High Throughput Search of Drought Tolerant Genes in Agave sisalana L.
SANIA RIAZ
CENTRE OF EXCELLENCE IN MOLECULAR BIOLOGY UNIVERSITY OF THE PUNJAB LAHORE PAKISTAN
(2015)
High Throughput Search of Drought Tolerant Genes in Agave sisalana L.
A THESIS SUBMITTED TO UNIVERSITY OF THE PUNJAB IN FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY IN MOLECULAR BIOLOGY By
SANIA RIAZ Supervisor: Dr. Tayyab Husnain (Prof & Acting Director)
Centre of Excellence in Molecular Biology. University of the Punjab, Lahore
CERTIFICATE
It is certified that the research work described in this thesis is the original work of the author Ms. Sania Riaz and has been carried out under my direct supervision. I have personally gone through all the data reported in the manuscript and certify their correctness and authenticity. It is further certified that the material included in this thesis have not been used in part or full 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 and we endorse its evaluation for the award of Ph.D degree through the official procedures of the university.
In accordance with the rules of the centre, data book #852 is declared as unexpendable document that will be kept in the registry of the Centre for a minimum of three years from the date of the Thesis defense examination.
Signature of the supervisor______
Name: Dr. Tayyab Husnain
Designation: Prof & Acting Director
(Allah) Most Gracious! It is He Who has taught the Qur'an. He has created man: He has taught him speech (and Intelligence). The sun and the moon follow courses (exactly) computed; and the herbs and the trees- both (alike) bow in adoration. And the Firmament has He raised high, and He has set up the balance (of Justice), in order that you may not transgress (due) balance. It is He Who has spread out the earth for (His) creatures: There in is fruit and date-palms, producing spathes (enclosing dates): Also corn with (its) leaves and stalks for fodder and sweet- smelling plants. Then which of the favours of your Lord will you deny? (SURAH Rehman, AYAH 1-13)
DEDICATED TO
My BELOVED PARENTS
ACKNOWLEDGEMENT I am extremely grateful to almighty “ALLAH” whose bountiful blessings enabled me to complete this research project. He bestowed us with his "HOLY QURAN", and prophet “MUHAMMAD” (Peace be upon him), who enlightens the hearts of us in our lives. I wish to acknowledge several key figures that contributed much to my research endeavor. A journey is easier when you travel together. Interdependence is certainly more valuable than independence. This thesis is the result of six years of work whereby I have been accompanied and supported by many people. It is a pleasant aspect that I have now the opportunity to express my gratitude for all of them.
First and foremost I would like to take this opportunity to place on record my deep sense of gratitude to my supervisor, Dr. Tayyab Husnain (Prof & Acting Director, CEMB). I have been in his project since January 2010 when I started my PhD research work. During this whole period of six years I have known him as a sympathetic and principle-centered person. His overly enthusiasm and integral view on research and his mission for providing „only high quality work and not less‟, has made a deep impression on me. I owe him lots of gratitude for having me shown this way of research. Especially the extensive comments and the many discussions and the interactions with him had a direct impact on the final form and quality of this thesis. He could not even realize how much I have learned from him. Besides of being an excellent supervisor, I am really glad that I have come to get know Dr. Tayyab Husnain as a brilliant teacher and hardworking supervisor.
I am greatly indebted to my Lab Incharge Dr. Bushra Rashid (Assistant Prof), for her sympathetic attitude and cordial co-operation throughout the progress of this research. Cordial thanks are due to Dr. Ahmad Ali Shahid (Associate Prof.) & Dr. Abdul Qayyum (Assistant Prof) who made it a convivial place to work. They all kept an eye on the progress of my work and always were available when I needed their advice and valuable suggestions. I am also obliged to pay my sincere thanks to all my lab colleagues especially Beenish Aftab, who helped me in difficult circumstances to accomplish this project. It was a great pleasure to work with all of them.
I can‟t express my feelings about the Higher Education Commission (HEC), who provided me such opportunity to make my dreams true. Without HEC 5000 Indigenous Ph.D fellowship scheme this opportunity would mere a dream for me.
I am also very much thankful to almighty ALLAH Pak Who granted me the most beautiful and sweetest feelings of life and for which a mother can wish for. I was blessed with a daughter Hareem Ayesha and a son Abdul Hadi during the journey of my doctorate studies. Last but not the least, I wish to pay my sincerest gratitude to my parents Muhammad Riaz and Jahan Ara Riaz, who always remembered me in their prayers and raised me with a love of science and supported me in all pursuits and of course this is the sweetest outcome of their blessings. I am highly indebted and obliged to thank my better half Mr. Rizwan-ur-Rehman, a Ph.D scholar in Tianjin university of science and Technology,China. He has always supported and encouraged me to do my best in all matters of life. I wish to thank my affectionate brothers Irfan Afzal, Sami Riaz, Yasir Riaz, Babar Riaz and Hassan Riaz and my dearest sisters Shazia Irfan and Dr. Sadaf Abdul Rauf. They all have always supported and encouraged me to do my best in all matters of life. I will simply say thank you very much to all of you.
Sania Riaz
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CONTENTS
Table of Contents i List of Figures vi List of Tables ix Abbreviations xi Summary xiv 1 INTRODUCTION 1 2 REVIEW OF LITERATURE 5 2.1 HISTORY AND ORIGIN OF AGAVE 5 2.2 TAXONAMY AND CLASSIFICATION OF AGAVE 5 2.3 CRASSULACEAN ACID METABOLISM 6 2.4 LIFE SPAN OF AGAVE SPECIES 7 2.5 PHARMACOLOGICAL AND ETHNO MEDICINAL PROPERTIES 8 OF AGAVE PLANTS 2.6 EFFECT OF LOW AND HIGH TEMPERATURES ON AGAVE 9 2.7 MOLECULAR STUDIES ON AGAVE PLANTS 10 2.8 HIGH THROUGHPUT SEARCH OF UPREGULATED GENES IN AGAVE SISALANA L. 10 2.9 ROLE OF ABIOTIC STRESSES ON AGRICULTURAL CROPS AND THEIR PRODUCTION 11 2.10 PLANTS DEFENCE AGAINST ABIOTIC STRESSES 13 2.11 COMPLEXITY OF ABIOTIC STRESS SIGNALING 14 2.12 SENSORS INITIATE MULTIPLE SIGNALING PATHWAYS 15 2.13 SIGNAL TRANSDUCTION SIGNALING PATHWAYS 15 2.14 OXIDATIVE STRESS SIGNALING UNDER ABIOTIC STRESSES 16 2.15 ROLE OF LEA TYPE GENES UNDER ABIOTIC STRESSES 17 2.16 ROLE OF SOS PATHWAYS AND ACTIVATION OF 18 HOMEOSTASIS 2.17 POSSIBLE FATE OF SIGNALING PATHWAYS 18 2.18 GENE EXPRESSION REGULATION BY TRANSCRIPTION 19 FACTORS (TFS) 2.19 ZINC FINGER (ZNF) TRANSCRIPTION FACTORS 21
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2.20 ROLE OF bZIP TFS IN STRESS TOLERANCE IN PLANTS 22 2.21 ROLE OF WRKY TFs and Cys2/His2 ZINC FINGER PROTEINS 22 UNDER OSMOTIC STRESS 2.22 ROLE OF AP2/ERF, MYB AND bHLH TF‟s IN STRESSED 23 ENVIRONMENT ADAPTATION 2.23 GENE EXPRESSION TRIGGERED BY NAC TRANSCRIPTION 23 FACTOR 2.24 DROUGHT STRESS INFLUENCES ON GAS EXCHANGE 24 PARAMETERS 2.25 EFFECTS OF DROUGHT STRESS ON PLANT WATER RELATIONS 27 2.26 ROLE OF BIOCHEMICAL MARKERS IN RESPONSE TO 27 DROUGHT STRESS 2.27 ROLE OF MOLECULAR BIOLOGY IN PRESENT ERA 31 3 MATERIALS AND METHODS 33 3.1 PLANT MATERIAL AND DROUGHT TREATMENT 33 3.2 DETERMINATION OF FIELD CAPACITY 34 3.3 MICROSCOPIC EXAMINATION OF LEAF EPIDERMAL TISSUE 35 3.4 PLANTS‟ PHYSIOLOGICAL ANALYSIS UNDER DROUGHT STRESS 35 3.5 WATER RELATED ATTRIBUTES AND LEAF SURFACE AREA 37 35 3.5.1 Leaf Relative Water Content (LRWC) 35 3.5.2 Leaf Surface Area 36 3.6 PLANTS‟ BIOCHEMICAL ANALYSIS UNDER DROUGHT STRESS 36 3.6.1 Proline Content 36 3.6.2 Lipid Peroxidation Assay (Malondialdehyde Content) 37 3.6.3 Total Chlorophyll Content 37 3.7 STATISTICAL ANALYSIS 37 3.8 TOTAL RNA ISOLATION 38 3.8.1 Agarose Gel Electrophoresis 38 3.8.2 Quantification of Total RNA 39 3.8.3 DNase Treatment 39 3.9 CONSTRUCTION OF cDNA LIBRARY 39 3.9.1 Isolation of mRNA from Total RNA 39 3.9.2 Precipitation of mRNA 40
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3.9.3 Double Strand cDNA Construction 40 3.9.4 Ligating the attB1 Adapter 42 3.9.5 cDNA Size Selection 43 3.9.6 Gel Elution 43 3.9.7 BP Recombination Reaction 43 3.10 SCREENING OF COLONIES ON MEDIA 45 3.10.1 Plasmid Isolation 45 3.10.2 Restriction Analysis of Cloned cDNA 46 3.11 PREPARATION OF cDNA MICROARRAY PLATFORM 46 3.11.1 Clone Pickling and Culturing 46 3.11.2 PCR Amplification of Inserts 46 3.11.3 Purification of PCR products prior to sequencing 47 3.12 CLONE SEQUENCING 48 3.13 REMOVAL OF VECTOR SEQUENCES USING VEC SCREEN 49 3.14 BLAST SEARCH 49 3.15 GENE ONTOLOGY (GO) AND FUNCTIONAL ANNOTATION 49 3.16 PRINTING OF cDNA MICROARRAY 49 3.17 HYBRIDIZATION OF TARGET WITH cDNA MICROARRAY 51 PLATFORM 3.17.1 Target Preperation 51 3.17.1.1 Aminoallyl Labeling 51 3.17.1.2 Removal of Un-Incorporated aa-dUTP and free amines 52 3.17.1.3 Coupling aa-cDNA to Cyanine Dyeester 52 3.17.1.4 Removal of Uncoupled Dye 52 3.17.2 Hybridization 53 3.17.2.1 Pre-Hybridization 53 3.17.2.2 Hybridization 53 3.17.2.3 Slide Washing 53 3.17.3 Slide Scanning 53 3.18 IMAGES PROCESSING AND RAW DATA GENERATION 54 3.19 DATA NORMALIZATION AND ANALYSIS 54 3.19.1 Data Normalization 54 3.19.2 The Midas Project 54
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3.19.3 Tm4 Mev Analysis 54 3.20 SEQUENCING OF DIFFERENTIALY EXPRESSED TRANSCRIPTS 55 3.21 VALIDATION STUDIES BY QUANTITATIVE REAL-TIME PCR 55 3.22 BIOINFORMATIC STUDIES 55 3.22.1 Blast Search 55 3.22.2. Gene Ontology (GO) and Functional Annotation 56 4 RESULTS 57 4.1 EFFECT OF DROUGHT STRESS ON EPIDERMAL TISSUE OF 57 AGAVE SISALANA LEAVES 4.2 EFFECT OF DROUGHT STRESS ON PHYSIOLOGICAL 58 BEHAVIOUR OF AGAVE SISALANA 4.3 EFFECT ON WATER RELATED ATTRIBUTES AND LEAF 58 SURFACE AREA OF AGAVE SISALANA 4.4 EFFECT OF DROUGHT STRESS ON BIOCHEMICAL ATTRIBUTES 59 OF AGAVE SISALANA 4.5 CORRELATION BETWEEN PHYSIOLOGICAL, BIOCHEMICAL 67 AND WATER RELATED ATTRIBUTES 4.6 cDNA LIBRARY 67 4.6.1 Total RNA 67 4.6.2 Size Selection 67 4.6.3 cDNA Library Cfu 69 4.6.4 Plasmid Isolation and Restriction Digestion Confirmation 69 4.7 PCR AMPLIFICATION 70 4.8 cDNA LIBRARY CLONE SEQUENCING 71 4.9 HOMOLOGY SEARCH 71 4.10 FUNCTINAL CHARACTERIZATION BY GENE ONTOLOGY 87 4.10.1 Molecular Characterization 87 4.10.2 Cellular Chatracterization 88 4.10.3 Biological Characterization 88 4.11 cDNA MICROARRAY 99 4.12 TARGET PREPARATION 99 4.13 CHIP HYBRIDIZATION AND SCANNING 100 4.14 DATA NORMALIZATION 101 4.14.1 R-I Plot 101
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4.14.2 Z-Score Histogram 101 4.14.3 Box Plot 106 4.15 SIGNIFICANCE ANALYSIS OF MICROARRAY (SAM) 4.16 BIOINFORMATIC STUDIES OF DIFFERENTIALLY EXPRESSED 110 cDNA CLONES 4.17 MICROARRAY DATA ANALYSIS 112 4.18 K MEANS CLUSTERING AND EXPRESSION GRAPH 112 4.19 MICROARRAY RESULTS VALIDAITON STUDIES BY 117 REALTIME PCR 5 DISCUSSION 118 5.1 EFFECT OF DROUGHT STRESS ON EPIDERMAL TISSUE OF 118 AGAVE SISALANA LEAVES 5.2 EFFECT OF DROUGHT STRESS ON PHYSIOLOGICAL 118 BEHAVIOUR OF AGAVE SISALANA 5.3 WATER RELATED ATTRIBUTES AND LEAF SURFACE AREA 121 OF AGAVE SISALANA L. 5.4 EFFECT OF DROUGHT STRESS ON BIOCHEMICAL ATTRIBUTES 122 OF AGAVE SISALANA L. 5.5 CORRELATION BETWEEN PHYSIOLOGICAL, BIOCHEMICAL 124 AND WATER RELATED ATTRIBUTES 5.6 AGAVE SISALANA L. cDNA LIBRARY CONSTRUCTION AND 125 EXPRESSION PROFILING 5.7 DIFFERENTIALLY EXPRESSED ESTS 138
LITERATURE CITED 140 APPENDICES
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LIST OF FIGURES
Figure No. Figures Page No. Figure 1 Signal transduction pathways involved in Plant 16 metabolism Figure 2 Role of reactive oxygen species in transcriptional and post 19 transduction gene regulation Figure 3 Drought responsive pathways in plants. 24 Figure 4 Progeny of Agave plants developed in CEMB 33 Figure 5 Agave sisalana L. plants under drought stress 34 Figure 6 Samples of control and drought stressed leaves of Agave 36 sisalana L. Figure 7 Thermocycling profile for the amplification of inserts by 47 cPCR Figure 8 Thermocycling profile for the sequencing PCR 48 Figure 9 Map and Features of pDONR 222 with Site of PCR 50 Product Figure 10 Thermocycling profile for cDNA synthesis 51 Figure 11 Schematic representation of BLAST2GO application 56
Figures 12 Stomatal aperture of Agave sisalana leaf epidermis under 57 microscope Figure 13 Comparison of photosynthetic rate of control, 10% and 60 2% field capacity drought stressed leaf tissue Figure 14 Comparison of transpiration rate of control, 10% and 2% 60 field capacity drought stressed leaf tissue Figure 15 Comparison of stomatal conductance of control, 10% and 61 2% field capacity drought stressed leaf tissue Figure 16 Comparison of water use efficiency of control, 10% and 61 2% field capacity drought stressed leaf tissue Figure 17 Comparison of relative water content of control, 10% and 62 2% field capacity drought stressed leaf tissue Figure 18 Comparison of proline content of control, 10% and 2% 63
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field capacity drought stressed leaf tissue Figure 19 Comparison of lipid peroxidation (MDA) content of 63 control, 10% and 2% field capacity drought stressed leaf tissue Figure 20 Comparison of total chlorophyll content of control, 10% 63 and 2% field capacity drought stressed leaf tissue Figure 21 Nanodrop plots showing Agave sisalana L. total RNA in 68 control and drought stressed leaf epidermis samples Figure 22 Total RNA isolation of control and drought stressed leaf 68 epidermis tissue of Agave sisalana L., showing two intact rRNA bands in control and stressed plants with mRNA smears Figure 23 Plasmid isolation of cDNA library clones 69 Figure 24 Restriction digestion confirmation showing the presence 69 of inserts Figure 25 Confirmation of clones by PCR amplification lane 1-96, 70 PCR amplified cDNA clones (M = 1Kb) Figure 26 A single sequenced clone from Agave sisalana L. cDNA 72 library, showing quality of sequence Figure 27 Agave sisalana L. EST‟s distribution with top hit species 73 Figure 28 GO molecular functions categorization by annotation 87 Figure 29 GO cellular processes categorization by annotation 89 Figure 30 GO biological processes categorization by annotation 89 Figure 31 Qualitative and quantitative confirmation of labeled 99 cDNA by nanodrop (ND-1000) Figure 32 Microarray image showing scanned images of hybridized 100 slide Figure 33A R-I plot for non-normalized data 102 Figure 33B R-I plot for normalized data 103 Figure 34A Z-score histogram for non- normalized data 104 Figure 34B Z-score histogram for normalized data 105 Figure 35A Box plot for non-normalized data 107 Figure 35B Box plot for normalized data. 108
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Figure 36 SAM plot analysis of differentially expressed cDNA 109 clones Figure 37 Agave sisalana potential drought stress candidate EST‟s 110 distribution with top hit species Figure 38 Agave sisalana potential drought stress candidate EST‟s 111 molecular functional categorization Figure 39 Agave sisalana potential drought stress candidate EST‟s 111 cellular component categorization Figure 40 Heat map analysis showing the differential expression of 116 up regulated genes in epidermal leaves of Agave sisalana L. Figure 41 Relative fold expression of candidate ESTs of Agave 117 sisalana L. in control and drought plants through real- time PCR
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LIST OF TABLES Table no. Tables Page No. Table 1 Sequence of primers used for colony PCR 47 amplification. Table 2 Sequences of the primers used in real-time PCR 56 with their GenBank Acc_No. Table 3 Mean values for physio-chemical and water 64 related attributes under control, 10 and 2% field capacity drought stress Agave sisalana plants Table 4 Analysis of variance (ANOVA) for physiological 65 attributes under control, 10 and 2% field capacity drought stress Agave sisalana L. plants Table 5 Analysis of variance (ANOVA) for biochemical 65 attributes under control, 10 and 2% field capacity drought stress Agave sisalana L. plants Table 6 Analysis of variance (ANOVA) for relative water 66 content and leaf surface area under Control, 10 and 2% field capacity drought stress Agave sisalana L. plants Table 7 Correlation coefficients (r) between physio- 66 chemical and water related attributes of Agave sisalana L. plants under drought stress Table 8 Homology of Agave sisalana L. EST‟s with land 74 plants (BLAST-nucleotide) along with genbank accession numbers and user_ID. Table 9 Homology search of Agave sisalana L. EST‟s with 82 land plants (BLAST-protein) along with genbank accession numbers and User_ID. Table 10 Gene function(s) of EST‟s biological processes, 90 molecular function and cellular components along with genbank accession numbers, User_ID and Arabidopsis genbank accession numbers
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Table 11 Accession numbers and homology with NCBI 113 genbank against nucleotide, EST and protein data basis.
