC34 was detected.
Multiple sequence alignment of GA 2-oxidase 4 sequence reads obtained from
somaclones raised from 2, 4 D sub-culture callus and their parental clones from all the
varieties depicted no true SNPs changes in sequences while somaclones developed
from irradiated callus of variety S-05-US-54 showed one SNP change in somaclones.
A transition of T into C at position 190 of parental clone’s read was detected in SC30,
SC31, SC32, SC33 and SC34. Similarly, no SNP was detected in somaclones of all
varieties in case of TB1 while in somaclones raised from irradiated callus of variety
SOMACLONAL VARIATION
141
S-05-US-54 showed SNP change in one somaclone. A transversion of G into T at
position 170 of parental clone’s read in somaclone SC32.
Overall in all the somaclones, candidate genes showed no variation in the
coded regions of exon nucleotide sequences, except somaclones raised from irradiated
callus. The findings clearly depict that somaclones raised from callus 2, 4 D sub-
culture not affect single nucleotide sequence changes in genome. However, 2, 4 D
rapid cell proliferation may have caused addition, deletion, inversion or transversion
of large chromosomal segments or large DNA fragments. On the other hand, gamma
radiations are lethal when heavy dosage applied on callus and causes deletion,
transversion or transition of nucleotides. They can directly target the nucleotide
sequences and break the either phosphodiester bond between nucleotide sequences or
glyosidic bond between pentose sugar and nitrogen basis. A change in coded region
nucleotide sequence definitely change the amino acid sequences in a polypeptide upon
translation of coded region. A change in amino acid sequence alter the phenotype of
organism. A nucleotide change in coded region of important candidate genes affects
the phenotype. Genetic integrity of candidate genes is important in mutated population
for normal growth and development, metabolic function and defence mechanism.
SOMACLONAL VARIATION
142
Fig 4.5: Multiple alignment of CAT1 sequence reads obtained from parental
clone of S-03-SP-93 and its 5 somaclones; SC1, SC2, SC3, SC4 and SC5, showed
no SNPs.
Fig 4.6: Multiple alignment of CAT1 sequence reads obtained from parental
clone of S-05-US-54 (10Gy) and its 5 somaclones; SC30, SC31, SC32, SC33 and
SC34, showed transversion of C into G at position 673 of parental clone’s read in
SC32, SC33 and SC34.
SOMACLONAL VARIATION
143
Fig 4.7: Multiple alignment of SPS exon-I sequence reads obtained from parental
clone of S-05-US-54 and its 5 somaclones; SC6, SC7, SC8, SC9 and SC10, showed
no SNPs.
Fig 4.8: Multiple alignment of exon-I sequence reads obtained from parental
clone of S-05-US-54 (10Gy) and its 5 somaclones; SC30, SC31, SC32, SC33 and
SC34, showed transition of T into C at position 607 of parental clone’s read in
SC30, SC32, SC33 and SC34 while a transition of G into A at position 673 in
SC30, SC31, SC32, SC33 and SC34.
SOMACLONAL VARIATION
144
Fig 4.9: Multiple alignment of SPS exon-II sequence reads obtained from
parental clone of S-03-US-694 and its 5 somaclones; SC11, SC12, SC13, SC14 and
SC15, showed no SNPs.
Fig 4.10: Multiple alignment of GA 2-oxidase 4 sequence reads obtained from
parental clone of S-06-US-300 and its 5 somaclones; SC16, SC17, SC18 and SC19,
showed no SNPs.
SOMACLONAL VARIATION
145
Fig 4.11: Multiple alignment of GA 2-oxidase 4 sequence reads obtained from
parental clone of HSF-240 and its 5 somaclones; SC20, SC21, SC22, SC23
andSC24 showed no SNPs.
Fig 4.12: Multiple alignment of GA 2-oxidase 4 sequence reads obtained from
parental clone of S-05-US-54 (10Gy) and its 5 somaclones; SC30, SC31, SC32,
SC33 and SC34, showed transition of T into C at position 190 of parental clone’s
read in SC30, SC31, SC32, SC33 and SC34.
SOMACLONAL VARIATION
146
Fig 4.13: Multiple alignment of TB1 sequence reads obtained from parental clone
of SPF-213 and its 5 somaclones; SC25, SC26, SC27, SC28 and SC29, showed no
SNPs.
Fig 4.14: Multiple alignment of TB1 sequence reads obtained from parental clone
of S-05-US-54 (10Gy) and its 5 somaclones; SC30, SC31, SC32, SC33 and SC34,
raised from irradiated callus showed transversion of G into T at position 170 of
parental clone’s read in somaclone SC32.
