PATTERN OF GENETIC DIVERGENCE AND EXPLOITATION OF

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 ___________________________


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


3.3. 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


3.4.1. RESULTS

3.4.2. DISCUSSION


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


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


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 2.7 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


reads obtained from parental clone of HSF-240 and

its 5 somaclones; SC20, SC21, SC22, SC23

andSC24 showed no SNPs.

145


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


73

Picture 3.6 PCR products of primer P-101. 73


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


161

Graph 4.12 Mean values of brix percentage in somaclones and


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.


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


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


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.


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,


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.


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).


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).


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


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-


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


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.


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).


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.


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


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


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


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


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


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.


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%.


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


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


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.


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,


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.


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.


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


9 S-06-US-300 Canal Point, America Not known Not known

10 S-03-SP-93 Sao Paulo, Brazil 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



20 HSF-240 Sindh, Pakistan CP -43-33 open

pollination


27

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


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


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.


30

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


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


32


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.


33

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


34

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


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.


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.


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.


38

Fig 2.3: Loading of PC1.

Fig 2.4: Loading of PC2s.


39


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.


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.


40




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.


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.


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.


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


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.


46

Fig.2.8: Cluster Diagram of 20 Sugarcane Genotypes on the basis of morpho-

physological traits.


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


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


49


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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50

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


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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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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3.3.1. 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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63

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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64

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.


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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67


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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68

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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69

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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70

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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71

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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73

Picture.3.4: PCR products of primer P-89.



Where,



272; 12. S-03-US-127; 13. S-06-US-658; 14. S-03-US-778; 15. S-05-FSD-317; 16.


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Picture.3.8: PCR products of primer SMs037.

Picture.3.9: PCR products of primer SMs009.

Where,



272; 12. S-03-US-127; 13. S-06-US-658; 14. S-03-US-778; 15. S-05-FSD-317; 16.


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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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78

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

MOLECULAR STUDIES

79

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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81

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.


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


83

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


84

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.,


86

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.


87


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


90

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


92

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


93

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


94

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.


95

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


96

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%).


97

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


99

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


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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4.3.1. 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


103

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


105

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


106

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.


107

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.


109

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


110

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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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.


113

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


114

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


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


115

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.


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.).


116

Chapter: 4


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


117

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


118

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.


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


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


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


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.


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.


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


(10Gy)

Su

rviv

al

%a

ge

Somaclones

Survival %age after hardening Survival %age after transplantation


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


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


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).


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.


(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


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.


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


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


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


PCoA-2 0.004 14.729


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


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).


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

http://www.http/phytozome.jgi.doe.gov


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


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

http://www.ncbi.nlm.nih.gov/


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.


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.


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


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


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.


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.


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.


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.


145


parental clone of HSF-240 and its 5 somaclones; SC20, SC21, SC22, SC23

andSC24 showed no SNPs.


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.


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.


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


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


(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


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


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.


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


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.


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


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


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


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.


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.


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


(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


(10GY)

No

. o

f ti

ller

s p

er p

lan

t

Somaclones

NUMBER OF TILLERS


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


158

Graph 4.9: Mean values of stem diameter of somaclones and their parental clones.


Graph 4.10: Mean values of number of internodes per plant of somaclones and



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


(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


(10GY)

No

. o

f n

od

es

Somaclones

NUMBER OF INTERNODES


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


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.


161

Graph 4.11: Mean values of internodes length of somaclones and their parental

clones.


Graph 4.12: Mean values of brix percentage in somaclones and their parental

clones.


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


(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


(10GY)

Bri

x %

ag

e

Somaclones

BRIX %age


162


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


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).


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

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