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EXPRESSION OF FLAVONOID PIGMENT RELATED
GENES IN COTTON (Gossypium hirsutum)
Ammara Ahad
CENTRE OF EXCELLENCE IN MOLECULAR BIOLOGY,
UNIVERSITY OF THE PUNJAB, LAHORE,
PAKISTAN.
(2018)
EXPRESSION OF FLAVONOID PIGMENT RELATED
GENES IN COTTON (Gossypium hirsutum)
A THESIS SUBMITTED TO
THE
UNIVERSITY OF THE PUNJAB
In Partial Fulfillment of the requirement for the Degree of
DOCTOR OF PHILOSOPHY
In
MOLECULAR BIOLOGY
By
Ammara Ahad
Supervisor:
Prof Dr. Tayyab Husnain
NATIONAL CENTRE OF EXCELLENCE IN MOLECULAR
BIOLOGY
UNIVERSITY OF THE PUNJAB
LAHORE, PAKISTAN
2018.
“God is the Light of the heavens and the earth. The parable of His light is,
as it were, that of a niche containing a lamp; the lamp is [enclosed] in glass,
the glass [shining] like a radiant star: [a lamp] lit from a blessed tree - an
olive-tree that is neither of the east nor of the west the oil whereof [is so bright
that it] would well-nigh give light [of itself] even though fire had not touched it:
light upon light! God guides unto His light him that wills [to be guided]; and
[to this end] God propounds parables unto men, since God [alone] has full
knowledge of all things.”
(Surah Noor ayah 35)
I
AUTHOR’S DECLARATION
I hereby state that my Ph.D. thesis entitled “Expression of Flavonoid Pigment related
Genes in Cotton (Gossypium hirsutum)” is my own work and has not been submitted by me
previously for taking any degree as research work, thesis or publication from University of
the Punjab or anywhere else in country/world.
At any time, if my statement is found to be incorrect even after my graduation, the
university has the right to withdraw my Ph.D. degree.
_______________
Signature of Deponent
Ammara Ahad
September, 2018
II
CERTIFICATE
It is to certify that the research work described in this thesis is the original work of the
author Ms. Ammara ahad and has been carried out under my direct supervision. I have
personally gone through all the data reported herein and certify their correctness/authenticity.
I have found that the thesis has been written in pure academic language and is free from any
typos and grammatical errors. It is further certified that the data reported in this thesis has not
been used in part or full, in a manuscript already submitted or in the process of submission in
partial/complete fulfillment of the award of any other degree from any other institution. It is
also certified that the thesis has been prepared under my supervision according to the
prescribed format of the university and I endorse its evaluation for the award of Ph.D. degree
through the official procedures.
In accordance with the rules of the Centre, data book (1119) is declared as un-
expendable document that will be kept in the registry of the Centre for a minimum of three
years from the date of thesis defense.
Signature of the Supervisor: __________________
Name: Prof Dr. Tayyab Husnain
Professor
III
PLAGIARISM UNDERTAKING
I solemnly declare that research work presented in the thesis titled “Expression of
Flavonoid Pigment related Genes in Cotton (Gossypium hirsutum)” is solely my research
work with no significant contribution from any other person. Small contributions/help
wherever taken, has been duly acknowledged and that complete thesis has been written by
me.
I understand the zero-tolerance policy of the Higher Education Commission of
Pakistan (HEC) and “University of the Punjab” towards plagiarism. Therefore, as an author
of the above titled thesis, I declare that no portion of my thesis has been plagiarized and any
material used as reference has been properly cited.
I undertake that if I am found guilty of any formal plagiarism in the above titled
thesis even after award of the Ph.D. degree, the university reserves the rights to withdraw/
revoke my Ph.D. degree and that HEC and the university has the right to publish my name
on the HEC/ university website on which names of students are placed who submitted
plagiarized thesis.
_______________
Signature of Deponent
Ammara Ahad
September, 2018.
IV
ACKNOWLEDGEMENTS
In the name of ALLAH, the Most Gracious and the Most Merciful
Almighty “ALLAH” The Lord of lords, Owner of divine Throne, All praises are for
Him, Who enabled me to seek knowledge and use for the benefit of mankind. Blessings
upon Holy Prophet “MUHAMMAD” (Peace be upon him), the source of guidance and
beacon of light for the mankind.
First of all deepest regards and thanks to my worthy supervisor, Prof Dr. Tayyab
Husnain, Acting Director, Centre of Excellence in Molecular Biology, University of the
Punjab, Lahore. Without his guidance it would be impossible to complete this research
project. His support enabled me to achieve my research goals.
Humble thanks goes with kind and worthy lab in-charge Plant Biotechnology
Laboratory, National Center of Excellence in Molecular Biology, University of the Punjab,
Dr. Abdul Qayyum Rao who dedicated himself in introducing scientific attitude among
students and taught us the art of scientific writings. He remained a great source of
encouragement in the entire study period.
I would like to express my sincere thanks to Dr. Ahmad Ali Shahid for his
generous advices during research studies. My deepest appreciation belongs to Dr. Idrees
Ahmad Nasir and Dr. Bushra Rashid for their valuable guidance in field study of my
research project.
There have been many people who walked besides me during last five years and
guided me. I pay heartiest gratitude to Dr. Naila Shahid who always manage time in her
busy schedule to guide me; and also pay gratitude to Ms. Ayesha Latif, Ms. Saira Azam,
Mr. Tahir Rehman Samiullah, Ms. Aneela Yasmeen, Dr Azmat Ullah Khan and Dr. Kamran
Shahzad Bajwa. I am thankful to my lab colleagues Mr. Salah ud din, Mr. Mukhtar Ahmad,
Mr. Muhammad Azam, Mr. Adnan Iqbal, Ms. Samina Hassan, Ms. Sana Shakoor, Mr. Tahir
Iqbal, Mr. Ibrahim Bala Salisu for their help and support.
V
I am truly thankful to my friends Ms. Rabia Nawaz, Ms. Ambreen Gul, Ms. Sidra
Akhtar, Ms. Amina Yaqoob and Ms. Khadija Aliya, Ms. Iqra Almas, Ms. Jaweryia and Ms.
Sayyeda Fatima Nadeem for their love, support and continuous help in all times.
Most importantly a tribute is to my parents for their financial and practical support.
Their eyes were long awaited to see me at this stage. I am also grateful to my siblings
Nasira Muhammad, Khalida Farooq and Ayesha Mudassara. A simple word “thanks”
cannot explain their efforts and love in words. How can I forget to thank my niece, Rabia
Afaq and I believe that she will fly higher, InshAllah.
I must also thank to every person who contributed in this accomplishment especially
my tailor, Mr Mansoor who stitch beautiful clothes for me and remain concerned through
his prays.
Lastly, thanks to my beloved husband Maroof Muhammad Mahmud for his
generous love, trust and support during the study.
In end, I am thankful to everyone who raises hands to pray for my success.
Ammara Ahad.
VI
Dedicated
To
My Parents
Abdul Ahad Khan
&
Adla Mehboob
VII
SUMMARY
Accumulation of anthocyanin pigments in plants not only involved in imparting the
colour in different plant parts but also acts as a great osmoregulator. The increase in turgor
pressure through positive osmoregulation can leads towards improvement in fiber
characteristics of cotton. Based on this fact, an effort was made in the current study to
improve fiber in local cotton variety by transforming flavonoid genes dihydroflavonol 4-
reductase (DFR) & Flavonoid 3’5’ hydoxylase (F3’5’H).
The DFR is an active enzyme of the flavonoid pathway and highly substrate specific.
Protein docking analysis revealed that proline rich region, amino acids at positions 12, 26 and
132-157 in Iris as well as Gossypium based DFRs were not involved in determining substrate
preference but a play role in substrate attachment and anthocyanin production.
The F3’5’H enzyme is known for synthesis of 3’, 5’- hydroxylated anthocyanins.
Protein docking results showed the best binding energies of Viola F3’5’H with ligands i-e -
7.6 (naringenin) & -8.3 (quercetin), revealing its greater capability to reduce substrates and
produce anthocyanins as compared to Gossypium F3’5’H which has binding affinities -7.9
(naringenin) and -7.4 (quercetin).
Plant expression vector pCAMBIA-1301 was constructed with F3’5’H and DFR
genes for cotton transformation. The excision of 4032 bp and 11000 bp bands from
pCAMBIA-F3’5’+DFR through restriction digestion with KpnI and XbaI enzyme confirmed
successful ligation of both genes in plant expression vector. After the confirmation of F3’5’H
and DFR genes ligation in pCAMBIA1301, the recombinant plasmid (pCAMBIA-
F3’5’+DFR) was electroporated in Agrobacterium (LBA4404) cells by using electroporation
VIII
device. The amplification of 476 bp and 537 bp through Agrobacterium colony PCR revealed
introduction of recombinant plasmid in Agrobacterium.
The cotton variety, VH-319 embryos were subjected to inoculation with
Agrobacterium containing both genes and the cotton plantlets developed from the embryos
were subjected to confirmation of transgenes. Amplified products of 476 bp and 537 bp from
extracted genomic DNA confirmed successful integration of transgenes in cotton plants.
Further signal obtained through hybridization of gene specific probe on nitrocellulose
membrane in DNA dot blot assay also validated the presence of both genes in transgenic
cotton plants. Overall transformation efficiency was calculated to be 2.1%.
The mRNA expression level of F3’5’H and DFR genes was measured to be 1.0-5.3
and 1-4 fold higher in leaves and 1-3 fold higher in fiber of transgenic cotton plants
respectively as compared to non-transgenic control cotton plants through quantitative Real
Time PCR. Similarly, gene integration revealed single copy number of transgene F3’5’H and
DFR on chromosome number 16 when subjected to fluorescent in situ hybridization (FISH)
and its Karyotyping.
Quantitative estimation of anthocyanin contents in transgenic cotton lines was
undertaken by pH differential method. Maximum obtained anthocyanin concentration was in
range of 1.79 µg/g to 1.0 µg/g. The anthocyanins produced in transgenic cotton plants,
though did not impart any phenotypic change but have shown a positive impact on other
physical properties of fiber particularly length and strength. Fiber data analysis showed
significant improvement in staple length which was found to be increased from 26.3 mm to
31.6 mm (20.1%), fiber strength ~ 23.8 to 32.4 g/tex (32.7%), uniformity index ~ 82-86
(5.2%) and the micronaire value was found to be improved from 4 to 3.2 µg in transgenic
IX
cotton plants. Electron microscopic examination showed that transgenic cotton fibers possess
greater number of twists in addition to smooth and compact surfaces as compared to non
transgenic control cotton plant.
A positive correlation of transgene was found with physiology of transgenic cotton
plants like maximum photosynthetic and evaporation rate along gaseous exchange in
transgenic cotton plant which was recorded to be 6.5 µmol/m2/s, 6.55 mmol/m
2/s and 154
mmol/m2/s respectively as compared to 3.2 µmol/m
2/s, 1.67 mmol/m
2/s and 54 mmol/m
2/s in
non transgenic cotton plants. Morphological traits like plant height were found as
independent factor with respect to monopodial and sympodial branches. Two other key
characters i-e boll and lint weight showed positive significant correlation according to
Pearson correlation. The study resulted in provision of unique information for better
utilization of this trait in molecular breeding program which in combination with other fiber
trait will provide a great breakthrough to cotton growers and to textile industry in specific for
saving their import losses.
X
LIST OF ABBREVIATIONS
TAC Total anthocyanin contents
bp base pair
DF dilution factor
CaCl2 Calcium chloride
CV Column volume
cm Centimeter
MW Molecular weight
CTAB cetyltrimethylammounium bromide
dH2O Distilled water
DMSO Dimethyl sulfoxide
DNA Deoxyribonucleic Acid
dNTPs Dinucleotide Triphosphate
E. coli Escherichia coli
EDTA Ethylene Diamine Tetra Acetic Acid
ELISA Enzyme Linked Immune Sorbent Assay
et al. (et alii) and others
G Gram
GOT Ginning out-turn
Na2HPO4 Disodium hydrogen phosphate
H2O Water
HCl Hydrochloric acid
HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid
HgCl2 Mercuric chloride
XI
IBA Indole Butyric Acid
i.e. That is
Kb Kilo base
Kg Kilo gram
KDa Kilo Daltons
KCl Potassium Chloride
L Liter
LB Luria Broth
Min Minutes
mm Millimeter
mg Milligram
ml Milliliter
mm Milli meter
M Molar
MS Murashige and Skoog
NaCl Sodium chloride
NaOH Sodium Hydroxide
No. Number
nm Nanometer
ng Nano gram
OD Optical Density
PCR Polymerase Chain Reaction
pmol Pico moles
pH Negative log of hydrogen ions
Pfu Pyrococcus furiosus
XII
qRT-PCR Quantitative Real Time Polymerase Chain Reaction
RNA Ribonucleic Acid
RNase Ribonuclease
DPA Days post anthesis
NADPH Nicotinamide adenine dinucleotide phosphate
rpm Rotations per minute
SDS Sodium dodecyl sulfate
Sec Seconds
TAE Tris-acetate EDTA
Taq Thermus aquaticus
Tm Temperature
U Unit
UV Ultra violet
V Volts
YEP Yeast extract peptone
% Percent
C Degree centigrade
µg Microgram
µl Microliter
XIII
TABLE OF CONTENTS
AUTHOR’S DECLARATION ............................................................................................... I
CERTIFICATE ...................................................................................................................... II
PLAGIARISM UNDERTAKING ....................................................................................... III
ACKNOWLEDGEMENTS ................................................................................................. IV
SUMMARY ......................................................................................................................... VII
LIST OF ABBREVIATIONS ............................................................................................... X
TABLE OF CONTENTS .................................................................................................. XIII
LIST OF FIGURES ........................................................................................................ XVIII
LIST OF TABLES ............................................................................................................... XX
CHAPTER 1 : INTRODUCTION ......................................................................................... 1
CHAPTER 2 : REVIEW OF LITERATURE ...................................................................... 8
2.1. BACKGROUND OF COTTON CROP ......................................................................... 8
2.2. SOCIO-ECONOMIC IMPACT OF COTTON IN PAKISTAN .................................... 9
2.3. CHARACTERISTICS OF COTTON FIBER .............................................................. 10
2.4. MODIFICATIONS IN FIBER TRAITS AT MOLECULAR LEVEL ........................ 11
2.5. NATURAL PROTECTIVE PIGMENTS IN PLANTS ............................................... 14
2.6. FLAVONOIDS BIOGENESIS .................................................................................... 15
2.7. FLAVONOIDS LOCALIZATION .............................................................................. 17
2.8. GENETIC REGULATION OF FLAVONOID BIOSYNTHESIS .............................. 19
2.9. FLAVONOID PIGMENTS OF COTTON .................................................................. 21
2.10. BIOLOGICAL ROLES OF FLAVONOIDS IN COTTON CROP ........................... 22
2.10.1. FLAVONOIDS: A PIGMENT WITH MULTIPLE ROLES IN PLANT ........... 23
2.10.2. FLAVONOIDS: COTTON COLOURING AGENTS ........................................ 23
2.10.3. FLAVONOIDS; SHIELD AGAINST ABIOTIC STRESSES ............................ 24
2.10.3.1. Flavonoids; The Photo-protectors ................................................................. 25
2.10.3.2. Flavonoids; The Thermoregulators ............................................................... 26
2.10.3.3. Flavonoids; The Osmoregulators .................................................................. 27
2.10.4. ROLE OF FLAVONOIDS AGAINST BIOTIC STRESSES ............................. 28
2.11. FLAVONOIDS ROLE IN MODIFYING COTTON FIBER .................................... 31
XIV
CHAPTER 3 : MATERIALS AND METHODS ............................................................... 34
3.1 RETRIEVAL OF DFR AND F3’5’H GENES SEQUENCES ..................................... 34
3.2 IN-SILICO ANALYSIS OF DFR & F3’5’H GENES .................................................. 34
3.2.1. MOLECULAR DOCKING OF DFR GENE ........................................................ 35
3.2.1.1. Determination of Substrate Binding Region among Different Plant Species: 35
3.2.1.2. Modeling of Receptor Molecules for Docking Analysis ................................ 36
3.2.1.3. Refinement and Evaluation of DFR Protein Model ........................................ 36
3.2.1.4. Ligand Preparation .......................................................................................... 37
3.2.1.5. DFR Protein and Ligand Docking Analysis ................................................... 37
3.2.2. MOLECULAR DOCKING OF F3’5’H GENE .................................................... 38
3.2.2.1. Sequence Alignment and Primary Analysis ................................................... 38
3.2.2.2. Secondary Structure Prediction....................................................................... 39
3.2.2.3. Template Selection.......................................................................................... 39
3.2.2.4. Sequence Alignment ....................................................................................... 39
3.2.2.5. Three-Dimensional (3D) Model Prediction .................................................... 40
3.2.2.6. Energy Minimization ...................................................................................... 40
3.2.2.7. Validation of Predicted Model ........................................................................ 40
3.2.2.8. Prediction of Ligand Binding Sites ................................................................. 41
3.2.2.9. F3’5’H Docking Analysis ............................................................................... 41
3.3 FLAVONOID CONSTRUCT DESIGN ....................................................................... 42
3.4 IN-SILICO DESIGNING OF CONSTRUCT IN pCAMBIA1301............................... 43
3.5 CHEMICAL SYNTHESIS OF FLAVONOID CONSTRUCT .................................... 43
3.6 PREPARATION OF COMPETENT CELLS (E. coli, Top10 strain) .......................... 45
3.7 TRANSFORMATION OF pUC- F3’5’H & DFR IN E. coli ........................................ 45
3.8 PLASMID ISOLATION ............................................................................................... 46
3.9 CONFIRMATION OF PLASMID BY AMPLIFICATION AND RESTRICTION
DIGESTION........................................................................................................................ 47
3.9.1 PCR AMPLIFICATION OF F3’5’H & DFR GENES ........................................... 47
3.9.2 RESTRICTION ANALYSIS ................................................................................. 47
3.10 CLONING OF F3’5’H & DFR IN pCAMBIA1301 ................................................... 48
3.10.1 GEL ELUTION .................................................................................................... 49
XV
3.10.2 LIGATION OF INSERT (F3’5’H & DFR) IN PCAMBIA-1301 VECTOR ....... 49
3.11 SCREENING OF TRANSFORMED COLONIES ..................................................... 50
3.11.1 DETERMINATION OF FLAVONOID CASSETTE BY RESTRICTION
DIGESTION .................................................................................................................... 50