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ABBREVIATIONS
aadUTP Amino allyl Deoxy uridine triphosphate
ABA Abscisic acid
ANOVA Analysis of variance
AOGTR Australian Office 0f the Gene Technology Regulator
BLAST Basic local alignment search tool
BLASTN Nucleotide blast
BLASTX Protein blast
BSA Bovine serum albumin
C Stomatal conductance cDNA Complementary deoxy ribo nucleic acid
CFU Colony forming unit
CTAB Cetyl Trimethyl Ammonium Bromide
Cy3 Cyanine 3
Cy5 Cyanine 5
DEPC Diethyl pyrocarbonate
DMSO Dimethyl sulfoxide dNTPs Deoxynucleotide triphospahtes
DRE Drought responsive element
DTT Dithiothreitol
E Transpiration
EDTA Ethylenediaminetetra acetic acid
ERF ETS repressor factor
EST Expressed Sequence Tags
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FC Field Capacity
FDR False discovery rate
FW Fresh weight
GDP Gross domestic product
GH Gravimetric humidity
GO Gene Ontology h Hour
ICAC International Cotton Advisory Committee
IRGA Infra Red Gas Analyzer
LB Luria-Bertani medium
LEA Late Embryogenesis Abundant
LOWESS Locally weighted scatterplot smoothing
LSD Least significant difference
MAF Million acre feet
MAPK Mitogen activated protein kinase
MEV Multi Experiment Viewer
MIDAS Microarray data analysis system mM Millimolar
MPa Mega psacal
MYB Myeloblastosis
NCBI National center for biotechnology information
NCC National Cotton Council of America
NH4OAC Ammonium acetate
OA Osmotic adjustment
PAR Photosynthetic active radiation
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PCI Phenol chloroform isoamyl alcohol
Pfu Pyrococcus furiosus
PVP Polyvinylpyrrolidone q RT- PCR Quantitative real time Polymerase chain reaction
RLK Receptor like kinases
ROS Reactive oxygen species
RWC Relative water content
SDS Sodium dodecyl sulfate
SNRK sn related kinase
SOC Super optimal broth (catabolite)
SOS Salt overly sensitive
SSC saline-sodium citrate
TAE Tris-acetate-EDTA
TAIR The Arabidopsis Information Resource
TE Tris-HCL EDTA
TF Transcription factor
TIFF Tagged Image File Format
ZFHD Zinc finger homeodomain
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SUMMARY
Agave sisalana, a hard succulent CAM (crassulacean acid metabolism) plant along with other land plants like cactus, pineapple and vanilla orchids, has evolved over millions of years to drive a different kind of photosynthesis that allows the plants to survive in semiarid environments where water isn‟t always readily available. This process is known as CAM and it is the main area of interest for the scientists all over the world to develop drought resistant plants. Modern genomic approaches like gene identification, their characterization and expression under various abiotic stresses lead to the crafting of genetically resistant crops. The genomes of a number of different CAM plants have been sequenced in the past two years but Agave sisalana L. has received limited attention by many researchers around the globe as far its ability to survive under drought conditions is concerned. Therefore present study was aimed to develop drought stressed cDNA library and to find out potentially up-regulated genes expressed under drought in leaf epidermal tissue of Agave sisalana.
Agave sisalana plant selection under drought stressed conditions was done on the basis of their physio-biochemical and water related attributes. All the physiological parameters including photosynthetic and transpiration rate, stomatal conductance and water use efficiency showed decreasing trend with increasing drought stressed conditions. Biochemical analyses of control and drought stressed Agave sisalana plants also played an important role in the adaptation of plants to adverse environment conditions. Plant under drought stress produces certain osmolytes like proline and products of reactive oxygen species which triggers the regulatory signaling pathways involved in the plant defense mechanism. In the present study the correlation coefficients (r) among various physiological, biochemical and water related factors under drought stress conditions also indicated that decreasing photosynthesis, transpiration, total chlorophyll content and other parameters are well monitored by the accumulation of osmolytes produced in response to abiotic traumas.
In case of water related measuring parameters, the values of relative water content decreases with the drought stress compared to control where it remain significantly high. Microscopic examination of epidermal tissues of leaves of Agave
xv sisalana showed partially and fully closed stomata upon the induction of drought stress. Stomatal conductance also decreased and showed accordance with the closed stomata under drought stress. Instantaneous water use efficiency showed contradictory results of showing decreasing trend with abiotic stress. It has been reported in many cases that it varies with different plant species as has been explained in the discussion part of the dissertation. All the biochemical assays performed in Agave plants confirmed the accumulation of macro molecules that could lead to support the idea of searching drought tolerant functional EST in leaves of Agave sisalana L.
A cDNA library from drought stressed epidermal tissue of leaves of Agave sisalana L. has been constructed. Ten thousands clones were randomly picked, replicated and PCR amplified. The inserts size was found in a range of 100-1000bp. One hundred and five (105) clones (submitted to NCBI GenBank (JZ892707 - JZ892811) were sequenced and annotated. As there were no reported sequences on Agave sisalana L. under drought stress so the homology search was done in comparison with already reported sequences in land plants. Blast ( EST, nucleotide and protein) database in NCBI GenBank was used for homology search. Approximately 4% clone sequences didn‟t show homology at selection criteria (e < 1.0) whereas maximum homology was found in Elaeis guineensis (African palm 16%) followed by Phoenix dactylifera (date palm 8%), Musa acuminate (Banana 5%), Solanum species (5%), Medicago tranculata (5%), Populus trichochorpa (desert poplar 4%), Vitis vinifera (Grapes 4%), Nicotiana species (3%) and Agave species (3%) respectively.
The clones (amplified PCR products) were printed in duplicate at an expected ratio of 9,408 spots per microarray chip. The labeled cDNAs were prepared from total RNAs of control and drought stressed leaves of Agave sisalana L. These labeled cDNAs were hybridized to cDNA chips, scanned and data were analyzed. Ten (10) clones were found to be differentially expressed on cDNA microarray platform. The microarray results were validated by real time PCR. EST sequences of potential candidates for drought stressed genes were analyzed through BLAST2GO programe. Out of ten (10) ESTs, maximum homology was found in Phoenix dactylifera plant. Six EST‟s which gives the best homology with drought tolerant genes in other land
xvi plants on nucleotide BLAST (nr) and protein BLAST (p) were further evaluated with real time PCR along with bioinformatics studies.
Real time data analysis showed highest expression in EST‟s (JZ892752 and JZ892726) whereas EST (JZ892743, JZ892761 and JZ892787) showed low expression of drought tolerance in Agave sisalana L. The differentially expressed EST JZ892778 showed no expression or upregulated activity in stressed leaves of Agave sisalana L. Similar expression of two up-regulated ESTs (JZ892726 and JZ892752) was observed in expression behavior and fold change when compared with K means in cluster analysis of microarray.
This new EST collection for the first time in Agave sisalana L. indicated an important step towards the identification of many molecular markers that aided the selective hybridization and biotechnological approaches to further improve Agave sisalana L. as drought resistant plant. Furthermore, the public availability of the novel up regulated cDNA clone sequences generated in this study will enable testing of the biological function of the genes represented and the development of transgenic plants in future.
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1. INTRODUCTION
A major challenge of the current agricultural era is to meet the basic need of food production worldwide for global population that will reach 9 billion mark by 2050 (Godfray et al. 2010; Tester and Langridge, 2010). At the same time this increasing demand for food is severely hampered by the destructive environmental factors specially drought, thus making life more miserable in rainfed areas. Drought and, to a large extent salinity, are the two prime abiotic factors that have a strong impact on agricultural land, its productivity and crop yields. If drought, due to scarcity of water, is crucial for crop production in all agronomic areas, water resources having high salinity levels are also found inadequate for the successful crop production in some areas of the world. Accordingly, side-by-side, drought and soil salinity have become major agricultural issues nowadays (Flower, 2004). This problem surely requires an urgent need of transformed crops with increased salt tolerance and water use efficiency to fit appropriately in problem areas.
Agave sisalana is considered as the miracle plant for having multidimensional characteristics. It is a major fibre-yielding crop throughout the world having pharmacological properties and strong potential to withstand adverse environmental conditions. Agave sisalana is a xerophytic plant of same genus i.e., agave belongs to the family agavaceae and is suitable for various natural habitats, ranging from seashores to high desert mountains and desert plains (Irish, M. 2003). It has the unique feature of growing in any style of garden under rough climatic conditions. This over the year enables the researchers throughout the world to increase its yield, production and quality. Another area of research in this plant is to discover drought tolerant genes and develop trangenic plants that can help overcoming drought problem throughout the world.
Agave plant consists of large rosette of thick fleshy leaves with a sharp and spiny margin and the short stout stem with the leaves apparently springing out from the roots. It has fleshy tuber with deep or spreading fibrous roots under the soil surface to increase water-use efficiency and growth (Nobel, 1977). Agaves are successfully adapted to adverse environmental conditions because of their capacity to maintain high water level in their leafy portion. They possessed a specialized structure called “pinna” a central head through which 2 the basal parts of the leaves grow out while the growth of new leaves takes place from the upper part of the shoot. The pinna is a kind of "store house" of polysaccharides in the form of sugars resulting as an endproduct of photosynthesis (Gentry, 1982), which is one of the basic ingredients for manufacturing agave in industry. The weight of the pinna ranges from 25 kg to 75kg however it may become as heavy as 200 kg. Their nutrients are used up by other parts of plants such as roots, rhizomes and floral stalk. The sizes of long fleshy leaves of agave plant range approximately from 20cm to 2m, making it one of the most important morphological characteristics (Nobel, 1988; Valenzuela-Zapata and Nabhan, 2003). The presence of cuticle in Agave plant helps covering the leaves that are impermeable thereby reducing the transpiration (Smith and Nobel, 1986). The big size of leaves and cuticle formation are two major morphological characters that help retaining the maximum water storage that in turn facilitates the adaptation under dry and arid habitats. The color of the leaves varies from bluish to green and grey (Gentry, 1982). Most of Agave plants possess spiky leaves, serving as a defense against herbivores. However in some varieties the spikes are absent. Agave plants possess an interesting inflorescence, which is mostly very tall andranges between 2-10 meters. However, commercial agave varieties of Agave sialana are harvested before the formation of inflorescence.
Several cultivated species of Agave including Agave sisalana grow well in areas where inadequate rainfall inhibits the cultivation of many C3 and C4 crops. The thick cuticle of their leaves minimizes non-stomatal water loss and helps agave plants to practice crassulacean acid metabolism (CAM) photosynthesis by their reduced stoma. The key feature of the CAM photosynthetic pathway adapted by Agaves is the stomata opening and CO2 uptake during the night, thus allowing less water to be lost by transpiration. Escamilla- Treviño (2011) reported the information regarding productivity, by-products and biofuel processability of Agaves. They also suggested that Agave sisalana could be a potential bioenergy crop which could complement other bioenergy crops due to its capacity to grow with inadequate rainfall or other inputs thus making semi-arid land more productive under abiotic environmental stresses. The responses generated at molecular level by these stress- resistant crops also provided ideas on how to genetically engineer crops for stress tolerance (Kahn et al., 1993). 3
Drought is considered to be the most promising abiotic factor affecting cash and bioenergy crops production and quality every year. Drought basically is an extended time period when water availability becomes inadequate or below the statistical requirements for a certain region. It is an interplay between natural availability of water and human demands for water supply (Ramanjulu and Bartels, 2002). Major drought conditions prevailing all over the worldultimately affect plant growth, quality and yield and it happens only when there is scarcity of water (Boyer, 1982; Neill and Burnett, 1999). Drought stress is a complex agronomic trait, which disrupts the overall plant defense system (Ingram and Bartels, 1996; Cushman and Bohnert, 2000) which makes it more susceptible towards other abiotic and biotic stresses (English-Loeb, 1990). Its adverse effects vary depending on environmental, agricultural and urban needs for water. Overall, it disturbs cropping programs, causes reduction in breeding stock, and induces soil erosion which affects the farming community and downfall of national economy. Sustainability of agriculture is at risk due to the longterm implications of drought stress every year. However, since selection for drought tolerant crop is a major interest of researchers and breeders throughout the world (Basal et al., 2005). Drought stress induces the expression of several up-regulated genes in plants, which may produce regulatory functional proteins to survive under abiotic stressed conditions (Shinozaki et al. 2006).
Pakistan‟s agriculture is predominantly irrigated and most of the land in the country is arid and semiarid because of low rainfall. Of the total cultivated area, about 80 percent is irrigated while crop production on the remaining 20 percent depends mainly on rainfall. Reduction in food crop production with each passing day due to dreadful and long lasting effects of various biotic and abiotic stresses is a prime area of concern now a days to ensure food security under abrupt environmental changes. Approximately one-third of the total cultivated area of the world is suffering from poor water supplies.
High salinity, low temperature and drought are the common abiotic stresses that hinder plant growth and crop production. These conditions are very common in rainfed areas (Wang et al. 2003). To overcome these problems plants develop adaptive strategies at cellular, physiological and morphological level, which help them to sustain life. These adaptive responses are modulated by sets of specific genes whose products allow plants to 4 avoid the stress or become tolerant (O‟Connell‟ and Rodriguez-uribe, 2006). Understanding these mechanisms by which plants respond and perceive environmental stimuli and then transmit these signals to cells and tissues to activate adaptive molecular pathways is of fundamental importance in biology.Several hundred stressed genes that respond to these environmental stresses and generate responses at transcriptional level have been identified (Kreps et al, 2002; Zhu 2002; Shinozaki et al., 2003). Therefore, it is important to analyze the functions of stress inducible genes not only for understanding the molecular mechanisms but also for improving the stress tolerance of crops by gene manipulation. The determination of these mechanisms which are directly involved in drought stress tolerance is a challenging task for the scientists as it involves several metabolic pathways which are difficult to understand (Price et al.,2002).
With Agave sisalana plant it can be expected that improvements will eventually be made in all crops that serve as staple foods for much of the world's population against drought stress.The first step towards this goal is the rapid discovery of differentially expressed genes under drought stress tolerance. This will be done through sequencing of randomly selected cDNA clones or expressed sequence tags of cDNA library of Agave sisalana. Recent advances in high-throughput search make it possible for scientists to explore and sequence entire genomes. Microarray technology employing cDNAs is one of the most powerful tools used for analysing gene expression profiles of plants exposed to abiotic stresses such as drought (Seki et al., 2001; Krebs et al., 2002). The advent of microarrays and other similar technologies allows for the comparison of expression patterns of several thousand genes with a single hybridization. Once genes of particular interest are identified, scientists will begin to understand their functions. Different research groups from all over the world have reported high throughput search of drought tolerant genes in many land plants. The identification of genes associated with drought stress tolerance is of prime importance in order to develop drought tolerant crop plants (Tuberosa and Salvi 2006; Sreenivasulu et al., 2007). Lot of work has been done on different crops for the identification of stress inducible genes as mentioned above but high throughput search of such genes in Agave sisalana L. has not yet been explored. This project has therefore, proposed to identify the highly up- regulated genes expressed in Agave sisalana L. under drought stress conditions. 5
2. LITERATURE REVIEW
2.1 HISTORY AND ORIGIN OF AGAVE
The agave that had previously been described by the Anglo-Americans as the “century plant” is today well known as “mescal” by the Mexicans (Valenzuela-Zapata and Nabhan, 2003). From the advent of North American colonization, it became the part of the human life. However, evidence given by the archeologists has linked the use of agave by humans as early as 9000 years ago. The pre-historical cultivation of agave plants for food, fiber and tools has also been recorded in Native American tribes. As a result of human activity, a gradual change in the genetic characteristics has also been found in this plant (Sheldon 1980; Gentry 1982; Colunga and Maypat 1993). The fiber produced by the leaves of different species of agave plant was also utilized to make ropes and baskets. At the same time, medicinal importance of different agave plants were found due to their antiseptic, anti- inflammatory, diuretic and laxative properties (Verastegui et al., 1996). The sugars produced by this plant have long been used to prepare alcoholic beverages by fermentation and one of the most famous one is pulque that has been used in the religious rituals (Miller and Taube, 1993). Even today, this plant is utilized for the production of fibers, medicines and construction material in some rural areas of Mexico (Badano and Pugnaire, 2004). The climatic adaptation of agave plants to semi-arid regions is very successful, contributing a significant proportion of the flora found in these regions. At the same time these plants are also found in a wide range of habitats and can resist the severe diverse environments such as deserts, grasslands, oak-pine woodlands and rocky steep surfaces (Nobel, 1988).