SOMACLONAL VARIATION
147
4.4.5. SCREENING OF SOMACLONES AGAINST RED ROT
A total of 134 somaclones from six varieties (Graph. 4.5) were inoculated with
red rot (Colletotrichum falcatum L.) suspension culture and then scored according to
the disease infestation scale given by Srinivasan and Bhat (1961), of wihich 69 were
resistant, 39 moderately resistant, 12 moderately susceptible, 8 susceptible while 6
were highly suceptible (Table. 4.3). In case of somaclones raised form variety S-03-
SP-93, a total 35 somaclones were innoculated, of which 6 were found resistant, 9
moderately resistant, 7 moderately susceptible, 8 susceptible while 5 were highly
susceptible. In case of somaclones raised form variety S-05-US-54, a total 13
somaclones were innoculated, of which 8 found resistant, 4 moderately resistant, 1
moderately susceptible. Somaclones produced from variety S-03-US-694, a total 13
somaclones were innoculated, of which 7 found resistant, 7 moderately resistant and
two moderately susceptible. In somaclones genrated from S-06-US-300, total four
plants were inoculated, of them two were resistant, two moderatly resistant. A total of
28 somaclones from variety HSF-240 were inoculated with red rot spores, among them
20 were resitant and 8 were moderatly resistant. In case of somaclones raised from
variety SPF-213, a total of 25 somaclones were inoculated, of them 20 were resistant
and 5 were moderately resistant. In case of somaclones raised from irradiaterd callus
from variety S-04-US-54, a total of 13 somaclones were generatd, of which 6 were
resistant, 4 were moderately resistant and 1 was highly susceptible.
Almost 51% somaclones showed full resistanec against red rot, 29% depicted
moderate resistance, 9% were moderately susceptibe, 6% were susceptible and only
5% were fully susceptible (Table. 4.5). A wide range of disease reaction was
SOMACLONAL VARIATION
148
Graph 4.5: screening of somaclones against red rot by using 0-9 scale as described
by Srinivasan and Bhat (1961).
Table 4.5: Total number of somaclones raised from parental clones of six varieties
innoculated with red rot spores suspension culture and their response agaist red
rot.
No. o
f
som
acl
on
es
Res
ista
nt
(0
-2.0
)
Mod
erate
ly
resi
stan
t
(2.1
-4.0
)
Mod
erate
ly
Su
scep
tib
le
(4.1
-6.0
)
Su
scep
tib
le
(6.1
-8.0
)
Hig
hly
susc
epti
ble
Ab
ov
e 8.0
Total 134 69 39 12 8 6
%age 51.5% 29.1% 9% 6% 5%
35
13
16
4
28
25
13
6 67
2
20 20
6
9
5
7
2
8
54
7
2 2
0 0 0
2
8
0 0 0 0 0 0
5
0 0 0 0 01
0
5
10
15
20
25
30
35
40
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(10Gy)
(No
. o
f p
lan
ts)
Somaclones
Somaclones screening against red rot
No. of somaclones Resistant (0-2.0)
Moderately resistant (2.1-4.0) Moderately Susceptible (4.1-6.0)
Susceptible (6.1-8.0) Highly susceptible Above 8.0
SOMACLONAL VARIATION
149
observed in somaclones, the ratio of susceptible and highly susceptible clones was less
in all varieties except somaclones from variety S-03-SP-93, of which 8 somaclones
were susceptible while 5 were highly susceptible. This variety was observed more
susceptible to red rot as comapred to other varieties under study. Large number of
resistant somaclones were observed from varieties i.e. HSF-240 and SPF-213.
Several studies have reported development of somaclones resistant to red rot
by in-vitro culture and irradiation mutagenesis. Screening for red rot in regenerated
plants was reported by Samad and Begum (2000) while studying the somaclonal
variation of irradiated and non-irradiated calli of sugarcane and observed moderately
resistance somaclones against red rot. Singh et al., 2000 reported that somaclones
developed from callus culture of leaf depicted wide variability for resistance against
red rot and documented that out of 42 somaclones, three were moderately resistanat
against red rot by inoculation method. Ali et al., (2007) and Sengar et al., (2009)
inoculated red rot pathogen ex situ for season and reported 70% of selected somaclones
revealing enhanced resistance as compared to their parental clones. Singh et al., (2008)
inoculated 228 somaclones with red rot pathotype Cf 08 and identified three resistant,
four moderately resistant somaclones whereas, while inoculation with pathotype Cf
03, produced 14 resistant and 19 moderately resistant products. These results are
almost similar with our findings
SOMACLONAL VARIATION
150
Picture 4.7: Leaf samples of parental clone and somaclones. Where (a) represents
red rot infected leaf of one of the representative parental clone while (b), (c), (d),
(e), (f), (g) and (h) represent red rot free somaclones leaf samples of varieties i.e.
S-03-SP-93, S-05-US-54, S-03-US-694, S-06-US-300, HSF-240 SPF-213 and S-05-
US-54 (10Gy) respectively.
Picture 4.8: Response of somaclones against red rot after inoculation. Where (a)
represents highly susceptible clone of S-05-US-54 (10Gy), (b) represents highly
susceptible clone of S-03-SP-93, (c) represents resistant somaclone of S-03-SP-93
and (d) represnts highly resistant somaclone of S-03-SP-93.