3.12 AGROBACTERIUM COMPETENT CELLS PREPARATION ................................. 51
3.13 ELECTROPORATION OF RECOMBINANT PLASMID INTO THE
AGROBACTERIUM COMPETENT CELLS ...................................................................... 51
3.14 CONFIRMATION OF pCAMBIA (F3’5’H & DFR) IN AGROBACTERIUM .......... 52
3.15 TRANSFORMATION OF F3’5’H & DFR IN COTTON (Gossypium hirsutum) VAR.
VH-319 ................................................................................................................................ 52
3.15.1 PREPARATION OF PLANT MATERIALS ....................................................... 52
3.15.1.1 Delinting Cotton Seeds .................................................................................. 52
3.15.1.2 Seeds Surface Sterilization and Germination ................................................ 53
3.15.1.3 Embryos Isolation .......................................................................................... 53
3.15.1.4 Agrobacterium Inoculum Preparation............................................................ 53
3.15.1.5 Cotton Transformation Experiments.............................................................. 54
3.15.1.6 Infection Period .............................................................................................. 54
3.15.1.7 Co-cultivation Period ..................................................................................... 54
3.15.1.8 Shoot Induction Media ................................................................................... 54
3.15.1.9 Calculation of Transformation Efficiency ..................................................... 55
3.15.1.10 Shifting of Putative Transgenic Cotton Plants to Pots ................................. 55
3.16 MOLECULAR ANALYSIS OF TRANSGENIC COTTON PLANTS ..................... 55
3.16.1 GENOMIC DNA EXTRACTION ....................................................................... 56
3.16.2 PCR CONFIRMATION OF PUTATIVE TRANSGENIC COTTON PLANTS . 56
3.16.3 DOT BLOT HYBRIDIZATION ASSAY ............................................................ 57
3.16.3.1 Probe Labeling ............................................................................................... 57
3.16.3.2 Hybridization & Washings ............................................................................ 57
3.16.3.3 Immunological Detection of Probe ................................................................ 58
3.16.4 EXPRESSION ANALYSIS OF TRANSGENIC COTTON PLANTS ............... 59
3.16.4.1 RNA Extraction ............................................................................................. 59
3.16.4.2 cDNA Synthesis ............................................................................................. 60
3.16.4.3 Primer Design ................................................................................................ 61
XVI
3.17 ANTHOCYANIN CONTENTS ASSAY ................................................................... 62
3.17.1. SAMPLE PREPARATION ................................................................................. 63
3.17.2. ESTIMATION OF ANTHOCYANIN CONTENT ............................................ 63
3.18. DETERMINATION OF COTTON FIBER QUALITY ............................................ 64
3.19. ELECTRON MICROSCOPIC ANALYSIS OF COTTON FIBER SURFACES ..... 64
3.20. AGRONOMIC TRAITS ............................................................................................ 64
3.21. FLUORESCENCE IN SITU HYBRIDIZATION (FISH) ......................................... 65
3.21.1 PREPARATION OF CHROMOSOME ............................................................... 65
3.21.2 RNASE TREATMENT ........................................................................................ 65
3.21.3 HYBRIDIZATION ............................................................................................... 66
3.21.4 POST HYBRIDIZATION .................................................................................... 66
3.21.5 CHROMOGENIC DETECTION REACTION .................................................... 66
3.21.6 COUNTERSTAINING WITH DAPI ................................................................... 66
3.21.7 COUNTERSTAINING WITH PROPIDIUM IODIDE (PI) ................................ 67
3.21.8 SIGNAL DETECTION ........................................................................................ 67
CHAPTER 4 : RESULTS .................................................................................................... 68
4.1 BIOINFORMATICS ANALYSIS OF DFR ................................................................. 68
4.1.1 COMPARISON OF DFR REPORTED RESIDUES INVOLVED IN
SUBSTRATE SPECIFICITY.......................................................................................... 68
4.1.2 ROLE OF Asn AND Asp TYPE DFRS IN SUBSTRATE SPECIFICITY ........... 69
4.1.3 MODELING, REFINEMENT, EVALUATION AND VALIDATION OF DFR
PROTEIN ........................................................................................................................ 72
4.1.4 PROTEIN-LIGAND DOCKING RESULTS ......................................................... 72
4.2 BIOINFORMATICS WORK ON F3’5’H GENE ........................................................ 78
4.2.1 SEQUENCE HOMOLOGY & STRUCTURE PREDICTIONS............................ 78
4.2.2 VALIDATION OF REFINED MODELS .............................................................. 78
4.2.3 F3’5’H BINDING SITES IN VIOLA & GOSSYPIUM .......................................... 85
4.2.4 PROTEIN-LIGAND DOCKING ANALYSIS ...................................................... 85
4.3 FLAVONOID GENES DESIGN AND CONSTRUCTION ........................................ 88
4.4 IN-SILICO CLONING OF FLAVONOID CONSTRUCT IN BINARY PLASMID .. 88
4.5 CONFIRMATION OF SYNTHESIZED EXPRESSION CASSETTE IN pUC57 ...... 90
XVII
4.5.1 BY PCR .................................................................................................................. 90
4.5.2 BY RESTRICTION DIGESTION ......................................................................... 91
4.6 CLONING OF F3’5’H & DFR GENES IN PLANT EXPRESSION VECTOR .......... 91
4.7 CONFIRMATION OF CONSTRUCT IN AGROBACTERIUM .................................. 93
4.8 GENERATION OF PUTATIVE TRANSGENIC COTTON PLANTS ....................... 94
4. 9 MOLECULAR ANALYSIS OF TRANSGENIC COTTON PLANTS ...................... 97
4.9.1 SCREENING OF PUTATIVE TRANSGENIC COTTON PLANTS THROUGH
PCR IN T0 GENERATION ............................................................................................. 97
4.9.2 CONFIRMATION OF TRANSGENE INTEGRATION BY DOT BLOT IN T0
GENERATION ............................................................................................................... 99
4.9.3 CONFIRMATION OF F3’5’H AND DFR GENES BY PCR IN T1
GENERATION ............................................................................................................. 100
4.9.4 INTEGRATION OF F3’5’H & DFR GENES BY DOT BLOT IN T1
GENERATION ............................................................................................................. 100
4.9.5 TRANSCRIPTIONAL ANALYSIS OF F3’5’H AND DFR GENES ................. 103
4.10 ESTIMATION OF ANTHOCYANIN PIGMENTS ................................................. 106
4. 11 PHENOTYPIC MODIFICATIONS IN TRANSGENIC COTTON LINES ........... 108
4.12 FIBER QUALITY PARAMETERS ......................................................................... 108
4.13 ELECTRON MICROSCOPIC FIBER EXAMINATION ........................................ 115
4.14 MORPHOLOGICAL & PHYSIOLOGICAL CHARACTERS ANALYSIS ........... 116
4.15 FLUORESCENCE IN SITU HYBRIDIZATION ANALYSIS................................ 119
CHAPTER 5 : DISCUSSION ............................................................................................ 121
REFERENCES .................................................................................................................... 133
APPENDICES ..................................................................................................................... 157
PUBLICATIONS ................................................................................................................ 163
XVIII
LIST OF FIGURES
Figure 2-1: Types of potential environmental stresses for plant ........................................... 30
Figure 2-2: An overview of flavonoid responses against different environmental stresses .. 31
Figure 3-1: Illustration of Flavonoid construct in pUC57 ..................................................... 43
Figure 3-2: Diagrammatic representation of pCAMBIA1301 ............................................... 44
Figure 4-1: Alignment of the amino acid sequences ............................................................. 69
Figure 4-2: Multiple sequence alignment of dihydroflavanol 4-reductase. .......................... 70
Figure 4-3: Three dimensional DFR protein model of Gossypium hirsutum ....................... 73
Figure 4-4: Three dimensional DFR protein model of Iris hollandica ............................. 73
Figure 4-5: Ramachandran plot analysis of Iris hollandica model .................................... 74
Figure 4-6: Ramachandran plot analysis of Gossypium hirsutum protein model .................. 75
Figure 4-7: Two and three dimensional interaction diagrams of DFR Iris hollandica with
dihydroflavolnols. ................................................................................................................... 76
Figure 4-8: Two and three dimensional interaction diagrams of Gossypium hirsutum with
dihydroflavolnols. ................................................................................................................... 77
Figure 4-9: Consensus amino acid sequences alignment of F3’5’H ..................................... 79
Figure 4-10: Predicted Secondary structure for Viola wittrockiana .................................. 80
Figure 4-11: Predicted Secondary structure for Gossypium hirsutum ................................... 81
Figure 4-12: a) 3D models of Viola wittrockiana predicted by I-TASSER (b) 3D models
of Gossypium hirsutum predicted by I-TASSER .................................................................... 82
Figure 4-13: Ramachandran plot analysis of Viola wittrockiana F3’5’H model .............. 83
Figure 4-14: Ramachandran plot analysis of Gossypium hirsutum F3’5’H protein model ... 84
Figure 4-15: Predicted ligand binding sites of a) Viola and b) Gossypium highlighted ........ 85
Figure 4-16: Docking analysis of Viola wittrockiana and Gossypium hirsutum .............. 87
Figure 4-17: Graphs of Codon Adaptation index (CAI) of F3’5’H gene sequence ............ 88
Figure 4-18: Graphs of Codon Adaptation index (CAI) of the DFR gene sequence ............ 89
Figure 4-19: Schematic representation of binary vector constructed for cotton fiber
modification ............................................................................................................................ 89
Figure 4-20: Confirmation of Flavonoid genes (DFR & F3’5’H) in pUC57 through PCR .. 90
Figure 4-21: Confirmation of DFR & F3’5’H construct in pUC57 by Restriction digestion 91
XIX
Figure 4-22: Cloning and confirmation of Flavonoid construct in plant expression vector .. 92
Figure 4-23: Agrobacterium colonies harboring plasmid (pCAMBIA-Flavonoid construct) 93
Figure 4-24: Confirmation of DFR and F3’5’H genes in Agrobacterium colonies............... 94
Figure 4-25: Agrobacterium mediated transformation methodology to generate cotton
transgenic plants...................................................................................................................... 95
Figure 4-26: Confirmation of F3’5’H and DFR genes in putative transgenic plants of T0
generation ................................................................................................................................ 98
Figure 4-27: Dot blot analysis to determine F3’5’H and DFR genes integration ................. 99
Figure 4-28: Confirmation of F3’5’H & DFR genes in transgenic plants of T1 generation .101
Figure 4-29: Detection of F3’5’H and DFR genes in T1 generation by Dot blot assay ....... 102
Figure 4-30: qRT-PCR based study to quantify the expression of flavonoid genes............ 104
Figure 4-31: qRT-PCR based study to quantify the expression of flavonoid genes ............ 105
Figure 4-32: Anthocyanin extracts from leaves quantified at pH 0.8 and pH 3.5. .............. 107
Figure 4-33: Anthocyanin accumulation in young leaves of transgenic cotton lines
determined spectrophotometrically at 530 nm. ..................................................................... 107
Figure 4-34: Fiber length in transgenic cotton lines and non transgenic control line ......... 110
Figure 4-35: Comparison of different fiber characteristics of different cotton transgenic
plants with control in T0 progeny.......................................................................................... 112
Figure 4-36: Fiber parameters in non transgenic cotton control and transgenic cotton lines
............................................................................................................................................... 114
Figure 4-37: Scanning electron microscopic images of the surfaces of mature fibers ...... 115
Figure 4-38: Fluorescence in situ hybridization (FISH) of the Flavonoid construct ........... 120
XX
LIST OF TABLES
Table 2-1 : Major Biological Plant Pigments with Types ...................................................... 14
Table 3-1: Primers used in PCR ............................................................................................. 47
Table 3-2: Primers used in RT-PCR ...................................................................................... 61
Table 4-1: Amino acid percentage in both Gossypium hirsutum and Iris hollandica (Asn,
9: Asp, 23) by using Protparam tool ..................................................................................... 71
Table 4-2: ProtParam tool analysis of Viola wittrockiana & Gossypium hirsutum. Amino
acid (AA).Grand average of hydropathicity (GRAVY), Instability index (II), Aliphatic index
(AI) .......................................................................................................................................... 82
Table 4-3: Binding energies of compounds interaction computed by Auto Dock/vina ......... 86
Table 4-4: Germination index of local Cotton Variety, VH-319 ........................................... 96
Table 4-5: Experimental data for Flavonoid construct (F3’5’H & DFR) Transformation in
VH-319 ................................................................................................................................... 96
Table 4-6: Anthocyanin Quantification of Transgenic Cotton plant samples of T1 generation
............................................................................................................................................... 106
Table 4-7: Fiber Analysis of Transgenic Cotton plants with Flavonoid genes of T0 Progeny
............................................................................................................................................... 109
Table 4-8: CCRI Fiber Analysis of Transgenic Cotton lines of T1 Progeny. ...................... 109
Table 4-9: Co-relation matrix among Morphological and Physiological characteristics
among transgenic cotton lines & non transgenic control cotton lines……………………118
1
CHAPTER 1 : INTRODUCTION
Textile industry being the most important economic sector in Pakistan, contributes
8.5 percent to the GDP (Gross domestic production) and about 55 percent to foreign
exchange earnings of the country (Economic Survey of Pakistan, 2016-17). According to the
economic survey of Pakistan for year 2016–2017, an area of 2489 thousand hectares is
under cotton cultivation (Economic Survey of Pakistan, 2016-17). Annual cotton production
of world is about 26.84 million tons over an area of 30 to 36 million hectares (Nix et al.,
2017).
Cotton fiber is the main natural raw material in textile sector and constitutes 80% in
exported clothing products. Total export earnings of country from textile sector are
consisted of US$14 billion (Ahad et al., 2018). Staple length and strength are two major
quality defining factors. The processing of fabric is highly dependent upon fiber quality.
Unfortunately, in Pakistan the quality of cultivated cotton fiber does not meet the demand of
textile industry in terms of length and micronaire value. To cope with the need of hour,
Pakistan has to import nearly 55,000 tons of long length fiber which cost about US$ 157
million per year. During current year 2018, about 20,000 bales of cotton are expected to
import from neighboring country, India (Ahmed et al., 2018). Besides economic issues,
Pakistan textile sector is also facing social and environmental challenges like processing of
textile wastewater. Moreover, effluents of chemicals and dyes used in fabric manufacturing
2
cause serious environmental and health issues. Therefore, need is to introduce eco-friendly
textile products which on long term has no negative impact on our ecosystem.
Cotton fiber is an elongated singular cell originated from ovule epidermis and made
up of four over lapping developmental stages. These stages consisted of initiation phase (3–
0 DPA), elongation phase (1–25 DPA), secondary cell wall deposition phase (16–40 DPA)
and maturation phase (40–50 DPA) (Tiwari and Wilkins, 1995). The length and fineness of
lint is highly determined during initiation as well as elongation phase. Transcriptome study
has revealed that transcription factors such as WRKY and MYB along genes involved in
gibberellins, ethylene, auxin, abscisic acid, brassinosteroid acid and other metabolic
pathways play important role in cellular development of fiber (Samuel et al., 2006). Cotton
fiber development is under control of multiple genes network; though the lack of knowledge
at molecular level about structural and regulatory genes that control lint development is a
major barrier in improving its traits.
Various genetic strategies are known for modification in chemical and physical traits
of cotton fiber. Existing lint characteristics, such as length and strength, can be enhanced by
another plausible strategy. This approach is based on identification of already characterized
genes from bacteria, plants or animals, which may have the ability to modify lint, either by
producing new enzymes to utilize existing substrates or synthesizing structural proteins or
enzymes that create new substrates and new products. In this regard, metabolic engineering
of flavonoid biosynthetic pathway in cotton can be a useful approach to modify fiber. A
recent study based on functional classification of differentially expressed genes in extra-
long fiber revealed the expression of flavonoid biosynthetic pathway structural genes during
elongation phase (Qaisar et al., 2017). Most importantly, flavonoids act as auxin
3
modulators. These facts show that flavonoid pathway engineering in cotton may enhance
fiber characteristics such as quality and colour by inducing new traits.
Coloured cotton is defined as fiber having natural colouration. Naturally, coloured
cotton is superior to white cotton with respect to less dyeing steps involved in fabric
manufacturing. It could also eliminate the dyeing expenses and dye based toxic waste
disposal (Yatsu et al., 1983; Dickerson et al., 1999; Dutt et al., 2004). Secondly, major
pollutants in cotton industry are the waste discharges from the dying processes, leaving
hazardous effects on human health (Qiu, 2004). Cotton is bleached before dying which
require heavy metal mordant for adhering of dyes to the fabric. Today, chemicals used in
dying process are highly toxic, carcinogenic or even explosive. They include Azo dyes and
chemicals such as dioxin (hormone disrupter and carcinogen), lethal heavy metals like
copper, chrome, zinc-based carcinogens and formaldehyde etc. In the textile dye procedure,
2 to 20% of dyes are released as wastewater sewages leaving a severe hazard to the aquatic
life (Zaharia et al., 2009). About 15104 tons of dyes are annually discharged in the
surroundings (Gupta and Suhas, 2009; Foo and Hameed, 2010). Such toxic effluents can
cause mutagenic and carcinogenic effects on human and animals health (Almasian et al.,
2015).
Currently, various technologies have been interrogated to decolorize textile elutes.
Naturally coloured cotton is considered as environmental friendly option to protect human
health and environment in the current era (Murthy, 2001). Available naturally coloured
cotton varieties are in green and brown shades but unfortunately its textile market is limited
due to poor fiber quality, lower yield and monotonous colour (Feng et al., 2011). Therefore,
4
considering the eco-friendly nature of coloured cotton the researchers are motivated to
develop genetically modified coloured cotton with enhanced fiber traits.
On other hand, new cultivars having natural colour pigments in cotton cannot be
produced by conventional breeding practices due to lack of germplasm of different coloured
cottons (Liu et al., 2018). However, the molecular occurrences leading to colour
development in fiber yet need to be identified; previously it was assumed that the colour of
cotton flower petals is driven from flavonoids (Feng et al., 2013). But the recent work on
cotton fiber pigmentation conducted by Liu et al. (2018) clearly showed that fiber colour in
natural coloured cotton is regulated by flavonoid biosynthesis pathway. This particular study
highlighted that modifications in flavonoid pathway has the potential to alter fiber traits
such as colour and quality by selecting the regulation and expression of flavonoid genes
(Liu et al., 2018).
More than 200,000 different types of compounds have been shown to be produced
collectively by higher plants, and some of these are able to generate bright colours in
flowers, fruit or foliage (Feng et al., 2013). The human eye can detect light, as reflected or
transmitted by a compound under wavelengths of 380 and 730 nm, while insects recognize
the light of shorter wavelengths (Davies, 2004). In plants, three major classes of pigments
for colouration exists which includes carotenoids, flavonoids/anthocyanins and betalains.
Diversity of red, purple and blue colours of flowers as well as fruits are due to the
nature of these polyphenolic pigments. In plants, these secondary metabolites are found
ubiquitously. Among factors influencing flower colour, the flavonoid/anthocyanin
biosynthesis has been studied most extensively. The various factors which influence the
5
final colour formation include anthocyanin structures, vacuolar pH, co-pigments and metal
ions.
In higher plant species, the pathway leading to anthocyanidin 3-glucoside is
generally conserved (Grotewold, 2006; Tanaka and Brugliera, 2006). Only six major classes
of anthocyanidins do exist i.e pelargonidin, cyanidin, peonidin, delphinidin, petunidin and
malvidin (Yoshida et al., 2009). Among cytochromes P450s two genes i.e flavonoid3’-
hydroxylase (F3’H) and flavonoid3’5’-hydroxylase (F3’5’H), catalyze the hydroxylation of
B-ring (Tanaka, 2006).
The increased hydroxylation pattern of this ring was found to be involved in shifting
the anthocyanin colour toward blue. They exhibit broad substrate specificity and catalyze
hydroxylation of flavanones, dihydroflavonols, flavonols, and flavones. Flavanones along
with dihydroflavonols are precursors of anthocyanidins. Trihydroxylated delphinidin based
anthocyanins from blue or violet colours is achieved by the presence of F 3’5’H (Honda and
Saito, 2002).
Dihydroflavonol 4-reductase (DFR) is a vital enzyme of the flavonoid pathway
which shows a major impact on the formation of anthocyanins, flavan 3-ols, and flavonols.
In ornamental flower plants, the colour has been modified by altering the expression levels
of DFR genes (Aida et al., 2000). The substrate specificity of the DFR plays a crucial role in
determining which anthocyanidins, a plant will accumulate (Forkmann and Heller, 1999).
DFR is unique in a sense that it uptakes flavonoid substrates depending on the B-ring
hydroxylation pattern. The DFRs of several plants accept dihydroflavonols having one
(dihydrokaempferol, DHK), two (dihydroquercetin, DHQ), or three (dihydromyricetin,
6
DHM) hydroxyl groups on the B-ring. NADPH is used as a cofactor of DFR, which helped
in catalyzing the reduction of dihydroflavonols to leucoanthocyanidins which were common
precursors of anthocyanin (Helariutta et al., 1993). Substrate specificity of DFR determines
the conversion of metabolic flux toward desired anthocyanidin biosynthesis. Similarly, a
member of cytochrome P450 family, Flavonoid 3’5’hydoxylase (F3’5’H), is a significant
enzyme in the synthesis of 3’, 5’- hydroxylated anthocyanidins (i.e delphinidin) (Holton and
Tanaka, 1994). As previously known this enzyme induces two hydroxyl groups (OH−) on
the B ring of flavonoid frame. So, only those plants which can express the F3’5’H gene are
able to generate blue colour pigments, as they are wholly dependent on 5’-hydroxylated
anthocyanins.
Recently, the role of flavonoid pathway in cotton crop has been reviewed by Nix et
al. (2017) and Ahad et al. (2018). It is reported that flavonoids affect fiber length and
micronaire by regulating auxins. Attempts around the world are being continuously made to
develop cotton varieties with superior fiber quality but still fiber quality is investigated and
molecular studies are in process to solve this puzzle.
The technological breakthroughs in fields of bioinformatics and other areas of
genomics will enable scientists to approach science with true engineering of plants.
Predictive metabolic engineering is a critical theme to make predictions as how to alter
metabolic pathways. The knowledge of molecular basis will help in discovery of more and
selective pigment related genes. At present, considerable attention has been paid to on
identifying naturally occurring colour pigments, whose genetic transformation will be able
to modify the fibers. The molecular docking procedures are extensively used to evaluate the
binding affinities with various ligands. In the current work, docking analysis of both genes
7
(F3’5’H & DFR) was carried out to evaluate their ability to reduce substrates
(dihydrokaempferol 4-reductase, dihydromyricetin reductase and dihydroquercetin
reductase) which are naturally present in cotton plant. MOE and AutodockVina, two
bioinformatics software were used in docking experiments.
In background of above cited literature, the current study was proposed to over
express synthetic flavonoid genes F3’5’H and DFR in local cotton variety, VH-319 to
improve cotton staple characteristics i-e length, strength, micronaire value, uniformity index
and colour.
Chapter # 2
8
CHAPTER 2 : REVIEW OF LITERATURE
One of the oldest and widely used multipurpose natural fibers is ‘Cotton fiber’. It is a
lignocellulosic biomass primarily composed of cellulose with hemicelluloses (Wanassi et
al., 2017). Other non-cellulosic matters present in the cotton fiber are starch, sugars, proteins
and a little inorganic matter. However, some traces of lignin are also found in it. By acting
as binding force among different compounds, it makes the entire structure of fiber steady
and firm (Rowell et al., 2000).
Cotton fiber has been distinguished from other existing natural fibers due to its
properties like absorbence, luster, softness, strength and wearing comfort. Globally cotton
demand has increased with the increase of textile industry. Cotton is basic raw material of
textile sector and fiber characteristics directly affect the quality of fabric. Therefore,
enhancement of fiber characteristics at genetic and molecular level is an attractive study area
all over the world.
2.1. BACKGROUND OF COTTON CROP
Cotton is the principal fiber crop throughout the world, used for the betterment of
mankind since time immemorial. Commercially it is grown in more than 80 countries
including Pakistan, India, China, USA, Australia and the Middle East (Smith, 1995).
Historical background of cotton is of great significance. Literature revealed harvesting of
cotton to make fabrics in old ancient times since 3000 BC in India, Neil valley and Peru.
9
Although many other fibers are in use for centuries yet cotton has its own distinction due to
superior qualities (Pillay and Myers, 1999).
In Pakistan, cotton is the second largest grown crop after wheat; Pakistan has also
introduced its own local diploid cotton varieties in the world. Threads of cotton fiber have
been discovered from Baluchistan, Pakistan about 8000 years ago (Moulherat et al., 2002).
Gossypium stocksii, which is the wild Gossypium species of Asian origin, grows in the arid
surroundings of Karachi. Moreover, G. herbaceum grows in Baluchistan (Afzal and Ali,
1983). The G. arboreum and G. herbaceum have been cultivated in Pakistan since pre-
history. American cotton (G. hirsutum) contributes mostly to the commercially grown
cotton in Pakistan while G. arboreum (Desi cotton) is also grown but on a smaller area (3%)
(Afzal and Ali, 1983).
2.2. SOCIO-ECONOMIC IMPACT OF COTTON IN PAKISTAN
Cotton is harvested in 82 countries covering a cultivable land of about 33 million
hectares which is equivalent to 2.5 percent. In world’s cotton nearly 77% yield is supplied
by southern countries contributing about 58% of total world cotton exports (Banuri, 1998).
Cotton along its products constitutes an elementary economic segment in Pakistan, giving
significant trade experience at each step of production. Pakistan is the largest seller of cotton
yarn, 3rd
major trader of raw cotton, 4th
bigger consumer and 5th
largest producer. New
challenge for year 2017/18 is set to increase the cotton yield up to 14.1 million bales by
2489 thousand hectares; while from province Punjab alone about 10 million bales are
expected over an cultivable area of 2.43 million hectares (Ashraf et al., 2018). Presently,
Punjab and Sindh contributes nearly 80% and 18% respectively in cotton production (Ali et
al., 2013). Bahawalpur, Vehari, Burewala and Multan are the major cotton growing districts
10
in Punjab. Overall, in country approximately 42.3% employment of workforce is supported
by cotton industry (Chaudhry et al., 2009). Cotton production was recorded as 730kgs/Hec
during the corresponding year. Rates of raw cotton (lint) and its seeds in year 2017 were Rs.
1875 and 7609 per maund respectively. Similarly, total export of country was estimated as
129,476 million bales and import was 716,188 million bales which worth Rs. 43,142 million
(Ashraf et al., 2018). Pakistan has to import cotton from other countries due to the inability
of domesticated cotton which possess low or medium length fiber and it is insufficient to
meet the demand of textile industry.
The cotton industry is comprised of 503 textile mills, 8.1 million spindles and 1263
ginning factories (Khan et al., 2011), 650 finishing and dyeing sectors having annual
competence of 1,150 MM Sq m (million square meters), about four thousand garment
sections (with sewing machines 200,000), three hundred crude oil expellers as well as
15,000 to 20,000 indigenous small scale oil expellers usually named as “Kohlus” (Khan et
al., 2011). To increase cotton trade, there is need to improve fiber of local cotton varieties.
A molecular biological approach of combating the cotton fiber quality can prove to be vital
for textile industry.
2.3. CHARACTERISTICS OF COTTON FIBER
As a major fiber crop; the fiber properties of cotton decide its market fate and
importance among consumers. The physical traits of cotton fibers ranges from strength
(degree of flexibility), elongation (degree of extensibility), fineness (linear density, a
function of diameter and thickness), micronaire value (resistance to air flow across a plug
of fibers) and maturity (extent of cell wall thickening) to colouration (Lacape et al., 2010).
11
Cotton is the fundamental natural plant based raw material for the textile industry.
Due to its natural origin, the agronomic traits of cotton crop differ remarkably, depending on
certain factors such as cultivation area, growing conditions, and variety used. Moreover,
basic properties of cotton fiber (length, maturity, fineness, tenacity and colour) are largely
influenced by cotton cultivation procedures such as soil, climatic conditions, irrigation,
insecticidal and fungal attacks as well as the harvesting practices (Ibrahim et al., 2010).
To predict the performance of cotton fiber during processing and the quality of
manufactured cotton products, it is necessary to assess the cotton quality in terms of its
properties (Frydrych et al., 2002). So, the production of cotton varieties having long fiber is
the demand of local textile industry. Fiber length is directly linked to yarn strength, fineness
and spinning efficiency (Moore, 1996). Last two decades showed successful
commercialization of genetically modified cotton having useful agronomic and fiber traits.
2.4. MODIFICATIONS IN FIBER TRAITS AT MOLECULAR LEVEL
Molecular and cellular mechanisms that regulate the rate of growth in rapidly
elongating cotton fibers have been argued about for a long period. Over the last decade,
fiber yield and quality of cotton varieties declined this trend which has been attributed due
to attrition in genetic variety of breeding stocks as well as due to raised vulnerability caused
by environmental stresses (Ulloa and Meredith, 2000). In G. hirsutum, the level of genetic
diversity is very low which can be enhanced by the application of advanced approaches such
as mutagenesis, germplasm introgression and transformation (Lacape et al., 2010). The
process of elongation in developing cotton fiber can be modified at several cellular and
molecular levels especially at the stages of cell wall loosening and deposition with polar
vesicular trafficking. The review will highlights various scientific approaches for cotton
12
fiber quality improvement taken into account by different researchers working for such
important task to benefit the cotton community around the world.
Actin binding proteins (ABPs), categorized as capping or actin monomer binding
proteins (G-actin binding or globular proteins) are known to raise fiber elongation which is a
desirable character (Wang et al., 2010). By silencing GhACTIN1 inhibition in fiber cell
elongation is noticed due to reduction in quantity of F-actin, signifying the importance of F-
actin arrays in staple elongation in a similar way as reported in Arabidopsis for root hair
growth (Qin and Zhu, 2011). GhCFE1A and WLIM1a act on actin bundler which functions
in fiber elongation by becoming a dynamic linker between the actin cytoskeleton network
and endoplasmic reticulum, respectively (Han et al., 2013). In addition, actin filaments
together with MTs linked by kinesin could function more efficiently to modify fiber length
(Xu et al., 2009). In this regard, GhKCH1 and GhKCH2 (kinesins containing calponin
homology domains) were over expressing and up regulated in transgenic lines at 10, 15, and
17 DPA, with the exception of OE-5 at 10 DPA when compared with the control.
Among efflux and influx carriers of the auxin transporter mostly dispersed in the
cytoplasm membrane, the PIN (PIN-FORMED) protein is most significant as it plays crucial
role in the distribution of auxin and controls the multiple biological phenomenons.