2.2 TAXONAMY AND CLASSIFICATION OF AGAVE
The plants of the genus agave have been classified into two basic groups: 1) the plants with inferior ovaries belong to the family Amaryllidaceae while the plants possessing superior ovaries, for example, Yucca are grouped in to the family Liliaceae (Bentham and Hooker, 1883; Engler and Prantl, 1888). This traditional classification was revised in 1934, combining the plants possessing fibrous leaves like Yucca and Agave into a new family Agavaceae (Hutchinson, 1934). There are two prominent taxonomic systems of classification of agave plants that include Cronquist‟s system classifying the Agavaceae into 18 genera 6
(Cronquist, 1981), while the other system classified this family further into two tribes, the Yucceae and Agavaceae comprising 9 genera of plants (Dahlgren and Yeo, 1985).
With the development of new technologies such as chloroplast DNA restriction site analysis helped making a more precise classification of Agavaceae (Bogler and Simpson, 1995) while the internal transcribed spacer region of the ribosomal DNA facilitated the narrow definition of the Agavaceae family. Dahlgren (1985) and his colleagues also classified this family based on the sequence analysis of the large subunit of ribulose biphosphate carboxilase (Duvall et al., 1993). The estimated age of the Agavaceae family attracts different opinions and is believed to be between 20-26 million years (Good-Avila et al., 2006) and 35 million years (Wikstrom et al., 2001). The genus Agave has been grouped with three other genera and collectively called Agave sensulato. However, the Agave genus itself is termed as Agave sensu stricto (Eguiarte et al., 2000). Agavaceae family comprises 293 recognized species out of which 208 species are included in Agave sensulato. Forty-nine belong to Yucca species, and if these are also included, the total number will stand at 257. The Agave sensulato, constituting biggest group of species of this family, is also the youngest one (Good-Avila et al., 2006) indicating the highest-level diversification of this genus within a short period of evolution.
There are two subgenera of Agave sensu stricto, one is known as Littaea and other is called as Agave. The subgenus Agave consists of 113 species (Good-Avila et al., 2006). However, not only due to large number of species and varieties, but also due to complex polyploidy variations, the exact number of Agave species and their varieties is not known (Palomino et al., 2003). Additionally, the classification of different varieties of the same species becomes difficult on account of multiple reasons such as low reliability of old classification methods, non-availability of appropriate data involving modern techniques (Garcia-Mendoza and Chiang, 2003) and lack of availability of floral structure due to long lifespan of most of the species such as Agave tequilana(Gentry, 1982; Valenzuela-Zapata, 1997).
2.3 CRASSULACEAN ACID METABOLISM (CAM)
Water shortage is thought to be involved in the adaptation of Agave plants to arid and 7 dry land habitats (Gentry, 1982). At the same time carbon metabolism-related drought- adaptation also plays a major part in their adaptation to semi-arid and arid habitats. Agavaceae family comprised members which belong to those plant species which followed CAM biochemical pathway and are involved in the fixation of atmospheric CO2 for photosynthesis during the night when temperatures are significantly lower than daytime temperature (Winter and Smith, 1996).
Most of plants of the dry and arid environment such as desert plants exhibits CAM pathway, closing the stomata opening during the day time when the temperature is high, resulting in less water loss through transpiration, while opening them up throughout the night time when the temperature drops down, allowing the uptake of CO2 and its fixation by phosphoenolpyruvate (PEP) in the presence of PEP-carboxylase (PEPC) enzyme. This results in the production of malate that is stored in the vacuole of the cell with the help of another enzyme H+-ATPase (Dodd et al., 2002). At the beginning of the day the diurnal phase of CAM and photosynthesis is initiated by the leaf cells, closing the stomata, diminishing the PEPC and passively quitting the malate from the vacuole into the cytosol where it is enzymatically de-carboxylated. The Calvin cycle is initiated resulting in fixation of the available CO2 thereby synthesizing carbohydrates. This CAM pathway thus triggers many genes that contains cis-regulatory elements that are involed in the regulation and expression of circadian clock genes involved in CAM metabolism (Ray et al., 2015).
2.4 LIFE SPAN OF AGAVE SPECIES
Species of the family Agavaceae mostly possess long life span however, depending upon different species. It ranges from 5-6 years to 20 years (Gentry, 1982). Many factors, such as environmental conditions and soil fertility etc., impact the life expectancy of different species (Nobel, 1988). In Agaves, the metabolic activities are enhanced in hot conditions resulting in shorter life span. Both sexual and asexual reproduction takes place in Agaves but in commercially important species like A. tequilana and A. sisalana, propagation through asexual reproduction is more common. Asexual reproduction involves the production of vegetative offshoots from underground rhizomes of the mother plant (Tissue and Nobel, 1988). Subsequently these offshoots develop into daughter plants and remain attached to the 8 mother plant responsible for the translocation of nutrients to daughter plants and this process continues until the daughter plants are able to start producing their own food through photosynthesis and ultimately start living their own independent life. Asexual propagation also facilitates the local proliferation of some species in new areas; however it is also responsible for less variation in genetics of Agave species resulting in less resistance to different diseases and pathogens in the cultivated crops (Valenzuela-Zapata and Nabhan, 2003). Another but relatively uncommon propagation through asexual reproduction is by formation of bulbils growing from the cells at the flower stem of some agave species (Arizaga and Ezcurra, 1995).
Agaves also exhibit sexual reproduction developing a long inflorescence ranging from two to ten meters tall. The central head of the plant is a key point from where the inflorescence develops as a result of increased metabolic activities by utilizing all of the stored sugars. Subsequent events include pollination and seed production that take place in a short duration of time and ultimately the plants usually die (Gentry, 1982; Nobel, 1988). Seed production is high with increasing germination rates however, only few of the seedlings survive while most of them die after 8-9 days of germination (Arizaga and Ezcurra, 2002).
There are many pollinating carriers that pollinate the Agave, the best amongst them being the bats (Arita, 1991; Slauson, 2001). Sexual reproduction in Agaves has many benefits such as genetic diversity however, due to certain limitations like long time period and usage of commercially important sugars people usually do not cultivate Agave species.
2.5 PHARMACOLOGICAL AND ETHNO MEDICINAL PROPERTIES OF AGAVE PLANTS
Agave plants are currently being used in the production of fibers, sweeteners, alcoholic beverages and some other chemicals. Pulque, Mescal and Tequila are the famous products of different species of Agave (Nobel, 2010). One of the varieties of Agave known as blue weber is used to make Tequila. Another important product is syrup or nectar which is composed of non-structural carbohydrates. Few species of Agave namely A. lechuguilla, A. fourcroydes, and A. sisalana have been utilized in fiber production. Agave sisalana have various pharmacological properties and have been used in the treatment of various ailments. 9
Leaves of A. sisalana activate the uterine and intestinal musculature and help in the lowering of blood pressure. Juice of Agave sisalana leaves causes abortion in pregnant animals. Leaf sap of agave plants is used to inhibit bacterial growth in the intestine and stomach and exhibits antiseptic properties while fresh sap of A. schottii is used for skin abrasions, cuts and burns (Debnath et al, 200). It is also used as poultices on wounds (Chevallier, 1996). Agave cures food indigestion, dysentery, pulmonary tuberculosis, syphilis, constipation and jaundice (Bown, 1995) and acts as uterine stimulant and hypotensive drug (Sharaf and Zahran, 1967). Leaf fiber of Agave species is used as tonic in hair falling and scalp disinfectant (Lust, 1983) while roots have been used in the treatment of toothache, wound healing, diaphoretic, laxative and diuretic (Chopra et al., 1986). Homoisoflavonoids isolated from Agave plants possess immunological properties (Kuo et al., 2004), cytotoxicity and inhibitory activity against COX-2 enzyme. Few species of genus Agave, specifically Agave sisalana display ethno medicinal characteristics. The central bud of A. sisalana is used for the treatment of jaundice after boiling it with salt (Eldridge, 1975). Aqueous extract of A. attenuate has been experimented for its activity against Oreochromis mossambicus, Daphnia pulex, Bulinus africanus and Anopheles arabiensis which exhibited piscicidal, molluscicidal and larvicidal properties (Brackenbury and Appleton, 1997). Steroidal saponin extracted from A. attenuata was experimented for its hemolytic effect and anti-inflammatory characteristics (da Silva BP et al., 2002).
2.6 EFFECT OF LOW AND HIGH TEMPERATURES ON AGAVE
With the help of molecular biology tools, various traits of Agave plants can be improved for adding their value as bioenergy crops. Low temperature and freezing tolerance is of prime importance because they are very much susceptible to low and freezing temperatures below 0°C to -4°C and their cultivation in the field at low temperatures is not possible (Faucon, 2004). On the other hand Agave americana and and Agave weberi survive better in field at low temperatures between -8°C to -11°C. Among all the Agave species, Agave utahensis have shown highest frost tolerance (-23°C) at the expense of low production on annual basis. Some Agave species have also exhibited highest resistance to high temperatures and other biotic factors but this has not scientifically proved at least in Agave sisalana species. The extent to which the genome of Agave sisalana expresses in high 10 temperature and drought conditions needs to be worked out. This project is therefore designed to check the potential of differentially expressed genes in Agave sisalana under drought conditions.
2.7 MOLECULAR STUDIES ON AGAVE PLANTS
Genetic improvement of Agave species by conventional breeding is difficult because of its long life span as Agave progeny took more than seven years to reach maturity and even longer time period in species like Agave sisalana and Agave tequilana (Escamilla-Treviño, 2011). Genetic transformation may help this plant to get maturity in short time period but this again needs to be worked out. Several Agave species are being micropropagated through in vitro studies but there is only one finding on successful and controlled genetic transformation of Agave salmiana made by particle bombardment and Agrobacterium tumefaciens (Flores- Benitez et al., 2007). Co-cultivation of explants was controlled and successful with the use of uidA gene that act as reporter and transformational efficiency was found to be 2.7%.
The data related to the use of molecular techniques applied on Agave plants is very limited. Only little information is available on NCBI regarding transcriptomic studies. Even short ESTs data is not available for many Agave species. Thus using advanced molecular techniques for obtaining EST or genomic data would provide another ground for research for developing trangenics in Agave species. In Mexico, two research centers are currently working on the genome sequencing of A. tequilana but still a lot of research is needed to explore high throughput genes in this miracle plant.
2.8 HIGH THROUGHPUT SEARCH OF UPREGULATED GENES IN AGAVE SISALANA
First construction of normalized cDNA libraries containing full-length sequences of Agave sisalana at different developmental stages was reported by Zhou etal. (2012).They worked with SMART™ method and reported the maximum number of genes in Agave sisalana. No data is available on discovery of new genes in Agave sisalana plant growing under abiotic stresses. Therefore in this project, efforts would be made to generate new ESTs for the first time in Agave sisalana plant growing under drought stress conditions. 11
2.9 ROLE OF ABIOTIC STRESSES ON AGRICULTURAL CROPS AND THEIR PRODUCTION
Any environmental factor that is capable of making considerable change in the form of injury in any living organism is called stress as defined by Levitt (1982). In any Agroecosytem, plants are influenced by biotic as well as abiotic factors. The abiotic stresses include drought, cold, salt, nutrient deprivation, heat, flooding and heavy metal toxicity that affects plant life adversely (Mahajan and Tuteja, 2005). Different plant species have different responses and adaptability levels towards these abiotic stresses. (Bohnert et al.,1995). The decline in crop production in different crops due to environmental changes and abiotic stresses is reported in maize (65.8%), soybeans (69.3%), potatoes (54.1%), and wheat (82.1%) (Bray et al., 2000; Wang et al., 2013) resulted in decline of crop yield up to 70% (Acquaah, 2009). Change in agricultural practices and climate combined with soil constraints induced such changes in the environment that are mainly responsible for water scarcity and drought etc. How plants get affected with these abiotic factors and what kind of changes they produce in response in the form of complex mechanisms need to be investigated (Ahmad and Prasad, 2012).
In the growing season plants experience lot of distinct environmental changes concurrently or at some different time periods (Tester and Bacic, 2005) that ultimately produce a series of multiple factors including physiological, molecular, biochemical, morphological as well as water related attributes affecting overall plant health and productivity (Wang et al., 2000). Drought, cold, heat and salinity problems are intermingled and affect the water relations of plants at the cellular, tissue and organ level. (Beck et al., 2007).
2.9.1 Responses of Plants Towards Abiotic Stresses
Drought is considered as an environmental factor caused by insufficient rainfall or inadequate water supply (Toker et al., 2007). It tops all environmental stresses that hinder plant growth and limit its performance (Shao et al., 2009). It also induces strong impact on growth, membrane integrity, yield, pigment content, water related attributes and photosynthesis (Benjamin and Nielsen, 2006; Praba et al., 2009). 12
The responses towards abiotic factors are dynamic, abrupt and complex that cause low crop yields even below optimum levels. These changes are elastic and plastic that is, reversible and irreversible (Cramer, 2010). Drought is a major cause of crop yield losses every year that are estimated at more than 50% annually worldwide (Bray et al., 2000; Wang et al., 2003). Plants generate different responses towards drought stress depending on the type of organ, tissue or cell type (Dinney et al., 2008). The extent of stress level and duration also plays significant role in the complexity of the response (Tattersall et al., 2007).
Drought has the most significant impact that not only reduces crop production and yield every year (Parimala and Muthuchelian, 2010) especially in the countries where crop production mainly depends on rainfall but also affects their economy (Saeed et al., 2005). A drought affects approximately one third of the cultivated area worldwide (Massacci et al., 2008). Recent reports on drought showed that drought-to-rainfall ratio is increasing rapidly and it will go up to 30% (Yi et al., 2010; Gong et al., 2013) and as a result regional food security is also being threatened in countries like Pakistan (Saeed et al., 2009).
All the agronomic, climatic and edaphic factors affect drought stress and determine its level of severity on certain area. The plants show resistance and sometimes susceptibility to drought stress and it depends on stress level, combined effect of different stress factors, type of plant species and developmental stages (Demirevska et al., 2009). Under water- stressed conditions, plants get adaptive with changes in physiological and biochemical attributes in the form of osmolytes and antioxidants production. (Duan et al., 2007). So it is very important to trace the adaptive changes in plants in response to water deficit conditions to produce drought resistant crops and ensure their higher yield under unfavorable environment.
Plants experience severe drought stress on account of slow water supplyor high transpiration from leaves. Drought incidence may be controlled by escape, tolerance and avoidance (Levitt, 1980; Jones et al., 1981). Drought escape is defined as allowing a plant to complete its life cycle before soil water becomes scarce whereas drought avoidance is the maintenance of water level in stem and leaves of any plant under low water availability. Plants will have to maintain balance in both ways, either to draw enough water from plant 13 roots or prevent enough water loss through transpiration. If plant gets vulnerable to dry conditions in a prescribed way, the cells may avoid drought or water deficit condition. In contrast, drought tolerance is a characteristic whereby the plant works at tissue-specific and cellular level by producing sugars, proteins, enzymes and certain osmolytes that help it survive and work under drought stressed conditions (Rao and Cramer, 2003).
2.10 PLANTS DEFENCE AGAINST ABIOTIC STRESSES
Plants get adaptive to abiotic stresses at various morphological, physiological, cellular, and biochemical levels resulting in up regulated gene expression. The cell physiology of whole plant in response to drought is highly complex and involves many deleterious and adaptive changes. Plants cope with any adverse environmental change by combined strategies of stress avoidance and stress tolerance. Early response to drought stress includes stomatal closure, which helps the plant to survive that condition for smaller time period. But for longterm survival under severe drought, plants usually work by producing certain metabolites and Reactive Oxygen Species (ROS) under regulatory pathways (Ivan et al., 2015)
Plants exhibit different characteristics while responding to water stressed conditions like maintenance and regulation of normal homeostasis, counteracting against damages, scavenging of ROS to work under oxidative stress and plant growth recovery. Biochemical responses include up regulation of genes and onset of different metabolic pathways like sensing, perceiving and transducing the initial signals by osmo sensors (AtHK1, kinases and phospholipases) their control at transcriptional level by transcription factors known as DREB (dehydration-responsive transcription factors) and finally activation of stress response mechanisms which features detoxification of ROS by SOD (Superoxide dismutase) and CAT (Catalase).
Plants have evolved a series of biochemical pathways, including enzymatic and non- enzymatic antioxidant systems to fight drought and address oxidative damages. Reactive 2- - oxygen species like Super oxidant ion O , hydroxyl ion OH and hydrogen per oxide H2O2 are produced and accommodated by plants under drought stressed conditions. (McCord, 2000). It has also been reported (Sminrnoff, 1993) that excessive generation of reactive 14 oxygen species causes photo inhibition and ultimately ceases the photosynthetic apparatus and completely destroys the plant machinery. However, accumulation and production of ROS have some positive role in the activation of many defense reactions, which lead to plant survival including functional and structural protection.
2.11 COMPLEXITY OF ABIOTIC STRESS SIGNALING
Due to several environmental stresses different signaling pathways take their way to cope with the related stresses; and as reported in different studies of molecular biology and genetics, many important components are involved in these signaling pathways. The multiple information stores in abiotic stress signaling highlighted one of the complex aspects of stress signaling (Chinnusamy et al., 2004).
Nevertheless, most studies on water stress signaling have focused primarily on salt stress because plant responses to salt and drought are closely related and the mechanisms overlap (Zhu 2002). Responses to stress are not simple; it involves the chain of more complicated integrated circuits including multiple pathways and specific cellular compartments, tissues, and the interaction of additional cofactors or signaling molecules to coordinate a specified response to a given stimulus (Dombrowski, 2003). Plants not only respond to these stresses at different molecular and cellular levels, but also at several physiological levels. As a result of these stresses, various genes become active and induce their expressions. The products of these genes‟ expressions are thought to be involved in different functions, at the same time playing important roles not only in tolerating the stress but also in regulating the gene expression and signal transduction in response to stress (Shinozaki et al., 2002 c; Shinozaki et al., 2003). Drought-tolerant plants at low water potentials maintain the turgor level by increasing the uptake of number of solute molecules into the cell. Nearly 40-90% of the total intracellular volume of a mature plant cell comprises plant vacuoles, thereby generating the cell turgor that is responsible for growth and plant rigidity. H+ pumps activity maintains the H+ electrochemical gradient across the membrane of vacuole, allowing the secondary active transport of inorganic ions, organic acids, sugars, and other compounds, thereby determining cell turgor. The water balance is thus maintained by the storage of these solutes. In principle, increased vacuolar solute accumulation could 15 determine the salt and drought tolerance.