SOMACLONAL VARIATION
151
4.4.6. SCREENING OF SOMACLONES AGAINST SUGARCANE MOSAIC
VIRUS (SCMV)
A total of 34 somaclones almost five representatives from each variety and
their parental clones were evaluated against sugarcane mosaic virus (SCMV). Results
presented in the Graph (4.4) contained positive and negative control of sugarcane
mosaic virus (SCMV) O.D (optical density) values 0.72 and 0.20, respectively at 405
nm. All the samples of somaclones and their mother clones were compared with these
controls and among themselves.
In case of variety S-03-SP-93, its mother clone depicted O.D value 0.26 while
its somaclones (i.e SC1, SC2, SC3, SC4 and SC5) showed O.D values ranged from
0.16 to 0.23. Minimum value showed by SC2 and SC4 (0.61 and 0.17, respectively).
Somaclones having O.D values close to negative control are more resistant to SCMV
a somaclones having O.D values in the range of positive control. In case of variety S-
05-US-54, its mother clone showed O.D value 0.38 while its somaclones (i.e SC6,
SC7, SC8.SC9 and SC10) gave values ranged from 0.20 to 0.26. Minimum values
depicted by somaclones SC9 and SC6 (0.2 and 0.21, respectively), these values were
similar to the negative control.
In case of variety S-03-US-694, its mother clone showed O.D value 0.41
while its somaclones (i.e SC11, SC12, SC13, SC14 and SC15) depicted O.D values
ranged from 0.17 to 0.24. Minimum values depicted by somaclones SC15 (0.17) while
maximum value shoed by SC14 (0.24). All somaclones from variety have similar
values to the negative control. Somaclones from variety S-06-US-300 (SC16, SC17,
SC18 and SC19) showed O.D values ranged form 0.15 to 0.18. Somaclones SC17,
SC18 and SC19 depicted minimum values 0.15 while SC16 showed O.D value 0.18
SOMACLONAL VARIATION
152
while their mother clone gave values 0.28. Somaclones from this variety showed less
O.D vales than negative control. It means they were more resistant.
Somaclones (SC20, SC21, SC22, SC23 and SC24) from variety HSF-240
generated O.D values ranging from 0.13 to 0.14, less than negative control while their
mother clone generated 0.25 O.D value. These somaclone were more resistant to virus
as comapre to their mother clones. In case of variety SPF-213, mother clone depiced
O.D value 0.27 while its somaclones (SC25, SC26, SC27, SC28 and SC29) generated
O.D values ranging from 0.13 to 0.16. These values were less than the values of
negative control and their mother clones. In case of somaclones (SC30, SC31, SC32,
SC33 and SC34) raised from irradiated (10 Gy) callus of variety S-05-US-54 showed
O.D values at 405 nm agaist SCMV rainged from 0.12 to 0.27 while their mother clone
showed value 0.38. Minimum value (0.12) was showed by SC33 while maximum
value (0.27) was depicted by somaclone SC30.
All the somaclones from six varieties showed far less virus concentration than
their mother clones. Similar findings were reported by Gaur et al., (2002) and
Smiullah et al., (2012). However, our results were different from the findings of
Oropeza and Garcia (1996) who reported somaclones with complete absence of virus.
Young meristematic tissues of sugarcane plants are almost free from virus particles
and somaclones developed from these tissues remain almost free from virus. Leaves
of somaclones showed various responses like resistance to tolerance to susceptible
reaction. Resistant mode of plant also contained presence of infection but disease
pathogens fail to proliferate due to hypersensitive reaction (Acquaah, 2012). This may
be a one of the reason for the little presence of virus particles in the somaclones
samples detected in ELISA, however appearance of mosaic virus streaks on leaves
were totally absent.
SOMACLONAL VARIATION
153
Graph 4.6: Screening of somaclones against sugarcane mosaic virus (SCMV).
Where PC and NC represent positive and negative controls of SCMV respectively
while SC represents somaclones. (Bar = Standard Error)
Picture 4.9: Leaf samples of parental clone and somaclones. Where (a) represents
SCMV infected leaf of one of the representative parental clone while (b), (c), (d),
(e), (f), (g) and (h) represent virus free somaclones leaf samples of varieties i.e. S-
03-SP-93, S-05-US-54, S-03-US-694, S-06-US-300, HSF-240 SPF-213 and S-05-
US-54 (10Gy) respectively.
0.7
20
.20 0.2
60
.22
0.1
6 0.2
20
.17 0.2
30
.38
0.2
10
.25
0.2
60
.20 0.2
60
.41
0.2
00
.23
0.2
10
.24
0.1
70
.28
0.1
80
.15
0.1
50
.15 0
.25
0.1
30
.13
0.1
30
.13
0.1
40
.27
0.1
60
.14
0.1
50
.14
0.1
30
.38
0.2
70
.25
0.2
50
.12 0
.22
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
PC
NC
Moth
er c
lon
eS
C1
SC
2S
C3
SC
4S
C5
Moth
er c
lon
eS
C6
SC
7S
C8
SC
9S
C1
0M
oth
er c
lon
eS
C1
1S
C1
2S
C1
3S
C1
4S
C1
5M
oth
er c
lon
eS
C1
6S
C1
7S
C1
8S
C1
9M
oth
er c
lon
eS
C2
0S
C2
1S
C2
2S
C2
3S
C2
4M
oth
er c
lon
eS
C2
5S
C2
6S
C2
7S
C2
8S
C2
9M
oth
er c
lon
eS
C3
0S
C3
1S
C3
2S
C3
3S
C3
4
Control S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54 (10 Gy)
(SC
MV
co
nc. a
t O
.D 4
05
)
Somaclones
Screening of somaclones against SCMV
SOMACLONAL VARIATION
154
4.4.7. FIELD PERFORMANCE OF S0 GENERATION OF SOMACLONES
Morphological performance of somaclones were assessed after transplantation
in the research area of Agricultural Biotechnology Research Institute AARI,
Faisalabad along with their parental clones and data for the parameters like plant
height, number of tillers per plant, stem diameter, number of nodes, internode length,
leaf area, brix percentage and non-reducing sugar were recorded.