Literature highlighted some genes such as GhPIN8-At, GhPIN6-At and GhPIN1a-Dt for
increasing density and lengths of trichomes (Zhang et al., 2017). Another study revealed the
highest expression of GhSCFP during fiber initiation & rapid elongation phase (Hou et al.,
2008).
13
Staple length is a key trait in determining the economical value of cotton. Three
important influential factors for rapid fiber cell elongation are osmotic pressure, cell wall
loosening and the production of structural molecules (Wang et al., 2010). Many scientists
tried to improve this trait through molecular engineering of transcriptional factors. Among
GhHOX genes GhHOX1, GhHOX2 and GhHOX3 are particularly linked with the
quantitative trait loci to refine fiber length, fineness and uniformity in cotton. Other genes
such as GhCeSA1, GhCeSA2, and GhGluc1 are highly expressed during secondary wall
biosynthesis (SCW) which caused cellulose deposition of high rates (Ruan et al., 2004).
Zhang et al. (2016) reported that GhFAnnxA is also associated with fiber traits. It plays role
during SCW by regulating Ca+2
conductances which in result build elevated intracellular
turgor and cell wall loosening. Similarly, inhibition of fiber length was observed by down-
regulating GhAnn2 due to decrease in Ca2+
flux at the cell apex (Tang et al., 2014).
Mainly, endo-1,4-beta-glucanase and expansin are two chief proteins which sustain
the loosening of the fiber cell wall during the elongation stage. The two homoeologous fiber
specific α-expansins GbEXPA2 and GbEXPATR which particularly express in G.
barbadense were over-expressed in G. hirsutum to obtain fiber of long length by Li et al.
(2016). The over expression of GbEXPA2 was found to has no drastic effect on mature fiber
length. But on other interestingly, over expression of GbEXPATR has showed dramatic
results during secondary wall synthesis and metabolism thus proved best candidate gene for
developing American cotton cultivars with superior fiber quality (Li et al., 2015). Literature
highlighted GhEXPA8 as another useful gene regarding fiber improvement. Field data of
three generations collected by Bajwa et al. (2015), on the expression of GhEXPA8 in a local
cotton variety NIAB 846 showed major improvement in staple length and micronaire values
14
when compared to control plants (non transgenic). Guo et al. (2017) unrevealed a novel link
among Ca2+
, K+ and fiber elongation. Moreover, reduction in fiber length is notified from
potassium (K) deficiency in cotton. Potassium acts as a primary osmotic agent contributing
in fiber elongation by increasing cell turgor pressure (Yang et al., 2014).
However, a new trend in research area of green revolution is prevailing which
promotes the idea of altering the regulating mechanisms of naturally present biological
cycles in plants to drive desired traits.
2.5. NATURAL PROTECTIVE PIGMENTS IN PLANTS
A number of biological pigments are found in plant kingdom performing broad
range of functions including photosynthesis, flower colouration and plant protection. Some
of the major plant pigments are summarized below (Table 2.1).
Table 2-1 : Major Biological Plant Pigments with Types
Pigments Types Occurrence Key Functions
Chlorophylls
Chlorophyll Green plants
Green colour
formation,
photosynthesis
Carotenoids
Carotenes and
xanthophyll e.g
astaxanthin
Bacteria and
green plants
Orange, red, pink
yellow colour
formation, anti-
oxidants, Sun screen
Flavonoids
Anthocyanins,
aurones, chalcones,
flavonols and
proanthocyanidins
Plants
Yellow, red, blue,
purple. Shield
against abiotic &
biotic stresses
Betalains Betacyanins and
betaxanthins Flowers
Red,yellow, orange
colour, anti-oxidant,
detoxifier
15
2.6. FLAVONOIDS BIOGENESIS
Efforts have been made from last two consecutive decades to highlight the genetic
prospects of flavonoid biosynthetic pathway. The pigments perform diverse biological
activities ranging from plant stress relief to creation of variety of colours in different
vegetative parts of plants (Nix et al., 2017).
Being water soluble, these natural pigments are produced by the phenyl propanoid
pathway, converting phenylalanine in 4 coumaroyl CoA, which eventually enter in the
flavonoid biogenesis pathway. Chalcone synthase, is specified as first enzyme of the
flavonoid pathway which produces chalcone scaffolds from where entire flavonoid
compounds originates. Though the central flavonoid pathway is conserved in plants, based
on the species a set of enzymes, like hydroxylases, reductases, isomerases, and various
Fe2+/2-oxoglutarate-dependent dioxygenases transform the primary flavonoid skeleton,
directing to the diverse flavonoids sub groups (Martens et al., 2010).
Basic flavonoid structure is consisted of 2-phenylbenzopyranone having three-
carbon bridges in phenyl groups which are further cyclised with oxygen. They exhibit a
three ring chemical structure i.e., C6–C3–C6. In actual, the degree of oxidation and
unsaturation of 3-carbon fragment determines the main groups of flavonoids (Nix et al.,
2017). Mainly six classes of flavonoids exist, characterized as anthocyanins (red to purple),
flavanols (colorless to brown in response to oxidation), flavonols (colourless to pale yellow)
and condensed tannins or PAs (proanthocyanidins) (Yoshida et al., 2009).
The genes counted in flavonoids synthesis are broadly categorized as the structural
genes, which directly participate in the production of flavonoids and the regulatory genes
16
that control expression of structural genes during the production of flavonoids (Forkmann et
al., 1980). The main precursors related to flavonoids biosynthesis are p coumaroyl-CoA and
malonyl-CoA, which are the derivatives of phenylepropanoid and carbohydrates pathways
respectively (Martens and Forkmann, 1999).
Flavonoid biosynthesis is initiated by production of yellow colour chalcone
(naringenin chalcone) that is synthesized as a result of enzymatic step catalyzed by chalcone
synthase (CHS). This yellow colour product is not the end product of flavonoid pathway,
but keeps on generating diverse classes of flavonoids in the presence of numerous other
enzymes (Schijlen et al., 2004).
Chalcone synthase, a structural gene have been long explored by plant scientists
(Jorgensen et al., 1996) and their down regulation divert colourful flowers to white. After
the production of naringenin chalcone, flavanones are formed by an enzyme renowned as
chalcone isomerase CHI. The flower colour modification in Diathus cayophyllus and change
of seed coat colour in Arabidopsis was achieved by mutation in CHI genes. Transformation
of CHI genes in tomato also increased the flavonoid contents (Muir et al., 2001).
Two other important genes, i.e flavonoid 3′-hydroxylase (F3′H) and flavonoid 3′, 5′-
hydroxylase (F3′5′H), catalyze the hydroxylation of B-ring (Tanaka, 2006a). The increased
hydroxylation pattern of this ring was found to be involved in shifting the anthocyanin
colour toward blue. They exhibit broad range substrate specificity and catalyze
hydroxylation of flavanones, dihydroflavonols, flavonols, and flavones. Flavanones along
with dihydroflavonols are precursors of anthocyanidins (Honda and Saito, 2002). The next
17
enzymes dihydroflavonols 4-reductase (DFR) in flavonoid pathway reduces
dihydroflavonols to leucoanthocynidines (Kristiansen and Rohde, 1991).
Finally, the last enzyme of pathway anthocyanidin synthase (ANS) catalyzes the
conversion of leucoanthocynadine (colourless) in anthocyanidin but if the reaction is further
catalyzed by anthocyanidin reductase (ANR), eventually pro-anthocyanidins (pigmentation)
will be produced (Nakatsuka et al., 2010).
Biological functions of flavonoids include protection against ultraviolet light,
phytopathogens, male fertility, legume nodulation, visual signals and auxin transport control
(Kitamura, 2006). Additionally, the leaf cells are protected against oxidative damage with
nutrient retrieval during senescence in fall season by flavonoids (Feild et al., 2001).
Besides physiological role in plants, the colour generating classes of flavonoids
“anthocyanin” are linked with protection against certain cardiovascular diseases, cancers
along with other chronic human disorders (Tsuda et al., 2003). Due to their antioxidant
capacity they help to maintain human health by the suppression of specific signalling
pathways which are involved in inflammation and disease development (Meiers et al.,
2001). Stability and colour variation of these pigments is enhanced by coumaroyl/acetyl
group esterification and methyl/hydroxyl group substitution (Springob et al., 2003; Conde et
al., 2007).
2.7. FLAVONOIDS LOCALIZATION
“Cytosols” are the sites for flavonoids production. Mostly flavonoid biosynthetic
enzymes are anchored in the endoplasmic reticulum while the pigments accumulate
18
themselves in vacuole (anthocyanins and proanthocyanidins) or into cell wall (Winkel-
Shirley, 2001).
The vesicular and ligandin transport mechanisms are two generally proposed models
for the transport of anthocyanin from the endoplasmic reticulum to the vacuole storage sites
(Zhao and Dixon, 2010). In case of ligandin transport model, vacuolar sequestration of
pigments is taking place by glutathione transferase (GST)-like proteins particularly in
petunia, Arabidopsis (AtTT19) and maize (Marrs et al., 1995; Alfenito et al., 1998).
Moreover, in maize the anthocyanins vacuolar sequestration needs a multidrug resistance
associated protein-type (MRP) transporter, whose expression is co-regulated by anthocyanin
structural genes (Goodman et al., 2004). These proteins are actually GS-X (glutathione S-X)
pumps associated with transfer a range of glutathione conjugates. Whereas the proposed
vesicle-mediated transport model explained that other flavonoids and anthocyanins
accumulates in the cytoplasm via distinct vesicular bodies known as “anthocyanoplasts”,
and later by the mechanism of autophagy, induced to the vacuole (Pourcel et al., 2010).
According to Zhao and co-workers, above narrated modifications facilitate in
transporter binding along esterification of flavonoid glycosides with malonate provide
MATE (Multidrug And Toxic compound Extrusion protein) and finally facilitate
anthocyanins in transportation (Zhao et al., 2011). As many secondary metabolites,
flavonoids strictly need to be transported correctly to the discrete compartments, principally
cell wall and vacuole at cellular level (Markham et al., 2000; Yazaki, 2005; Kitamura,
2006). Genome wide approaches have been utilized to determine molecular basis of
anthocyanins vacuolar uptake in plant cells (Terrier et al. 2005; Kitamura 2006; Conn et al.,
2010).
19
2.8. GENETIC REGULATION OF FLAVONOID BIOSYNTHESIS
Gene expression and its regulation are considered to be basics of an organism’s life.
Phenylalanine metabolism consisted of an important branch named as “Flavonoid
biosynthesis”. Regulation of its compounds are under the transcriptome profiles of chalcone
synthase, flavanone-3-hydroxylase, flavonoid-3'-hydroxylase, dihydroflavonol-4-reductase,
flavonoid-3-O-glucosyltransferase, anthocyanidin synthase and leucoanthocyanidin
reductase genes. These genes are regulated by a number of transcription factors like MYB,
R2R3, WD40 and basic helix-loop-helix (Bhlh) in higher plants (Grotewold, 2006). So,
manipulation of these elements leads to accumulation of different flavonoids (anthocyanins
procyanidins, flavanols, flavonol andflavone) in plants.
Research studies showed that a number of family rosaceous members e.g. cherry,
peach, plum, apple, rose, raspberry and rose has been used for transformation of R2R3-
MYB10 genes, isolated from petunia AN2, for the over expression of the anthocyanin in
flowers and fruits. The strawberry plants transformed with MYB10 under constitutive
promoter have shown elevated level of anthocyanin in almost all parts of plant i.e stigma,
leaves, fruits and roots (Lin-Wang et al., 2010).
Similarly, enhanced red colouration stimulus in apple has also been reported by
rearrangement of MYB10 factor. As a result of this rearrangement, an auto-regulatory
region was found to be produced in MYB10 which enhanced its expression and eventually
over expressed anthocyanin in leaves, fruit and other plant parts (Espley et al., 2009).
Similarly, over expression of PAP2 (AtMYB90) from Arabidopsis was done in Tobacco for
anthocyanin production. However, it was noticed that R2R3-MYB conversion was limiting
20
factor in pigment formation of Tobacco. It happened due to absence of 78th amino acid in
AtMYB90 at C-terminus (Velten et al., 2010).
Tanaka and Ohmiya (2008) reported that over expression of R2R3-MYB or Bhlh
resulted in dark colour pigmentation of flowers through ectopic expression of anthocyanins.
Purple tomato fruits were developed through the expression of snapdragon Delila (bHLH)
and snapdragon Rosea 1 (R2R3-MYB) under fruit specific promoter. Consumption of such
tomatoes was found to have health benefits. Their anthocyanins levels were found to be
similar as in black and blueberries (Butelli et al., 2008).
Similarly, studies on grapevine R2R3-MYB genes (Matus et al., 2008) has proved
that pericarp colour of grapes involves R2R3-Myb (VvmybA1c) genotype and regulates
anthocyanin levels by regulating F3GT gene expression. When promoter region of
VvmybA1c gene was inserted in a retro-transposon, VvmybA1a expression was observed
along with anthocyanin colouration of grapes (Kobayashi et al., 2004). More than hundred
R2R3-MYBs in grapevine have been identified.
Moreover, anthocyanin biosynthesis is also found to be regulated by other
transcription factors besides bHLH and R2R3-MYB. For instance, flavonoid production is
suppressed by a complex of MYBL2 (R3-MYB) where a minor MYB protein becomes
attached with MBW. Any mutation in R3-MYB protein could improve anthocyanin
production in Arabidopsis seeds (Dubos et al., 2008; Matsui et al., 2008). Over-expression
of R3-MYB triggered pro-anthocyanidin inhibition in seedlings (Dubos et al., 2008). NAC
is a plant specific transcription factor which control anthocyanin biosynthesis. Anthocyanin
21
biosynthesis genes are found to be activated by ANAC078 of Arabidopsis using
transcription factors (Morishita et al., 2009).
2.9. FLAVONOID PIGMENTS OF COTTON
Flavonoids are the most important pigments among secondary metabolites produced
by plants. Flavonoids are concentrated in cytoplasmic vacuoles and retain multiple functions
of plants (Nix et al., 2017).
Studies on floral pigmentation in Gossypium hirsutum appeal the researcher’s
attention towards flavonoids. It was also attributed through depth insight that cotton flower
colouration is also genetically regulated by flavonoid pathway (Tan et al., 2013). Research
studies indicated that pigments of brown fiber belong to the flavonoid family but the exact
mechanism of pigment deposition is still unclear. Therefore, flavonoid gene expression got
significance with respect to pigmentation in cotton fibers (Feng et al., 2013). Moreover
work done by Liu et al. (2018) clearly demonstrated that pigmentation process in both green
and brown cotton was under control of flavonoid biosynthetic pathway. This study further
strengthens the idea about the potential of flavonoid pathway modifications to alter cotton
fibers quality and colour.
Naturally cotton colours (NCCs) are reflected as the pigment mutants of
conventional variety of white cotton (Endrizzi et al., 1985).There are four colours of cotton
fiber i.e. white, brown, blue and green. Whereas white colour range from shinning to
creamy white. Brown coloured fiber also occurs in a number of shades from light, medium
to dark brown and mahogany. Similarly, shades of green also exist from light to deep green.
22
However, blue colour is not very common and clear in shade; only very light blue fiber of
cotton is naturally available (Chaudhry and Guitchounts, 2003).
History of NCCs is very old and have been cultivated for more than 4500 years (Zhu
et al., 2006) but their commercial importance is not very high due to their limitations of low
productivity, reduced quality fiber, non-uniformity of colours, and fiber strength. The
NCCs have been studied for the pathways of flavonoid related genes which are responsible
for pigment production and therefore, the transcript levels of structural genes i.e. GhANR,
GhANS, GhDFR, GhF3H and GhCHI (Xiao et al., 2007) were investigated at primary
developmental stages of fiber.
However, in present era, much more importance has been given to flavonoid
pathways due to their diverse functions in cotton plant physiology. Since they are secondary
metabolites, hence their appropriate concentrations influence photosynthetic processes in
plants by affecting photoprotectors as well as they regulate the phytohormone transportation
specially auxin, the growth promoting hormone (Noctor et al., 2017). Moreover, Flavonoids
are also attracting attention in field of pigment engineering. Researchers started using
pigment pathways for proposed colour development in cotton fiber along with enhanced
fiber characteristics. Similar attempt has been done in current study to unravel role of
flavonoid pathway in up-regulating cotton fiber quality.
2.10. BIOLOGICAL ROLES OF FLAVONOIDS IN COTTON CROP
Flavonoids are naturally occurring secondary metabolite pigments which are well-
known for their multiple roles. Some of their prominent properties are listed below:
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2.10.1. FLAVONOIDS: A PIGMENT WITH MULTIPLE ROLES IN PLANT
Plants produce reactive oxygen species (ROS) when undergo biotic and abiotic
environmental stresses. As a result oxidation of different cellular biomolecules occur i.e
nucleic acids, proteins, lipids which eventually disturb the cellular physiology. For survival,
anti-oxidative defense system of plants respond to ROS accumulation by producing
secondary metabolites (You and Chan, 2015). Secondary metabolites are organic in nature.
Phytohormones, flavonoids, lignin, tannins and other phenolic acids are categorized
as secondary metabolites. These metabolites are not directly involved in plant development
but they work under environmental stress conditions. Their imbalance can cause severe
plant deformities. Accumulations of such phenolic compounds in response to stress cause an
inhibition of harmful ROS and secure the plant cells. Similarly, role of lignin precursor
against abiotic stress conditions are also found as shown in Figure 2 (Bach et al., 2015).
Plants are very sensitive towards ambient light conditions and undergo specific
physiological changes to modulate its developmental process. They use multiple
photoreceptors to fight environmental stresses such as cryptochrome, phytochrome,
phototropin and photo protectors. Flavonoids and its derivatives such anthocyanins,
flavonols along flavanones are among these photo protector, performing multiple functions
(Ouzounis et al., 2015). Some of them are summarized below.
2.10.2. FLAVONOIDS: COTTON COLOURING AGENTS
Flavonoids are the aesthetic molecules of nature which beautifully decorate the
nature with colourful fruits and flowers. Moreover, flavonoids also shield the plant against
environmental stresses. In cotton, flower colour is also controlled by flavonoid pathway
(Tan et al., 2013b). Transcriptome analysis of fiber development stages showed the
24
significant expression of flavonoid synthesis genes (Hua et al., 2007). Primarily, expression
of five structural gene i.e GhANR, GhANS, GhDFR, GhF3H and GhCHI are reported to
involve in cotton fiber development and pigmentation. The reddening in cotton leaves occur
due to increase peroxidase activity, proline content and loss of chlorophyll which is
indication of the major biochemical disturbances within plant as a result of salt, temperature,
mineral deficiency and eradication etc (Dixon and Paiva, 1995). It has been observed that
anthocyanin accumulation causes leaf reddening and therefore, one can say that a very
critical and primary role is played by anthocyanins in response to stress which demands a
careful nurturing of the stressed condition afterwards (Velikova et al., 2002). Another study
also reported that humic acid (HA) when applied exogenously to Gossypium barbadense
improved the stress defense response by upgrading anthocyanin levels along with a
significant impact on plant growth and fiber quality (Rady et al., 2016). Photo-protective
flavonoids, anthocyanin are responsible for orange to blue colouration in leaves, flowers,
seeds, fruits and other tissues as well as promoting stress tolerance in cotton plant (Park et
al., 2015).
2.10.3. FLAVONOIDS; SHIELD AGAINST ABIOTIC STRESSES
Among major cash crops of Pakistan, cotton is predominant and a lot has been
reported about the efficient role of flavonoids against abiotic stress in background of Cotton
plant. The phenylpropanoid (subgroup of flavonoid family) promotes growth and
development of cotton plant whereas, Anthocyanin performs protective activities against
drought, herbivores and pathogen attack (Nakabayashi and Saito, 2015).
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2.10.3.1. Flavonoids; The Photo-protectors
Anthocyanins act as sun block for plants. The UV-absorbance capacity of flavonoids
has been evident from experimental studies, particularly quercetin 3-O and luteolin 7-O-
glycosides in the flavonoid metabolic pathway acts as an antioxidant against solar UV-B
radiation which detoxify the reactive oxygen species (ROS) in stressed plant cells (Rozema
et al., 2002; Agati et al., 2013).
Plant flavonoids respond to sunlight in very influential way as they are the first
elements to respond the sunlight for capturing a photon of light and initiate the photosystem
for food synthesis within plant cell. On the other hand, flavonoids are also scavenging the
ROS to reduce photo inhibition losses caused by intense sunlight (Gould, 2004). Pure
anthocyanin scavenges reactive oxygen and nitrogen more efficiently, up to four folds
greater than α-tocopherol and ascorbate which are renowned antioxidant agents (Gould,
2004).
The elevated anthocyanin levels in stress conditions are considered to be the ultimate
defense line against ROS when all other protective mechanisms become exhausted (Gould,
2004). Therefore, highest anthocyanin concentration is present in young leaves which
protect them against photobleaching effect of sunlight on chlorophyll. Another unique
feature of anthocyanins is sheltering the foliar nutrient resorption during senescence via
protection of photosynthetic tissues from excessive light. A comparison of anthocyanin-
deficient mutants and wild type of deciduous woody species revealed that higher
photochemical efficiency was present in wild type plants than mutants and therefore, wild
plants were more capable to overcome the abiotic stress environment (Hoch et al., 2003).
Cotton leaf Anthocyanins are largely produced in cytosol and stored in vacuoles of
26
epidermal cells. Changes in cotton leaf pigmentation pattern was noticed when they were
unusually exposed to sunlight as a result red coloured scars on the abaxial side of cotton
leaves appeared. These pigments were anthocyanins and meant to provide protection to
photosynthetic tissues (Treutter, 2005).
2.10.3.2. Flavonoids; The Thermoregulators
Temperature is an important factor to affect the intracellular concentration of
flavonoids. Anthocyanin biosynthetic genes are not only down-regulated, but somehow
degraded under high temperatures which induce an inhibition of cellular transcription. As
compared to other crops, cotton is more responsive to high temperature. Shortly after the
onset of 4-5 days of a heat wave, small boll senescence in cotton plant occurs. In the
absence of appropriate moisture a decrease in crop yield is obtained due to shedding of
immature bolls. Similarly, more damaging effect is observed on cotton during bloom period
as high temperatures often cut short the boll-setting period, followed by inadequate
shrinkage of fluid within the bolls which lowers fiber quality by adversely affecting
micronaire values. The boll maturation is least accelerated by high temperature as compared
to other developmental stages of seedling growth. Plants adapt themselves for water
deficiency by accumulating anthocyanins or related phenolics in cellular compartments
(Roby et al., 2004). The metabolic inducers for this preventive effect are still ambiguous
(Kennedy et al., 2002).
It has also been reported that water deprivation in cotton stimulates an up-regulation
of genes involved in secondary metabolism (Grimplet et al., 2007). As a result mRNA
accumulation of UFGT, CHS and F3H (genes involved in flavonoid pathways) is found in
plant cell which increased anthocyanin level up to 80%. But such mechanisms are mostly
27
seen in pulp and skin tissues and rarely in seeds. Stress conditions activate the whole
flavonoid biosynthetic pathway i.e. gene expression, protein transport and accumulation
(Petrussa et al., 2013).
Drought stress is one of the common reasons to initiate oxidative stress by inhibiting
photosynthesis (Smirnoff, 1993) which eventually results in production and accumulation of
toxic oxygen species i.e. hydroxyl radicals, peroxide radicals and hydrogen peroxide (Foyer
et al., 1997). Anthocyanins also play a significant role in maintaining homeostasis to prevent
water loss by controlling turgor pressure. This evaluates that anthocyanins function as solute
which reduces the leaf osmotic pressure potential thus contributing in osmotic adjustment
caused by drought stress during senescence (Chalker-Scott, 1999).
2.10.3.3. Flavonoids; The Osmoregulators
Cotton fiber quality is adversely effected by water-deficiencies (Hearn, 1994).
Water deficiency is also a critical stress. Marani and Amirav (1971) revealed that the
osmotic stress in early flowering season of cotton had zero effect on fiber quality, but could
be adverse if occurred just after flowering period. Theoretically, the elongation phase of
fiber development process is primarily reliant on turgor pressure (Dhindsa et al., 1976).
Deficiency in plant water supply along with decreased photosynthetic rate and
depleting carbohydrate supply adversely affect the fiber quality. Increased growing plant
cell volume is proportional to water uptake capacity by the vacuole. So, the lint yield,
number of seeds per unit area and number of fibers per seed (Lewis et al., 2000) all these
factors are greatly dependent on the turgidity of plant cells. Hence, the imperfections in cell
volume due to osmotic stress could be resulted in increased flavonoid production and
28
eventually modify the auxin balance in plant cells as well as fiber development (Tan et al.,
2013a). Since a strong correlation exists between dry matter and water content both in the
developing lint and seeds which showed that quick water uptake supports seeds growth
(Rabadia et al., 1999).