2.12 SENSORS INITIATE MULTIPLE SIGNALING PATHWAYS
The initial stress signals are sensed by the molecules called sensors. These sensor molecules either initiate or suppress a cascade to transmit the intracellular signal that in turn express a particular set of genes by activating the relative nuclear transcription factors. A particular aspect of stress conditions may activate a particular single sensor, which in turn regulates a cascade of signals. The environmental stresses such as salt, cold and drought + stresses are responsible for Ca2 influx to induce into the cell cytoplasm obtained either from + the apoplastic space or from internal stores. This Ca2 influx represents only one type of sensor for channelizing the stress signals.
Both animals and plants possess receptor-like kinases (RLKs). They consist of an extracellular, a transmembrane and an intracellular domain, where ligand binding occurs to extracellular domain, which is a specific type of protein-protein interaction (Christiaan et al., 2012) On perceiving the signal by the extracellular sensor domain, a phosphorylation moiety is channelized by auto-phosphorylation of the cytoplasmic histidine residue and is passed to a response regulator through an aspartate receiver. The cellular response is initiated as a result of the sensors coupled either with MAPK (mitogen activated protein kinase) cascade or else phosphorylates the specific targets directly. Mostly the cells follow the multiple phosphor- protein cascades on getting a signal from membrane receptors thereby transducing and amplifying the information. Protein phosphorylation and dephosphorylation play key role and are the best modes for the intracellular signaling. By this type of signaling most of the cellular processes such as enzyme activation, assembly of macromolecules, protein localization and degradation are regulated. However, secondary signals channelize another cascade of signaling events, differing from the primary signaling events in time and space (Xiong and Zhu, 2001).
2.13 SIGNAL TRANSDUCTION SIGNALING PATHWAYS
There are three major signaling types of signal transduction pathways for cold, 16 drought, and salt stresses (Figure 1). The figure shows: (I) the generation of ROS scavenging enzymes antioxidant compounds by utilizing MAPK molecules in response to + osmotic/oxidative stress; (II) Ca2 dependent signaling network that produces proteins of stress response that are responsible for initiating the expression of late embryogenesis abundant (LEA)-type genes (such as the DRE/CRT class of genes); and (III) another + Ca2 signaling pathway regulating the ion homeostasis, also called as salt overlay sensitive (SOS) pathway that is specific in response to ionic stress (Xiong et al., 2002).
Figure 1: Signal transduction pathways involved in plant metabolism (Adapted from Xiong and Zhu, 2001).
2.14 OXIDATIVE STRESS SIGNALING UNDER ABIOTIC STRESSES
- The production of H2O2, superoxide and OH radicals have a significant impact on cellular damage and inhibition of photosynthesis. These radicals, known as ROS radicals, are produced as a result of salt, drought, heat and cold stress and the phenomena is called oxidative stress, one of the well-known major causes of plant damage in response to environmental stresses (Sunkar et al., 2003). Osmolytes, proteins and tocopherol are the compounds that work as ROS scavengers (Xiong et al., 2002). Recently it has been studied that free radical scavangers or chemical chaperones can also be produced by compatible 17 solutes by stabilizing the membranes or proteins. There are three major groups of compatible solutes including amino acids (e.g. proline), quaternary amines (e.g. glycine betaine, dimethylsulfoniopropionate) and polyol/sugars (e.g. mannitol, trehalose) (Wang et al., 2003).
2.15 ROLE OF LEA TYPE GENES UNDER ABIOTIC STRESSES
+ As discussed earlier Ca2 is responsible for different intracellular signaling networks + both in animals and plants. The concentration of intracellular Ca2 is critically monitored. + When there is low Ca2 concentration in the cytosol, they are liberated from the intracellular + storage or enter the cell via various Ca2 channels in response to stimulation. One of the most + important sensors to regulate the Ca2 influx in plants is Calcium-dependent protein kinases (CDPKs). CDPKs are serine/threonine protein kinases having a C-terminal calmodulin-like + domain, binding Ca2 directly. CDPKs are transcribed by multigene families and their expression levels are spatially and temporally controlled through the whole course of development. In addition, external stimuli may activate subset of CDPK genes. The CDPK network is seemed to be specific for LEA protein expression for antidesiccation protection (Serrano et al., 2003).
The dehydration-responsive element (DRE)/C-repeat (CRT) class of stress- responsive genes or LEA type genes are controlled by different channels or pathways from those regulating the osmolyte production. When LEA-type genes are activated, it may represent damage repair pathways (Xiong et al., 2002). The LEA proteins are believed to be the first protein during development and maturation stage as during the natural desiccation, seeds accumulate transcripts and proteins are produced at a relatively high concentration.
Under the adverse conditions of desiccation, LEA proteins accumulate in higher plants. LEA proteins are accumulated whenever there is stress of water deficiency, high osmolarity, and low temperature. These proteins bind with water, thereby preserving the structure of membrane protein leading to protection from denaturation or renaturation of unfolded proteins and sequestering ions in stressed tissues. LEA proteins and chaperones are also believed to be responsible for protecting the macromolecules like enzymes, lipids and mRNAs from dehydration (Shinozaki et al., 2000). At least six different families are found in LEA proteins as evidenced on the basis of sequence similarity. 18
2.16 ROLE OF SOS PATHWAYS AND ACTIVATION OF HOMEOSTASIS
Salt overly sensitive pathway (SOS) is a calcium dependent signaling network that seems to be relatively specific for the ionic aspect of salt stress (Hongtao et al., 2013). This signaling functions by activating the targets that are ion transporters controlling the ion homeostasis under salt stress. As the SOS pathway is specific to function under ionic stress, therefore the homologs of SOS3 and SOS2 are thought to be responsible for functioning in the transduction of other stress or hormonal signals (Figure 2). Arabidopsis represents eight + SOS3-like Ca2 binding proteins and twenty-two SOS2-like protein kinases (Guo et al., 2001). The hormones like ABA and ethylene are produced in high quantity during biotic and abiotic stress. In addition, salicylic acid and jasmonic acid are thought to be involved in some parts of stress responses. These hormones regulate the stress signaling pathways and stress tolerance by interacting with each other. Salt, drought, and up to some extent, cold stress activate the genes that code for ABA enzymes that maximize the level of ABA biosynthetic enzyme that subsequently catabolized to relief from the stress. ABA is also involved in the upregulation of many stress-responsive genes. Another aspect of ABA feedback is that by + Ca2 dependent phosphoprotein cascade, it stimulates the expression of ABA biosynthetic genes. ROS may be responsible to mediate both ABA signaling and ABA biosynthesis, suggesting that the regulation of ABA biosynthetic genes by ABA might be activated, in part, by ROS through a protein phosphorylation cascade (Zhao et al., 2001). Subsequently these regulatory molecules can mediate a second round of signaling that might be involved in following the above generic pathway. The secondary signals might also be different in respect of their specificity from primary stimuli, may be shared by different stress signaling pathways. Also they might be responsible to underlie the interaction among signaling pathways under different stresses and stress cross-protection. Therefore, one primary stress condition may lead to the multiple signaling pathways differing in time, space, and outputs. These pathways may interlink with one another creating intertwined networks by using shared components (Hasegawa et al., 2000; Wang et al., 2003).
2.17 POSSIBLE FATE OF SIGNALING PATHWAYS
The osmotic signaling pathways involve gene expression thereby activating the 19
osmolyte biosynthesis enzymes and water and osmolyte transport systems. Other changes caused by salt and drought stress are thought to be mediated by detoxification signaling. These changes include: (a) Phospholipids hydrolysis; (b) Changes in the expression of LEA/dehydrin-type genes, molecular chaperones, proteinases responsible to remove denatured proteins; and (c) activation of enzymes responsible for the production and removal of reactive oxygen species and other detoxification proteins (Zhu, 2002).
Figure 2: Role of Reactive oxygen species in transcriptional and post transduction gene regulation (Adapted from Guo et al., 2001).
2.18 GENE EXPRESSION REGULATION BY TRANSCRIPTION FACTORS (TFS)
On a DNA molecule certain specific sites are present to which small molecules are attached, called as transcription factors (TFs) that are involved in the activation or deactivation of specific genes. They belong to some of the large multigene families. The members of the same family sometimes exhibit different respond to different stress stimuli 20 while on the other hand the same TFs may play a role in the activation of some of the stress responsive genes, depending on the overlapping of the gene-expression profiles that are activated in response to different stresses (Seki et al., 2001; Chen et al., 2002).
The genes responsible for transcription-factor are also present among the stress- inducible genes, ensuring better functioning of different transcriptional regulatory mechanisms in drought, salt or cold stress signal transduction pathways. There are many different transcriptional regulatory systems that are responsible and play a role in the activation of stress-responsive genes as evident from numerous molecular and genomic analyses. In this system of stress responsive transcription, numerous sets of cis and trans- acting factors are involved. They are either controlled by ABA or by some others. Hence, both ABA-dependent and -independent regulatory systems are responsible for expression of stress-responsive genes (Shinozaki and Yamaguchi, 2004).
Several hundreds of the genes are involved in responding to abiotic stresses at transcriptional level. However, there are doubts on the functioning of these gene products under stress (Kreps et al., 2002; Seki et al., 2002; Xiong et al., 2002; Zhu, 2002; Shinozaki et al., 2003; Matsui et al., 2008). These analyses of stress-inducible genes have recently described a cross dialogue in the expression profile of stress responsive gene (Seki et al., 2002).
The gene clusters are switched by some very important group of regulators called Transcription factors (TFs). A single transcription factor is responsible for controlling many target genes by binding to specific sites called cis-acting element in the promoter regions of confirming target genes. This type of transcriptional regulatory system is called as regulon. Numerous chief regulons have been described in Arabidopsis that are mediated in response to abiotic stress. Dehydration-responsive element binding protein 1 (DREB1), C-repeat binding factor (CBF) and DREB2 regulons function in ABA-independent gene expression while the ABA-responsive element (ABRE) binding protein (AREB)/ABRE binding factor (ABF) regulon function in ABA-dependent gene expression (Nakashima et al., 2009) (Figure 3). 21
Several other transcription factors such as MYB, bZIP, NAC, and zinc-finger are either directly or indirectly being responsible for the regulation of plant stress responses and plant defense (Zhu, 2002; Seki et al., 2003; Shinozaki et al., 2003; Fujita et al., 2004; Yanhui et al., 2006). In Arabidopsis, two ABRE motifs have been described that are engaged in the regulation of ABA-responsive expression of RD29B gene encoding a LEA-like protein (Uno et al., 2000). Transcription factors such as DREB2A and DREB2B activate the DRE cis- element of osmotic stress genes thereby being involved in maintaining the osmotic equilibrium of the cell (Liu et al., 1998). Another dehydration stress responsive cis-element (CRE)/C-repeat (CRT) (A/GCCGAC) has been extensively studied to investigate other transcriptional regulating factors such as DRE-binding protein (DREB)/C-repeat binding factor (CBF), and subsequently their post-translational regulatory mechanisms (Shinozaki and Yamaguchi-Shinozaki, 2000; Thomashow, 2001). Furthermore, genetic screening to investigate the possible mutations that might have an impact on the expression of stress- inducible genes has led to identify some novel components in the regulatory system (Chinnusamy et al., 2003).
2.19 ZINC FINGER (ZNF) TRANSCRIPTION FACTORS
The zinc-finger motifs play major role in interacting with other molecules and are found in several transcription factors. They are classified on the basis of their specific arrangement with zinc binding amino acids (Chao et al., 2009; Sun et al., 2010). Several molecular biological processes including stress tolerance regulation systems involve numerous zinc finger transcriptions. A specific finger like conformation is formulated on the basis of particular sequence motif of cysteines and/or histidines that surround a zinc atom, thus giving a specifc name as zinc finger transcription factor (Ben Saad et al., 2010). This domain allows zinc finger proteins to bind to DNA or other proteins. Stresses such as salt, drought and cold mediate the stress-associated proteins (SAPs) with the A20/ANI zinc-finger domain (Vij and Tyagi, 2006). These transcriptional factors have an impact on several signaling pathways, affecting the protein-protein interactions thereby altering expressions (Ben Saad et al., 2010). Their examples include OsSAP1 and AlSAP (Ben Saad et al., 2010).
At the same time there are some other zinc finger TFs such as TFIIIA-type or Cys2/His2
(C2H2) which possess a specific DNA-binding motif that in response to salt, cold and 22 dehydration stresses permits them to play their role as transcription factors. Similarly, some of biological processes like photosynthesis and carbohydrate metabolism are regulated by the genes activated by transcriptional factors such as ZFP252, ZFP245, ZFP179 and DST, STZ/ZAT10 and AZF1. Some other zinc finger TFs such as Zat12 works in ROS scavenging and AZF2 is responsible for repressing transcriptional process (Saibo et al., 2009; Kodaira et al., 2011; Fujita et al., 2006; Todaka et al., 2012). Some other zinc finger TFs such as
BrRZFP1, a C3HC4-type RING, have recently been investigated to play their role for abiotic stresses (Jung et al., 2013). However, the functions of some of zinc fingers TFs (C2C2, C3H, LIM, PHD, ZF-HD) are still unclear.
2.20 ROLE OF bZIP TFS IN STRESS TOLERANCE IN PLANTS
The members of bZIP transcriptional factors function in an integrated manner to play a major role in salt and drought related regulatory networks, and their potential for increased stress tolerance has been investigated repeatedly. A differential screening technique was explored in salt-induced transcripts of A. thaliana to identify F group bZIP TF bZIP24, which is an important regulator of salt stress adaptation (Yang et al., 2009). Other than bZIP24, there is bZIP, dealing with drought stress, including AREB1, AREB2, and ABF3 factors, called as group A, which play a regulatory role in ABA signaling network. Therefore, the species, A. thaliana AREB1, AREB2 and ABF3 exhibit a triple knockout impact on mutants leading to an increased tolerance to ABA, reducing the drought stress (Yoshida et al., 2010). Also, tolerance to water deficiency and salt stress increased in transgenic modified rice and tomato with a group A bZIP TFs (Amir Hossain et al., 2009; Hsieh et al., 2010) indicating the potential of these factors against stress conditions.
2.21 ROLE OF WRKY TFs and Cys2/His2 ZINC FINGER PROTEINS UNDER OSMOTIC STRESS.
WRKY proteins are responsible for regulating not only different abiotic and biotic stresses but also various pathway mediated by hormones (Ramamoorthy et al., 2008). The function of WRKY63 in A. thaliana has been investigated and it is found that this protein is involved to knock out mutants that exhibited decreased sensitivity to drought and ABA (Ren et al., 2010). In Agave, the expression of the transcription factors such as AREB1/ABF2 and 23 closure of stomata are affected by WRKY factors in ABA dependent pathway of drought and salt adaptation (Ren et al., 2010). Another important group of protein is Zat proteins
(TFIIIA-type Cys2/His2 zinc finger proteins) that have been found to control and regulate the functions of WRKY (Miller et al., 2008). In addition the overexpression of GmWRKY54 in soya bean plant has resulted in an increased tolerance to salt and drought and as a result it is believed that GmWRKY54 is regulated by Zat10/STZ (Zhou et al., 2008).
2.22 ROLE OF AP2/ERF, MYB AND bHLH TF’s IN STRESSED ENVIRONMENT ADAPTATION
Members of the DREB/CBF, which is a subfamily of the AP2/ERF transcriptional factors, have been found to exert their actions in stress tolerance though ABA-dependent and -independent pathways. At the same time they also mediate regulation of sub-transcriptome involved in inducing a stress-response with more than hundred target genes including some of the other regulatory factors like ZAT12 and RAP 2.1 (Shinozaki and Yamaguchi- Shinozaki, 2000). Similarly, multi-functional regulations are performed by R2R3-MYB TF AtMYB41 that involve a transcriptionally induced response to cold, drought ABA and salinity (Lippold et al., 2009). In addition, these factors are believed to be involved in influencing the cell expansion and cuticle deposition which shows a linking function of stress to abiotic stress and cell wall modifications (Cominelli et al., 2008).
2.23 GENE EXPRESSION TRIGGERED BY NAC TRANSCRIPTION FACTOR
Another group of proteins known as NAC proteins are not only responsible for regulating the diverse processes such as development, defense, and biotic stress responses (Olsen et al., 2005; Hongbo et al., 2015) but they also play an important role in tolerating abiotic stresses including drought and salinity. Tran and his colleagues in 2007 demonstrated evidence of transcriptional factor families being involved in cooperative regulation of stress responses (Tran et al., 2007) describing a specific interaction and co-function between ZFHD1 and a NAC factor.
NAC-type (OsNAC5) is another abiotic stress responsive transcriptional factor responsible for controlling stress-inducible and -tolerant genes in rice plants (Takasaki, 24
2010). One of the major transcriptional factor families, NAC (NAM, ATAF, and CUC) is found only in plants. The N terminal of NAC protein contains highly conserved DNA- binding domain and is best characterized protein in this family while the C-terminal region of NAC proteins involves the highly diversified activation domain in both length and sequence (Ooka et al., 2003).
Figure 3: Drought responsive pathways in plants
Drought commonly induces endogenous ABA production by modulating expression of ABA biosynthesis genes (Blue rectangle). The ABA-dependent pathway is indicated by red arrows and three ABA independent pathways are indicated by purple arrows. Transcription factors (TFs) including AREB/ABFs, MYB2, MYC2, RD26(NAC) and CBF4 are induced by ABA and bind to their corresponding cis-acting elements ABRE, MYB, MYC, NAC and DRE/CRT, respectively. TFs of ABAindependent pathway include ZFHD, DREB2 and NAC(RD26). RD26 is induced through both ABA-dependent and ABA-independent pathways. DREB2 and AREB/ABF are activated by protein phosphorylation. (Adapted from Hirayama and Shinozaki, 2010; Seki et al., 2007).
2.24 DROUGHT STRESS INFLUENCES ON GAS EXCHANGE PARAMETERS
Under water stress conditions, the leaf transpiration gets reduced that represents a physiological indicator associated with stomatal transpiration and cuticular transpiration (Osmond et al., 1987). Under water stress conditions, many factors affect the stomatal 25 transpiration (TRst), for example stomatal conductance, and cuticular transpiration (TR cu) that includes leaf surface characters such as wax layer thickness and morphological structure (Richards et al., 1986).