4.4.7.1 PLANT HEIGHT
Mean plant height of somaclones along with their parental clones are presented
in Graph 4.5. In case of somaclones raised from variety S-03-SP-93 almost all the
somaclones showed greater plant height as compared to their parental clone. Parental
clones have plant height of 179 cm while maximum plant height was recorded (195
cm) in somaclone SC4. In case of somaclones raised from variety S-05-US-54 all
somaclones showed greater plant height than their parental clone. Plant height in
parental clone was recorded to be 172 cm while maximum plant height (190 cm) was
observed in somaclones SC10. Somaclones in the variety S-03-US-694 showed a plant
height ranging from 198 cm (SC13) to 220 cm (SC15) while in their parental clone
plant height was observed to be 210 cm. In S-06-US-300 plant height recorded in
mother clone was 181 cm while its parental clones had plant height ranging from 180
cm to 188 cm. Maximum plant height (188 cm) was observed in somaclone SC18. In
case of somaclones raised from variety HSF-240 plant height observed in somaclones
to be ranging from 150cm (SC24) to 185 (SC23) while mother clone’s height was
recorded to be 160 cm. In case of variety SPF-213 there was a variation in plant height.
Parental clone showed plant height of 211 cm while in somaclones plant height ranged
from 127 cm (SC26) to 257 (SC28). Somaclones raised from gamma rays treated
callus of variety S-05-US-54 there was no significant variation observed in plant height
SOMACLONAL VARIATION
155
and plant height was recorded in the range of 171cm to 182 cm. In parental clone plant
height was recorded to be 172 cm that was less than almost all its somaclones.
Sood et al., (2006); Singh et al., (2008); Junejo et al., (2010); Dalvi et al.,
(2012); Sobhakumari (2012); Seema et al., (2014); Khan et al., (2015); Beghum et al.,
(2015) and Gaddkh et al., (2015) reported plant height in sugarcane somaclones
ranging from 58 cm to 286 cm. These results are almost similar to our findings.
4.4.7.2 NUMBER OF TILLERS PER PLANT
Mean values of number of tillers per plant are presented in Graph 4.6. Number
of tillers per plant were recorded in somaclones of all the varieties ranging from 3 to
10. In case of somaclones of variety S-03-SP-93 the minimum 4 tillers were recorded
in somaclone SC5 and maximum 7 in SC2 while in their parental clone this number
was 6. In variety S-05-US-54 number of tillers in mother clone were recorded to be 7
but less number of tillers were observed in its somaclones. However, number of tillers
in somaclones of varieties i.e. S-06-US-300 and HSF-240 were recorded to be more as
compare to their parental clones. In S-06-US-300 number of tillers in parental clone
were recorded 5 but this number was recorded in its somaclones to be ranged from 5
to 7, while in case of HSF-240 tillers in parental clone were recorded 8 but its
somaclones i.e. SC22, SC23, and SC24 number of tillers were recorded 9, 10 and 10,
respectively. In case of somaclones raised from variety SPF-213 and gamma rays
treated calli of variety S-05-US-54 (10Gy) number of tiller were observed same as in
their parental clones.
Singh et al., (2008); Seema et al., (2014) and Khan et al., (2015); reported
number of tillers in sugarcane somaclones to be ranging from 2 to 8. These findings
are very much in accordance with our results.
SOMACLONAL VARIATION
156
Graph 4.7: Mean values of plant height of somaclones and their parental clones.
(Bar = Standard Error)
Graph 4.8: Mean values of number of tillers per plant in somaclones and their
parental clones.