2.10.4. ROLE OF FLAVONOIDS AGAINST BIOTIC STRESSES
Flavonoids also have distinguishing features to protect plants against biotic stresses
like pathogens, herbivore and disease attacks. These secondary metabolites are considered to
be the principal mediators of plant defense against insects. The C-glycosyl flavones is
effective against Helicoverpa zea besides bacterial pathogen P. syringae pv. Glycinea (Yong
and Man-Tian, 2005). Similarly, up regulation of certain flavonoid structural genes that
enhanced the production of isoflavone and isoflavonoid compounds in phenyl-propanoid
pathway were found to be a natural effective remedy against causal agents of powdery
mildew i-e M. truncatula and Erysiphepisi (Foster-Hartnett et al., 2007).
Phytoalexins such as lacinilene C 7- methyl ether and 2, 7-Dihydroxycadalene
gathers at infection sites in response to cotton foliage caused by Puccinia malvacearum,
Xanthomonas campestris and hypersensitivity due to bacterial pathogen. As a result, the
adaxial epidermal cells which cover the infection sites become red and possess higher
capacity of absorbing photo activating sunlight wavelengths as compare to other epidermal
colourless cells. These epidermal pigments are of great importance because they protect
living cells from the lethal effects of phytoalexins.
Experiments on UV-absorbing material obtained by the epidermal strips of
inoculated and mock-inoculated cotton cotyledons signify that primary increase in capacity
29
to absorb the photo activating wavelengths was due to a yellow and red anthocyanin
flavonol, which were mainly known as quercetin-3-O-b-glucoside and cyanidin-3-O-b-
glucoside, respectively (Edwards et al., 2008).
Anthocyanins are also the indicators for pest and pathogen resistance. Cyanidin-3-
glucoside compounds are responsible for maintaining resistance against Heliothis virescens
and tobacco budworm in cotton leaves (Hedin et al., 1983). Smilarly leucoanthocyanins in
infected cotton leaves have been reported as resistance against bacterial blight.
In another study conducted under controlled environmental conditions showed
production of anthocyanins against X. campestris pv. Malvacearum. The epidermal adaxial
surface of the leaves were main tissue involved in anthocyanin production thus intimating
anthocyanins protective role in damage by light activated phytoalexins and infection
reactive oxygen species (Kangatharalingam et al., 2002). Another research conducted on
expression of Lc transgene in cotton transgenic lines showed increased anthocyanin levels
which developed resistance against t-third-instar cotton bollworm larvae (Fan et al., 2015).
Flavonols which appear as front line defense mechanism triggers the insect response.
The insecticidal activity of well-known flavonols or flavonoid pathway such as kaempferol,
quercetin, isoquercitrin and rutin in cotton crop has already been reported. Flavonols are
more effective for pink bollworm as compared to the cotton bollworm and tobacco
budworm.
Adequate concentrations of free quercetin and kaempferol were identified as
glucosides in cotton plant tissues. More than 0.2 percent concentration of rutin and
isoquercitrin in epidermal cells inhibit larval growth particularly pupal formation of cotton
30
bollworm, tobacco budworm and pink bollworm. The concentrations of 0.05 to 0.1% of
rutin added to 0.1 % gossypol significantly increased toxicity in bollworms representing a
synergistic relationship between terpenoids and flavonoids in developing natural resistance
to insects (Chan et al., 1978). Before using flavonols in pest control, it is the needed to have
more toxicity data on major glycosides which would prove lethal doses against insects in
cotton crop (Bell, 1986).
Different species of genus Gossypium have different quantities of glycosides for
example rhamnoglucosides are more abundant in G. hirsutum but present in trace amounts
in G. barbadense. Whereas kaempferol-3-glucoside and quercetin-7-glycosides are
abundantly present in G. barbadense as compare to G. hirsutum.
Figure 2-1: Types of potential environmental stresses for plant.
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Figure 2-2: An overview of flavonoid responses against different environmental
stresses.
2.11. FLAVONOIDS ROLE IN MODIFYING COTTON FIBER
The exact mechanism of anthocyanins in fiber development is not clear yet but
literature review showed that there exists a co-relation between these phenolic compounds
and phytohormones in promoting high fiber quality. It has also been evident that
phytohormones can considerably modify the expression level of anthocyanin biosynthesis
genes.
Abscisic acid (ABA) upregulate the transcription of CHS, CHI, DFR and UFGT
genes of anthocyanin biosynthesis pathway (Jeong et al., 2004). Similarly, application of
another phytohormone, 2-chloroethylphosphonic acid (2-CEPA) stimulated the long lasting
expression of anthocyanin genes such as CHS, F3H, ANS and UFGT but not DFR. Stability
32
of anthocyanins during post-harvest cotton plant is also found to be improved due to
application of ABA hormone (Bellincontro et al., 2006).
Other phytohormones such as jasmonic acid and salicylic acid activated as a result of
biotic as well as abiotic stresses were also found to up-regulate various genes of flavonoid
pathway i-e phenylalanine ammonia-lyase, CHS and UFGT. Therefore, plant hormones
stimulate the anthocyanin production and they together with phytohormons play a
synergistic role in producing high quality fiber.
Flavonoid functions as endocrine effector to determine PIN gene expression along
with protein localization and act as an indirect modulation of auxin transport (Santelia et
al., 2008). These PIN genes i.e GhPIN1a-Dt, GhPIN6-At and GhPIN8-At jointly promote
fiber growth and enhance fiber elongation through the auxin transport. Where auxin
involves in loosening of fiber cell wall during cell wall elongation phase of development in
allotetraploid cotton, Gossypium hirsutum (Zhang, 2017).
Transcriptome analysis of G. hirsutum and G. barbadense showed up regulated
expression of isoflavonol genes in G. barbadense and down-regulation in G. hirsutum which
confirmed their supportive roles in development of extra-long fiber in G. barbadense.
Padmalatha et al. (2012) also performed transcriptome study of G. hirsutum during different
fiber developmental stages and reported down regulation of flavonoid genes during fiber
initiation and up-regulation before the onset of elongation phenomenon. A meta-analysis
study done by gene expression omnibus (GEO) portal available at NCBI on differentially
expressed genes in extra-long fiber as compare to shorter fiber showed the up regulation of
flavonoid biosynthetic process in long fibers (Qaisar et al., 2017).
33
Various types of flavonoid genes actively expressed during early stages of fiber
formation in ovule culture. Naringenin (NAR) is found to reduce the fiber development by
silencing flavanone 3-hydroxylase (F3H) gene. Although over-expression of the F3H-gene
also didn’t directly result in increased in fiber development, but it’s silencing significantly
disturb the fiber initiation.
Phytohormones and flavonoid pigments are correlated and together contribute in
number of ways such as in maintain cotton plant physiology, fiber development as well as in
environmental stress tolerance. A few experimental studies have been done on verifying the
role of flavonoid genes in modifying fiber traits. In this regard a recent study on pigment
development in cotton fiber enlightened the role of flavonoids and further explained that
control over temporal expression and regulation of key genes of this pathway has the
potency to modify fiber traits (Liu et al., 2018). Based on the background literature, the
current study was proposed to over express flavonoids genes in local variety of cotton for
improvement of fiber quality and to further evaluate the role of flavonoids in imparting
colour in cotton fiber.
34
CHAPTER 3 : MATERIALS AND METHODS
3.1 RETRIEVAL OF DFR AND F3’5’H GENES SEQUENCES
The entire nucleotide sequence of both structural genes DFR and F3’5’H was
retrieved in FASTA format from NCBI (https://www.ncbi.nlm.nih.gov/) with accession
numbers, GenBank: AB332098.1 and GenBank: BAF93855.1 respectively. The sequences
of DFR and F3’5’H genes were retrieved from Iris hollandica and Viola wittrockiana
respectively.
3.2 IN-SILICO ANALYSIS OF DFR & F3’5’H GENES
An in-silico study was conducted to evaluate the substrate preference of DFR &
F3’5’H genes with respect to cotton. The dihydroquercetin reductase (DHQ),
dihydromyricetin reductase (DHM) and dihydrokaempferol 4-reductase (DHK) were the
described substrate for DFR while Naringenin and Quercetin were the respective substrates
of F3’5’H. NCBI database was used for sequence information during the In-silco analysis.
Following steps were performed to show successful Protein-ligand docking such as
amino acid sequence alignment, designing the tertiary structures of protein, retrieval of
ligands structures and molecular docking. Greater the value of binding energy more will be
utilization of substrate and larger will be the chances of modifications in fiber.
35
3.2.1. MOLECULAR DOCKING OF DFR GENE
The involvement of flavonoid biosynthesis pathway structural gene (DFR) in
phenotypic alteration of cotton fiber was evaluated through Molecular docking.
The sequence alignment for homology and protein modeling was done between
sequences of each of two DFR genes along with blue and white colour flower sequences
retrieved from NCBI. Furthermore, the presence of proline rich region along with
positions12 and 26 was reported to be important in determining substrate specificity for
DFR of Angelonia angustifolia (Gosch et al., 2014). Other region of 26-amino acid (132–
157) was also considered to play a major role in utilizing specific dihydroflovonols: DHK,
DHQ and DHM (Johnson et al., 2001; Xie et al., 2004). This region was tested in
Gossypium hirsutum as well as in Iris hollandica by protein-ligand docking analysis.
3.2.1.1. Determination of Substrate Binding Region among Different Plant Species:
All above mentioned positions (12, 26 & from 132-157) were evaluated for the
presence of particular residues and its role in specific substrate uptake as illustrated in
published data. For this purpose full length four DFRs sequences: Angelonia angustifolia,
Ang. DFRI (GenBank. AIR09398.1), Ang. DFRII (GenBank. AHM27144.1), Gossypium
hirsutum (GenBank. AHG97389.1) and Iris hollandica (GenBank. BAF93856.1) were
retrieved from Genbank. The sequences were arranged by using ‘Bioedit’ program to find
out the positional similarities between the residues of these sequences. To further validate
the role of this particular position in substrate specificity, sequences from five other species
were taken which includes Rosa chinensis (GenBank. AHF58604.1), Vaccinium
macrocarpon (GenBank. AF483835.1), Gerbera hybrid (GenBank.CAA78930.1), Petunia
36
hybrid (GenBank. AF233639.1) and Ampelopsis grossedentata (GenBank. AGO02174.1).
These nine sequences were aligned by using the CLC Genomics Workbench 8.
Analysis of gene cluster encoding dihydroflavonol 4-reductases in the Lotus
japonicus genome showed that three out of six DFR proteins exhibit catalytic activity, their
substrate preferences settled with the variation of a specific active site residue (Aspartic acid
or Asparagine) and found to be involved in controlling the substrate specificity (Shimada et
al., 2005). Thus Asn as well as Asp percentage estimation in DFR sequences for Iris
hollandica and Gossypium hirsutum was done by using ‘Expasy ProtParam tool’.
3.2.1.2. Modeling of Receptor Molecules for Docking Analysis
Protein sequences of Gossypium hirsutum and Iris hollandica (retrieved from
NCBI) were used for 3D modeling as their protein structures were not available on protein
structure databases. For modeling purpose, sequences were submitted to I-TASSER server
(http://zhanglab.ccmb.med.umich.edu/I-TASSER/). This tool generated protein model based
on homology modeling and threading.
For homology modeling of Gossypium hirsutum DFR, the PDB templates used were
PDB: 2C29F (Identity 82%, coverage 92%) and PDB: 2C29A (Identity 82%, coverage
91%). Whereas, for protein modeling of DFR (Iris hollandica) PDB: 2C29F (Identity
66%, coverage 90%) and PDB: 2C29A (Identity 67%, coverage 90%) template were used.
3.2.1.3. Refinement and Evaluation of DFR Protein Model
The model was further refined by using online tool, ModRefiner accessed on Zhang
Lab website (http://zhanglab.ccmb.med.umich.edu/ModRefiner/). This tool minimized the
energy of the model and took the residues of protein in the allowed region. The models were
37
evaluated and validated by producing Ramachandran plot. These plots were plotted by using
the online RAMPAGE tool (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php).
Ramachandran plots of proteins determined their stability.
3.2.1.4. Ligand Preparation
The structures of biological compounds of flavonoid pathway dihydrokaempferol
(PubChem: 122850), dihydroquercetin (PubChem: 439533) and dihydromyricetin
(PubChem: 161557) were downloaded from the PubChem database in 2D format. For
preparation of ligand structures which were used in docking, hydrogen atoms were added to
each ligand and their energy was minimized by the means of MMFF94X force field at 0.05
gradients. Then, these ligand structures were saved in .mol2 file format. A database of
ligands (DFR acceptor compounds) was created in MOE software.
3.2.1.5. DFR Protein and Ligand Docking Analysis
The three-dimensional models of Gossypium hirsutum and Iris hollandica were
constructed by using I-TASSER server. The water molecules were removed with the help of
MOE software. After the removal of water molecules, hydrogen atoms were added to the
receptor proteins. Optimization of receptor molecule was achieved by energy minimization
and 3D protonation (with help of AMBER99 force field option of MOE). The gradient was
0.05 and receptor was minimized unless root mean square gradient fall below 0.05. After 3D
protonation of the receptor protein, the hydrogen molecules were hidden. This resulted in
minimization of the energy, 3D protonated receptor molecules were then used for docking
analysis. Box of 26 residues as reported by Shimada et al. (2005) was aligned with Iris
hollandica and Gossypium hirsutum. These aligned residues were used as pocket site.
38
Molecular docking was carried out against the databases mentioned previously, after
the modeling and preparation of ligand and receptor molecules. The receptor residues in
region 132-157 of Gerbera DFR correspond to 148-174 residues in G. hirsutum as well as
127-153 in Iris hollandica were selected and docked with ligands. Docking output
database file having receptor ligand complex was saved in .mdb format. The docked
complexes were categorized with increasing S value (Final score to indicate binding free
energy). The complexes with minimum S were taken to evaluate the interactions of ligand
with the active site residues of the receptor proteins. Best hydrogen bonding plus π-π
interactions were evaluated by the using ligX option of MOE.
3.2.2. MOLECULAR DOCKING OF F3’5’H GENE
A comparative molecular docking was conducted between Viola and Gossypium
F3’5’H genes. To predict which source gene has better ability to reduce substrate and gather
other altered pigments than naturally occurring pigments in cotton plant.
3.2.2.1. Sequence Alignment and Primary Analysis
Amino acid sequences of Viola wittrockiana (accession no. BAF93855.1) and
Gossypium hirsutum, GhF3’5H (accession no. ACH56524.1) were retrieved from NCBI. To
determine the sequence homology CLC Genomics Workbench 8 was used while
hydrophobic portion of F3’5’H proteins were observed through plots generated by EXPASY
ProtScale online tool (http:// web.expasy.org/protscale/). These graphical figures showed the
hydrophobic values of all amino acids present in the sequence.
The Prot Param Server available on Expasy platform
(http://web.expasy.org/protparam) was used to study the physiochemical characters of
39
F3’5H proteins such as instability index, isoelectric point (pI), aliphatic index (AI),
extinction coefficients, GRAVY (grand average of hydropathy) and molecular weight.
The instability index gives an in vitro approximate estimate of a protein’s stability.
Proteins having Instability index value smaller than 40 were regarded as stable. Aliphatic
index was mainly defined as the relative volume occupied by aliphatic side chains (alanine,
valine, isoleucine and leucine) and it was generally predicted as a positive factor for the
increase of thermostability of globular proteins. However, GRAVY score was computed as
the sum of all hydropathy values of amino acids, divided by the number of residues in the
sequence.
3.2.2.2. Secondary Structure Prediction
The secondary structure elements of F3’5’H proteins (Gossypium hirsutum and
Viola wittrockiana) were determined by using PSIPRED server of UCL Department of
Computer Science (http://bioinf.cs.ucl.ac.uk/psipred/).
3.2.2.3. Template Selection
The 3D models of desired genes were not available in Protein Data Bank, therefore
first step was the prediction of their 3D models. To achieve this, template was explored
from ModBase (www.modbase.compbio.ucsf.edu) and selected on the basis of percentage
having maximum sequence identity among all explored templates.
3.2.2.4. Sequence Alignment
The obtained template and target sequences were aligned using the CLUSTALW
program for pair-wise alignment.
40
3.2.2.5. Three-Dimensional (3D) Model Prediction
The tertiary structure of F3’5’H proteins were modeled through online server I-
TASSER (http://zhanglab.ccmb.med.umich.edu/I- TASSER/). The raw amino acid
sequences of target proteins were uploaded in FASTA format to I-TASSER server. The
tool deduced protein models on the basis of homology modeling as well as threading. The
PDB templates provided for homology modeling of Gossypium hirsutum, F3’5’H was
PDB: 2hi4A and F3’5’H (Iris hollandica) PDB: 4i8vA, both having more than 50%
identity.
This confirmed the modeling of F3’5’H protein accurately according to the template
requirement. The resultant 3D models were predicted in PDB file format and viewed in
RasMol software. Against each entry five top models were generated, the one with the
highest confidence score (c-score) was considered as best model and selected for further
study.
3.2.2.6. Energy Minimization
The “ModRefiner” algorithm was used for high resolution protein structure
refinement. Aim of using this tool was to draw the initial starting models closer to their
native state, in terms of hydrogen bonds, backbone topology and side-chain positioning.
3.2.2.7. Validation of Predicted Model
Protein models of F3’5’H were validated and evaluated by using the online
tool RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php) to generate
Ramachandran plot by computinging their physiochemical characteristics. The
41
Ramachandran plot also examines stability of protein model by determining its
stereochemical properties.
3.2.2.8. Prediction of Ligand Binding Sites
The ligand binding sites of both F3’5’H proteins were predicted by COACH server
available on I-TASSER. The fasta sequence was run on COACH server which generates
models having the similar binding sites.
3.2.2.9. F3’5’H Docking Analysis
AutoDock/Vina with its default parameters was employed for docking, using
protein-ligand information along with defined grid box properties in the configuration file. It
is based on a sophisticated optimization algorithm that uses a gradient optimization method
in order to calculate the binding energy of the receptor-ligand complex (Blum et al., 2008).
These docking experiments were conducted in order to explore the substrate utility efficacy
of receptor proteins, F3’5’H with their respective ligands, Naringenin and Quercetin.
The ligands, Naringenin (CID: 932) and Quercetin (CID: 5280343)
were downloaded from pubChem database in 3D format and converted to pdb file, because
the autodock software could only recognize files in pdb format. The Pdbqt files of the
receptor and ligand molecules were generated by using the Autodock tools software
downloaded from MGLm (http://mgltools.scripps.edu/downloads). In order to generate
receptor pdbqt files, water molecules were removed, hydrogen atoms and kollman charges
were added followed by preparation of grid box to cover whole molecule in order to make it
ready for ligand binding. Similarly, pdbqt file for ligand was prepared and root was detected
by going to torsion tree. For preparation of the grid box, size was set as 46 × 52 × 46 xyz
42
points with spacing (grid) of 1 Å. Broyden-Fletcher-Goldfarb-Shanno algorithm was used
for docking calculations.
The ligand binding orientation and conformations (generally known as posing) was
predicted by Search algorithms (Seeliger et al., 2010; Rauf et al., 2015). The obtained output
files of docking experiments were opened in Pymol. After visualization of the receptor-
ligand complex, the final interpretation was made.
3.3 FLAVONOID CONSTRUCT DESIGN
The DFR (Iris hollandica) and F3’5’H (Viola wittrockiana) gene sequences
were redesigned according to the codon preference of cotton plant to get high expression by
using web based tool on GenScript (https://www.genscript.com/codon-opt.html). In
GenScript, OptimumGeneTM
algorithm optimizes a variety of parameters out of which GC
content and codon adaptation index (CAI) were the most critical features to obtain efficient
gene expression. Ideal percentage of GC content for cotton ranges from 30-70% while CAI
value of 1.0 was considered to be perfect to get desired expression in mentioned organism,
and CAI of > 0.8 is regarded as good, in terms of high gene expression level.
A well reported translational enhancer, ADH-5’UTR (58bp) from Arabidopsis
thaliana (Aida et al., 2008) was added to the N-termianls of DFR and F3’5’H genes.
Expression of both genes was studied under CaMV35S promoter and Nos terminator. A
short stretch of about 18 random nucleotides was added as identity tag right after Nos
terminator. Restriction sites of KpnI and XbaI were introduced into the 5′ and 3′ ends of the
synthetic expression cassette respectively.
43
3.4 IN-SILICO DESIGNING OF CONSTRUCT IN pCAMBIA1301
In silico designing of construct was done by using features of molecular biology
software “Snapgene”. Constructs expressing F3’5’H & DFR genes were prepared by
inserting the F3’5’H along DFR into the corresponding sites at MCS (multiple cloning sites)
under the control of CaMV35S promoter and Nos terminator in the plasmid
pCAMBIA1301.
3.5 CHEMICAL SYNTHESIS OF FLAVONOID CONSTRUCT
The whole Flavonoid gene cassette of 4032 bp having both genes (F3’5’H & DFR)
were chemically synthesized from BioBasic Inc. (https://www.biobasic.com/us/gene-splash-
gene-in-vector/) (Ontario, Canada). Initially, the expression cassette was made available
after synthesis in a cloning vector pUC57 with an ampicillin resistance marker. The
physical map of the cassette and pCAMBIA 1301 are shown below (Figure 3.1 & 3.2).
Figure 3-1: Illustration of Flavonoid construct in pUC57.
44
Figure 3-2: Diagrammatic representation of pCAMBIA 1301.
Source: http://www.cambia.org/.
45
3.6 PREPARATION OF COMPETENT CELLS (E. coli, Top10 strain)
Glycerol stock of E. coli (Top10 strain) was obtained and streaked on LB media
plates having tetracycline selection with the help of sterilized inoculating loop. The plates
were incubated at 37οC in a static incubator for overnight.
A single colony was picked, re-suspended in 5 ml LB broth (Appendix-I) having
tetracycline (50 µg/ml) and kept overnight in shaking incubator (300 rpm) at 37οC. This
primary culture was further diluted in a ratio of 1:100 and left for 3 hours at 37οC in a
shaking incubator with shaking speed of 350 rpm to get OD up to 0.8. Then the secondary
culture was harvested through centrifugation at 4C and 13000 rpm for 3 minutes. After
centrifugation, the supernatant was discarded and pellet was re-suspended in ice-chilled
CaCl2 (100 mM). Again the tubes were spun at same conditions to achieve the maximum
cell pellet. Finally the pellet was re-suspended in 80 µl of ice-chilled CaCl2 (100 mM).These
E. coli competent cells were ready for transformation.
3.7 TRANSFORMATION OF pUC- F3’5’H & DFR IN E. coli
Three microliters of plasmid having flavonoid genes were transformed in to E. coli,
Top10 competent cells. The mixture was blended thoroughly, incubated on ice for fifteen
minutes and subjected to heat shock at 42C for 1.5 minutes followed by its immediate
incubation on ice for 5 minutes. Then 800 µl of LB Broth was added in E. coli transformed
product. The mixture was multiplied through incubation at 37C on shaking incubator for 1
hour. The pellet produced was by centrifugation for 2.5 minutes was suspended in 200 µl of
fresh LB Broth.
46
Then 60 µl of this culture (freshly grown cells of transformed E. coli) was spread on
LB selection plates having 50 µg/ml ampicillin and tetracycline. Moreover, these plates
were incubated overnight at 37C in a static incubator.
3.8 PLASMID ISOLATION
Randomly selected colonies were subjected to inoculation in LB broth for overnight
to get culture. The culture was used for plasmid isolation, which was performed by using
GeneJet Plasmid Extraction Kit (Catalogue # K0503). The fully grown cultures were
harvested through centrifugation for two minutes at 13000 rpm to get pellet. The pellet was
re-suspended in 250 µl re-suspension solution (Solution I, RNase A added). Lysis solution
(Solution II, 250µl) was added and mixed completely. Then neutralization solution
(Solution III, 350µl) was added and mixed thoroughly by inverting the tubes 4 to 6 times.
Further the tubes were centrifuged for 5 minutes and supernatant was transferred to GeneJet
spin column supplied with kit. Again the tubes were allowed to centrifuge for 1 minute. The
column flow-through was discarded and columns were inserted back into same collection
tubes.
Later on, wash buffer (500 µl, ethanol diluted) was added to each column followed
by 1 minute centrifugation and follow-through was disposed off. Again the washing step
was repeated. An additional spin was given to the columns for the removal of any residual
wash solution and then the columns were transferred to new microfuge tube.