The guard cells play a key role in closing and opening of stomata. This phenomenon takes place by 2 ways including hydropassive closure that deals with direct water loss from guard cells while the other way is called hydroactive closure, which defines the water loss from whole leaf. The root system is also considered to be responsible for stomatal response under the conditions of water stress. Several studies (Ackerson, 1980; Hartung et al., 1998; Schroeder et al., 2001; Borel and Simonneau, 2002) have investigated the stomatal closure under drought stress and it has been found that transportation of ABA concentration from the root to shoot and then perceived at the apoplast of guard cell may also be a key factor .
The severe conditions of water deficiency determine the stomatal limitations with respect to photosynthesis. After a low water stress, considerable changes occur in photosynthetic reactions (Cornic and Briantais, 1991). Under drought conditions, the water loss is controlled by stomata, which is actually a first event of plant response that in turn affects carbon uptake by leaves (Cornic and Massacci, 1996). Stomata closure involves mzaqany factors including a decline in leaf turgor or water potential and low humid atmosphere (Maroco et al., 1997). Also there is a specific link between stomatal responses, moisture contents of the soil and the leaf water status. The stomatal responses are connected with chemical signals (e.g. ABA) that are created by water deficient roots (Davies and Zang, 1991). Several changes occur in carbon metabolism of cell in the earliest phase of dehydration process as described by Lawlor (2002). The functioning of stomata is controlled by drought-tolerant species, which is an essential step to fix carbon under stress conditions. This in turn improves water use efficiency, and/or in case of any improvement in water deficient conditions, the stomatal opening maintains the physiological processes.
This phenomenon of stomatal closure usually takes place under drought stress. However, in some cases of severe stress, the process of photosynthesis is more controlled by the capacity of chloroplast to fix CO2 than by its high resistance to diffusion (Faver et al., 1996, Herppich and Peckmann, 1997). This indicates that stomatal closure takes place before 26
inhibition of photosynthesis and at the same time it reduces the availability of CO2 to chloroplast to assimilate.
The oxidation-reduction cycles during photosynthesis provide an important source of electron sink for photosynthetic activity under mild drought (Cornic and Fresneau, 2002). Also the process of photosynthesis is not changed quantitatively under desiccation. The opening and closing mechanism of stomata in dry conditions results in the diminishing of
CO2 molar fraction in the leaf chloroplasts consequently in C3 plants with an increase in RuBP oxygenation and therefore attains the form of main sink for photosynthetic electrons.
In place of CO2, the O2 through photorespiratory activity may act as an electron acceptor but that depends on prevailing photon flux density (PFD). The duration of drought also has an impact on photosynthetic activity. A drought with long-term duration reduces the water contents resulting in diminished photosynthetic activity. The effect of different environmental stresses such as heat, drought and strong light was investigated by Havaux in 1992 to study the change in photosynthetic activity. The stresses were applied both separately and in combination and established a marked antagonism between water deficiency and HT, proving that water deficit conditions may increase the resistance of photosystem (PSII) to stresses such as heat and strong light. Several studies have demonstrated the impact of drought stress on decline in photosynthetic activity owing to stomatal or non-stomatal reasons (Del Blanco et al., 2000; Samarah et al., 2009). The cellular membranes ensure maintainance of cell integrity, by channelizing the processes of signal transduction and ion homeostasis in response to environmental stresses (Kaur and Gupta. 2005; Tuteja and Sopory. 2008) and as a consequence, a series of evident changes occurs in the cellular membranes of organelle (Dionisio-Sese et al., 1999; Wahid et al., 2007). Lipid peroxidation takes place during high temperature that damages the membrane (Bhattacharjee and Mukherjee, 1998) resulting in the more permeability of ions (Wen-yue et al., 2001). By measuring the quantity of ion leakage the scale of stress damage can be assessed indicating the harshness of existing stress (Foyer et al., 1997). A severe heat shock may result in the denaturation of membrane protein and also at the same time it may cause the unsaturation of fatty acids, resulting in the rupturing of membrane to cause an increased loss of cellular solutes (Savchenko et al., 2002). 27
2.25 EFFECTS OF DROUGHT STRESS ON PLANT WATER RELATIONS
Many factors determine the plant water relations including relative water content (RWC), leaf water potential, stomatal resistance, rate of transpiration, leaf temperature and canopy temperature. Relative water contents, an important index that provides the information regarding the water status, determines the metabolic activity of the tissues and therefore can be used to assess the dehydration tolerance. Under drought stress conditions, relative water contents exhibit a declining trend and this phenomena is found in almost all varieties of plants as studied by Nayyar and Gupta (2006) and they have found that the leaves exhibit a decreased RWC and water potential when they are exposed to drought conditions. In another study (Siddique et al., 2001), a substantial decline in leaf water potential, RWC and transpiration rate with an increase in the leaf temperature when plants are subjected to drought was found. High temperature and decline in humidity may cause water deficiency in plants. Another important factor that causes an acute water deficiency is the movement of dry air mass into the environment. As a consequence of these changes in the environment, vapor pressure gradient increased between leaf and air, resulting in an increased transpiration rate. Also an increase in water loss is found from the soil under high vapor pressure gradient. Apart from the stomatal impact, there are other indicators of drought resistance that include relative water content (RWC) and the rate of water loss from excised leaf, which are simple and more reliable indicators in cotton (Quisenberry et al., 1982). The plants adapted to dry land possess RWC with low rate of excised leaf water loss, indicating that both factors are involved in maintaining leaf water during water deficiency.
2.26 ROLE OF BIOCHEMICAL MARKERS IN RESPONSE TO DROUGHT STRESS
Drought spans occur in different parts of the world every year, leaving behind many devastating effects on crop sustainability and production (Ludlow and Muchow, 1990). There are several metabolites that are produced in response to drought and many other abiotic stresses in cellular components such as proline, beta glycine, sugars and MDA to decrease the effect of drought stress on plant functionality (Wang et al., 2003). Proline accumulation in various crops has been considered as marker or parameter for the selection of crop resistant to abiotic stresses. Proline synthesis takes place in response to multiple stresses like 28 temperature, starvation and drought (Sairam et al., 2002). Drought induces low water potential in the plants and proline plays a major role in helping the plant to withstand water stressed conditions. Another role of these osmolytes involved the triggering of several other regulatory pathways that help in plant survival under adverse environment within the organism (Kumar et al., 2003).
Proline and glycine betaine (GB) are two types of osmolytes that are produced in most of the plant species when subjected to environmental stresses such as drought, salinity and UV radiation etc. There are controversial aspects about their exact roles in osmo- tolerance of plants, however it is thought that both compounds not only impart positive impacts on enzyme and membrane integrity but also they play their role to mediate the osmotic adjustment in plants when subjected to stress conditions. Also a lot of work has been done to determine the presence of a positive relationship between plant tolerance subjected to stress and accumulation of GB and proline. Some scientists have emphasized that the high concentration of GB and proline is not an adaptive response to stress but actually a product of stress (Ashraf and Foolad, 2007). In an attempt transgenes specific for the production of GB and proline were genetically engineered in 19 plants. The plants when subjected to stress were unable to produce sufficient amounts of these compounds to minimize the stress effects. However, an alternative approach called as shotgun was adopted whereby proline and GB were applied exogenously to plants subjected to stress and it gained a considerable attention.
The beneficial aspects of proline include mediation of mitochondrial functions by functioning as signaling molecule, cell proliferation or cell death impacts the initiation of a particular gene expression, thereby helping the plant to recover from stress (Szabados and Savoure´, 2009). Production of proline, in many plant species exposed to stress, has been linked with stress tolerance, and it has been shown that its concentration is higher in stress- tolerant plants as compared to stress-sensitive plants. It has an effect on protein solvation and preserves the quaternary structure of complex proteins, maintains membrane integrity under dehydration stress and inhibits the oxidation of lipid membranes or photo-inhibition (Demiral and Turkan, 2004).
The abiotic stress also affects the carbon metabolism and synthesis of specific sugars, 29 starch, sucrose and other soluble sugar contents. At the same time, sucrose-based metabolism may replace starch-based metabolism as starch synthesis and degradation is more affected in comparison to sucrose synthesis (Silva and Arrabaça, 2004). Trehalose, a non-reducing sugar, is found in many bacteria, fungi and in few higher plants tolerant to desiccation. It is believed that trehalose protects the biomolecules when subjected to environmental stress, as it possess the reversible water-absorption capacity that in turn prevents the bio molecules from the damage induced by the desiccation. The transgenic plants are the best example of particular trehalase activity exhibition. The low trehalose level in these plants is due to degradation of trehalase by trehalase activity, suggesting an increase in trehalase level by declining the trehalase activity (Penna, 2003). Mannitol is another sugar that is also produced in response to salt and water stress and can thus reduce the impact of abiotic stress.
Several compounds produced during this process play a major role in maintaining the osmotic equilibrium, membrane and other macromolecules protection. Mannitol glutamate, sucrose, fructans, trehalose sorbitol, oligosaccharides, polyols and inorganic ions like K+ are some of the compounds. These compounds help the plants to maintain their hydrated state by increasing the plant resistance against the adverse effects of dehydration (Hoekstra et al., 2001). The hydrophilic interaction with the lipid and protein macromolecules of the membranes is maintained by alcoholic sugars, for example mannitol, involving the substitution of their OH group with the hydroxyl group of water thereby maintaining the integrity of membranes. Another important feature about the accumulated solutes is that they do not interfere with the normal metabolic processes of the cell. There is a change in the carbohydrate status of the leaf that might trigger a metabolic signal while responding to a stress situation (Jang and Sheen, 1997). While even under normal water deficit conditions, there is an enormous inhibition in starch synthesis (Chaves, 1991), an increasing trend is generally found in soluble sugar concentration under a stress condition (Pinheiro etal 2001). Recently it has been reported that the plant leaves under stressed conditions, produce invertase to deal with the accumulated amount of simple sugars like glucose and fructose (Trouverie et al., 2003). The solutes for example betaines, proline and ectoine are produced in plants in response to different environmental stresses (Rontein et al. 2002). The very first compound produced by the plants when subjected under water deficit stress is proline that helps to protect the cells from injury. Similarly it has been found that the maize plant when 30 exposed to progressive drought stress, produced a considerable amount of proline. The proline contents reached maximum when soybean plants were exposed to progressive drought stress of 10 days and then decreased after 15 days of severe stress (Anjum et al., 2011b).
The defense mechanism of cell can also be activated by proline produced in response to heat, drought and salinity stresses by inducing a gene expression that would not be expressed under normal conditions (Morimoto, 1993; Feder, 2006). In short the specific response to various stresses is expressed in almost all living beings at the molecular level, specifically the abrupt change in genotypic expression results in enhanced production of protein groups, called as „„heat-shock proteins‟‟ and „„Stress-induced proteins‟‟ or „„Stress proteins‟‟ (Morimoto et al., 1994; Gupta et al., 2010). Almost all types of stresses channelize the gene expression and produce heat-shock proteins in cells that are exposed to stress (De Maio, 1999). In Arabidopsis and other plant species desiccation, oxidative, low temperature, high intensity irradiations, osmotic, salinity, wounding, and heavy metals stresses were found to activate the synthesis of stress proteins (Swindell et al., 2007). However, the important events of metabolic processes such as DNA replication, transcription, mRNA export and translation etc are stopped immediately in the presence of these stressing agents (Biamonti and Caceres, 2009). It is suggested that stress proteins play a role to act as molecular chaperones that is involved in regulating the folding and proteins accumulation as well as localization and degradation in all plants and animal species (Feder and Hofmann, 1999; Panaretou and Zhai, 2008; Hu et al., 2009; Gupta et al., 2010). These chaperones proteins resist the irreversible aggregation of some other proteins and take part in protein refolding during stress conditions (Tripp et al., 2009). It was found that a decrease in protein means an increased breakdown or decreased synthesis that result in an increased level of free amino acid production (Navari-Izzo et al., 1990). Stewart & Larher (1980) had found production of free amino acids in water deficit conditions, resulting in dynamic adjustment of N metabolism.
Biochemical studies have demonstrated that in response to abiotic stress conditions, chemical compounds like praline-types sugars, proline and polyols are produced via osmotic adjustment (osmotically-active metabolites or osmolytes) (Bohnert et al., 1995). 31
Accumulated osmolytes protect biological proteins and membranes and also act as scavengers of intermediates of reactive oxygen.
2.27 ROLE OF MOLECULAR BIOLOGY IN PRESENT ERA
Functional genomics includes transcriptional profiling by using mutants and transgenics to determine the gene functions, involving multiple techniques (Vij and Tyagi, 2007). Study of gene functioning requires the determination of gene sequences, expressed sequence tags (ESTs) and molecular markers. Transcriptomics, proteomics and metabolomics are 3 different branches of functional genomics. Transcriptomics deals with the study of generating the gene expression profiles of an organism and its analysis under a specific treatment of biotic or abiotic stress. Similarly, proteomics and metabolomics deal with the global expression profiling of the proteins or metabolites, respectively under a specific stress treatment. Numerous molecular tools such as microarrays, serial analysis of gene expression (SAGE), massively parallel signature sequencing (MPSS), two-dimensional gel electrophoresis (2DGE), matrix-associated laser desorption/ionisation time-of-flight (MALDI-TOF), or yeast two-hybrid expression are different molecular techniques that are involved in the expression profiling of protein and gene. Microarray is a high throughput technique that is used to study the global gene expression profiling, helping the scientists to make a parellel study of all the genes of an organism (Wang et al., 2003a). This expression profile is produced through hybridization by using probes that are obtained from gene sequences or ESTs, immobilised on a solid surface (Chen et al., 1998).
In the most modern era of molecular biology, novel genes have been utilized in plant breeding and that has attracted the interest of scientists. ESTs are small DNA molecules ranging about 300-500bp and are produced by reverse transcription of cellular mRNA population (Mackill, 2007). They can be generated by randomly selecting cDNA clones by single pass sequencing thus making it possible to have an efficient and rapid means to identify novel genes. EST‟s are excellent source of information about expressed genes and therefore help discover the genes at large scale (Xu et al., 2008). The functions of these new cDNA clones can be achieved by adopting comparative genomic approaches (Velculescu et 32 al., 1995) making a specific tool to have better information of plant genome structure, gene expression and gene function (Mohammadi et al., 2007).
33
3. MATERIALS AND METHODS
3.1 PLANT MATERIAL AND DROUGHT TREATMENT
Progeny of Agave sisalana plants was developed in the green house from the young saplings of already grown Agave plants taken from local nursery (Figure 4). Young saplings of agave plants were transplanted in composite soil (peat, sand, soil, 1:1:1) in mud pots placed in green house at temperature 25±2°C and relative humidity approximately 45-50%. Metal halide illumination lamps (400V) were used to supplement natural radiation. Light radiation reached a maximum of 1,500µmol m2s-1 at the top of canopy at mid day. The volume of water added to the pots was calculated periodically to maintain the pots of stressed treatments at 10 and 2% gravimetric humidity (GH) and non-stressed treatments at 80% GH. The volume of water added to plants was calculated periodically to maintain the field capacity of the planted mud pots (Maqbool et. al, 2008). After six months of plants development, irrigation was withheld at 10 and 2% FC to drought stress the plants for 70 days. Control plants were irrigated normally. Completely randomized design (CRD) with four replications of each experimental unit was used.
Figure 4: Progeny of Agave sisalana L.plants developed in CEMB 34
3.2 DETERMINATION OF FIELD CAPACITY
For the determination of field capacity, three samples of 100 g each of the soil used in the experiment were taken at the time of filling of the pots. These samples were then incubated at 105 ºC for 24 h. These oven-dried samples were weighed and averaged for the determination of the total moisture contents of the soil at the time of sowing of the young plantings. Then the saturation percentage of the three soil samples was estimated. 100 g each of this oven-dried soil was approximated by measuring and then averaging the distilled water used in making complete saturated paste of the three samples. The field capacity was determined by using the following formula:
Field Capacity= Saturation percentage/2
Since the weight of each pot along with soil and moisture contents there in at the time of sowing were already known, therefore the weight of each pot containing moisture contents equal to 10% and 2% field capacity was calculated which represented the drought treatment (figure 5).
Figure 5: Agave sisalana L. plants under drought stress 35
3.3 MICROSCOPIC EXAMINATION OF LEAF EPIDERMAL TISSUE
Microscopic glass slides were prepared for control (non stressed), 10 and 2% FC drought stressed plants by peeling or scraping off the epidermal layer and mounting it on microscope slide according to the method of Prat (1948). Data was recorded with respect to cell arrangement, size and shape of stoma with a scanning electron microscope at 10X.
3.4 PLANTS PHYSIOLOGICAL ANALYSIS UNDER DROUGHT STRESS
Physiological analyses of Agave sisalana plants were determined with IRGA (infrared gas analyzer) (model, LCA-4; Analytical Development Company, Hoddesdon, England). leaf chamber was placed on the top of agave sisalana leaves. All these observations were recorded at 14.30-15.30 hours mid-day around under sunshine.
During data recording, leaf chamber molar gas flow rate was 248 µmol s-1, ambient -1 CO2 conc. (Cref) was 352 µmol mol , temperature of leaf chamber (Tch) varied from 32.3 to 35.7 °C, ambient pressure (P) was 98.01 kPa, molar flow of air/leaf area was 221.06 mol m-2 s-1, PAR was maximum up to 890 µmol m-2 s-1 and leaf chamber volume gas flow rate (v) was 300 mL/min. Observations recorded for non stressed control plants were immediately followed by that of the same cultivar under drought stress.
3.5 WATER RELATED ATTRIBUTES AND LEAF SURFACE AREA
3.5.1 Leaf Relative Water Content (LRWC)
The relative water content (RWC) of control, 10% and 2% FC drought stressed plants was measured according to the method described by Barrs and Weatherley (1962). A fully developed and young leaf from each plant was taken and fresh weight of each leaf was recorded. All the samples were immersed in distilled water for 12 h and weight of each turgid leaf was recorded. Then all the samples were oven dried at 70°C for measuring dry weights. Then RWC (relative water content) was calculated using the following equation:
Relative water content (%) = Leaf fresh weight - Leaf dry weight × 100 / Leaf turgid weight - Leaf dry weight 36
3.5.2 Leaf Surface Area
Total leaf area of control and stressed plants was measured with digital photographs with default parameters (Figure 6). Data was finally analyzed through Image J Software as reported by Igathinathane et al. (2008).