(Bar = Standard Error)
17
91
80
19
01
80 19
51
90
17
2 19
01
90
18
01
87
19
0 21
02
00 21
51
98
21
02
20
18
11
80
18
51
88
18
01
60
16
31
56 1
80
18
51
50
21
11
60
12
72
50 26
52
57
17
21
71
18
31
80
18
21
75
0
50
100
150
200
250
300M
oth
er c
lon
eS
C1
SC
2S
C3
SC
4S
C5
Moth
er c
lon
eS
C6
SC
7S
C8
SC
9S
C1
0M
oth
er c
lon
eS
C1
1S
C1
2S
C1
3S
C1
4S
C1
5M
oth
er c
lon
eS
C1
6S
C1
7S
C1
8S
C1
9M
oth
er c
lon
eS
C2
0S
C2
1S
C2
2S
C2
3S
C2
4M
oth
er c
lon
eS
C2
5S
C2
6S
C2
7S
C2
8S
C2
9M
oth
er c
lon
eS
C3
0S
C3
1S
C3
2S
C3
3S
C3
4
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(10GY)
Pla
nt
Hei
gh
t (c
m)
Somaclones
Plant Height 6 6
75
64
65 5
45
65 5
45
34
57
6 65
8 88
91
0 10
75 6
7 7 76
46
45
6
0
2
4
6
8
10
12
Moth
er c
lon
eS
C1
SC
2S
C3
SC
4S
C5
Moth
er c
lon
eS
C6
SC
7S
C8
SC
9S
C1
0M
oth
er c
lon
eS
C1
1S
C1
2S
C1
3S
C1
4S
C1
5M
oth
er c
lon
eS
C1
6S
C1
7S
C1
8S
C1
9M
oth
er c
lon
eS
C2
0S
C2
1S
C2
2S
C2
3S
C2
4M
oth
er c
lon
eS
C2
5S
C2
6S
C2
7S
C2
8S
C2
9M
oth
er c
lon
eS
C3
0S
C3
1S
C3
2S
C3
3S
C3
4
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(10GY)
No
. o
f ti
ller
s p
er p
lan
t
Somaclones
NUMBER OF TILLERS
SOMACLONAL VARIATION
157
4.4.7.3 STEM DIAMETER
Results for stem diameter are presented in Graph 4.9. In case of S-03-SP-93
stem diameter in mother clones was measured to 2.0 cm while in somaclones it was
estimated in range of 1.5 to 2 cm. In S-05-US-54 mother clone and its somaclones
showed almost same diameter of 2 cm. In S-03-US-694 stem diameter in mother clone
was estimated to 2.3 cm while in its somaclones diameter was recorded in the range of
2.0 to 2.1 cm. Somaclones in variety S-06-US-300 showed higher stem diameter than
their parental clones, in mother clone diameter was recorded as 1.8 cm while in
somaclones diameter was estimated in the range of 2.1 to 2.5 cm. In case of HSF-240
stem diameter in mother clone was estimated 2.4 while in its somaclones it ranged
from 1.8 to 3.0 cm. Maximum stem diameter was noted in somaclones i.e. SC21
(2.7cm), SC (2.7cm) and SC23 (3.0 cm). In SPF-213, two somaclones i.e. SC23 and
SC27 showed higher stem diameter (2.5 and 2.7 cm, respectively) than their parental
clone. Somaclones raised from irradiated callus of variety S-05-US-54 showed higher
stem diameter than their parental clone with minimum value (2.0 cm) for stem
diameter being observed in somaclones i.e. SC30 and SC31 while maximum 2.7 cm
was estimated in SC33.
Junejo et al., (2010); Sobhakumari (2012); Dalvi et al., (2012); Islam and
Begum (2012); Seema et al., (2014); Khan et al., (2015); Begum et al., (2015) reported
stem diameter in sugarcane somaclones being ranged from 1.4 cm to 2.8 cm. These
finding match with our results.
4.4.7.4 NUMBER OF INTERNODES
Results for number of internodes per plant are presented in Graph 4.10.
Somaclones raised form all the varieties i.e. S-03-SP-93, S-05-US-54, S-03-US-694,
S-06-US-300, HSF-240 and SPF-213 showed higher number of internodes than their
SOMACLONAL VARIATION
158
Graph 4.9: Mean values of stem diameter of somaclones and their parental clones.
(Bar = Standard Error)
Graph 4.10: Mean values of number of internodes per plant of somaclones and
their parental clones.
(Bar = Standard Error)
2 21
.5 1.7
21
.52
.11
.8 2 2 2.1
1.2
2.3
2 22
.22
.22
.11
.82
.12
.52
.12
.52
.41
.82
.71
.83
.02
.72
.4 2.5
2.2 2.3
2.7
2.0
2.0
2 22
.32
.72
.5
0
0.5
1
1.5
2
2.5
3
3.5
Moth
er c
lon
eS
C1
SC
2S
C3
SC
4S
C5
Moth
er c
lon
eS
C6
SC
7S
C8
SC
9S
C1
0M
oth
er c
lon
eS
C1
1S
C1
2S
C1
3S
C1
4S
C1
5M
oth
er c
lon
eS
C1
6S
C1
7S
C1
8S
C1
9M
oth
er c
lon
eS
C2
0S
C2
1S
C2
2S
C2
3S
C2
4M
oth
er c
lon
eS
C2
5S
C2
6S
C2
7S
C2
8S
C2
9M
oth
er c
lon
eS
C3
0S
C3
1S
C3
2S
C3
3S
C3
4
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(10GY)
Ste
m d
iam
eter
(cm
)
Somaclones
STEM DIAMETER (cm)
10 1
3 16
15
13 1
6
9
12
12
10 11 1
3
12 13
12 1
4
12
11
11
11 1
4
10 1
2
10
.33 15 16
12 1
5
13
9
21
15
24
23
23
9 10 1
2
10 11
10
0
5
10
15
20
25
30
Moth
er c
lon
e
SC
1
SC
2
SC
3
SC
4
SC
5
Moth
er c
lon
e
SC
6
SC
7
SC
8
SC
9
SC
10
Moth
er c
lon
e
SC
11
SC
12
SC
13
SC
14
SC
15
Moth
er c
lon
e
SC
16
SC
17
SC
18
SC
19
Moth
er c
lon
e
SC
20
SC
21
SC
22
SC
23
SC
24
Moth
er c
lon
e
SC
25
SC
26
SC
27
SC
28
SC
29
Moth
er c
lon
e
SC
30
SC
31
SC
32
SC
33
SC
34
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(10GY)
No
. o
f n
od
es
Somaclones
NUMBER OF INTERNODES
SOMACLONAL VARIATION
159
parental clones. In parental clones, number of internodes were recorded in the range
of 9 to 12 while in somaclones this number ranged from 10 to 24. Maximum number
of internodes were counted in somaclones raised from variety SPF-213 while in rest
of somaclones number of internodes were recorded in the range from 10 to 16.