Finally the plasmid was harvested by putting 30 µl of ribonuclease free water in the
center of each column membrane followed by spun for short time.
47
3.9 CONFIRMATION OF PLASMID BY AMPLIFICATION AND
RESTRICTION DIGESTION
3.9.1 PCR AMPLIFICATION OF F3’5’H & DFR GENES
The isolated plasmid was subjected to confirmation through PCR amplification by
using gene specific primers (Table 3.1) with expected amplified products of (~476bp) for
F3’5’H and (~537bp) for DFR gene. Primers were made available after synthesized from
Gene-Link TM Hawthorne, USA. Thermo-cyclic profile used for amplification of F3’5’H
and DFR genes was comprised of: initial denaturation at 95°C (4 min) followed by 40
cycles at 95°C (45 sec), annealing at 54°C/52°C (45 sec), elongation at 72°C (45 sec) and
final elongation at 72°C (10 min).
3.9.2 RESTRICTION ANALYSIS
The flavonoid cassette (F3’5’H & DFR genes) was cloned in pUC57 at MCS
(multiple cloning site) with KpnI and XbaI as flanking regions. Restriction digestion was
carried out to excise 4032 bp fragment from pUC57 to confirm flavonoid cassette by using
KpnI and XbaI enzymes. Following restriction reaction was used:
Table 3-1: Primers used in PCR
Primer
ID
Sequence (5´- 3´) Annealing
Tm
Product
size
F3’5’H -F 5´AAGCACAACCGAAGGATTTG3´ 54ºC 476 bp
F3’5’H -R 5´GCCGCTCAAACAGGAATAAA3´
DFR -F 5´ATATCCCGCAGTCGCATAAC3´ 52ºC 537 bp
DFR -R 5´TTAAACCCCACCATCCTTGA3´
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3.10 CLONING OF F3’5’H & DFR IN pCAMBIA1301
The binary vector pCAMBIA-1301 was used as plant expression vector. The
plasmid pUC57 harboring flavonoid cassette with KpnI and XbaI flanking sites at 5’ to
3’ends as well as pCAMBIA1301 at MCS was digested with restriction enzymes KpnI and
XbaI to generate overhangs. Digestion reactions were prepared as follows in separate tubes:
Reagent Quantity
Reagent Quantity
pUC57 with cassette 10 µl (1-3µg) pCAMBIA plasmid 10 µl (1-3 µg)
KpnI 1 µl KpnI 1µl
XbaI 2 µl XbaI 2 µl
Green buffer 2 µl Green buffer 2 µl
Injection water 1 µl Injection water 1 µL
Total volume 15 µl Total volume 15 µl
Reagent Quantity
pUC57(F3’5’H+DFR) 10 µl (13µg)
KpnI 1µl
XbaI 1µl
10X Green Buffer 2µl
Nuclease Free water 6µl
Total Volume 20µl
49
Reaction mixture was incubated at 37ºC for 20 minutes and resolved on 1 % agarose
gel. The digested pCAMBIA plasmid and the desired construct were carefully eluted from
the resolved gel as given below the standard gel elution protocol of GeneJet™ Gel
Extraction kit (Thermo Scientific Cat#k0692) and quantified on a nanodrop.
3.10.1 GEL ELUTION
Desired bands were eluted from gel by using GeneJet™ Gel Extraction kit (Thermo
Scientific Cat#k0692). Gel slices were weighed and binding buffer (1:1 v/w) was added to
the tubes for an incubation period of 10 minutes at 50-60 ºC to make homogenous mixture.
Further the solubilized gel solution was transferred to elution column followed by
centrifugation of 1 minute at 13,000 rpm. After discarding the flow-through about 500 µl
wash buffer (ethanol diluted) was added to the elution column and centrifuged for 1 minute.
The same step was repeated for purification. An additional centrifugation of 1 minute was
done to remove any contents of wash buffer solution. Finally, elution was performed by
adding 30 µl of ribonuclease free water to the center of column membrane followed by
centrifugation of 1 minute. Eluted product was quantified through nanodrop and preceded
for ligation in the plant expression vector.
3.10.2 LIGATION OF INSERT (F3’5’H & DFR) IN PCAMBIA-1301 VECTOR
Ligation of F3’5’H & DFR genes in the plant expression vector was done by using a
DNA ligation kit (Thermoscientific cat# K1422). Overhangs of both pCAMBIA vector and
flavonoid genes F3’5’H & DFR were proceed in 1:1 and 3:1 ratio by using T4 DNA ligase.
The ligation reaction mixture was carried out in tubes and all the required ingredients were
50
added followed by incubation at 22oC for 1 hour. The ligated product was saved at -20C.
Reagent Quantity
Reagent Quantity
Vector (60 ng/µl) 2 µl Vector (6 0ng/µl) 2 µl
Insert (70 ng/µl) 1.8 µl Insert (70 ng/µl) 2.3 µl
Ligase 1 µl Ligase 1 µl
Buffer 4 µl Buffer 4 µl
Injection water 11.2 µl Injection water 10.7 µl
Total volume 20 µl Total volume 20 µl
3.11 SCREENING OF TRANSFORMED COLONIES
Ligated product was transformed into E. coli competent cells through heat shock
method as described in section 3.6. Plasmid isolation was done by picking the random
colonies that emerged on LB selection plates after plating of transformants as explained in
sections 3.8.
3.11.1 DETERMINATION OF FLAVONOID CASSETTE BY RESTRICTION
DIGESTION
To confirm the ligation of insert (flavonoid genes) and vector (pCAMBIA 1301) the
restriction digestion was carried out as explained in section 3.10.2. Digested product was
resolved on 0.8 % agarose gel and visualized under UV for confirmation of successful
ligation.
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3.12 AGROBACTERIUM COMPETENT CELLS PREPARATION
Agrobacterium strain (LBA4404) was inoculated in YEP Broth (Appendix-I) with
selection of Rifampicin (50 μg/ml) and kept for 48 hours at 30C in shaking incubator.
Later, the primary culture was diluted to secondary in a ratio of 1:100 followed by
placement at 30C in a shaker incubator for 3 hours. The culture was taken and spun at 4C
(4000 rpm) for 10 minutes. The supernatant was discarded after centrifugation at 4C (10
minutes), further the pellet was washed twice with ice-chilled 1M HEPES solution (45 ml)
with centrifugation for 10 minutes. Later on, the last washing with ice-chilled 10% Glycerol
solution (30 ml) was given and finally the pellet was dissolved in 1 ml of the same ice-
chilled 10% Glycerol solution. These cells were further stored at -80 C for future use.
3.13 ELECTROPORATION OF RECOMBINANT PLASMID INTO
THE AGROBACTERIUM COMPETENT CELLS
Recombinant Plasmid (pCAMBIA+F3’5’H & DFR) was transformed into the
competent cells of Agrobacterium tumefaciens (LB4404 strain) using Electroporation
Device of Bio-Rad (165-2105). About 10 µl ligated product was transferred to
Agrobacterium competent cells, thoroughly mixed and incubated on ice for 30 minutes.
Electric shock was given to the cell mixture in cuvette at 25 μFD Capacitance, 2.2 kV
Voltage and 200 Ω Resistance at constant time. After electric shock, the mixture was
immediately transferred to a culture tube containing YEP Broth (800 µl) followed by
placement of tube at 30C in shaking incubator for 3 hours. At completion of incubation, the
Agrobacterium culture harboring required plasmids was spread on YEP agar plates
52
(Appendix I) having selection of kanamycin (50 µg/ml) and rifampicin (50 µg/ml) further
incubated at 37ºC for 48 hours.
3.14 CONFIRMATION OF pCAMBIA (F3’5’H & DFR) IN
AGROBACTERIUM
Agrobacterium colonies that appeared on YEP selection plates were marked
randomly and preceded to confirmation of the transformants through colony PCR. The
selected colonies were resuspended in 20 µl ribonuclease water and disrupted through heat
shock at 95C in a thermo-cycler machine for ten minutes. Further the supernatant collected
after 5 minutes centrifugation (13000 rpm) was used as template in PCR reaction. The PCR
was performed with F3’5’H and DFR specific primers according to procedure described in
section 3.9.1. The PCR product was resolved on 1% agarose gel and visualized under UV
light for presence of confirmation of gene constructs electroporation in Agrobacterium.
3.15 TRANSFORMATION OF F3’5’H & DFR IN COTTON (Gossypium
hirsutum) VAR. VH-319
Agrobacterium strain LBA4404, harboring recombinant plasmid (pCAMBIA+
F3’5’H & DFR) was used for transformation of cotton with F3’5’H & DFR genes. A local
cotton variety, VH-319 (Gossypium hirsutum) was used in transformation experiments.
Mature embryos of cotton were used as explants.
3.15.1 PREPARATION OF PLANT MATERIALS
3.15.1.1 Delinting Cotton Seeds
Sulphuric acid (concentrated 95-98 %) was used for delinting of cotton seeds
(Gossypium hirsutum) at the rate of 100 ml/kg of seeds. After the addition of few drops of
53
sulphuric acid, the seeds were stirred vigorously with the help of spatula for 5-7 minutes,
until all the cotton lint was removed and cotton seeds became shiny in appearance.
Additionally, 6-7 water washings were given to remove the acid completely. Later, the
sinker seeds were proceeded for surface sterilization and soaking.
3.15.1.2 Surface Sterilization and Germination of Seeds
Delinted seeds were sterilized with 10% SDS (1 ml) and 5% HgCl2 (2 ml) in 100 ml
of autoclaved water in flask followed by vigorous shaking of seeds for 5 minutes till the
foam appeared. Then water washings were given unless whole foam was removed. Whole
procedure was performed under aseptic conditions. Finally, seeds were allowed to germinate
in adequate moisture contents. The flask containing seeds was placed at 30C in a static
incubator in dark condition for 2 days. The germination index was calculated through the
following formula:
Germination Index = Germinated Seeds/Total Seeds × 100
3.15.1.3 Embryos Isolation
Mature embryos were isolated from germinated seeds of VH-319 by using sterilized
forceps. The testa and cotyledonary leaves were excised with help of surgical blades and
further subjected to transformation experiments.
3.15.1.4 Agrobacterium Inoculum Preparation
Agrobacterium culture containing plasmid pCAMBIA+F3’5’H & DFR was
maintained on solid LB medium (Appendix I) having rifampicin (50 mg/l) and kanamycin
(50 mg/l) at 30C (Appendix II). Single Agrobacterium colony was taken from the solid LB
medium plate and inoculated to 15 ml LB broth with selection and incubated on shaker (150
54
rpm) for 48 hours at 30C. These freshly grown transformed Agrobacterium cultures were
centrifuged (4000 rpm) at 4C for 10 minutes followed by re-suspension of pellet in MS
Broth (7 ml). This mixture was used as an inoculum.
3.15.1.5 Cotton Transformation Experiments
The isolated embryos were subjected to injury through sharp blade mounted on petri
plate by following shoot apex cut method, optimized in Plant Biotechnology Lab at CEMB
to achieve greater transformation efficiency (Rao et al., 2009). The complete transformation
protocol was comprised of below mentioned transformation steps.
3.15.1.6 Infection Period
The embryos were infected with Agrobacterium suspension with optical density
ranging from 0.6-0.8 and left for one hour at 30C in a shaking incubator (200 rpm) under
dark conditions.
3.15.1.7 Co-cultivation Period
After the infection period of one hour, Agrobacterium treated embryos were taken
and dried on sterile filter paper. Later, all embryos were shifted to MS media plates
supplemented with Cefotaxime (250 mg/ml) one by one, placing their radicle pointing
downwards. Then plates were moved to growth room at 25° C± 2° C under white light
conditions and co-cultivated for 3 days.
3.15.1.8 Shoot Induction Media
Co-cultivated embryos emerged as small plantlets were shifted to regenerative media
and incubated in white light at 30C. Regeneration media was comprised of MS Medium
55
supplemented with cefotaxime (250 mg/l) and kinetin (1 mg/ml). Antibiotic, cefotaxime was
used to control bacterial contamination.
3.15.1.9 Calculation of Transformation Efficiency
After transformation, plants were sub-cultured many times on new selection media
after every 10 days. On the basis of putative transgenic cotton plants survival, the total
transformation efficiency was calculated after 10 weeks by applying following formula:
Transformation efficiency = Number of plants survived/Total number of isolated embryos ×
100
3.15.1.10 Shifting of Putative Transgenic Cotton Plants to Pots
After 2 months, plants having well-established roots were shifted to small pots
(34×34 mm) having sand, peat moss and clay mixture in 1:1:1 ratio and fungicide (1%
MANCOZEB). Using long forceps, transformed plants were taken out of the glass tubes.
Later, their roots were washed with water, dried and dipped in rooting hormone i.e. Indole
Butyric Acid (IBA solution 1 mg/ml), finally the plants were shifted to pots provided a bit
of water and for their stabilization covered with polythene bags. The plants with polythene
covers were kept in a culture room at 30ºC under light conditions. After one week, plants
were uncovered for ten minutes and interval was prolonged until three weeks, when plants
were able to survive without covers, they were shifted to the greenhouse.
3.16 MOLECULAR ANALYSIS OF TRANSGENIC COTTON PLANTS
Molecular analysis of the putative transgenic cotton plants was done to confirm the
integration and expression of F3’5’H and DFR genes. Acclimatized putative transgenic
cotton plants that survived in field were subjected to PCR analysis.
56
3.16.1 GENOMIC DNA EXTRACTION
Plant genomic DNA was extracted from 0.5g of fresh leaves by using CTAB Method
with some modifications (Saha et al., 1997). First, CTAB (990 μl) and 2-mercaptoethanol
(10μl) were mixed in 1.5ml tube. Newly emerged fresh leaves were taken from experimental
plants and were grounded to fine powder in a chilled pestle and mortar followed by
immediate mixing in pre heated CTAB buffer until it became homogenous mixture. The
mixture was incubated at 65oC for 1.5 hour (Appendix III). The mixture was spun at 1300
rpm for 10 minutes followed by collection of the supernatant in a fresh 1.5ml tube. Equal
volume of chloroform: isoamyl alcohol (24:1) was added with gentle mixing. The mixture
was spun at 13000 rpm for 10 minutes. The upper phase was taken in a separate 1.5ml tube
and 0.6 volume of chilled isopropanol was added. Later the tubes were stirred through
vortex and placed for overnight at -20oC. Next day, the mixture was spun at 13000 rpm for
10 minutes. The supernatant was decanted and pellet was washed with chilled 70% ethanol.
The pellets were dried through centrifugation. Finally, each pellet was dissolved in 25 μl
ultra pure water. The quality of DNA was estimated by resolving DNA samples on 0.8%
agarose gel (Appendix III).
3.16.2 PCR CONFIRMATION OF PUTATIVE TRANSGENIC COTTON PLANTS
PCR analysis of genomic DNA was carried out in a 20 μl reaction tube, by using 50-
100 ng of isolated DNA as template. DNA isolated from non transgenic plants was used as
negative control while pCAMBIA+F3’5’H & DFR plasmids were used as positive control
under PCR conditions as describes in section 3.9.1.
57
Further, the PCR products were resolved on 1% agrose gel and visualized under UV
for assurance of specific amplification through gene specific primers.
3.16.3 DOT BLOT HYBRIDIZATION ASSAY
The integration of transgenes into the genome of cotton was further confirmed
through dot blot assay in both T0 and T1 generations. Genomic DNA of transgenic cotton
plants confirmed by PCR was used in experiment. The DNA isolation from transgenic
cotton plants was done through CTAB method and further preceded for dot blot analysis.
About 1 μg genomic DNA of each transgenic cotton plant was denatured at 95 oC for 10 min
with immediate chilling on ice for 5 min and spotted on a positively charged nylon
membrane (Roche Applied Sciences, Mannheim, Germany) according to manufacturer’s
recommendations. The DNA samples were fixed on the membrane through UV cross-
linkage (3minutes, 254 nm). Plasmid pCAMBIA1301 harboring flavonoid genes as well as
non transgenic cotton plants DNA were used as positive and negative controls respectively.
3.16.3.1 Probe Labeling
A F3’5’H-specific probe was labeled with the help of DIGof DIG-dUTP by the use
of DIG High Prime DNA Labeling and Detection Starter Kit (Cat #11585614910, Roche
Diagnostics Mannheim, Germany). Plasmid DNA was preheated at 95 o
C for 10 min, ice
chilled for 5 minutes followed by addition of DIG-dUTP/ DIG-High Prime (3-4uL) from kit.
Tube was spun briefly and incubated at 37 oC for overnight. Further the probe was
quantified by nano-drop.
3.16.3.2 Hybridization & Washings
Hybridization procedure with stringent washings and detection was carried out by
using a DIG Nucleic acids Detection Kit (Roche Diagnostics, UK) according to the
58
manufacturer’s instructions. Standard steel tray was used for the hybridization experiment.
Membrane was placed in the pre-hybridization (Appendix IV) solution for 1.5 hour at 65oC
in hybridization tray. After two hours 20 ml of pre- hybridization solution was taken and
mixed with labeled probe by heating on 65 oC for 10 minutes.
Ten microliters of the denatured labeled probe (heating 95 oC for 10 minutes) was
added to a hybridization tray containing preheated (65°C) hybridization solution along with
the membrane with spotted DNAs of transformants (as described above) and left overnight
for hybridization with constant agitation. Next to hybridization, two post-hybridization
washings were given to the membrane as follows: 15 ml of 2X SSC, 0.1% SDS for 15
minutes at room temperature and pre-warmed (65°C) 15 ml of 0.5X SSC, 0.1% SDS for 15
minutes.
3.16.3.3 Immunological Detection of Probe
The detection of spotted DNA on the membrane was done using the Roche kit
protocol for chromogenic detection at 37°C with steady agitation. Membrane was
equilibrated by single wash for 1 minute in Genius buffer I (Appendix IV). Later, the
membrane was incubated for 0.5 hour in 50 ml of blocking solution, 30 min in 20 ml of
antibody solution (AP conjugate as 1:5000), washed 2 twice (15 minutes) in 20 ml of
Genius buffer I and then preceded for incubation in 30 ml of Genius buffer III (1minute).
Further, the membrane was incubated under dark conditions at 37°C in immune-detection
solution which contained two crushed tablets of NBT/BCIP dissolved in 30 ml of Genius
buffer III. Finally, after 4-5 hours of colour development, NBT/BCIP reaction was stopped
by decanting immune-detection solution and membrane was rinsed 4-5 stimes with sterile
water.
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3.16.4 EXPRESSION ANALYSIS OF TRANSGENIC COTTON PLANTS
3.16.4.1 RNA Extraction
Total RNA was extracted from the transgenic cotton plants of T1 progeny as
described Jaakola et al. (2001) with some modifications. Expressional studies were
conducted in leaves and cotton ovules (20DPA) associated with some fibers. Sampling of
cotton plant material was done from green house and plant sample tissues were pulverized
to a fine powder in liquid nitrogen using a pestle and mortar. Ground samples were
transferred to micro-centrifuge tubes (1.5ml) containing 750 µl of pre-heated (65°C)
extraction buffer I (Appendix V) and mixed through vortex. The tubes were incubated at
65°C for 15 minutes followed by vortex during incubation. Total 750 µl of chloroform:
Isoamylalcohol (24:1) was added to the samples, vortex and centrifuge at 13000 rpm for 10
minutes at room temperature. Supernatant was shifted to neat micro-centrifuge tubes (1.5ml)
and same step was repeated. Again supernatant phase was shifted to new micro-centrifuge
tubes (1.5ml), about 500 µl of extraction buffer II was added and mixed later through vortex
followed by incubation on ice. Ice chilled chloroform (150 µl) was added to the tubes,
vortex and left for 10 minutes at room temperature. Tubes were centrifuged at 13000 rpm
for 10 minutes at 4°C. Further, the upper aqueous phase was transferred into new micro-
centrifuge tubes (avoid contamination with inter-phase).Then, 0.6 volume of ice-chilled
isopropanol was added and mixed through vortex followed by incubation at room
temperature (10 minutes). Tubes were spun at 13000 rpm for 10 minutes at 4°C to collect
RNA pellet which was washed with 500 µl of 70% ice-cold ethanol and left on bench for air
dry. Pellet was re-suspended in appropriate volume of ice-chilled DEPC treated autoclaved
deionized water. Integrity of RNA was visualized on 1% agarose gel resolved at 70-80 V for
30 minutes. Further the isolated RNA was quantified by nano drop.
60
3.16.4.2 cDNA Synthesis
The cDNA was synthesized after RNA quantification by using a Revert Aid First
Strand cDNA Synthesis Kit (Thermo Scientific, K1622). For cDNA synthesis the following
reagents were used:
Reaction mixture was incubated at 65°C for 5 minutes followed by quick ice
chilling. Then following ingredients were added according to manufacturer instructions:
Reagent Quantity
5X Reaction Buffer 4 µl
10 mM dNTP Mix 2 µl
RiboLockRNase Inhibitor 1 µl
RevertAid Reverse Transcriptase 1 µl
Total Volume 8 µl
Reagent Quantity
RNA Template 1µl
oligo-(dT)18 primer 1µl
Nuclease-Free water 10µl
Total volume 12µl
61
The cDNA synthesis was carried out as a single step reaction in a thermocycler by
placing it at 25°C for 10 min, 42°C for 60 min and 70°C for 5min. Now this cDNA
synthesized was used as template in RT-PCR. The cDNA was stored in cold chamber at -
70°C for future use.
3.16.4.3 Primer Design
Polymerase chain reaction (PCR) was used to amplify both genes using cDNA of
transformants as template (Table 3.2). Primers for both genes were designed using online
Primer3 tool (http://primer3.ut.ee/).
For amplification of both Flavonoid genes, the total 20µl reaction volume was used
at the given PCR conditions i.e. initial denaturation at 95˚C for 4min, followed by 40
cycles of amplifications (denaturation at 94˚C for 45sec, annealing at 61˚C for 45 sec,
extension at 72˚C for 45sec) final extension at 72˚C for 10 min was programmed in
thermos cycler. The mixture was prepared as.
Table 3-2: Primers used in RT-PCR
Primer
ID
Sequence (5´- 3´) Annealing
Tm
Product
size
FR -F 5´CACATGTTGGGAGGAAAGGC 3´ 59ºC 104 bp
FR -R 5´GGTTCGCCGCATCTACTTG 3´
DR -F 5´TGGAAGGCTGATTTGGGACA 3´ 61ºC 145 bp
DR -R 5´TAAGCACCCCGTTGATGGT 3´
62
The amplified PCR product was resolved on 0.8% agarose gel provided with
1.0µg/ml ethidium bromide and visualized under UV light.
3.17 ANTHOCYANIN CONTENTS ASSAY
The pH differential method was used to measure the anthocyanin contents of the
transgenic and non transgenic cotton plant samples from T1 generation as documented by
Lapornik et al. (2005). It is based on the principle of anthocyanin pigments to change their
colour with pH.
Reagent Quantity
Template DNA (100ng/µL) 1µl
Forward Primer (10 pmol) 1µl
Reverse Primer (10 pmol) 1µl
10X PCR Buffer 2µl
MgCl2 (25mM) 1µl
dNTPs (10.0mM) 1µl
Taq Polymerase (5U/µL) 0.7µl
Nuclease Free water 12.3µl
Total Volume 20µl
63
3.17.1. SAMPLE PREPARATION
About ~0.5 g of young leaves from transgenic and non transgenic cotton plants were
taken and homogenized in 70% methanol as the solvent. Mixture was left at room
temperature for overnight. Next day, the extracts were filtered with the help of filter paper
and further subjected for total anthocyanin contents analysis.
3.17.2. ESTIMATION OF ANTHOCYANIN CONTENT
Two dilutions of the each sample were prepared, the first dilution was done in 2%
HCl (10ml, pH 0.8) and the second one in citric buffer (10 ml, pH = 3.5) (Appendix VI).
Each dilution in addition was comprised of, one ml of filtered extract and one ml of 0.01%
HCl solution. Further, each solution was mixed thoroughly and their absorbance was
measured at 530 nm taking 70% methanol as blank. Three biological replicates were taken
for each sample.
Total anthocyanin contents were calculated by using the equation: TAC = (A1 – A2) × f
Where: TAC = total anthocyanin contents expressed as µg/g cyanidin
A1 = absorbance in 2% HCl (at pH 0.8), f = MW×DF×CF1×CF2/ ε ×l
A2 = absorbance in citrate buffer (at pH 3.5)
MW = molecular weight of cyanidin-3-glucoside (449 g/mol)
DF = dilution factor (50 ml/10 g) = path length (1 cm)
CF1 = conversion factor 1 (106 ug/g) CF1 = conversion factor 2 (1 L/1000 ml)
ε = molar extinction coefficient of canidin-3-glucoside (26,900 L/mol·cm)
64
3.18. DETERMINATION OF COTTON FIBER QUALITY
The data about distinguishing characteristics of cotton lint such as fiber fineness
(μg/inch), fiber strength (g/tex) staple length (mm) and uniformity index was taken at two
generations i-e T0 and T1. For fiber analysis, fiber sample of size 100g harvested at full
mature stage from both transgenic and non transgenic control plants were collected. All
fiber samples were sent to standard laboratory for cotton fiber characterization located at
Central Cotton Research Institute, Fiber Technology Section Multan, Pakistan.