Figure 6: Samples of control and drought stressed leaves of Agave sisalana L.
3.6 PLANTS BIOCHEMICAL ANALYSIS UNDER DROUGHT STRESS
3.6.1 Proline Content
Proline test was carried out according to the method of Bates et al. (1973). The leaves of Agave sisalana L. weighing 0.5 g each from control and drought stressed plants were homogenized in 10 ml of 3 % sulfo-salicylic acid. The homogenate was filtered through Wattman filter paper (No. 2). Two ml of the filtrate was made to react with 2 ml acid ninhydrin solution (1.25 g ninhydrin in 30 ml glacial acetic acid and 20 ml of 6 M orthphosphoric acid and 2 ml of glacial acetic acid in a test tube for 1 hr at 100 oC). The reaction was terminated in an ice bath. The reaction mixture was extracted with 4 ml toluene, mixed vigorously by passing a continuous stream of air for 1-2 minutes. The chromophore containing toluene was aspirated from the aqueous phase, warmed at room temperature and 37 the absorbance was read at 520 nm using toluene as a blank. The proline concentration was determined from a standard curve using 0-100µg L- proline (sigma).
3.6.2 Lipid Peroxidation Assay (Malondialdehyde Content)
Malondialdehyde (MDA) level, often used as an index for lipid peroxidation, was also measured. MDA levels were assayed according to the method described by Quan (2004). Agave leaves of stressed and non-stressed plants were homogenized in 5 ml of 10% trichloroacetic acid (TCA) and centrifuged at 12,000g for 10 min. Two ml of clear supernatant was added to 4 ml of 0.6% thiobarbituric acid (in 10% TCA). The reaction was terminated at room temperature and the reaction mixture was centrifuged at 12,000 g for 10 min after which the absorbance of the supernatant at 450, 532 and 600 nm was determined with a spectrometer, respectively. The concentration of MDA was calculated by the following formula: C (µmol l 1) = 6.45(OD532-OD600)-0.56OD450
3.6.3 Total Chlorophyll Content
The photosynthetic pigments (chlorophyll a and b) were determined according to method of Arnon and Whatley (1949). Chlorophyll extract was prepared from 100 mg fresh leaves by grinding in 10 ml of 80% acetone. The homogenate was left overnight at room temperature. The absorbance of the extract was read at 663 nm and 645nm. The concentration of chlorophyll a, b and total chlorophyll (mg/g fresh weight) was calculated using Arnon‟s equations.
Chlorophyll a = 12.7 (OD663) - 2.6 (OD645) × ml acetone/mg leaf tissue
Chlorophyll b = 22.9 (OD645) - 4.7(OD663) × ml acetone/mg leaf tissue
Total Chlorophyll = Chlorophyll a + Chlorophyll b
3.7 STATISTICAL ANALYSIS
Statistical analysis of the results was performed with STATISTIX V 9.0 (Analytical software Tallahassee, USA) freely available online. The data were subjected to analyses of 38 variance (ANOVA) procedure for a complete randomized design. The least significant difference (LSD) test (at 95% confidence level) was done to compare the means (Steel et al., 1997).
3.8 TOTAL RNA ISOLATION
Six months old young plants of Agave sisalana were kept without water for seventy days. Epidermis tissue was isolated from the leaves of control and stressed plants and quickly immersed in liquid N2. Total RNA was extracted by the method described by Jakola et al. (2001) with some modifications. The leaves were cut and the epidermis peeled off was ground into a fine powder in a pre-cooled mortar and transferred to a falcon tube (50mL). RNA extraction buffer (Appendix-I) was preheated to 70ºC. Extraction buffer (15ml) containing 1g of fine powder was vortexed for two minutes followed by incubation at 70ºC for 20 minutes. The tubes were vortexed after every 5 min and finally centrifuged at 5,000g for 5 minutes at 4ºC. The supernatant was shifted to 1.5mL tube and centrifuged at 13,000 rpm for 20 min at 4ºC. Supernatant was transferred to new 1.5mL tubes and extracted twice with an equal volume of Chloroform: isoamyl alcohol (24:1). Phases were separated at 13,000rpm at room temperature. To the aqueous phase supernatant 1/4 volume of 10M Lithium Chloride solution was added and mixed gently. RNA was precipitated overnight at 4 ºC. The tubes were centrifuged at 13,000rpm for 20 min at 4ºC. The pellet was washed with 500ul of 70% ice cold ethanol. After airdrying, the pellet was dissolved in 100ul of pre- heated (65 ºC) SSTE buffer (Appendix-II). Tubes were combined in a single tube. The contents of tubes were extracted once with an equal volume of acidic Phenol: Chloroform: isoamyl alcohol (25:24:1). To the supernatant two volume of ice cold absolute ethanol was added and icubated at -20 ºC overnight to precipitate RNA. The tubes were centrifuged at 13,000rpm for 25 min at 4ºC. The pellet was washed with 500ul of 70% ice cold ethanol, air- dried and re-suspended in DEPC-treated deionized water.
3.8.1 Agarose Gel Electrophoresis
Agarose gel electrophoresis was used to check integrity of RNA. Agarose gel of 0.9% was prepared in 0.5XTAE buffer (Appendix III) with the addition of 0.5-1µg/ml of 39
Ethidium bromide. Gel was run at 70V for 1 hour and visualized with the help of Gel documentation system using software GrabIt.
3.8.2 Quantification of Total RNA
RNA conc. was measured with Nanodrop-ND-1000 (NanoDrop Technologies, Inc), spectrophotometer using the nucleic acid program. 1.5µl DEPC treated deionized water was taken as blank. 1.5µl of RNA was measured and results were taken at A260/280 and A260/230.
3.8.3 DNase Treatment
The DNA contamination from RNA was removed with the help of Ambion‟s DNAfree™ Kit. 0.1 volume of 10X DNase 1 Buffer and 1 µl of DNase 1 (2 units) was added to the RNA and incubated at 37°C for 30min. 0.1 volume of DNase Inactivation Reagent was added to the sample and incubated for 2 min at room temp. The tube was flicked once more during the incubation to re-disperse the DNase Inactivation Reagent. The tube was centrifuge at 10,000 x g for ~1 min to pellet the DNase Inactivation Reagent. The supernatant was taken in a new tube.
3.9 CONSTRUCTION OF cDNA LIBRARY
3.9.1 Isolation of mRNA From Total RNA
The mRNA was isolated from total RNA using the Oligotex mRNA minikit (Qiagen). For this purpose, 650µg of total RNA was taken in 1.5ml tube and its volume was made upto 500µl with RNase-free water. To completely homogenize the RNA, tube was heated for 3 min at 60°C followed by vortexing for 5 sec and sharply flicking the tube. This process was repeated twice. The tube was placed on ice and 500µl of Buffer (OBB) was added followed by the addition of 50µl Oligotex Suspension and kept at 37°C. Contents of the tube were thoroughly mixed by gentle pipetting. The sample was incubated for 3 min at 70°C in a water bath to disrupt secondary structures of RNA. After 3 min, sample was removed from the water bath and placed at 30°C for 10 min to hybridize poly-A tail of the mRNA to oligo dT30 of the Oligotex particle. Oligotex-mRNA complex was pelleted down by centrifugation 40 for 2 min at maximum speed (13,200 rpm), and the supernatant was carefully removed by pipetting. Approximately 50 µl of the supernatant was left in the microcentrifuge tube to avoid the loss of the Oligotex resin. Oligotex mRNA pellet was resuspended in 400 µl Buffer OW2 by pipetting and loaded onto a small spin column placed in a 1.5 ml microcentrifuge tube. Column was centrifuged for 1 min at 13,200 rpm. After centrifugation the spin column was transferred to a new RNase-free 1.5 ml microcentrifuge tube and washed with 400 µl Buffer (OW2) for 1 min at maximum speed and the flow-through was discarded. Spin column was transferred to a new RNase-free 1.5 ml microcentrifuge tube and 100 µl hot (70°C) Buffer OEB was loaded onto the column. The resin was resuspended 3-4 times by pipetting and centrifuged for 1 min at 13,200 rpm. To get maximal yield, elution with buffer OEB was repeated once again. The mRNA isolated was kept on ice, quantified with the help of Nanodrop, ND-1000 (NanoDrop Technologies, Inc), spectrophotometer and was used for the construction of cDNA libraries.
3.9.2 Precipitation Of mRNA
The mRNA isolated from total RNA was precipitated by adding 2.5 volume absolute ethanol, 0.1 volume of 3M sodium acetate (pH 6.0) and incubated overnight at -20 ºC. Next day, the tubes were centrifuged at 13,200 rpm for 25 min at 4 ºC to pellet down mRNA followed by washing with 70% ethanol for 5 min. The pellet was air dried at room temperature and resuspended in 10 µl of RNase-free water. This mRNA was used for first strand cDNA synthesis.
3.9.3 Double Strand cDNA Construction
For the construction of cDNA libraries “CloneMinerTM cDNA library Construction Kit” (Invitrogen) was used with minor modifications. mRNA isolated in the previous step was used for first strand cDNA synthesis as following: mRNA + DEPC-treated water 11 µl
Biotin-attB2-Oligo(dT) Primer (30 pmol/µl) 1 µl
10 mM (each) dNTPs 1 µl 41
The contents were mixed gently by pipetting and centrifuged for 2 seconds to collect the sample. The mixture was incubated at 65°C for 5 minutes and cooled to 45°C for 2 minutes and the following reagents were added in a fresh tube:
5X First Strand Buffer 4 µl
0.1 M DTT 2 µl
The contents were mixed gently by pipetting and centrifuged for 2 seconds to collect the sample. After the priming reaction was cooled to 45°C for 2 minutes, the above mixture was added to the priming reaction tube, mixed gently and incubated at 45°C for 2 minutes. After keeping the tube in thermal cycler for 2 minutes, 1 µl of SuperScript II RT (200 U/µl) was added and the whole contents were incubated at 45°C for 60 minutes. After the completion of incubation the first strand reaction was processed immediately for the second strand synthesis.
The tube containing the first strand cDNA was kept on ice and the following reagents were added:
DEPC-treated water 91 µl
5X Second Strand Buffer 30 µl
10 mM (each) dNTPs 3 µl
E. coli DNA Ligase (10 U/µl) 1 µl
E. coli DNA polymerase I (10 U/µl) 4 µl
E. coli RNase H (2 U/µl) 1 µl
Total volume 150 µl
The contents were mixed gently by pipetting and centrifuged for 2 seconds to collect the sample. The mixture was incubated at 16°C for 2 hours. After the completion of incubation, 2 µl of T4 DNA Polymerase was added to create blunt-ended cDNA. Contents were mixed gently by pipetting, centrifuge for 2 seconds to collect the sample and incubated 42 at 16°C for 5 minutes. After 5 minutes 10 µl of 0.5 M EDTA (pH 8.0) was added to stop the reaction and the reaction was preceded to Phenol/Chloroform Extraction. 160 µl of phenol:chloroform:isoamyl alcohol (25:24:1) was added, mixed well for approximately 30 seconds and centrifuged at room temperature for 5 minutes at 14,000 rpm. Upper aqueous phase was transferred to fresh 1.5 ml tube and was ethanol precipitated as following:
Glycogen (20 µg/µl) 1 µl
7.5 M NH4OAc 80 µl
100% ethanol 600 µl
The tube was inverted several times to mix the contents and incubated at -80°C for 10 minutes. After 10 minutes the sample was centrifuged at 4°C for 25 minutes at 14,000 rpm followed by washing with 70% ethanol for 5 minutes at 14,000 rpm. The cDNA pellet was dried in speedVac for 2 min and resuspended in 18 µl DEPC-treated water by pipetting up and down 30-40 times. The tube was centrifuged for 2 seconds to collect the sample and placed on ice to proceed with ligation attB1 Adapter.
3.9.4 Ligating attB1 Adapter
The blunt ended double strand cDNA was kept on ice and the following reagents were added:
5X Adapter Buffer 10 µl
attB1 Adapter (1 µg/µl) 10 µl
0.1 M DTT 7 µl
T4 DNA Ligase (1 U/µl) 5 µl
Total volume 50 µl
The contents were gently mixed by pipetting and the mixture was incubated at 16°C for 24 hours. 43
3.9.5 cDNA Size Selection
The adapter ligated cDNA was subjected to size selection by gel electrophoresis. 1% agarose gel was prepared in 0.5 X TAE buffer with the addition of 0.5µg/ml ethidium bromide. cDNA was loaded in the agarose gel with 1Kb ladder on both sides leaving one slot empty. Gel was run at 80 volts for 25 minutes. It was visualized on UV transilluminator and gel slice containing cDNA ≥ 200 bp was excised. This excised gel slice was used to elute cDNA from the gel.
3.9.6 Gel Elution
The dscDNA from the gel was eluted through Fermentas DNA Gel Extraction Kit, one volume of excised gel slice and three volumes of binding solution was added and incubated for 5 minutes at 55°C to dissolve agarose. Then re-suspended silica powder suspension was added upto 2µl/1µg of DNA and incubated for 5 minutes at 55°C and mixed by vortexing every 2min to keep silica powder in suspension. After incubation, silica powder/DNA complex was spun for 5 seconds to form a pellet and supernatant was removed. The pellet was washed three times with 500 µl of ice cold wash buffer. During each washing the pellet was re-suspended completely. After the last washing the pellet was air-dried for 10- 15 min.
To elute DNA into water, the pellet was re-suspended in 20µl of sterile deionized water and the tube was incubated at 55°C for 5 minutes. After spinning the tube, supernatant was taken into a new tube avoiding the pellet. The elution was repeated with another 20 µl of water. For the removal of small amounts of the silica powder, the tube was spun again for 30 sec at max. speed and the supernatant was shifted into a new tube. The eluted cDNA was quantified using nanodrop, ND-1000 (NanoDrop Technologies, Inc), and was used for BP (attB flanked cDNA + attP containing vector pDONRTM 222) recombinant reaction.
3.9.7 BP Recombination Reaction
For the BP recombination reaction 100 ng size cDNA was used in the following reaction: attB1-flanked cDNA + TE Buffer pH 8.0 7 µl 44 pDONRTM 222 (250 ng/µl) 1 µl
5X BP Clonase Reaction Buffer 2 µl
BP Clonase enzyme mix was removed from -80°C, thawed on ice and vortexed briefly. 3µl of BP Clonase enzyme was added to reaction mix and the mix was incubated at 25oC for 20 hours. After the completion of incubation 2 µl of proteinase K was added to reaction mix to inactivate BP Clonase and the reaction mix was incubated at 37oC for 15 minutes followed by 75oC for 10 minutes. Following reagents were added to 1.5ml tube in following order:
Sterile water 90 µl
Glycogen (20 µg/µl) 1 µl
7.5 M NH4OAc 50 µl
100% ethanol 375 µl
The tube was inverted several times to mix the contents and incubated at -80°C for 10 minutes. After 10 minutes sample was centrifuged at 4°C for 25 minutes at 14,000 rpm followed by washing with 70% ethanol for 5 minutes at 14,000 rpm. The cDNA pellet was dried in Vacuum concentrator for 2 min and resuspended in 9 µl TE buffer (Appendix IV). Six aliquots of the resuspended cDNA were made in six new 1.5 ml tubes by adding 1.5 µl cDNA in each tube followed by the addition of 50 µl thawed ElectroMAXTM DH10BTM competent cells added to each tube. The contents were mixed gently by pipetting up and down twice in a way that no air bubble gets introduced in the tubes. The entire contents of the tube were transferred to a cold cuvette (0.1 cm). Gentle tapping was done for even distribution of contents and electroporation was done under following conditions:
Voltage 2.0 kV
Resistance 200 Ω
Capacity 25 µF 45
One ml of SOC medium was added to the chilled cuvette containing electroporated cells and entire solution was transferred to 15ml snapcap tube. Same procedure of electroporation was repeated to all the six aliquots. The electroporated cells were shaken for 1 hour at 37°C at 250 rpm to allow expression of the kanamycin resistance marker. After the one-hour incubation at 37°C, all cells were pooled into a 15 ml snap-cap tube and an equal volume of sterile freezing media (60% SOC medium:40% glycerol) was added to it. Aliquots containing 200 µl of the cDNA library were made and stored at -80°C. Five (5) and fifteen (15) µl volume from cDNA library was spread on LB plates containing 50µg/ml Kanamycin. The plates were incubated at 37ºC for overnight. Colonies on each plate were counted after overnight incubation at 37ºC. The cfu/ml for the cDNA library was calculated according to the following equation: cfu/ml = colonies on plate × dilution factor volume plated (ml)
Total cfu = average titer (cfu/ml) x total volume of cDNA library (ml)
3.10 SCREENING OF COLONIES ON MEDIA
Colonies were selected for further culturing and each colony was inoculated into 3 ml of LB-kana broth and incubated for overnight at 37°C with shaking at 250 rpm.
3.10.1 Plasmid Isolation
The alkaline lysis protocol of Birnboim and Doly (1979) with certain modifications was used for isolation of plasmid. Colonies were inoculated into 10 ml LB with Kana50 (50µg/ml) and incubated overnight at 37 ºC with 250 rpm. Overnight cultures were harvested at 13,000rpm for 1 minute. Pellet was resuspended in 200µl of soln.I (Appendix- V) and incubated on ice for 10 min. The cells were lysed by adding 200µl of freshly prepared soln.II (Appendix-VI) incubated at room temperature. Finally 200µl of soln.III (Appendix-VII) was added to the lysate, mixed thoroughly and kept on ice for 10 min. The tubes were centrifuged for 10 min. at 13000rpm. Supernatant was shifted in new tubes and extracted with equal volume of phenol: chloroform: isoamyl alcohol (25:24:1). Supernatant was taken carefully and ethanol precipitation was done. The pellet was washed with 70% ethanol, air dried and 46 dissolved in 20 µl sterilized water. The samples were treated with 1µl of 10mg/ml RNaseA (Sigma, Germany). Plasmid DNA was visualized on 1 percent agarose gel along with 1 kb ladder.