Sood et al., (2006); Dalvi et al., (2012); Khan et al., (2015) and Gaddkh et al.,
(2015) reported similar findings with number of internodes being ranged from 11 to
24, while Singh et al., (2008) and Junejo et al., (2010) reported number of internodes
in parental lines ranged from 9 to 30. Number of internodes is a matric trait in
sugarcane. Products of photosynthesis accumulate in the internodes region so with
more the number of internodes more carbohydrates will be depositing.
4.4.7.5 INTERNODES LENGTH
Results for internodes length of somaclones and their parental clones are
presented in Graph 4.11. Internodes length in all somaclones were recorded less as
compare to their parental clones. In parental clones internodes length was measured in
the range from 10 cm to 12 cm while in somaclones internodes length was estimated
in the range from 6 cm to 12 cm. In case of parental clones of varieties i.e. S-03-SP-
93, S-05-US-54, S-03-US-694 and S-06-US-300, internode length was estimated
almost same (11 cm) while in their somaclones internod length was recorded in the
range from 5cm to 8 cm. In case of varieties HSF-240 and SPF-213, there were no
remarkable difference in parental clones and their somaclones.
Sood et al., (2006) reported internodes length in the range from 9 to 12.5 cm
and Singh et al., (2008) reported internodes length in the range from 6 to 18 cm in one
year old somaclones raised from sugarcane setts. The difference in our results may be
due to type of material used for somaclones development. In case of our experiment
we took data on internodes length for plants raised from transplant seedlings not from
SOMACLONAL VARIATION
160
sugarcane vegetative setts. Vegetative setts have food reservoir for newly raised
plantlets for initial boost up of early developmental stages while plants raised from
callus cultured transplant seedling have no reserve nutrient resources and this may be
a reason for less vigorous plants. There is a negative correlation in number of
internodes and internodes length, when number of internodes increased length of
internodes decreases. In case of our experiment number of internodes increased in case
of somaclones but length of internodes decreased however, plant height was same as
compared to parental clones.
4.4.7.6 BRIX PERCENTAGE
Results for brix percentage in somaclones and their parental clones are
presented in Graph 4.12. Brix percentage was recorded after 270 days of
transplantation in the field. Brix percentage in parental clones of all the varieties used
under study were recorded in the range of 14% to 19% while in all somaclones raised
from six varieties i.e. S-03-SP-93, S-05-US-54, S-03-US-694, S-06-US-300, HSF-240
and SPF-213 were having in higher numerical values in the range from 20% to 24%.
Maximum values of brix percentage (24%) were recorded in nine somaclones (SC1,
SC4, SC6, SC8, SC9, SC23 and SC33) while minimum value (20%) was recorded in
only one somaclone i.e. SC24 while in rest of the somaclones brix percentage was
recorded in the range from 21% to 23%.
Similar results were reported by Sobhakumari (2012) and Gadakh et al., (2015)
while assessing the performance of sugarcane somaclones but Singh et al., (2008);
Dalvi et al., (2012); Islam and Begum (2012) and Begum et al., (2015) reported brix
percentage ranged from 15% to 21%. The brix percentage in our experiment were
better than earlier findings.
SOMACLONAL VARIATION
161
Graph 4.11: Mean values of internodes length of somaclones and their parental
clones.
(Bar = Standard Error)
Graph 4.12: Mean values of brix percentage in somaclones and their parental
clones.