3.19. ELECTRON MICROSCOPIC ANALYSIS OF COTTON FIBER
SURFACES
For scanning microscopic analysis (SEM) of mature cotton fiber, samples from
transgenic along non transgenic cotton at T1 generation were prepared. Every fiber was
sectioned in three parts like tip, middle and base. The fiber’s screw pitch as well as distance
of rotation was measured thrice at 3600
for each fiber sample with scanning electron
microscope (Model SU8010 Hitachi Japan) by keeping voltage, 20kVand current, 10µA.
Further, the images were taken at following magnifications: 400X, 1000X and 4000X.
3.20. AGRONOMIC TRAITS
Stable transgenic cotton lines with non transgenic control line at T1 generation were
selected and morphological traits such as plant height (cm), number of monopodial
branches, number of sympodial branches, number of bolls per plant, number of damaged
boll, boll weight, lint weight, as well as physiological characters like leaf area, evaporation
rate, photosynthetic rate and gaseous exchange were measured. For morphological analysis
plant data was collected after every fifteen days (for 2 months). Pearson’s correlation was
65
applied on the data using SPSS (version 2016) with the purpose to find a direct or indirect
correlation between any two of these variables. Pearson’s co-relation was calculated using
mean values of the each variable (traits). A p-level of 0.05 and 0.01 was used for highly
significant correlations. Moreover at the crop harvest, the yield per plant was evaluated by
weighing cotton lint with seed at electric balance (using model Sartorius BP 4100).
3.21. FLUORESCENCE IN SITU HYBRIDIZATION (FISH)
3.21.1 PREPARATION OF CHROMOSOME
From germinated cotton seeds, 1-2 cm long radicle region was cut with sharp scalpel
blade and fixed in fixative (Ethanol: 3 volumes, Glacial Acetic Acid: 1 volume) for
overnight. Three times washing was done with water for the removal of fixative. The
meristematic tissue of radicle was taken and incubated in a solution of enzymes containing
2% Pectolyase (Sigma cat# P 3026) and 3% Cellulase (Sigma cat# C 1184) for 4 hours at
37 °C followed by washing with distilled water. Chromosomes were spread on glass slide
by adding a drop of fixative. After air drying, the slides were observed under phase contrast
microscope (Olympus Model BX51) and selected for FISH. The slides were dehydrated for
5 minutes in the following ethanol concentrations: 70%, 95% and 100% respectively.
Slides were labeled properly and stored at room temperature.
3.21.2 RNASE TREATMENT
The RNase (1%) was diluted to 1:100, added to each slide and incubated in wet
chamber at 37°C for 45 minutes. Then slides were washed with 2X SSC thrice for 5 minutes
at room temperature. Again the dehydration step with different concentrations of ethanol
was repeated.
66
3.21.3 HYBRIDIZATION
Hybridization solution was prepared denatured for 10 minutes at 80 °C and ice
chilled for 5 minutes. This solution (35 μl) was added to each slide and the slides were dried
by keeping them on working bench. Later on, the chromosomes were denatured in 2X SSC
solutions at 80 °C for 10 min in water bath. Further, the slides were incubated at 37 °C for
18 hours in a wet chamber.
3.21.4 POST HYBRIDIZATION
Cover slips were removed through washing twice with 2X SSC (20X= 0.3M Sodium
citrate; 3M NaCl; pH 7.0) at 42°C for 10 minutes. The third washing was done with 4X SSC
for 10 min at 42°C.
3.21.5 CHROMOGENIC DETECTION REACTION
Slides were rinsed in following buffer: 150 mM NaCl, 100mM TrisCI, pH 7.5 and
washed in TBS buffer thrice for 5 minutes. Then kept in blocking solution (TBS; 0.1 %
Triton X-100; 1.0% Blocking Reagent) for 30 minutes. Solution was drained and transferred
to anti-DIG antibody diluted with blocking reagent in a ratio 1: 400 in TBS for a minimum
period of 4 hours at room temperature. Again washing of slides in TBS was carried out
thrice for 5 minutes. Finally slides were incubated in colour substrate solution of NBT/BCIP
for overnight. The reaction was stopped by rinsing them with tap water.
3.21.6 COUNTERSTAINING WITH DAPI
DAPI stain stock solution was prepared and diluted to 250 times by the addition of
8μl, 100 μg/μl DAPI and 1992μl Mellavaine buffer (l00 mM Citric acid and 500 mM
Na2HPO4; pH 7.0). Later this solution was added to each slide and further incubated at
67
room temperature for 5 minutes. The slides were rinsed with Mellavaine buffer (3ml),
properly covered with cover slip and stored at 4°C in dark.
3.21.7 COUNTERSTAINING WITH PROPIDIUM IODIDE (PI)
PI stock solution was diluted to 2500 times by putting 0.8μl PI and 2000μl IX PBS
(70 mM Na2H PO4; 10X= l.3M NaCI; 30 mM NaH2PO4; pH 7.4) on ice. This diluted PI
solution was dropped to each slide and incubated at room temperature for 5 minutes. Again
1 X, PBS (3 ml) was used to wash the slides and stored at 4 °C in dark.
3.21.8 SIGNAL DETECTION
Fluorescent microscope (Olympus Model BX6l) was used in the experiment for
florescent signal detection. To get fluorescent image Blue filter for DAPI and Red Filter for
PI was used. The image of fluorescence signal was recorded by CCD camera attached to
microscope and analyzed with Adobe Photoshop 7.0 software.
Chapter#4
68
CHAPTER 4 : RESULTS
4.1 BIOINFORMATICS ANALYSIS OF DFR
4.1.1 COMPARISON OF DFR REPORTED RESIDUES INVOLVED IN
SUBSTRATE SPECIFICITY
For comparison, at position 12 and 26, DFR sequences were aligned by using the
CLC Genomics Workbench 8 as mentioned earlier. From sequence alignment results it was
evaluated that at position12, Ang.DFRI, Ang.DFRII, Gossypium hirsutum DFR and Iris
hollandica DFR have proline, serine, proline and glycine respectively. This result showed
same residue (proline) in both Gossypium hirsutum and Angelonia DFRI where as
Angelonia DFRII and Iris hollandica DFR had serine and Glycine which were
functionally similar residues (Figure 4.1). In the present study, these sequence alignment
showed proline at 12 position in Gossypium hirsutum from which it is hypothesized that it
would reduce dihydrokaempferol. Whereas, this particular region is absent in both Iris
hollandica and Ang. II DFRs, resulting in delphinidin accumulation which is responsible for
production of anthocyanin pigments of blue colour (Figure 4.2). For further confirmation,
DFRs from five more species including these four plant species were further carried out for
analysis to evaluate the results. However, with respect to Ang. DFRI, sequence alignment of
other five species (Rosa chinensis, Vaccinium macrocarpon, Gerbera hybrid, Petunia
hybrida and Ampelopsis grossedentata) showed the deletion of proline rich region and thus
was found unable to reduce DHK.
69
4.1.2 ROLE OF Asn AND Asp TYPE DFRS IN SUBSTRATE SPECIFICITY
Recent analysis on DFRs (Iris hollandica and Gossypium hirsutum) was done by
using “Expasy Prot Param tool” in order to get information about the presence of total Asn
and Asp residues. Results showed that Iris hollandica DFR has (Asn9:Asp23) while
Gossypium hirsutum DFR was found to have (Asn13:Asp21) (Table 4.1).This is postulated
that Iris hollandica. DFR (Asp-type) has more likeness to reduce DHM in comparison to
DHK hence it has a key role in accumulating delphinidin by utilizing DHM as substrate.
Figure 4-1: Alignment of the amino acid sequences encoded by Ang. DFRI & DFRII,
Gossypium hirsutum and Iris hollandica. Proline rich region is marked with a box.
70
Figure 4-2: Multiple sequence alignment of dihydroflavanol 4-reductase.
Consensus sequences of different plant species (Rosa chinensis, Vaccinium macrocarpon,
Gerbera hybrid, Petunia hybrid, Ang. DFRI, Ang. DFRII, Gossypium hirsutum, Iris
hollandica and Ampelopsis grossedentata) were achieved by using CLC Genomics
Workbench 8. The coloured bars at the bottom are representing the conservation %age.
71
Table 4-1: Amino acid percentage in both Gossypium hirsutum and Iris hollandica
(Asn, 9: Asp, 23) by using Protparam tool
A B
Number of amino acids:361 Number of amino acids:355
Molecular weight: 40221.2 Molecular weight: 39651.7
Theoretical pI:6.13 TheoreticalpI:5.67
Amino acid composition: Amino acid composition:
Ala (A) 32 8.9% Ala (A) 25 7.0%
Arg (R) 18 5.0% Arg (R) 8 2.3%
Asn (N) 9 2.5% Asn (N) 13 3.7%
Asp (D) 23 6.4% Asp(D) 2 15.9%
Cys (C) 7 1.9% Cys (C) 8 2.3%
Gln (Q) 4 1.1% Gln (Q) 9 2.5%
Glu (E) 26 7.2% Glu (E) 27 7.6%
Gly (G) 22 6.1% Gly (G) 20 5.6%
His (H) 13 3.6% His (H) 9 2.5%
Ile (I) 19 5.3% Ile (I) 25 7.0%
Leu (L) 25 6.9% Leu (L) 29 8.2%
Lys (K) 25 6.9% Lys (K) 32 9.0%
Met (M) 14 3.9% Met (M) 13 3.7%
Phe (F) 15 4.2% Phe (F) 18 5.1%
Pro (P) 17 4.7% Pro (P) 18 5.1%
Ser (S) 22 6.1% Ser (S) 25 7.0%
Thr (T) 23 6.4% Thr (T) 20 5.6%
Trp (W) 6 1.7% Trp (W) 5 1.4%
Tyr (Y) 8 2.2% Tyr(V) 7 2.0%
Val(V) 33 9.1%
Pyl(O) 0 0.0%
Sec(U) 0 0.0%
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4.1.3 MODELING, REFINEMENT, EVALUATION AND VALIDATION OF DFR
PROTEIN
For the construction of 3D Model of DFR protein, retrieved sequences of both Iris
hollandica DFR and Gossypium hirsutum DFR were submitted to onlineI-TASSER server
(Figures 4.3 & 4.4). Further refinement was achieved by using the ModRefiner tool. The
constructed models were subjected to RAMPAGE to create Ramachandran Plot for model
evaluation. Figures 4.5 and 4.6 showed a Ramachandran plot of the Dihydroflavonol-4-
reductase protein’s model. Plot displayed the presence of 343(97.2%) residues in favored
region, 8(2.3%) residues in allowed region while 2 (0.6%) residues in outlier region in case
of Gossypium hirsutum DFR (Figure 4.6) and 338 (94.2%) residues in favored region 17
(4.7%) residues in allowed region plus 4 (1.1%) residues in outlier region in Iris DFR
(Figure 4.5). These computed results validated the models because for a fine model more
90% residues should be in both favored and allowed region.
4.1.4 PROTEIN-LIGAND DOCKING RESULTS
Docking results in case of Iris hollandica showed that position 130 has Asp as
well as Gln in all: DHK, DHQ and DHM. Additional Glutamine at position135also showed
attachment with DHK. However, Lys at positions 132 (of Iris hollandica DFR) has been
engaged in DHM and DHQ binding. Ala in position 126 (DHM) and His 218 (DHQ) had an
impact on substrate binding (Figure 4.7). As far as Gossypium hirsutum DFR is concerned,
Ala at position 153 is present in all types of dihydroflavonols. Asp at position 151 is
involved in Gossypium hirsutum DFR binding with DHK (Figure 4.8). Serine is positioned
at 239 which showed interaction in DHM while lle at 240 is involved in DHQ. All data
73
gathered from these proteins docking leads towards conclusion that all above mentioned
residues at defined particular positions were just involved in attachment with
dihydroflavonols (DHK, DHQ and DHM) and they have no role in the specificity of
substrates, they can reduce any available substrate (DHK, DHQ, and DHM). Present work
showed that 26 residue region was highly variable in DFRs from different plant species.
Figure 4-3: Three dimensional DFR protein model of Gossypium hirsutum predicted by
I-TASSER.
Figure 4-4: Three dimensional DFR protein model of Iris hollandica predicted by I-
TASSER.
74
Figure 4-5: Ramachandran plot analysis of Iris hollandica DFR model to visualize
dihedral angles; φ against ψ.
75
Figure 4-6: Ramachandran plot analysis of Gossypium hirsutum DFR protein model to
visualize dihedral angles; φ against ψ.
76
Figure 4-7: Two and three dimensional interaction diagrams of DFR Iris hollandica
with dihydroflavolnols. Interaction diagrams were attained by using ligand interaction
analysis feature of MOE.
77
Figure 4-8: Two and three dimensional interaction diagrams of Gossypium hirsutum
with dihydroflavolnols. Interaction diagrams were attained by using ligand interaction
analysis feature of MOE.
78
4.2 BIOINFORMATICS WORK ON F3’5’H GENE
4.2.1 SEQUENCE HOMOLOGY & STRUCTURE PREDICTIONS
The consensus amino acid sequences of F3’5’H from Gossypium hirsutum and Viola
wittrockiana, aligned by CLC Genomics Work bench had shown 33% dissimilarity
between them (Figure 4.9) which could sufficiently affect the gene functionality. Secondary
structure of F3’5’H was predicted by PSIPRED server. Viola secondary structure contained
alpha helix, random coils and extended strand as 47.04%, 39.92% and 13.04% respectively
(Figure 4.10) whereas Gossypium mostly possess alpha helix and random coils which
individually constitute 42.75% and 13.04% extended strands (Fig. 4.11). Physiochemical
properties of amino acid sequences (Viola wittrockiana & Gossypium hirsutum) computed
by ProtParam tool were summarized in Table 4.2. Stability index values showed the stable
nature of both proteins. Predicted half-life of proteins was 30h in mammalian reticulocytes,
20 and 10h in yeast and Escherichia coli respectively.
4.2.2 VALIDATION OF REFINED MODELS
Protein models for Viola and Gossypium were predicted by I-TASSER and the best
models on the basis of “c” score were selected (Figure 4.12 a & b). Further these models
were refined by ModRefiner to minimize energy of models in terms of hydrogen bonds,
side-chain positioning and backbone topology. Later these models were submitted to
RAMPAGE tool for structure validation. The Ramachandran plot demonstrated that 477
residues of Viola predicted model were in the favored region which constitute 94.6% while
23 (4.6%) residues in the allowed region and 4 (0.8%) in the outlier region (Figure 4.13). In
case of Gossypium protein model total residues in favored region were found to be 468
(92.1%), 30 (5.9%) in allowed region and 10 (2.0%) in the outlier region (4.14). These
79
calculated results validated the protein models because more than 90% residues should be in
both favored and allowed region for a fine model.
Figure 4-9: Consensus amino acid sequences alignment of F3’5’H from Gossypium
hirsutum and Viola wittrockiana by CLC Genomics Workbench 8. The colored bars
at the bottom represent the conservation Percentage.
80
Figure 4-10: Predicted Secondary structure for Viola wittrockiana by PSIPRED
online server. Pink rods: α-helices, yellow arrows: β-strands, black lines: coils. Blue
bars on the top indicated confidence of prediction.
81
Figure 4-11: Predicted Secondary structure for Gossypium hirsutum by PSIPRED
online server. Pink rods: α-helices, yellow arrows: β-strands, black lines: coils. Blue
bars on the top showed confidence of prediction.
82
Table 4-2: ProtParam tool analysis of Viola wittrockiana & Gossypium hirsutum.
Amino acid (AA).Grand average of hydropathicity (GRAVY), Instability index (II),
Aliphatic index (AI)
Accession No. AA MW pI Asp +Glu Arg+ Lys AI II GRAVY
ACH56524.1 510 57371.9 9.14 54 63 91.61 38.69 0.137
BAF93855.1 506 56056.5 8.92 52 59 98.34 33.86 0.019
Figure 4-12: a) 3D models of Viola wittrockiana predicted by I-TASSER (C-score: -
0.18) b) 3D models of Gossypium hirsutum predicted by I-TASSER (C-score: -0.19) C-
score is typically in the range of (-5, 2), higher C-score value signifies more confident
model.
83
Figure 4-13: Ramachandran plot analysis of Viola wittrockiana F3’5’H model to
visualize dihedral angles; φ against ψ.
84
Figure 4-14: Ramachandran plot analysis of Gossypium hirsutum F3’5’H protein
model to visualize dihedral angles; φ against ψ.
85
4.2.3 F3’5’H BINDING SITES IN VIOLA & GOSSYPIUM
Ligand binding sites for F3’5’H were predicted by COACH server (Figure 4.15).
The amino acid sequences (Viola & Gossypium) run on COACH server showed that
following positioned amino acids together compose catalytic pocket in these protein models:
104,119,120,129,133,302,305,306,308,309,313,364,369,370,372,374,376,439,
441,445,446,447,448,449,452,453,457.
Figure 4-15: Predicted ligand binding sites of a) Viola and b) Gossypium highlighted
with red spheres using coach server.
4.2.4 PROTEIN-LIGAND DOCKING ANALYSIS
Docking results computed by Auto dock Vina were evaluated in terms of binding
energy. For Viola F3’5’H, docked results determined binding energy – 8.3 kcal/mol with
quercetin . Amino acid residues on positions Glu-277, Cys- 278, Asn-282, Gly-283 and Glu-
284 showed hydrogen bonding with quercetin. These amino acids directly contribute in the
catalytic activity of the enzyme. Calculated binding energy for naringenin was found to be
86
-7.6 kcal/mol. From these results it was inferred that Viola F3’5’H has greater ability to
utilize quercetin as substrate rather than naringenin (Figure 4.16).
Binding energies in case of GhF3’5’H were evaluated as -7.9 kcal/mol with
naringenin and -7.4 kcal/mol with quercetin. Positions such as Ala-305, Asp-308, Thr-
309and Leu-372 were involved in making bond with naringenin (Table 4.3). Single amino
acid which interacted with quercetin was Asp-210. Docking experiments of GhF3’5’H
predicted its greater affinity towards naringenin to adopt as substrate. Over all docking data
based on binding energy calculation revealed that F3’5’H gene from Viola species had more
likelihood to reduce substrate than GhF3’5’H. Moreover, Viola F3’5’H would consume
quercetin more efficiently thus showing more probability to generate blue colour. So, by
expressing Viola F3’5’H there is a greater chance to bring phenotypic modifications in fiber.
Table 4-3: Binding energies of compounds interaction computed by Auto Dock/Vina
Proteins
Ligands
Binding
energy
(KJ/mol)
No. of
Hydrogen
bonds
Bonded
Amino
acids
Gossypium
hirsutum
Quercetin
Naringenin
-7.4
-7.9
1
3
ASP-210
ALA-305, Asp-308,
Thr-309, Leu-372
Viola
wittrockiana
Naringenin
Quercetin
-7.6
-8.3
0
5
--
Glu-277, Cys278,
Asn- 282, Gly-283,
Glu-284
87
Figure 4-16: Docking analysis of Viola wittrockiana and Gossypium hirsutum with
Naringenin & Quercetin.
Viola F3’5’H docked with (a) Naringenin & (b) Quercetin. Gossypium F3’5’H docked with
(c) Naringenin & (d) Quercetin
88
4.3 FLAVONOID GENES DESIGN AND CONSTRUCTION
DFR and F3’5’H were not cotton based thus derived from Iris hollandica and
Viola wittrockiana respectively. So, to acquire efficient expression, the nucleotides
compositions were altered by using codon optimization application of GenScript. The GC
contents of DFR & F3’5’H were adjusted to 42.83% and 43.34 % respectively. As a result,
codon adaptation index (CAI) was upgraded from 0.79 to 0.88 in case of DFR and 0.77 to
0.89 in F3’5’H (Figure 4.17 & 4.18).
4.4 IN-SILICO CLONING OF FLAVONOID CONSTRUCT IN BINARY
PLASMID
In-silico cloning of optimized F3’5’H and DFR genes in pCAMBIA 1301 was
carried out by using cloning feature of molecular cloning tool “snapgene” and selecting
KpnI with XbaI as restriction enzymes. This ensures successful cloning of flavonoid
construct at site multiple cloning sites (Figure 4.19).
Figure 4-17: Graphs of Codon Adaptation index (CAI) of F3’5’H gene.
a) Distribution of codon usage frequency along the length of the F3’5’H gene sequence after
optimization (CAI: 0.89) b) Distribution of codon usage frequency along the length of the
F3’5’H gene sequence before optimization (CAI: 0.77). The CAI value of 1.0 is considered
perfect while CAI > 0.8 value is regarded as good, to obtain high level of gene expression in
desired organism.
89
Figure 4-18: Graphs of Codon Adaptation index (CAI) of DFR gene.
a) Distribution of codon usage frequency along the length of the DFR gene sequence after
optimization (CAI: 0.88) b) Distribution of codon usage frequency along the length of the
DFR gene sequence before optimization (CAI:0.79).
Figure 4-19: Schematic representation of binary vector constructed for cotton fiber
modification.
90
4.5 CONFIRMATION OF SYNTHESIZED EXPRESSION CASSETTE
IN pUC57
4.5.1 BY PCR
Plasmids isolated from transformed E. coli colonies were subjected to PCR to
confirm the presence of flavonoid genes, provided in cloning vector pUC57, with the help of
gene specific primers. Amplified products of 476 bp and 537 bp confirmed the presence of
F3’5’H along with DFR in the provided synthetic construct cassette (Figure 4.20).
Figure 4-20: Confirmation of Flavonoid genes (DFR & F3’5’H) in pUC57 through
PCR.
a) Amplification of DFR gene from pUC57 b) Amplification of F3’5’H gene from pUC57
Lane 1:1 kb DNA ladder Lane 1-4: Transformed colonies
Lane 2-3: Non-transformed colonies Lane 5: Non-transformed colony
Lane 4-7: Transformed colonies Lane 6: 1kb DNA ladder.
91
4.5.2 BY RESTRICTION DIGESTION
Cloning vector pUC57 harboring desired genes cassette was further proceeded
through restriction digestion by using restriction enzymes KpnI & XbaI in order to confirm
and excised the required gene fragments. The digested samples resolved on 1 % agarose gel
showed two bands, one of 4032 bp (flavonoid cassette) and other of 2710 bp (pUC57) as
illustrated in figure (4. 21) .
Figure 4-21: Confirmation of DFR & F3’5’H construct in pUC57 by Restriction
digestion.
Lane 1:1 kb DNA ladder
Lane 2-6: Transformed colonies.
4.6 CLONING OF F3’5’H & DFR GENES IN PLANT EXPRESSION
VECTOR
Restriction digestion analysis of pCAMBIA1301 was also performed. The flavonoid
genes cassette ligated with pCAMBIA1301 was confirmed through restriction digestion by
using KpnI & XbaI enzymes. Plasmid isolated from E. coli colonies was digested to confirm
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the successful ligation through banding pattern. Appearance of two bands, flavonoid
construct of 4032 bp and 11000 bp of pCAMBIA 1301 confirmed successful ligation of
flavonoid genes in plant expression vector pCAMBIA 1301 (Figure 4.22).
Figure 4-22: Cloning and confirmation of Flavonoid construct in plant expression
vector.
a) Digestion of pCAMBIA and pUC 57- flavonoid construct
Lane 1: Control (undigested pCAMBIA)
Lane 2-5: Digestion of pCAMBIA with KpnI and XbaI
Lane 6: Control (undigested pUC57- flavonoid construct)
Lane 7: Digested pUC57- flavonoid construct with KpnI and XbaI
Lane 8: 1kb DNA ladder
b) Restriction analysis of pCAMBIA to verify Flavonoid construct ligation
Lane 1: Control (undigested pCAMBIA)
Lane 2: 1kb DNA ladder
Lane 3, 6 & 8: Non-ligated colonies
Lane 4, 5, 7 & 9: Ligated colonies
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4.7 CONFIRMATION OF CONSTRUCT IN AGROBACTERIUM
Recombinant plasmid (pCAMBIA+F3’5’H & DFR) was transformed to
Agrobacterium by electroporation. After 48 hours of incubation, creamy white
Agrobacterium colonies appeared on YEP medium selection plates. Transformed
Agrobacterium colonies were confirmed through colony PCR by using gene specific
primers further the bands of 476 bp and 537 bp confirmed the successful transformation of
plasmid in Agrobacterium (Figure 4.23 & 4.24).