3.10.2 Restriction analysis of cloned cDNA
To confirm the cDNA library event, the recombinant plasmids were subjected to restriction digestion. To release the insert, 10U of BsrGI (Bsp14071) enzyme (Fermentas, Germany) was added along with the enzyme buffer supplied by the manufacturer to 25µg of isolated plasmid DNA. The pDONR 222 vector has BsrGI restriction site on either side of the inserted DNA fragment. The reaction mix was incubated at 37ºC for overnight. Recombinant plasmids and digested vector were analyzed and confirmed on 0.8% agarose gel.
3.11 PREPARATION OF cDNA MICROARRAY PLATFORM
3.11.1 Clone picking and culturing
For the picking of clones, aliquots of cDNA library containing ~1000-1500 clones were spread on LB Agar plates (245 x 245 x 18 mm). Individual clones were picked and used to culture in 96 well cultured plates containing LB-Kanamycin broth. The sealed plates were incubated over-night at 37 ºC in an incubator shaker at 250 rpm.
3.11.2 PCR amplification of inserts Twenty five µl of overnight grown culture was diluted in 50 µl water. Heat shock was given at 95 ºC for 5 minutes and spin at 3000rpm for 5 minutes at 4 ºC. PCR was performed to amplify insert within the clone with 5 µl of diluted culture as template DNA in 75 µl reaction mixture containing 0.8 µl M-13 forward and 0.8 µl M-13 reverse primers (10 µM)
(Table 01), 7.5 ul of 10X PCR buffer (200mM Tris-Cl, pH 8.8, 100 mM (NH4)2SO4 ,100mM
KCl, 20mM MgSO4, 1 mg/ml BSA and 1% Triton), 0.8 µl of 10 mM dNTPs and 2 unit of Pfu DNA polymerase. 47
3.11.3 Purification of PCR products prior to sequencing
Rest of the PCR product was ethanol precipitated by adding 2.5 volume absolute ethanol and 0.1 volume 3M sodium acetate (pH 6.0) and this mixture was incubated overnight at -20 oC.
Table 1: Sequence of primers used for colony PCR amplification.
Primer ID Sequence
M13Forward primer 5′-GTAAAACGACGGCCAG-3′
M13Reverse primer 5′-CAGGAAACAGCTATGAC-3′
Figure 7: Thermocycling profile for the amplification of inserts by cPCR
Thermocycling profile (Fig. 7) for amplification of ten thousand cDNA clones was used. 2 µl of each PCR amplified product was checked on 1.5% agarose gel in 0.5X TAE to confirm insert amplification. The plates were centrifuged at 4000 rpm for 30 min at 4ºC. The pellet was washed with 170 µl of 70% ice cold ethanol. After air drying the pellet was dissolved in 5 µl low Electrical conductivity (EC) water. DNA was quantified using 48
Nanodrop, ND-1000 (NanoDrop Technologies, Inc), and finally 500-1200ng/µl DNA concentration was obtained in low EC water.
3.12 CLONE SEQUENCING
After amplification, purification and precipitation, the PCR products of the inserts were used as a template for sequencing. Almost 200 clones, randomly selected, were sequenced with Dye terminator Chemistry on Applied Biosystems Sequencer model 3700. The following sequencing PCR program was used (Figure 8):
Figure 8: Thermocycling profile for the sequencing PCR
PCR products after sequencing reactions were precipitated with absolute ethanol. 20ul of absolute ethanol was added in the PCR-Product. The reactions were vortexed, mixed and left for precipitation at room temperature for 30 minutes. Centrifugation was done at 4,000rpm for 35 minutes at room temperature. The supernatant was discarded carefully. The pellets were washed with 20ul of 70% ethanol and air dried. Pellet was suspended in 15ul of formamide. The suspension was poured in 96-wells plate. The samples were denatured at 95°C for 5 minutes and quick chilled by placing in ice for ten minutes before loading on the ABI PRISM 3700 sequencer genetic analyzer according to the manufacturer‟s instructions given in technical manuals. Sequence was analyzed manually by using Bioedit software version (v 1.45). 49
3.13 REMOVAL OF VECTOR SEQUENCES USING VEC SCREEN
Analyzing the vector pDONRTM 222 map (Figure 9) showed that the sites of M13 primers were away from the insertion site of PCR- Product, so the sequence read with M13 primers contained additional sequences of vector along with the sequence of PCR-Product. Vector was screened both manually and NCBI‟s online software VecScreen (http://www.ncbi.nlm.nih.gov/VecScreen/VecScreen.html). The Vector sequences were removed and pure sequences were obtained.
3.14 BLAST SEARCH
The nucleotide sequence or the deduced amino acid sequence of each clone was compared with DNA, EST, and protein sequences from various databases by means of the Basic Local Alignment Search Tool (BLAST) to find the homology.
3.15 GENE ONTOLOGY (GO) AND FUNCTIONAL ANNOTATION
The gene code names (Atg) of Arabidopsis orthologs, identified by similarity search, were subjected to GO functional categorization at TAIR website (http://Arabidopsis.org/tools/bulk/go/index.jsp) on the basis of cellular components, molecular functions and biological processes. The genes annotation list and pie charts were saved.
3.16 PRINITNG OF cDNA MICROARRAY
The amplified insert cDNA was spotted on a glass slide of ArrayIt® brand SuperAmine 2 using a microspotter (microGrid610) made by Genomic Solutions®. The spots were made by nano-liters of volume in duplicate at an expected ratio of 9,408 spots per slide. Two Internal control, β-Actin and GAPDH were used as internal controls for the normalization of data. The clones were printed in a format of 14×14 sub-grids, leaving four (4) blank spots per sub-grid for background correction. Total 12×4 sub-grids were printed per slide with the help of solid pins (Genomic Solutions®). The slide printing conditions were 20±2 ºC and 45±2% humidity. After printing, slides were dried and stored in dark at room temperature for future use. 50
Figure 9: Map and features of pDONR 222 with site of PCR product 51
3.17 HYBRIDIZATION OF TARGET WITH cDNA MICROARRAY PLATFORM
3.17.1 Target preparation
3.17.1.1Aminoallyl labeling
For the aminoallyl labeling of cDNA, 45 µg of total RNA (DNA free), was taken from control and stressed Agave sisalana plant, and 2 µg of OligodT18 primer was added to it and final volume was made up to 18.0 µl with RNase-free water. The contents were mixed well and incubated at 70 ºC for 10 minutes. After incubation the mixture was placed on ice for 30 seconds, centrifuged and following contents were added:
5X First Strand buffer 6.0 µl
0.1 M DTT 3.0 µl
50X aminoallyl-dNTP mix 0.5 µl
SuperScript III RT (200U/µl) 2.0 µl
RNAse inhibitor 0.5 µl
The contents were mixed well, centrifuged briefly and incubated at 42 ºC for 3 hours. To hydrolyze RNA, 2U of RNAse H were added, mixed and incubated at 37 ºC for 15 minutes and mixed with 25µl of 1M Tris (pH 6.8) was added to neutralize pH (Figure 10).
Figure10: Thermocycling profile for cDNA synthesis 52
3.17.1.2 Removal Of Unincorporated aa-dUTP and Free Amines
The synthesized cDNA was mixed with 300 µl (5X reaction volume) buffer PB (Qiagen supplied) and transferred to QIAquick column placed in 2ml collection tube (Qiagen supplied), centrifuged at 13,000 rpm for 1 minute and flowthrough was discarded. 750µl phosphate wash buffer was added to the column, centrifuged at 13,000 rpm for 1 minute, flowthrough was discarded and wash step was repeated. Column was placed in new collection tube and centrifuged for 1 minute at 13,000 rpm. Column was transferred to a new 1.5 ml microfuge tube, 30 µl phosphate elution buffers were applied to the center of the column membrane and incubated for 1 minute at room temperature. cDNA was eluted by centrifugation at 13,000 rpm for 1 minute. Second elution was done in the same way and sample was dried in a speed vac.
3.17.1.3 Coupling aa-cDNA to Cyanine Dyeester
Single foil pack of dye cyanine (Cy)3/cyanine (Cy) 5 (Amersham- PA23001) was re- suspended in 40µl DMSO. Dry cDNA was dissolved in 5µl 0.1M sodium carbonate (pH 9.0) and 5 µl Cy3/Cy5 dye was added to the sample and mixed. The reaction was incubated for 1 hour in the dark at room temperature.
3.17.1.4 Removal of uncoupled dye
Dye coupled cDNA was mixed with 250 µl (5X reaction volume) buffer PB (Qiagen supplied) and transferred to QIAquick column placed in a 2ml collection tube (Qiagen supplied), centrifuged at 13,000 rpm for 1 minute and flowthrough was discarded. 750µl phosphate wash buffer was added to the column, centrifuged at 13,000 rpm for 1 minute, flowthrough was discarded and wash step was repeated. Column was placed in new collection tube and centrifuged for 1 minute at 13,000 rpm. Column was transferred to a new 1.5 ml microfuge tube, 40 µl elution buffer (EB) was applied to the center of the column membrane and incubated for 1 minute at room temperature. cDNA was eluted by centrifugation at 13,000 rpm for 1 minute. Same steps were repeated for elution of other samples. The concentration and the dye incorporation of labeled cDNA were measured by Nano Drop (NanoDrop Technologies, Inc), using program “Microarrays”. 53
3.17.2 Hybridization
3.17.2.1 Pre-Hybridization
Spotted slide was rehydrated by array facing down on water at 40 ºC. The slide was cross linked in a Stratagene® UV linker twice at 1600 µJ x 100. Slide was placed in pre- heated pre-hyb (Appendix VIII) buffer in 42 ºC water bath and incubated for 45 min with occasional shaking. Slide was washed in millipore water for two times, once in isopropanol and then spin-dried by keeping slide in 50 ml tube with kimwipe stuffed in the bottom in a swing bucket rotor at 2000 rpm for 1-2 min.
3.17.2.2 Hybridization
Equal concentrations of Cy3 and Cy5 probes (200 pmole each) in terms of dye pmoles were taken and mixed in the 2X hybridization buffer (Appendix IX). The target was heated to 95 ºC for three minutes and then immediately put on ice. Slide was placed in chamber of hybstation (Genomic Solutions®) with array side up. Target was injected to slide in chamber at 65 ºC and then the slide was incubated at 42 ºC for 30 hours.
3.17.2.3 Slide Washing
The slide was removed from hybstation and washed in solution containing 1X SSC, 0.2% SDS at 42 ºC for 2 min with agitation. Then, the slide was shifted to second wash solution containing 0.1X SSC, 0.2% SDS at room temperature and incubated for 2 min with agitation. After 2 min, the slide was moved to third wash solution containing 0.1X SSC and kept for 2 min with agitation. The slide was spin-dried immediately by keeping it in 50 ml tube with kimwipe stuffed in the bottom in a swing bucket rotor at 2000rpm for 1 min and proceeded for slide scan.
3.17.3 Slide Scanning
Slides were scanned in Cy3 and Cy5 channels with the help of scanner UC 4X4 (Genomic solution®). The 16-bit tiff images of Cy3 and Cy5 channels were saved.
54
3.18 IMAGES PROCESSING & RAW DATA GENERATION
The 16-bit scanned tiff images of Cy3 and Cy5 were initially analysed with the help of TIGER SPOTFINDER software available freely on-line from the TM4 website. Poor- quality spots (sum of median <500) were filtered from the raw data before analysis. Background was subtracted and the signal ratio between Cy3 and Cy5 was calculated. The initial/raw data was saved as mev file.
3.19 DATA NORMALIZATION & ANALYSIS
3.19.1 Data Normalization
The data normalization and analysis was done with the help of freely available software Microarray Data Analysis Software (MIDAS) and Microarray Experiment Viewer (MEV) from the TM4 website. Data normalization methods proceed from the assumption that only a relatively small proportion of the genes change significantly in expression level between the two hybridized mRNA samples. The house keeping gene GAPDH and β-Actin were used for the normalization of spot signal intensities within the slide. The signal intensity was calculated as the mean intensities of the two replicates minus the background signal. The MIDAS component of TM4 provides a number of data normalization methods and filters and supports applying them in a pipelined fashion.
3.19.2 The Midas Project
A MIDAS project was applied consisting of total intensity normalization, lowess (locally weighted scatterplot smoothing) normalization, standard deviation regularization, and low intensity filtering to microarray data. MIDAS default parameters were used throughout; the default low intensity filter cut-off was RiGi < 10,000/1000.
3.19.3 Tm4 Mev Analysis
The Multi Experiment Viewer (MEV) component of TM4 provides a number of statistical analyses and clustering algorithms to identify differentially expressed genes. Results from the one-class t-test analysis applied to output of the MIDAS pipeline were analyzed. This test assumes that the paired distribution of treated and control groups is 55 normally distributed. Since the intensities measured from the same spot were correlated, one- class t-test for the two-group comparison was applied. The spots showing signal intensities ≥/≤ 2.0-fold were considered differentially expressed transcripts and p ≤ 0.05 was defined as the threshold for significant differential expression.
3.20 SEQUENCING OF DIFFERENTIALLY EXPRESSED TRANSCRIPTS
After microarray analyses, the already sequenced plasmids and the new plasmids containing the differentially expressed transcripts were isolated and sequenced with dye terminator chemistry on Applied Biosystems Sequencer model 3700 as mention above.
3.21 VALIDATION STUDIES BY QUANTITATIVE REAL-TIME PCR
Real-time PCR reactions were carried out to validate the results of microarray data using Real Time ABI 7500 system (Applied Biosystems Inc, USA) with a 96-well plate using the Maxima TM SYBR Green/ROX qPCR Master mix (2X) Fermentas. Six differentially expressed clones in Agave sisalana L. were randomly selected to validate microarray results. The sequences of primers used in real-time PCR with GENBANK ACC numbers are given in Table 2. The cotton Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as house-keeping control. 100ng of cDNA was used in each reaction. Each sample was used in triplicate pattern. A melting curve analysis was carried out by continuously monitoring fluorescence between 60°C and 95°C with 0.5°C increments every 30s.The relative gene expression analysis was carried out by the SDS V3.1 software (Applied Biosystems Inc, USA) and normalized with GAPDH gene.
3.22 BIOINFORMATIC STUDIES
3.22.1 Blast Search
Raw EST sequences data were edited to remove vector and poor quality sequences. The ESTs were subjected to BlastX analyses against the non-redundant database with E- value < 1, and BlastN analyses against the non-redundant (nr) and EST databases with E- value < 1.0e-7, at NCBI GenBank to search for similarity.
56
Table 2: Sequences of the primers used in real-time PCR with their genbank acc_no.
ACCESSION NO. FORWARD PRIMER (5’-3’) REVERSE PRIMER (5’-3’)
JZ892726 CCTTGTCCTGCGCCTTAGAG ACTCGAGGATGGGAGGACTC
JZ892743 TTGGTCGTGGGAAGCCATG TGCAAAGTGTCCGGTGATCA
JZ892752 CGCCCTCTTCACCCTCAAAA CCAATGAATTTCTGCCGGCC
JZ892778 ACACGCCGATAATGCCAAGA ATGCATGGAAGGCTGTCGAA
JZ892761 CCGTCTCCAGTGTGCAGAAT GTTATCATGGGACCCGTGGG
JZ892787 AAGAATGTGGCTGCCGAGTT TGCAAACTTGAAAGGGCGTG
3.22.2 Gene Ontology (GO) and Functional Annotation
All the differentially expressed ESTs were further subjected to Blast2GO software (Figure 11) for functional categorization on the basis of cellular components, molecular functions and biological processes (Conesa et al., 2005).
Figure 11: Schematic representation of BLAST2GO application 57
4. RESULTS
4.1 EFFECT OF DROUGHT STRESS ON EPIDERMAL TISSUE OF AGAVE SISALANA LEAVES
In microscopic examination, epidermal cells showed difference in stomatal aperture. Plant under 10% drought stress showed completely closed stomata and 2% FC drought stressed plant showed partially closed ones. On the other hand, the control plant showed open and well defined stomata on 10X magnification (Figure 12 A-C).
A B
C Figure 12: Stomatal aperture of Agave sisalana leaf epidermis under microscope
A: Open stomata in control plants
B: Closed stomata in 2% FC drought stressed plants
C: Partially closed stomata in 10% FC drought stressed plants
58
4.2 EFFECT OF DROUGHT STRESS ON PHYSIOLOGICAL BEHAVIOUR OF
AGAVE SISALANA
In control plants, 8.0 µmol m-2 s-1 photosynthetic rate was measured while it was 5.67 µmol m-2 s-1 and 1.45 µmol m-2 s-1 respectively in 10% and 2% FC drought stressed treated plants (Table 3). The photosynthetic rate of control plants was significantly higher than 10% FC drought stressed plants, whereas 2% FC treated drought stressed plants showed non- significant photosynthetic activity (Table 4). Figure 12 also shows the decreasing pattern of photosynthetic rate with increasing drought stress.
Highest transpiration rate of 3.71 mmol m-2 s-1 was measured in control plants followed by 0.40 mmol m-2 s-1 and 0.15 mmol m-2 s-1 in 10 and 2% FC drought stressed plants respectively (Table 3).Transpiration rate measured for control, 10 and 2% FC drought stressed plants also showed significant difference with the increasing drought stress intensity among the treatments (Figure 14). The data highlighted significantly variable results at 5% level as mentioned in the (Table 4).
Stomatal conductance was observed highest (Figure 15) in the control plants (70 µmol m-2 s-1) followed by 10% FC (44 µmolm-2s-1) and 2% FC (9.0 µmolm-2s-1) respectively (Table 3). Mean performance of the treatments showed that there is significant difference between control and drought stressed treated plants (10 and 2% FC) at p≤0.05 and p≤0.01 values. ANOVA values also states that the treatments differ significantly at 5% (Table 4).
Water use efficiency measured by IRGA was found maximum in control plants (0.5%) with gradual decrease in 10% FC (0.05%) and 2% FC (0.005%) plants (Table 3). Difference within two drought treatments was non-significant at p≤0.05 and p≤0.01 values (Figure 16) while difference between drought and control plants was significant (Table 4).