(Bar = Standard Error)
11
67
.57 6.5 7
11
6 65
6.5
61
1.4
98 8
.57
91
28 8
.57 6.5
10
9.8 1
0.8
11
.29
.68
.61
19
.8 10
.81
1.2
9.6
8.6
11
6 6.5
56
.86
0
2
4
6
8
10
12
14
Moth
er c
lon
eS
C1
SC
2S
C3
SC
4S
C5
Moth
er c
lon
eS
C6
SC
7S
C8
SC
9S
C1
0M
oth
er c
lon
eS
C1
1S
C1
2S
C1
3S
C1
4S
C1
5M
oth
er c
lon
eS
C1
6S
C1
7S
C1
8S
C1
9M
oth
er c
lon
eS
C2
0S
C2
1S
C2
2S
C2
3S
C2
4M
oth
er c
lon
eS
C2
5S
C2
6S
C2
7S
C2
8S
C2
9M
oth
er c
lon
eS
C3
0S
C3
1S
C3
2S
C3
3S
C3
4
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(10GY)
Inte
rno
des
len
gth
(cm
)
Somaclones
INTERNODE LENGTH (cm)
17
.4
24
21 22 2
42
1
18
24
23 24
24
23
19
22 2
4
23
23 24
17
.9 21
21 22 23
16
.32
2 23
22 2
4
20
14
21
21 22
22
22
18
22 23
22 2
4
23
0.0
5.0
10.0
15.0
20.0
25.0
30.0
Moth
er c
lon
e
SC
1S
C2
SC
3S
C4
SC
5
Moth
er c
lon
eS
C6
SC
7S
C8
SC
9
SC
10
Moth
er c
lon
eS
C1
1S
C1
2
SC
13
SC
14
SC
15
Moth
er c
lon
e
SC
16
SC
17
SC
18
SC
19
Moth
er c
lon
e
SC
20
SC
21
SC
22
SC
23
SC
24
Moth
er c
lon
e
SC
25
SC
26
SC
27
SC
28
SC
29
Moth
er c
lon
eS
C3
0
SC
31
SC
32
SC
33
SC
34
S-03-SP-93 S-05-US-54 S-03-US-694 S-06-US-300 HSF-240 SPF-213 S-05-US-54
(10GY)
Bri
x %
ag
e
Somaclones
BRIX %age
SOMACLONAL VARIATION
162
4.5. CONCLUSION AND RECOMMENDATIONS
All the varieties used in the experiment showed good response to callus
induction at 2, 4 D level 3mg/L supplemented in MS media. Callus treated with
irradiation at different levels of gamma rays showed poor response to regeneration and
lead to mortality in all varieties except variety S-05-US-54 at 10 Gy level. It is
suggested from this study that irradiation of callus in sugarcane is not suitable for
mutation induction. A high magnitude of polymorphism was recorded in somaclones
with respect to their donor clones. Genetic integrity assessment of somaclones for
important candidate gene exon regions revealed intact nucleotide sequences as their
parental clones in case of somaclones raised from sub-culturing of callus with 2, 4 D
while there are some SNPs detected in somaclones raised from irradiated callus. All
the somaclones showed negligible concentration of sugarcane mosaic virus with
variable disease response against red rot. Except somaclones of variety S-03-SP-93,
all others varieties indicated maximum resistance. Increase in number of internodes
and reduced internodes length with high brix percentage was observed in somaclones
as compared to their parental clones and selection in the succeeding generations will
be beneficial. It is concluded that somaclonal variation is a good source of variability
induction and alternative methodology for improvement in the sugarcane.
163
GENERAL CONCLUSIONS
Analysis of variance revealed highly significant differences among the
sugarcane varieties for the morpho-physological parameters compared. Principal
Component Analysis depicted 54.63% cumulative variance in genotypes under
study. Hierarchal and non-hierarchal cluster grouped genotypes into five clusters and
some diverse genotypes i.e. HSF-242 (Cluster I), S-05-US-307 (Cluster II), S-03-
US-694 and S-05-FSD-317 (Cluster IV) and S-03-US-127 (Cluster V) were
identified with superior morphological traits. These genotypes can be used as parent
for breeding programmes in sugarcane. Simple Sequence Repeat based genetic
diversity analysis depicted 50.1% variability in the material surveyed and four
genotypes (S-03-US-694, S-05-FSD-307, S-08-FSD-19, HSF-240 and S-03-SP-93)
were identified which may be utilized in future hybridization program of sugarcane.
All the varieties showed good response to callus induction at 3mg/L 2, 4-D
supplemented in MS media. Irradiation of callus showed poor response to
regeneration and maximum mortality in all varieties except S-05-US-54 at 10 Gy
level. It is suggested that irradiation of callus in sugarcane is not suitable for mutation
induction. Survival percentage of somaclones after hardening was recorded to be
33.3% while after field transplantation it was 60%. Somaclones showed considerable
magnitude of SSR based polymorphism. Genetic integrity assessment of candidate
genes in somaclones revealed intact nucleotide sequences however, some SNPs were
detected in somaclones raised from irradiated callus. Somaclones showed negligible
concentration of SCMV with variable disease reaction against red rot. Increase in
number of internodes with reduced length and high brix percentage was recorded in
somaclones as compared to their parental clones. It is concluded that somaclonal
variation is a good source of variability induction in the sugarcane.
164
GENERAL SUMMARY
Twenty sugarcane genotypes were evaluated for genetic divergence on the
bases of some morpho-physological traits. The experiment was conducted for two
years under irrigated condition at Arja Bagh, Azad Kashmir. Parameters recorded at
maturity included; plant height (cm), number of tillers per plant, stem girth (cm),
number of nodes, inter-nodes length (cm), numbers of leaves, leaf area (cm2), brix
percentage, reducing sugar (mg/ml) and non-reducing sugar (mg/ml).