Figure 4-23: Agrobacterium colonies harboring plasmid (pCAMBIA-Flavonoid
construct) on kanamycin and rifampicin selection plates.
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Figure 4-24: Confirmation of DFR and F3’5’H genes in Agrobacterium colonies.
a) Lane 1: 1 kb DNA ladder b) Lane 1: 1 kb DNA ladder
Lane 2: Negative control Lane 2 & 3: Positive clones
Lane 3: Positive control (pCAMBIA- Lane 3: Positive control (pCAMBIA-
flavonoid construct) flavonoid construct)
Lane 4, 5, 7 & 8: Negative colonies Lane 8: Negative control (without template)
Lane 6 & 9: Positive colonies
4.8 GENERATION OF PUTATIVE TRANSGENIC COTTON PLANTS
Agrobacterium mediated transformation was performed to transform flavonoid
construct in local cotton variety VH-319 by adopting shoot apex cut method. About 2 kg
seeds in total were used in all experiments. Germination Index of cotton variety, VH-319
based on total seed germination was found to be 74.7% (Table 4.4). In total ten
Agrobacterium mediated transformation experiments were performed. Whereas
transformation efficiency calculated from experimental data recorded on regular basis was
found to be 2.1% (Table 4.5). The systematic steps involved in generating transgenic cotton
plants from Agrobacterium infected embryos are shown (Figure 4.25). Next, the stable
putative transgenic plants grown in control field were subjected to molecular analysis.
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Figure 4-25: Agrobacterium mediated transformation methodology to generate cotton
transgenic plants.
a) Germinated seeds b) Agrobacterium treated embryos on MS medium c) Infected
embryos after 2 days d) Treated embryos after 3 days e) Seedlings in MS medium f) Shoot
& root development on MS medium g) Acclimatized putative transgenic plant h) Putative
transgenic plant shifted to field.
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Table 4-4: Germination index of local Cotton Variety, VH-319
Total no. of seeds Germinated seeds Ungerminated seeds Germination
Index (%)
3027 2261 766 74.7
Table 4-5: Experimental data for Flavonoid construct (F3’5’H & DFR)
Transformation in VH-319
No of Exp.
No. of
Isolated
embryos
Survived
embryos
in MS
plate
Survived
embryos
in Pyre
Tube
Plants in pots Plants in field
1 250 17 12 5 0
2 370 24 20 3 1
3 180 15 8 0 0
4 465 103 65 15 3
5 319 23 30 6 1
6 120 55 2 2 0
7 78 147 30 13 1
8 235 23 15 5 1
9 130 45 37 16 1
10 90 90 43 20 4
Total 2237 542 262 85 12
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4. 9 MOLECULAR ANALYSIS OF TRANSGENIC COTTON PLANTS
Putative transgenic cotton plants were analyzed to confirm successful integration,
expression and determination of copy number of flavonoid genes i.e. DRF &F3’5’H through
different molecular techniques like PCR; Dot Blot analysis; Real Time PCR; Fluorescence
In Situ Hybridization (FISH) and Anthocyanin estimation.
4.9.1 SCREENING OF PUTATIVE TRANSGENIC COTTON PLANTS THROUGH
PCR IN T0 GENERATION
Flavonoid genes integration in cotton genome was confirmed in T0 and T1 generation
by using gene specific primers. PCR analysis was performed at optimized conditions by
using 100-200ng genomic DNA from each plant. Amplified fragments of 476 bp (F3’5’H)
and 537 bp (DFR) confirmed successful incorporation of desired genes in cotton genome.
Out of 85 putative transgenic cotton plants in green house, only twelve were survived in
field conditions. In T0 generation nine cotton plants namely, P1, P2, P3, P4, P6, P7, P10,
P12 and P13 were found to be confirmed transgenic as they showed amplifications at their
respective sizes (476 bp ~F3’5’H and 537 bp ~DFR) however, three plants namely, P5, P8
and P9 were failed to be amplified for F3’5’H and DFR (Figure 4.26). A sharp band was
also observed in positive control (pCAMBIA 1301 + Flavonoid construct) while no
amplification was obtained in negative control (non transformants).
98
Figure 4-26: Confirmation of F3’5’H and DFR genes in putative transgenic plants of
T0 generation.
a) F3’5’H gene confirmation in transgenic plants
Lane 1: 1kb DNA ladder
Lane 2: Negative control (non transgenic plant)
Lane 3-7: P1, P2, P3, P4 & P6
Lane 9: Positive control (pCAMBIA-flavonoid construct)
Lane 10-13: P7, P10, P12 & P13
b) DFR gene confirmation in transgenic plants
Lane 1: 1kb DNA ladder
Lane 2: Negative control (non transgenic plant)
Lane 3-7: P1, P2, P3, P4 & P6
Lane 11-14: P7, P10, P12 & P13
Lane 15: Positive control (pCAMBIA-flavonoid construct)
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4.9.2 CONFIRMATION OF TRANSGENE INTEGRATION BY DOT BLOT IN T0
GENERATION
The stable integration of flavonoid genes (F3’5’H & DFR) in transgenic cotton
plants was further evaluated in T0 progeny by dot blot analysis. For this purpose, signal was
recorded in spotted DNA of PCR positive cotton plants on nylon membrane. Signal
detection occurred in five PCR positive plants out of total nine. Very clear signal was
observed on membrane in the following cotton plants namely: P2, P4, P6, P10 and P13
however, the signal intensity varied significantly among these transgenic cotton plants. No
signal was found in plants P1, P7, P12 and in non transgenic cotton control plant.
Experimental positive control and manufacturer provided kit control DNA showed strong
signals (Figure 4.27).
Figure 4-27: Dot blot analysis to determine F3’5’H and DFR genes integration.
Sample 1: Positive control (pCAMBIA1301-Flavonoid construct)
Sample 2: Negative control (non transgenic plant)
Sample 3: P2 Sample 4: P3 Sample 5: P4 Sample 6: P6
Sample 7: P10 Sample 8: P7 Sample 9: P12 Sample 10: P1
Sample 11: P13 Sample 12: Positive kit control
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4.9.3 CONFIRMATION OF F3’5’H AND DFR GENES BY PCR IN T1 GENERATION
The T0 transgenic cotton plants which were confirmed by both PCR and Dot blot
assay were selected for generation advancement studies. The T1 progeny was evaluated by
molecular techniques like PCR, Dot blot analysis, Real time PCR along with anthocyanin
assay, Fiber quality analysis, Electron microscopic analysis of fiber surfaces and
determination of agronomic characters.
Random plants were selected from field and subjected to genomic DNA isolation
according to standardize protocol. Fragments of 476 bp for F3’5’H and 537 bp for DFR
genes were amplified from P10 (7), P4 (2), P6 (6), P2 (7) and P13 (9) transgenic cotton
plants of T1 generation (Figure 4.28 a & b).
4.9.4 INTEGRATION OF F3’5’H & DFR GENES BY DOT BLOT IN T1
GENERATION
The DNA of PCR positive cotton plants of T1 progeny were collected and spotted on
membrane to confirm transgene integration through dot blot assay. On blot membrane
significant signals have been detected in transgenic plants namely as P10 (7), P4 (2) and P6
(6) (Figure 4.29). Similarly, the seeds of plants validated by dot blot in T1 generation were
harvested and further cultivated to get T2 generation. Next in T2 generation FISH analysis
were conducted to evaluate gene copy number and its karotyping.
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Figure 4-28: Confirmation of F3’5’H and DFR genes in transgenic plants of T1
generation
a) DFR gene confirmation in transgenic plants
Lane 1: 1kb DNA ladder
Lane 2: Negative control (non transgenic plant)
Lane 3: Positive control (pCAMBIA-flavonoid construct)
Lane 5: P2 (7)
Lane 7, 9, 10 & 11: P10 (7), P4 (2), P6 (6) & P13 (9)
b) F3’5’H gene confirmation in transgenic plants
Lane 1: 1kb DNA ladder
Lane 2: Negative control (non transgenic plant)
Lane 3 & 4: P2 (7) & P4 (2)
Lane 6, 8 & 9: P7, P10, P12 & P13
Lane 11: Positive control (pCAMBIA-flavonoid construct)
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Figure 4-29: Detection of F3’5’H and DFR genes in T1 generation by Dot blot assay
Sample 1: Positive control (pCAMBIA1301-Flavonoid construct)
Sample 2: P4 (2) Sample 3: P 2(7) Sample 4: P6 (6)
Sample 5: P13 (9) Sample 6: Negative control (non-transgenic plant)
Sample 7: P10 (7) .
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4.9.5 TRANSCRIPTIONAL ANALYSIS OF F3’5’H AND DFR GENES
Quantitative real time PCR was used to check the expression levels of both genes
F3’5’H and DFR in transgenic cotton lines. To normalize the expression level of genes,
GAPDH gene was used as reference gene. In T1 generation, all transgenic cotton lines
expressed different levels of mRNA expression in both F3’5’H and DFR genes in leaf
samples. Transgenic cotton lines such as P4 (4 fold), P6 (5.3 fold), and P10 (4.5 fold)
showed higher levels of F3’5’H gene expression as compared to other transgenic cotton
lines P2 (2 fold) and P13 (1.5 fold). The figure also determined highest expression of
F3’5’H gene in transgenic line P6 which was recorded to be 4.3 folds, P4 ~ 3 folds, P10 ~
3.5 folds greater as compared to control. Whereas, in case of DFR transgenic cotton line P10
showed higher expression i.e 4 folds while other lines such as P2, P4, P6 and P13 showed
relatively lower expression like 1.8 folds, 3.2 folds, 2.8 fold and 1.5 folds respectively.
Maximum expression, 3 folds was observed in transgenic cotton line P10 as compared to
non transgenic control cotton line (Figure 4.30).
The quantification of mRNA expression in ovules having fibers from five transgenic
cotton lines transformed with the flavonoid genes had been shown (Figure 4. 31). Plant
lines P6 and P10 produced the 3.0 and 2.7 folds expression of DFR gene in T1 generation.
Plant line P4 showed moderate expression of 2.3 folds while plant line P2 and P13 were
found to have least expression i.e 1.7 and 1.5 folds respectively. Likewise almost similar
expression pattern for F3’5’H gene was observed in transgenic cotton lines as demonstrated
in case of DFR. Here, the lowest expression level was found in transgenic cotton line, P2.
Small bars showed the variation among respective replicates.
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Figure 4-30: qRT-PCR based study to quantify the expression of flavonoid genes in T1
transgenic cotton lines
A) F3’5’H gene expression in leaf samples of transgenic lines and control.
B) DFR gene expression in leaf samples of transgenic lines and control.
105
Figure 4-31: qRT-PCR based study to quantify the expression of flavonoid genes in T1
transgenic cotton lines
A) F3’5’H gene expression in fiber samples of transgenic lines and control.
B) DFR gene expression in fiber samples of transgenic lines and control.
106
4.10 ESTIMATION OF ANTHOCYANIN PIGMENTS
Results for estimation of total anthocyanin contents by pH differential method were
done in T1 transgenic cotton lines. Total anthocyanin contents value was quantified in
triplicates from each transgenic cotton line in T1 generation. Experimental data was
recorded in terms of absorbance at 530 nm as anthocyanin pigments had a property to alter
the colour with pH. Highest anthocyanin contents have been obtained in transgenic cotton
lines lay in the following order: P4 (1.79µg/g), P10 (1.7µg/g), P6 (1.61µg/g), P13
(1.19µg/g), P2 (1.0 µg/g). The lowest values were obtained in non transgenic cotton line
(0.41 µg/g) used as experimental control (Table 4.6, Figure 4.32 & 4.33)
Table 4-6: Anthocyanin Quantification of Transgenic Cotton plant samples of T1
generation
Serial Number
Plant lines
Anthocyanin Quantity
TAC = (A1 – A2)×f
(µg/g)
1 P2 1.0
2 P4 1.79
3 P6 1.61
4 P10 1.7
5 P13 1.19
6 Control 0.41
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Figure 4-32: Anthocyanin extracts from leaves quantified at pH 0.8 and pH 3.5
Leaves extract in tubes clearly demonstrated presence of pigments at pH 0.8 (left side) and
no existence at pH 3.5 (right side) of each transgenic plant line.
Lane 1:P4 Lane 2: P10
Lane 3:P6 Lane 4: Control (non- transgenic plant)
Figure 4-33: Anthocyanin accumulation in young leaves of transgenic cotton lines
determined spectrophotometrically at 530 nm.
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4. 11 PHENOTYPIC MODIFICATIONS IN TRANSGENIC COTTON
LINES
Transgenic cotton plants were thoroughly examined in each generation for
production of coloured pigments in fiber or any other vegetative parts such as cotyledons
and hypocotyls likewise, in reproductive parts i-e stigma and style of transgenic cotton
plantlets. Besides the anthocyanin accumulation there was no colour alteration detected by
naked human eye, even when the transgenic cotton plantlets were shifted into soil. However,
transgenic cotton plants were found to be healthier and had appeared to be with lush green
leaves. Even in hot summer season (temperature above 500C) cotton transgenic plants
survived very well and showed no negative impact of flavonoid genes on yield and fiber
characteristics.
4.12 FIBER QUALITY PARAMETERS
Cotton fiber quality is one of the ultimate outcomes and most desired trait of the
cotton crop. Fiber length, fiber strength, micronaire and uniformity index were the lint
characters under study. Results of fiber analysis conducted by CCRI Multan are summarized
in Table 4.7 and 4.8 (Figure 4.34).
Quality analysis showed that in T0 generation fiber length was found to be increased
up to 12.8% while in T1 progeny 20.1%. Similarly, fiber strength was measured to be
increased up to 35.1% in T0 while 32.7% in T1 generation respectively (Figure 4.35 & 4.36,
A & B) as compared to non transgenic control cotton fiber. Similarly, a significant increase
in uniformity index was also obtained. Increase in uniformity index was recorded as 4.7% in
T0 and 5.2% in T1 progeny as compared to non transgenic control cotton fiber (Figure 4.35
& 4.36, C). Moreover, decrease in micronaire value was also observed up to 24.7% in T0
109
and 15.7 % in T1 generation transgenic cotton plants (Figure 4.35 & 4.36, D).Smaller the
micronaire values more finely would be the thread.
Table 4-7: CCRI Fiber Analysis of Transgenic Cotton lines of T1 Progeny. Each
value is average of triplicates
Plant Lines
Fiber Length
(mm)
Uniformity
Index
Micronaire value
(µg)
Fiber strength
(g/tex )
Control 26.3 82 4 23.8
P10(7) 31.6 86.3 3.8 27.8
P4(2) 29.8 85.4 3.5 31.6
P6(6) 29.5 85.6 3.2 32.4
P13(9) 28.8 84.6 3.3 30.8
Table 4-8: Fiber Analysis of Transgenic Cotton plants with Flavonoid genes of T0
Progeny
Plant Lines
Fiber Length
(mm)
Uniformity
Index
Micronaire value
(µg)
Fiber strength
(g/tex )
Control 27.3 82.9 3.8 28.2
P4 29.9 86.8 3.2 34.6
P10 29.7 84.6 3.2 28.5
P13 29.7 85.5 3.2 33.7
P6 30.8 86.6 3.12 38.1
P1 29.0 84.7 3.1 31
P2 29.2 82.4 2.56 29.2
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Figure 4-34: Fiber length in transgenic cotton lines and non transgenic control cotton
line.
Lane 1: P10 Lane 2: P4
Lane 3: Control Lane 4: P6
111
112
Figure 4-35: Comparison of different fiber characteristics of different cotton
transgenic cotton plants with non transgenic control cotton plant in T0 progeny
A) Fiber length B) Fiber strength C) Uniformity Index D) Micronaire value.
113
114
Figure 4-36: Fiber parameters in non transgenic cotton control lines and transgenic
cotton lines (P10, P4, P6 and P13) in T1 generation
A) Fiber length B) Fiber strength C) Uniformity Index D) Micronaire value. All values in
graphs are average of the three independent majorettes.
115
4.13 ELECTRON MICROSCOPIC FIBER EXAMINATION
Analysis through scanning electron microscope revealed that the mature cotton fiber
surface of transgenic cotton lines (P4, P10 and P6) was smoother and compact as compared
to non transgenic control line (Figure 4.37). These results showed that the over-expression
of flavonoid genes, F3’5’H & DFR can change the structural texture of cotton fiber cell
walls in transgenic cotton lines. Transgenic cotton fibers showed more number of twists as
compared to non transgenic control leading to the improved strength of fiber in transgenic
cotton plant lines.
Figure 4-37: Scanning electron microscopic images of mature transgenic fiber surfaces
and non transgenic control at different magnifications. a) 400X b) 1000X c) 4000X
116
4.14 MORPHOLOGICAL & PHYSIOLOGICAL CHARACTERS
ANALYSIS
Genetic variability is strongly related to phenotypic variations. Especially valuable
change in economically important characters (Fiber length, strength and fineness etc) forms
the basis for selection in genetic and breeding work. Agronomic traits, including plant
height, number of sympodial branches, number of monopodial branches, number of bolls,
number of damage boll, weight of lint and physiological characters such as leaf area,
evaporation rate, photosynthetic rate and gaseous exchange of transgenic cotton lines were
compared with non transgenic control lines. Moreover, co-relation was evaluated among
these characters in T1 progeny.
Non transgenic cotton line has a mean plant height of 49cm while transgenic cotton
lines P2 , 52 cm; P4 line, 48 cm; P6 line, 50cm; P10 line and P13 line, 52 respectively
(Table 4.9). Plant height had no significant influence on characters under study. Monopodial
branches in non transgenic control cotton lines were counted to be 6 while in transgenic
cotton lines the maximum branches were found to be 7 in P4 line. These branches showed
significant inverse relation with number of damage boll branches and significantly positive
correlation with number of sympodial branches. Data on other factors such as lint weight,
leaf area, evaporation and photosynthetic rate determined that there exists no relation among
these traits and monopodial branches. The non transgenic cotton control plants and
transgenic cotton lines namely P2, P4, P6, P10 and P13 were found to have mean value of
sympodial branches numbered as 12, 12, 10, 17, 28 and 17 per plant. Sympodial branches
showed positive association with number of damage bolls and negative association with
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monopodial branches. Number of bolls per plant is a positive indicator of cotton seed lint
yield.
The maximum number of bolls per plant were found in transgenic line P6 i.e P6 (7)
having 37 bolls, while minimum in line P2 i.e P2 (7) having 21 bolls and non transgenic
control cotton line was found to have 33 bolls. It was observed that numbers of bolls per
plant were negatively and significantly correlated with monopodial branches. While plant
height, sympodial branches, damage bolls, leaf area, evaporation rate, photosynthetic rate
and gaseous exchange showed no positive or negative association with number of bolls.
Bolls number and lint weight were two key traits that determine the final cotton
yield. The transgenic cotton line, P10 was found to have maximum boll weight (37.1 g) and
least weight of bolls (23 g) was observed in P2 while boll weight in non transgenic control
cotton plant was measured to be 23.1 g. Data analysis showed that boll and lint weight are
strongly co-related. This strong relationship between boll weight and lint weight is an
important indication of yield as well as improved fiber quality. Other physiological factors
were also studied. Maximum leaf area, evaporation rate, photosynthetic rate and gaseous
exchange was recorded as 221.31 cm2, 6.55 mmol/m
2/s,6.5 µmol/m
2/s and 154 mmol/m
2/s
respectively as compared to non transgenic cotton plants which possess leaf area ~122.2
cm2, evaporation rate ~ 1.6 mmol/m
2/s, photosynthetic rate ~ 3.23 µmol/m
2/s and gaseous
exchange ~ 54 mmol/m2/s. Data analysis showed high and significant correlation among leaf
area, evaporation rate, and photosynthetic rate while moderate and significant correlation
with gaseous exchange. These characters in combination determine the physiology of the
transgenic cotton plant as they directly affect process of photosynthesis (Table 4.9).
118
Table 4-9: Co-relation matrix among Morphological and Physiological characteristics among transgenic cotton
lines & non transgenic control cotton lines
Plant height (PH, cm), number of monopodial branches (MB), number of sympodial branches (SB), number of bolls per
plant (NB), number of damaged boll (DB), Boll weight (BW,g), lint weight (LW,g), leaf area (LA),evaporation rate (ER),
photosynthetic rate (PR), gaseous exchange (GE).
PH MB SB NB DB BW LW LA ER PR GE
PH 1
MB -0.330 1
SB 0.097 0.95** 1
NB 0.715 -.860* 0.681 1
DB 0.197 -.98** 0.97** 0.801 1
BW 0.363 -0.221 0.248 0.280 0.234 1
LW 0.378 -0.193 0.214 0.271 0.205 0.999** 1
LA 0.852* 0.072 0.197 -0.494 0.54 -0.370 -0.391 1
ER -0.745 0.246 0.012 -0.570 -0.137 -0.416 -0.427 0.95** 1
PR 0.913* 0.155 0.110 -0.554 -0.009 0.337 0.354 0.982**
0.920** 1
GE 0.893* 0.531 -0.297 -0.806 -0.409 -0.473 -0.476 0.875* 0.908* 0.911* 1
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4.15 FLUORESCENCE IN SITU HYBRIDIZATION ANALYSIS
Transgenic cotton plant line, P4 (2-1) of T2 generation which previously showed
improved fiber traits was selected for determination of transgene copy number. The
chromosome location and copy number of the F3’5’H and DFR genes was determined
through Karyotyping by using gene specific probe. A single copy of the flavonoid transgene
was found to be located on chromosome number 16 in transgenic cotton plant (Figure 4.38 a
& b). However, no signal was observed in non transgenic control cotton plant (Figure 4.38
c).
120
Figure 4-38: Fluorescence in situ hybridization (FISH) of the Flavonoid construct in T2
generation plants.
a) Metastatic data for T2 transgenic cotton plants. The arrow points the actual location of
transgene integration, as visualized by fluorescent microscopy due to hybridization with a
sequence-specific probe. b) Karyotyping of a transgenic cotton plant P4 (2-1) of T2
generation. The arrow shows signal on chromosome 16, verifying transgene location. c) Non
transgenic control plant without signal. The data was reordered successively, using the
software of Karyotyping, Cytovision Genus version.
121
CHAPTER 5 : DISCUSSION
Cotton is an essential non-staple crop and the main source of foreign exchange in the
Pakistan. Economic importance of cotton solely depends on fiber characteristics i.e fiber
length, tenacity, strength and colour. Up to now, fiber quality has not met the increased
market demand for a high quality fiber. The quality of textile products largely depends on
fiber properties. Therefore, researchers are striving to explore effective breeding and genetic
approaches to acquire high quality fiber for effective commercialization. Molecular methods
are considered superior to conventional breeding programs in order to induce desired
characters to improve fiber quality and yield (Arpat et al., 2004; Wilkins and Arpat, 2005).
To maximize and improve cotton yield, the research has now integrated in exploring
the role of flavonoids in improving fiber properties including colour development (Liu et al.,
2018). Transcriptome analysis has revealed the involvement of different signal pathways
associated in fiber developmental stages (Walford et al., 2011). Advance metabolome and
phylogenetic studies have determined that flavonoid biosynthesis pathway genes actively
play their role in pigment formation in cotton fiber but still, the information on effect of
individual gene on fiber characteristics is missing (Liu et al., 2018). Regulating anthocyanins
in various ways including altered metabolic pathway, cofactor engineering, vacuolar pH
modification, site-directed mutations and transcriptional factor engineering showed the
potential to modify fiber characters (Tanaka et al., 2009).
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In present work, over-expression of DFR (Iris hollandica) & F3’5’H (Viola
wittrockiana) was led to investigate changes in pigmentation pattern, agronomic traits,
anthocyanin contents and fiber quality in a local cotton variety VH-319. In-silico study was
conducted to investigate the impact of transgene expression on reduction of their respective
substrates. The substrate specificity of DFR has been widely studied in a numberof plants
(Hua et al., 2013) Dihydroflavonol-4-reductases from seven different species (Ang. DFRII,
Rosachinensis, Vaccinium macrocarpon, Gerbera hybrid, Petunia hybrida, Ampelopsis
grossedentata and Iris hollandica) displayed deletion of the proline rich region and had
glycine mostly in close proximity or at position 12 in comparison of position 26 of Ang.
DFRI. Therefore, most of these DFRs could be able to reduce DHQ or DHM but not DHK.