Analysis of variance revealed highly significant differences among the
genotypes. Multivariate data analysis techniques including Principal Component
Analysis and cluster analysis were performed. Principal Component Analysis
depicted 54.63% cumulative variance in genotypes under study and biplot diagram
for PC1 and PC2 in PCA and hierarchal and non-hierarchal cluster analysis revealed
similar genotyping pattern. Genotype HSF-242 from cluster I and genotype S-03-
US-127 from Cluster V showed maximum genetic distance (8). Genotype S-05-US-
307 from Cluster II and from Cluster IV genotypes S-03-US-694 and S-05-FSD-
revealed Euclidian Distance 5. These genotypes can be used for hybridization
programmes.
Genetic diversity on molecular level was assessed by using 49 SSR markers
for identification of diverse genotypes for future breeding programmes in sugarcane.
Genomic DNA was isolated from young leaves with standard protocol and PCR was
conducted by using SSR primer and PAGE gel was done. Data for genetic similarity
coefficient, number of alleles. Polymorphic information content, polymorphism
percentage and diversity index were calculated. Cluster analysis following UPGMA
was conducted to assess the genetic similarity among genotypes while Principal
Coordinate Analysis was conducted to estimate the genetic variation.
165
A total of 420 SSR alleles were identified with a mean polymorphism of
89.12% estimated for all markers. The total number of alleles generated by any single
SSR primer pair ranged from 3 to 22. Polymorphic information content estimated to
be ranged from 0.0 to 0.728 while diversity index value ranged from 0.60 to 0.95.
PCoA; depicted 50.1% variability in tested genotypes and four genotypes i.e. S-03-
US-694, S-05-FSD-307, S-08-FSD-19, HSF-240 and S-03-SP-93) were identified
which may be used for future hybridization programme in sugarcane.
For variability induction in the material, somaclones were developed from six
sugarcane varieties namely; S-03-SP-93, S-05-US-54, S-03-US-694, S-06-US-300,
HSF-240 and SPF-213. Callus induction on MS media supplemented with different
concentration levels of 2, 4 D (i.e. control, 1mg/L, 3mg/L, 5mg/L and 7mg/L). All
the varieties showed good response to callus induction at 2, 4 D level 3mg/L. One set
of callus from all varieties was subjected to irradiation at different levels of gamma
rays (10 Gy, 20 Gy, 30 Gy and 40 Gy) that showed poor response to regeneration
and lead to mortality in all varieties except variety S-05-US-54 at 10 Gy level. A total
of 671 somaclones were developed from six varieties from subculturing of callus at
3mg/L. The overall survival percentage of somaclones after hardening was 33.3%
with maximum survival percentage 40.9% in S-03-SP-93 while minimum 25.5%
somaclones survived from S-05-US-54. Survival percentage after field
transplantation was 60% with maximum 37% somaclones survived from SPF-213
and minimum 5.4% survival rate was recorded from S-06-US-300.
For detection of somaclonal variations, ten highly polymorphic SSR primers
were utilized. Polymorphism percentage in somaclones was estimated in the range
from 29 to 51 percent, somaclones raised from varieties HSF-240 and SPF-213
showed high polymorphism (51.2% and 40.6%, respectively). Principal coordinated
166
analysis was done to estimate the genetic variance and genetic distance among
somaclones and their parental clones. Cumulative percentage variation ranged from
71.12% to 91.21%. Maximum variation was observed in somaclones of variety S-06-
US-300 (91.21%) followed by SPF-213 (82.50%) and HSF-240 (80.89%).
Genetic integrity analysis of some important candidate genes was done that
included catalase, sucrose phosphate synthase, gibberellin 2-oxidase 4 and teosinte
branched1 (referred as CAT1, SPS, GA2 oxidase 4 and TB1). Nucleotide sequences
of these genes were searched on sorghum gene database (Phytozome database
version 9.0. www.http://phytozome.jgi.doe.gov). Intron and exon boundaries of these
sequences were identified and only exon, the coding sequences were used for primer
synthesised with maximum coverage and then PCR amplification was done on
sugarcane genomic DNA and expected band sizes were amplified, gel purified,
sequenced and pairwise sequence alignments were made with sorghum candidate
genes sequences. Sequenced reads of somaclones and their parental clones were
aligned and SNPs were searched that showed intact nucleotide sequences as with
their parental clones in case of somaclones raised from sub-culturing of callus with
2, 4 D while some SNPs were detected in somaclones raised from irradiated callus.
Somaclones showed minute concentration of SCMV and variable resistant
response against red rot, except somaclones of variety S-03-SP-93 while rest of
others varieties were indicated maximum resistance. Increase in number of
internodes and reduced internodes length with high brix percentage was observed in
somaclones as compared to their parental clones hence, selection in the succeeding
generations will be beneficial. It is concluded that somaclonal variation is a good
source of variability induction in the sugarcane.
LITERATURE CITED
167
Chapter: 05
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