Results obtained are in accordance with previous studies done by Johnson et al. (2001) who
reported inability of petunia DFR to reduce DHK but the transformation of maize DFR in
petunia, generated orange coloured flowers showing significant DHK reduction (Meyer et al.,
1987).
Besides of 99% homology between Ang. DFRI and DFRII sequences, yet the position
12 and 26 in them was reported to be crucial in defining substrate specificity. These findings
were similar to Gosch and his co-workers who documented proline rich region near N-
terminus and same residue at position 12 while glycine at position 26 (in all DFRs except
Ang. DFRI) and further emphasized on alteration of Ang I/IIDFR functional activity by
interfering with this region (Gosch et al., 2014). However, the region was a proline rich motif
that acts as a NADPH binding site (Petit et al., 2007). On account of proline at position 12 in
Gossypium hirsutum DFR showed ability to reduce dihydrokaempferol. Recent results
indicate that reduction of dihydrofavonols by DFR can be a significant enzymatic step for
123
flower colour determination by DHK hydroxylation mediated by F3′H or F3′5′H.Those DFRs
which have the ability to consume DHQ along with DHM as substrates could produce red or
blue flowers. Absence of proline rich region in DFRs would reduce DHQ and DHM as
substrate. Results were in harmony with Gosch et al. (2014) who reported blue colour
generation by the replacement of arginine residue by glycine in Ang. DFRI and mutation of
proline at position 12. Authors further explained variability among amino acid sequences in
particular region or variation in substrate specificity by a single mutation in a particular area
in DFRs from different plant species or even in different cultivars of same species could have
different substrate preferences. In another report, aspartic acid at position 134 in petunia
showed its ability to utilize DHM thus produced blue coloured flowers (Johnson et al.,
2001).These contradictions in results may be due to difference in species and amino acid
residues.
Earlier studies have highlighted that alteration in amino acid residues at specific site,
changes the substrate preferences (Gosch et al., 2014). Transformation of Iris DFR in rose
converted DHM substrate to delphinidin and generated blue hued flowers whereas in
Gossypium hirsutum, DFR reduced DHK substrate and produced brown coloured lint
(Katsumoto et al., 2007). It is anticipated that transformation of Iris hollandica DFR in
Gossypium hirsutum could produce blue pigmentation in cotton fiber. Likewise, in Viola
derived F3’5’H docking analysis, the calculated inter-molecular energy with two substrates
(Naringenin and Quercetin) was -7.6: -8.3 Kcal/mol and -7.9: -7.4 Kcal/mol in the docked
poses created by AutoDockVina. Previously, Ahmad et al. (2015) used similar molecular
docking approach to introduce broad-spectrum Vip3Aa-Cry1Ac fusion protein to effectively
control cotton pests particularly lepidopterons.
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For proper functioning of P450 enzymes to generate naturally coloured phenolic
pigments coupling with those genes which can act as electron donors were required such as
DFR. Utilization of substrate varies species to species in flavonoid pathway genes.
Particularly, DFR genes are highly variable in substrate selection. Some DFRs reduce DHQ
in one plant species and DHM in others as substrates to generate red or blue colours.
Hence, the determination of suitable gene in a particular crop was important as over-
expression could efficiently consume substrate and induce desirable traits in transgenic crops.
In previous study, same concept of expressing suitable DFR gene regarding substrate
preference and consumption has been presented in cotton crop (Ahad et al., 2015). Currently
In-silico study showed that in comparison of F3’5’H gene from two different sources clearly
showed that Viola F3’5’H gene was found superior to Gossypium F3’5’H in effective
substrate consumption. Thus, there exit a brighter prospect to altering the pigmentation
pattern in cotton. This hypothetical study was in correspondence with Noda et al. (2013) who
engineered Chrysanthemum with Campanula F3’5’H to generate different colour flowers. In
another work roses colour was opted to be changed from red to blue by using Viola F3’5’H
gene and Iris DFR as well as by down regulating endogenous DFR to avoid substrate
competition between exogenous and endogenous DFRs (Katsumoto et al., 2007). In-silico
analysis supported the idea that over expression of Viola F3’5’H gene and Iris DFR has the
potential to alter pigmentation pattern and imparting the colour along with improvement of
cotton fiber quality.
The flavonoid cassette (4032bp) was cloned in plant expression vector,
pCAMBIA1301 at the multiple cloning site using KpnI and XbaI restriction sites under the
control of 35S promoter. The cloned construct was transformed in Agrobacterium
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tumefaciens strain LBA4404. The transgenic plants of local cotton cultivar VH-319,
Gossypium hirsutum having successfully integrated flavonoid cassette were generated by
Agrobacterium mediated transformation method with the efficiency of 2.1% similarly as was
done by Bajwa et al., (2015) while introducing GhEXPA8 to improve fiber trait in cotton and
obtained efficiency of 0.07%. While 0.27% transformation efficiency was reported by
McCabe et al. (1998) for cotton transformation through particle bombardment shoot tips
method and nearly 6.5% in shoot apex cut method of cotton by Majeed et al. (2000). The
difference in efficiency of cotton transformation is attributed to efficiency method used,
cotton variety and health of seed to be used.
Further the introduced flavonoid transgenes in cotton were confirmed through
visualization of hybridized spots on nitrocellulose membrane in Dot blot analysis. Seo et al.
(2006) detected DNA-A and DNA-B components of Gemini virus in cotton leaves having
CLCr symptoms by PCR and visual rating through dot blot hybridization. Moreover,
southern analysis also confirmed the single-copy T-DNA integration of Viola F3’5’H, along
Iris DFR in transgenic rose plants (Katsumoto et al., 2007). Another study revealed the
successful insertion of transcription regulator gene, Lc by southern blotting with a DIG-
labeled Lc probe which regulated the structural genes of anthocyanin pathway in T1 cotton
progeny (Fan et al., 2015). The gene expression was also studied through reverse
transcription-polymerase chain reaction (RT-PCR). The F3’5’H and DFR mRNA expression
was evaluated in leaves and 20 DPA (Days post-anthesis) ovules. In this case, more
expression was observed in transgenic cotton lines P4, P6 and P10 in case of ovules as well
as in leaves. Likewise minimum gene expression was found in transgenic cotton line, P2 in
both ovules and leaves. Expression of Lc gene was noticed in leaves, floral tissues and during
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all the fiber developmental stages in transgenic plants. Higher expression levels were
recorded in anthers in the 4 to 16 DPA ovules while the moderate expression was found in
stigma and 18 DPA ovules. However, petals showed no expression. Similar results were
obtained by Li et al. (2015) while taking the expression of GhUGP1 gene at different DPA
(15 & 20) in cotton ovules.
The basic principles and validity for the determination of anthocyanin pigment
concentration through the pH differential method has been widely accepted for years by
natural product chemists. Currently, anthocyanins were quantified spectrophotometrically by
using pH differential method. Two transgenic cotton lines P4 and P10 showed highest
anthocyanin development (1.7µg/g) as compared to control non transgenic cotton plant
(0.41µg/g). Results were strongly supported by Fan et al. (2015) while analyzing
anthocyanins in fresh and old leaves of transgenic cotton lines expressing Lc gene, was
estimated by applying same pH differential method. Similarly, in beverages, fruit juices,
natural colourants and wines the anthocyanin pigments were quantified at commercial scale
by this method (Lee et al., 2005). In another report, pigments in cotton leaves resulted after
prolong sunlight exposure were estimated in acidified methanol and concentrated HCl
spectrophotometrically at 530nm (Riar et al., 2013). Gallik (2012) had described the actual
mechanism of light absorbance of anthocyanins with changing pH. Flavonoid compounds
share a general skeleton made up of two aromatic rings (A & B) bound with each other by
three carbon atoms that compose an oxygenated hetero-cycle (ring C) (Welch et al., 2008).
The anthocyanin pigmentation is widely pH dependent due to the presence of positive charge
on C ring of the molecule (flavylium cation). In actual, this charge is pH dependent. At pH
1.0, C ring carries positive charge, the resultant molecule gets pigmented and absorbs light
127
between 460-550 nm, maximum at 530 nm. While at pH 4.5 or higher, the positive charge
become neutralize due to loss of this charge on C-ring therefore, anthocyanins lose
pigmentation, turn colourless and transmit visible light (Gallik, 2012).
Naturally coloured brown and green coloured cotton was driven through flavonoid
pathway and its structural genes could bring phenotypic alterations (Liu et al., 2018). So, the
effect of F3’5’H and DFR genes was investigated for the accumulation of anthocyanin
pigments in different vegetative and reproductive tissues of transgenic cotton plants.
Moreover, the bioinformatics docking experiments strongly supported the hypothesis that
over expressed exogenous flavonoids genes could efficiently reduce substrates than
endogenous genes present in cotton plant; hence capable to synthesize anthocyanins which
may bring phenotypic changes in fiber. In vitro results clearly showed that hypothesis was
correct in terms of anthocyanin production, transgenic cotton plants successfully produce
anthocyanins however, no change was detected in pigmentation pattern in either part of
cotton plant. Current results were in accordance with He et al. (2013), results obtained
through expression of the Senecio cruentus derived F3′5′H gene in chrysanthemum showed
significant increase of anthocyanin compounds in the transgenic chrysanthemum i.e cyanidin
but change in colour was not observed. However, Fan et al. (2015) reported that Lc gene
alone was sufficient to accumulate anthocyanins and showed red colour pigments when
expressed in floral tissues, fiber cells and leaves of the transgenic cotton plants.
Quantification of anthocyanins in Lc expressed transgenic cotton plants was reported to be
increased from 9.74 mg/100 g (Wt) to 12.80 mg/ 100 g (Lc) in the fresh leaf extract and from
15.41 mg/100 g (Wt) to 53.60 mg/100 g (Lc) in the dry leaf extract. In comparison
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anthocyanins value was measured to be increased from 0.41µg/g non transgenic control
cotton plants to 1.79µg/g transgenic cotton plants.
Therefore, from experimental data it is inferred that to bring phenotypic change greater
accumulation of anthocyanins is required which is directly link to high expression of pigment
related genes.
According to Katsumoto et al. (2007) the constitutive expression of the Viola based
F3’5’H and Iris DFR genes successfully accumulated delphinidin and resulted in blue
coloured roses. Colour alternation was due to suppression of endogenous DFR through gene
silencing and over expression of exogenous DFR to avoid internal substrate competition and
production of adequate quantity of delphinidin which brought blue colour modifications.
Further, Holton and Tanaka (1994) empathized that to produce a colour compound
(delphinidin) of desirable quantity, selection of appropriate host cultivars that possess least
substrate competition between external and internal gene is necessary as documented in blue
carnation.
Recently, Liu et al. (2018) reported that over expression of Arabidopsis thaliana
based 3GT and Gh3GT gene in brown cotton generated green coloured fiber. Here, colour
change in transgenic cotton fibers was driven by flavonoid pathway. So, another idea is to
express these flavonoid genes (F3’5’H & DFR) in naturally coloured cotton, in order to
produce blue coloured fibers, due to presence of well established flavonoid pathway in
coloured fibers with more compatible metabolon (enzyme complex) of anthocyanin pathway.
Modifications in fiber traits by the expression of flavonoid genes i-e F3’5’H and DFR
was key feature of current study because it has already been reported by Liu et al. (2018) that
129
flavonoids can impart positive impact on fiber of cotton. Notable improvement was seen in
fiber characteristics of transgenic cotton lines which showed increased anthocyanin contents
in T1 progeny. Significant improvement was observed in fiber length and strength which was
measured to be increased up to 20.1% and 35.1% respectively. The results are comparable
with previous studies of Bajwa et al. (2015) who transformed GhEXPA8 gene, responsible
for fiber elongation along expansion and found 20% enhancement in fiber length and 17%
rise in fiber strength. Similarly in another attempt for development of high quality fiber, by
the over expression of GhUGP1 in upland cotton revealed 14.9–15.8% increase in fiber
length and up to 7.7–14.1% increase in strength (Li et al., 2015). Current study showed
remarkable improvement in fiber strength whereas uniformity index (5.2%) and micronaire
value (24.7%) also improved in T1 generation. Similar findings were evident in studies of
Zhang et al. (2010), Qin and Zhu (2011) and Li et al. (2015). Nix et al. (2017) also reported
the role of flavonoids during fiber elongation stage, highlighting its influence in enhancing
the fiber characteristics. This is the first practical outcome of flavonoid genes in the form of
fiber improvement which has been discussed in the form of reviews by different authors. It is
evident from literature that increased in fiber length due to increased anthocyanin may be
attributed to its characteristics of osmoregulation or as they are also reported to be modulator
of PIN gene which is auxin carrier (Dhindsa et al., 1975; Chalker -Scott, 1999; Zhange et al.,
2017).
Moreover, the results of scanning electron microscope exposed that the surface of
mature fiber of flavonoid transgenic cotton lines was more smooth and compact as compared
to non transgenic control cotton fiber. These results further demonstrated the role of
flavonoid genes in altering the structural texture of cell walls of cotton fiber in transgenic
130
cotton lines. Results were supported by Li et al. (2015) who studied the fiber surface under
SEM of GhUGP1transgenic cotton lines and found smoother transgenic cotton fiber surfaces
due to increase cellulose deposition as compared to wild type.
Morphological traits like plant height were found as independent factor with respect
to monopodial and sympodial branches. This was contrary to previous studies which showed
positive influence on both type of branches (Naveed et al., 2004; Bajwa et al., 2015). This
may be due to difference of trait introduced and also varietal response. Current work showed
positive significant relation between monopodial and sympodial branches and the same
results were presented by Ahuja et al. (2006) and Chattha et al. (2010).
Two other key characters i-e boll and lint weight showed positive significant
correlation according to Pearson correlation. Results were supported by Chao-zhu et al.
(2007), who studied positive correlation among boll number, boll weight and lint percentage.
However Bajwa et al. (2015) described that plant height, number of monopodial branches,
bolls per plant and plant yield are significantly correlated. The correlation analysis based on
the positive association of these characters would be quite effective to improve the yield and
fiber quality in upland cotton. Likewise negative and significant relations found in study
would be fixed in advanced generations. A positive correlation of transgene was found with
physiology of transgenic cotton plants like maximum photosynthetic and evaporation rate as
well as gaseous exchange in transgenic cotton plant which was recorded to be 6.5 µmol/m2/s,
6.55 mmol/m2/s and 154 mmol/m
2/s respectively as compared to 3.2 µmol/m
2/s, 1.67
mmol/m2/s and 54 mmol/m
2/s in non transgenic cotton plants. Results are in accordance with
results of Chattha et al. (2010) who studied correlation in yield and quality contributing
131
characters with environmental factors i.e photosynthetic, evaporation rate and stomatal
conductance in upland cotton and reported positive association of traits with each other.
Transgenic cotton plants which showed higher expression of F3’5’H and DFR genes
were subjected to FISH for evaluation of copy number and chromosome location. Transgene
expression is greatly influenced by its copy number and location. One gene copy number was
found in transgenic cotton plant at chromosome number 16. Results were supported by
Puspito et al. (2015), they determined single copy number of Cry2A gene at chromosome
number 6 and GTG gene at chromosome number 3 in transgenic cotton plants. Similarly Rao
et al. (2013), showed PhyB gene with three gene copy number inserted at multiple sites in
transgenic cotton plants (Rao et al., 2013).
Experimental data collected in the current study showed that transgenic fibers
resulted in enhanced fiber physical properties like fiber length, fiber strength, micronaire
value and uniformity index. This progress will facilitate the industry to expand its market
share by developing local cotton variety with improve fiber characteristics. Future
perspective is the identification of signaling pathways involved side by side with flavonoids
in improving fiber quality. Regarding this interaction among plant hormones ethylene,
salicylic acid, jasmonate and abscisic acid including the flavonoid pathway requires further
exploration. Application of advance technologies like microarray analysis of these transgenic
lines will be very helpful in solving this puzzle.
Conclusion
Current study was an effort to elevate anthocyanin pigments level in transgenic cotton
and to further visualized its effects on imparting colouration and fiber quality improvement
132
of cotton. It is clear from the outcomes that anthocyanin play a significant role in cotton fiber
improvement which is a multigenic character though alteration in fiber colour was not so
evident. The study resulted in provision of unique information for better utilization of this
trait in molecular breeding program which in combination with other fiber trait will provide a
great breakthrough to cotton growers and to textile industry in specific for saving their import
losses.
133
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APPENDICES
APPENDIX-I
Luria Bertani (LB) Medium
Tryptone 10 g
Yeast Extract 5 g
NaCl 10 g
Dissolved in 1 liter of distilled water, adjusted pH to 7.5 and autoclaved.
LB Agar
LB containing 15 g / liter of Bacto Agar.
MS Medium (Murashige and Skoog, 1962) Composition
MS Salts 4.33 g / l
MS Vitamins 1 ml / l
Sucrose 30 g / l
Phytagel 3 g / l
pH 5.8
YEP Medium
Bactopeptone 10 g / l
Yeast Extract 5 g /
NaCl 10 g / l
pH 7.5
158
YEP Agar
YEP containing 15 g / liter of Bacto Agar.
APPENDIX-II
Antibiotic Stocks
i) Kanamycin 1. Kanamycin (500 mg/10 ml)
2. Double distilled water up to 10 ml volume
Filter sterilized it and store at -20 oC.
ii) Rifampicin
1. Rifampicin powder (12.5 mg)
2. 70% Ethanol (10 ml)
Filter sterilized it and store at -20 oC.
iii) Ampicillin
1. Ampicillin powder (1 g)
2. Distilled H2O (10 ml)
iv) Tetracycline
1. Tetracycline powder (12.5 mg)
2. 70% Ethanol (10 ml)
v) Kanamycin
1. Kanamycin powder (1 g)
2. Distilled H2O (20 ml)
vi) Cefotaxime
1. Cefotaxime Powder (0.25 g)
2. Distilled H2O (5 ml)
159
APPENDIX-III
CTAB DNA Extraction Buffer
Stock Working Volume (50 ml)
10 % CTAB 2% 10 ml
5M NaCl 1.4 M 14 ml
0.5 M EDTA (pH 8.0) 0.02 M 2 ml
1 M Tris-Cl (pH 8.0) 0.1 M 5 ml
10 % PVP 2 % 10 ml
Autoclaved H2O 8.5 ml
β-Mercepto Ethanol 2% 0.5 ml
6X DNA Loading Dye
Ficoll 20 %
EDTA 0.1 M
SDS 1 %
Bromophenol blue 0.25 %
Xylene Cyanol 0.25 %
50 X TAE Buffer (Tris-Acetate-EDTA) 1 Litre
Tris Base 242 g
Acetic Acid 57.1 ml
0.5 M EDTA 100 ml (pH 8.0)
160
APPENDIX-IV
20x SSC
NaCl 350.6g
Na-Citrate 176.4g
Adjust pH to 7.0 with NaOH and make up volume to 2 liter with distilled water.
2x SSC (500 ml)
Dissolve 50 ml of 20x SSC and 5ml of 10% SDS in 445ml of autoclaved distilled water.
0.5x SSC (500 ml)
Dissolve 12.5 ml of 20x SSC and 5ml of 10% SDS in 482.5 ml of autoclaved distilled
water.
Genius Buffer I
TrisCl 100mM (pH 7.5)
NaCl 150mM
Genius Buffer II (Blocking solution)
TrisCl 100mM (pH 7.5)
NaCl 150mM
Blocking reagent 2%
Genius Buffer III
TrisCl 100mM (pH 9.5)
NaCl 100mM
MgCl2 50mM
161
APPENDIX-V
RNA Extraction Buffer
Stock Working Volume (50 ml)
10% CTAB 2% 2.5 ml
5M NaCl 1.4 M 10 ml
0.5 M EDTA (pH 8.0) 0.02 M 1.25 ml
1 M Tris-Cl (pH 8.0) 0.1 M 2.5 ml
10% PVP 2% 2.5 ml
Autoclaved H2O 30.25 ml
β-Mercepto Ethanol 2% 1 ml
SSTE Buffer
Stock Working Volume (50 ml)
5% SDS 0.5% 1 ml
1.5 M NaCl 1 M 2.85 ml
0.5 M EDTA (pH 8.0) 1 mM 20 µl
1M Tris-Cl (pH 8.0) 10 mM 100 µl
162
APPENDIX-VI
Reagents for Anthocyanin Extraction
70% Methanol
Add 700 ml of methanol in 300 distilled water.
2% HCl acid (pH 0.8)
Add 10ml of conc. HCl in distilled water and set volume up to 500ml.
0.01% HCl (in 95% Ethanol)
About 100µl conc.HCl in 95% Ethanol and set volume to 100ml.
0.2M Na2HPO4
Add 2.839g of anhydrous Na2HPO4 in 100ml distilled water.
0.1M Citric acid
Add 4.8g of Citric acid powder in 250ml water.
Citrate Buffer (pH 3.5)
Add 64.4ml of 0.2M Na2HPO4 and 135.6 ml of 0.1M Citric acid and set volume to 200ml.
pH was maintained at 3.5 by using solutions of citric acid and Na2HPO4.
163
PUBLICATIONS
From thesis
Ahad, A., Ahmad, A., Din, S. ud, Rao, A. Q., Shahid, A. A., & Husnain, T. (2015). In silico
study for diversing the molecular pathway of pigment formation: an alternative to manual
coloring in cotton fibers. Frontiers in Plant Science 6:751.
Ahad, A., Yaqoob, A., Nawaz, R., Gul, A., Shahid, N., Ullah, T.R.S., Abdul Q Rao, A.
Q., Shahid, A. A., Husnain, T., & Yildiz, F. (2018). Multidimensional roles of flavonoids in
background of Gossypium hirsutum. Cogent Food & Agriculture 4(1): 1-9.
Ahad, A., Tahir, S., Ali, M.A., Nawaz, R., Iqbal, A., Ahmed, M., Akhtar, S., A. Q., Shahid,
A. A., & Husnain, T. (2018). Functional prediction of F3’5’H in color alteration in Cotton:
An In-Silico Comparative analysis between Cotton and Viola. International Journal of
Biosciences 13(3):185-197.
Miscellaneous
Ahad, A., Maqbool, A., & Malik, K.A. (2014). Optimization of agrobacterium tumefaciens
mediated transformation in eucalyptus camaldulensis. Pakistan Journal of Botany 46 (2):
735-740.
Bajwa, K. S., Shahid, A. A., Rao, A. Q., Dahab, A. A., Muzaffar, A., Rehman, H. U.,
Ahmad, M., Shaukat, M.S., Gul, A., Ahad, A., & Husnain, T. (2014). Stable genetic
transformation in cotton (Gossypium hirsutum L.) using marker genes. Advanced Crop
Science 3: 811–821.
164
A. Ahmad, A. Ahad, A.Q. Rao, & T. Husnain. (2015). Molecular docking based screening of
neem-derived compounds with the NS1 protein of Influenza virus. Bioinformation 11(7):
359–365.
Ahmad, A., Javed, M.R., Rao, A.Q., Khan, M.A.U., Ahad, A., Din, S., Shahid, A.A., &
Husnain, T. (2015). In-silico determination of insecticidal potential of Vip3Aa-Cry1Ac
fusion protein against lepidopteran targets using molecular docking. Front Plant Science
6:1081.
Gul, A., Ahad, A., Akhtar, S., Ahmad, Z., Rashid, B., & Husnain, T. (2016). Microarray:
gateway to unravel the mystery of abiotic stresses in plants. Biotechnology letters 38(4):527–
543.
Nawaz R., Zahid S., Idrees M., Rafique S., Shahid M., Ahad A., Amin I., Almas I., Afzal S.
(2017). HCV-induced regulatory alterations of IL-1β, IL-6, TNF-α, and IFN-ϒ operative,
leading liver en-route to non-alcoholic steatohepatitis. Inflammation Research 66(6):477–
486.
Shahid, N., Rao, A.Q., Kriste, P.E., Ali, M.A., B, Tabassum., Umar, S., Tahir S., Latif, A.,
Ahad, A., Shahid, A.A., & T. Husnain. (2017). A concise review of poultry vaccination and
future implementation of plant-based vaccines. Poultry Science Journal 73(3): 471-482.
Ahad, A., John, E., Maqbool, A., & Malik, K.A. (2018). Development of efficient micropropagation
system for E. Camaldulensis with respect to age of explants Pakistan Journal of Agricultural
Sciences 55(1): 23-27.
Ahmed, M., Shahid, A.A., Din , S.U., Akhtar, S., Ahad, A., Rao, A.Q., Bajwa, K.S., Khan,
M.A.U., Sarwar, M.B., & Husnain, T. (2018). An overview of genetic and hormonal control
of cotton fiber development. Pakistan Journal of Botany 50:433–443.