4.3 EFFECT ON WATER RELATED ATTRIBUTES AND LEAF SURFACE AREA OF AGAVE SISALANA
Variables related to water attributes showed a decreasing pattern (Figure 17). Non- significant difference of leaf relative water content was evaluated for control and 10% FC 59 water stressed plants whereas 2% FC treated plants showed significant difference at p≤0.05 and p≤0.01. Highest leaf relative water content was given by control plants (69.3%) followed by 10% FC (68.9%) and 2% FC (30.7%) drought stressed plants (Table 3). ANOVA showed the significant difference for the performance of leaf relative water content at p≤0.05. (Table 6). Reduction in leaf area was highest at 2% FC drought stressed plants. Mean performance also exhibited highest leaf surface area in control plants (15.53 cm2) followed by 10% FC (14.37cm2) and 2% FC plants (12.9 cm2) respectively (Table 3). ANOVA showed the significant variation for the treatments at p≤0.05 (Table 6).
4.4 EFFECT OF DROUGHT STRESS ON BIOCHEMICAL ATTRIBUTES OF AGAVE SISALANA
Proline accumulation occured in the leaves of Agave sisalana (10 and 2% FC) plants as a result of drought stress (Figure 18). Highest proline content was produced in 2% FC plants (4.26 µg g-1) followed by 2.02 µg g-1 in 10% FC drought stressed plants (Table 03). The control plants showed lowest proline content 1.23 µg g-1. ANOVA showed significant difference among the variables at p≤0.05 (Table 5). With prolong and severe drought the activity of the protective enzymes was decreased and MDA content increased. In present study, highest MDA content was produced by 2% FC plants (0.99 µmol g-l FW) followed by 10% FC plants (0.209 µmol g-l FW )(Figure 19). Significant difference was recorded in control and drought stressed plants at p≤0.05 and p ≤0.01 (Table 5). Lowest MDA content was observed in control plants (0.068 µmol g-l FW) and then drastically increased with increased drought intensity in 10% and 2% FC drought stressed plants (Table 3). Under drought stressed conditions, plants started losing their chlorophyll content and photosynthetic machinery got impaired as shown in Figure 20. Our results showed lowest chlorophyll content under highest drought stress condition such as at 2% FC (0.24 mg g-l) followed by 10% FC (0.34 mg g-l) as compared to control plants having chlorophyll content 0.59 mg g-l respectively (Table 1). Analysis of variance also showed the significant results at p≤0.05 (Table 5).
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Photosynthesis rate 10 9 8
7
1 -
s 6 2 2 - Control 5 10% stress level 4 µmolm 2% stress level 3 2 1 0 Stress level
Figure 13: Comparison of Photosynthetic rate of control, 10% and 2% FCdrought stressed leaf tissue
Transpiration rate 4.5 4
3.5
1 1
- 3
s 2 2 - 2.5 Control 2 10% stress level
mmolm 1.5 2% stress level 1 0.5 0 Stress level
Figure 14: Comparison of transpiration rate of control, 10% and 2% FC drought stressed leaf tissue
61
Stomatal conductance 80
70
60
1
- 50
s 2
- Control 40 10% stress level
µmolm 30 2% stress level 20
10
0 Stress level
Figure 15: Comparison of stomatal conductance of control, 10% and 2% FC drought stressed leaf tissue
Water use efficiency 0.6
0.5
0.4 Control 0.3 10% stress level
percentage 0.2 2% stress level
0.1
0 Stress level
Figure 16: Comparison of Water Use Efficiency of control, 10% and 2% FC drought stressed leaf tissue
62
Leaf Relative Water Content 80 70
60
50 Control 40 10% stress level
percentage 30 2% stress level 20 10 0 Stress levels
Figure 17: Comparison of relative water content of control, 10% and 2% FC drought stressed leaf tissue
Proline Content 5 4.5 4
3.5
1 - 3 Control
µg g µg 2.5 10% stress level 2 1.5 2% stress level 1 0.5 0 Stress levels
Figure 18: Comparison of total proline content of control, 10% and 2% FC drought stressed leaf tissue
63
Lipid Peroxidation 1.2
1
0.8
FW 1
- Control 0.6
10% stress level molg µ 0.4 2% stress level
0.2
0 Stress levels
Figure 19: Comparison of lipid peroxidation (MDA) content of control, 10% and 2% FC drought stressed leaf tissue
Total Chlorophyll 0.7
0.6
0.5
1
- 0.4
Control mgg 0.3 10% stress level 2% stress level 0.2
0.1
0 Stress Levels
Figure 20: Comparison of total chlorophyll content of control and 2% FC drought stressed leaf tissue 64
Table3: Mean Values for physio-chemical and water related attributes under control, 10 and 2% FC drought stress Agave sisalana plants
Physio-chemical Parameters P - value Stress Levels
2 % 10 % Control Photosynthetic Rate 0.05 1.45a* 5.67b* 8.0c* 0.01 1.45aNS 5.67abNS 8.0bcNS Transpiration 0.05 0.15a* 0.40b* 3.71c* 0.01 0.15aNS 0.40abNS 3.71bcNS Stomatal Conductance 0.05 9.0a* 44.0b* 70.0c* 0.01 9.0a** 44.0b** 70.0c** Water Use Efficiency 0.05 0.005aNS 0.05abNS 0.5* 0.01 0.005aNS 0.05abNS 0.5* Total Chlorophyll 0.05 0.24a* 0.34b* 0.59c* 0.01 0.24a** 0.34b** 0.59c** Lipid Peroxidase 0.05 0.999a* 0.209b* 0.068c* 0.01 0.999a** 0.209b** 0.068c** Leaf Relative Water Content 0.05 30.7a* 68.9bNS 69.3bcNS
0.01 30.7a** 68.9bNS 69.3bcNS Proline 0.05 4.26a* 2.02b* 1.23c* 0.01 4.26aNS 2.02abNS 1.23c** Leaf Surface Area 0.05 12.9a* 14.37b* 15.53c* 0.01 12.9a** 14.37b** 15.53c**
*, denotes significant differences at 5% probability level (P≤0.05) **, denotes significant differences at 1% probability level (P≤0.01) NS, denotes non-significant
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Table 4 : Analyses of variance (ANOVA) for physiological attributes under control, 10 and 2% FC drought stress Agave sisalana plants
Physiological Attributes Treatment Error MS F P C.V MS Photosynthetic Rate 33.06 1.33 24.80* 0.0013 22.9 (µmol m-2 s-1) 1
Transpiration Rate 11.84 0.0034 3484.1 0.0000 4.11 (mmol m-2 s-1) 5*
Stomatal Conductance 2811.0 1.00 2811* 0.0000 2.44 (µmol m-2 s-1)
WUE (µmol m-2 s-1) 0.2247 0.0033 66.74* 0.0001 31.3 7 *, denotes significant differences at 5% probability level (P≤0.05) Treatment MS= Mean square (estimate of variance between groups), Error MS= Average of square of error value, F= Significance probability (variance ratio between Treatment MS and Error MS) , P=Probability value, CV (%)= Percent coefficient of variation.
TABLE5: Analyses of variance (ANOVA) for biochemical attributes under Control, 10 and 2% FC drought stress Agave sisalana plants
Biochemical Attributes Treatment Error MS F P C.V MS Total Chlorophyll content 0.0975 0.0004 243.75* 0.0000 5.13 ( mg g-l)
Lipid peroxidation 0.7553 0.000004 188842* 0.0000 0.47 ( µmol g-l FW)
Proline (µg g-l) 7.4113 0.0004 18528.25* 0.0000 0.80
*, denotes significant differences at 5% probability level (P≤0.05) Treatment MS= Mean square (estimate of variance between groups), Error MS= Average of square of error value, F= Significance probability (variance ratio between Treatment MS and Error MS) , P=Probability value, CV (%)= Percent coefficient of variation
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Table 6: Analyses of variance (ANOVA) for relative water content and leaf surface area under control, 10 and 2% FC drought stress Agave sisalana plants
Water Treatme Error MS F P C.V related nt MS parameters & Leaf surface Area
RWC (%) 1474.68 1.00 1474.6* 0.0000 1.78
LSA(cm2) 5.2117 0.02 260.59* 0.0000 0.99
*, denotes significant differences at 5% probability level (P≤0.05) Treatment MS= Mean square (estimate of variance between groups), Error MS= Average of square of error value, F= Significance probability (variance ratio between Treatment MS and Error MS) , P=Probability value, CV (%)= Percent coefficient of variation
Table 7: Correlation coefficients (r) between physio-chemical and water related attributes of Agave sisalana plants under drought stress PR Trans. SC WUE TC LPA Proline LRWC LSA PR * Trans. 0.7663 * SC 0.9349 0.8545 * WUE 0.8271 0.9789 0.8420 * TC 0.8831 0.9722 0.9418 0.9679 * LPA -0.9215 -0.6646 -0.9555 -0.6640 -0.8055 * Proline -0.9368 -0.7444 -0.9823 -0.7396 -0.8649 0.9936 * RWC 0.8952 0.5611 0.9082 0.5698 0.7266 -0.9901 -0.9685 * LSA 0.9494 0.8599 0.9953 0.8595 0.9521 -0.9451 -0.9728 0.9004 *
PR: Photosynthetic Rate; SC: Stomatal Conductivity; Trans: Transpiration; WUE: Water Use Efficiency, TC: Total Chlorophyll; LPA: Lipid Peroxidase; RWC: Related Water Content; LSA: Leaf Surface Area
67
4.5 CORRELATION BETWEEN PHYSIOLOGICAL, BIOCHEMICAL AND WATER RELATED ATTRIBUTES
The correlation coefficients (r) among various physiological, biochemical and water related factors under drought stress conditions appeared significant. Photosynthetic rate (A) was positively correlated with transpiration rate E (r=0.76), g (r=0.93), WUE (r=0.82), total Chlorophyll (r=0.88), LRWC (r=0.89) and LSA (r=0.94) whereas negatively correlated with proline (r=-0.93) and LPA(r=-0.92) at p≤0.05 (Table 7).
4.6 The cDNA LIBRARY
4.6.1 Total RNA
The quality and integrity of total RNA used for the construction of Agave sisalana L. cDNA library is the most important component required for overall microarray experiment. The Agave sisalana contains fiber yielding characteristics and therefore, were full of carbohydrates and phenolic compounds which may cause protein contamination in nucleic acid (DNA and RNA) isolation by forming quinines and ultimately getting conjugated with nucleic acids. So it is always difficult to extract RNA of excellent quality. Several kits and methods were tried to isolate good quality RNA but at the end the method prescribed by Jakola et al. (2001) with some necessary modifications was adopted to get final Total RNA. The Total RNA concentration was found to be 1361ng/ul and single sharp parabolic peak was also obtained on nanodrop at 260nm (Figure 21).
The total RNA isolated showed two intact ribosomal RNA (rRNA) bands on gel (Figure 22) which is an evidence of good quality total RNA.
4.6.2 Size Selection
For the cDNA synthesis for final cDNA library construction, purified mRNA was isolated from the total RNA isolated from drought epidermis tissues of Agave sisalana L. 68
Figure 21: Nanodrop plots showing Agave sisalana L. total RNA in control and drought stressed leaf epidermis samples
28S rRNA
18S rRNA
Figure 22: Total RNA isolation of control and drought stressed leaf epidemis tissue of Agave sisalana showing two intact rRNA bands in control and stressed plants with mRNA smears
69
The selected size of ds cDNA ranges between 200bp to 1kb. On 0.9% gel, ds cDNA showed smear like appearance that was cut and eluted from gel for cDNA library construction. Then ligation of ds cDNA with pDONRTM222 and transformation into ELECTROMAXTM DH10BTM cells is done.
4.6.3 The cDNA LIBRARY CFU
In five (5) and fifteen (15) µl volume from cDNA library that was spreaded on LB medium containing Kanamycine (50mg/l). Almost 975 and 3168 colonies were counted in five and fifteen micro-liter (µl) plated cDNA library. Total 1.22×106 cfu/ml was calculated in six (6) aliquots.
4.6.4 PLASMID ISOLATION & RESTRICTION DIGESTION CONFIRMATION
Plasmids were isolated and their vector presence was confirmed on 0.9% agarose gel (Figure 23). Few colonies were randomly chosen and screened by colony PCR using M13 (both forward & reverse) primer pairs. For library qualifying, positive clones were further confirmed with restriction digestion (Figure 23)
Figure 23: Plasmid isolation of cDNA library clones M= λ/hindIII ladder
Figure 24: Restriction digestion confirmation showing the presence of inserts M= 1.0 kb DNA ladder 70
4.7 PCR AMPLIFICATION
Almost twelve thousands (12,000) clones were selected from cDNA library. The inserts were then amplified through colony PCR. Three µl of the PCR products showed distinct sharp bands on 1.5% agrose gel (Figure 25). Ninety three percent (93%) bands showed cleared demarcation ranging from insert sizes 200bp to 1.0 kb. The amplified colony PCR determines the quality of the cDNA library (Figure 25).
Figure 25: Confirmation of clones by PCR amplification Lane 1-96, PCR amplified cDNA clones (M = 1Kb) DNA Ladder
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4.8 cDNA LIBRARY CLONE SEQUENCING
Random Clones sequencing is an important step of cDNA library confirmation. It not only determines cDNA library quality but also provide an insight into the organism genome response in that particular condition. Randomly selected three hundred clones were sequenced using dye terminator chemistry by ABI 3100 and 3700 sequencer with M13 forward primer. Raw EST sequences were subjected to editing by the removal of vector and poor quality sequences. After refining, the sequencing data was submitted to NCBI for further processing (Figure 26).
4.9 HOMOLOGY SEARCH
As there were no previously reported sequences on Agave sisalana L. under abiotic stresses, so the refined sequences were analysed for their homology with land plants by using Blast N and Blast p analysis against the no redundant (nr) database in NCBI GenBank and BLAST2GO programe. Approximately 4% clone sequences didn‟t show homology at selection criteria e < 1.0 whereas maximum homology was found in Elaeis guineensis plants (16%) followed by Phoenix dactylifera (8%), Musa acuminata (5%), solanum species (5%), Medicago tranculata (5%), Populus trichochorpa (4%), Vitis vinifera (4%), Nicotiana species (3%) and Agave species(3%) respectively. Almost 47% clone sequences showed significant homology with other plant species (Table 8). Similar blast hits were obtained when BLAST2GO was used to determine the homologues for Agave sisalana (Figure 27). One hundred and five clone sequences (105) were translated into deduced peptide sequences using Expasy and compared to other known homologues of land plants using Blast p online. Forty nine (49) clone sequences showed non-significant homology because of their short length and could not be translated into Oral Reading Frames required to predict any significant protein homology. Fourteen sequences (14) remained un-translated whereas forty two (42) sequences showed significant homology with the known proteins (Table 9).
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Figure 26: A single sequenced clone from Agave sisalana cDNA library showing quality of sequence.
73
Figure 27: Agave sisalana L. ESTs distribution with top hit species
74
Table 8: Homology studies of Agave sisalana L. ESTs with land plants (BLAST nr) along with genbank accession numbers and user_ID.
Gen Bank Acc. # User_ ID Organism Blast (nr) with land plants
Cucumis melo Cucumis melo genomic scaffold, Sequence ID: anchoredscaffold00007 JZ892707 cembSR001 emb|LN681875.1|
Solanum pennellii Solanum pennellii chromosome ch07, complete Sequence ID: genome JZ892708 cembSR002 HG975446.1
Gossypium hirsutum Gossypium hirsutum isolate GhCRR4 Sequence ID: pentatricopeptide repeat-containing protein mRNA, JZ892709 cembSR003 KF601225.1 complete cds
Elaeis guineensis PREDICTED: Elaeis guineensis 30S ribosomal Sequence ID: protein S13, chloroplastic (LOC105041319), JZ892710 cembSR004 XM_010918243.1 mRNA
Phoenix PREDICTED: Phoenix dactylifera tubulin alpha-1 JZ892711 cembSR005 dactyliferaSequence chain-like ID: XM_008806105.1 Beta vulgaris subsp. PREDICTED: Beta vulgaris subsp. vulgaris vulgaris Sequence ID: uncharacterized LOC104889487 JZ892712 cembSR006 XM_010674714 (LOC104889487), transcript variant X2, mRNA
Vitis vinifera Sequence Vitis vinifera contig VV78X142214.11, whole JZ892713 cembSR008 ID: emb|AM476387.2| genome shotgun sequence
Sesamum indicum PREDICTED: Sesamum indicum pathogenesis- Sequence ID: related protein STH-2-like (LOC105171566), JZ892714 cembSR009 ref|XM_011092729.1| transcript variant X3, mRNA Sequence ID: ref|XM_011092729.1|
Phaseolus Phaseolus vulgaris hypothetical protein vulgarisref|XM_00713 (PHAVU_009G004000g) mRNA, complete cds JZ892715 cembSR010 5869.1|
Prunus mume PREDICTED: Prunus mume G-type lectin S- Sequence ID: receptor-like serine/threonine-protein kinase JZ892716 cembSR011 XM_008230771 At2g19130 (LOC103328381)
Nicotiana tabacum Nicotiana tabacum clone pHS23 cytosolic class I Sequence ID: small heat shock protein 1A mRNA, partial cds JZ892717 cembSR013 gb|AY329047.1|
No Homology JZ892718 cembSR014
Solanum lycopersicum Solanum lycopersicum chromosome ch09, JZ892719 cembSR015 Sequence ID: complete genome emb|HG975521.1| 75
Phoenix dactylifera PREDICTED: Phoenix dactylifera CBL-interacting Sequence ID: protein kinase 19-like (LOC103706882), transcript JZ892720 cembSR016 ref|XM_008791147.1| variant X1, mRNA 7e-27 Brassica napus PREDICTED: Brassica napus chlorophyll a-b Sequence ID: binding protein, chloroplastic-like JZ892721 cembSR017 ref|XM_013873565.1| (LOC106432728), mRNA 2e-10 Elaeis guineensis PREDICTED: Elaeis guineensis 60S ribosomal Sequence ID: protein L35a-1-like (LOC105047105), mRNA JZ892722 cembSR018 ref|XM_010925912.1|
Elaeis guineensis PREDICTED: Elaeis guineensis ferredoxin, root R- Sequence ID: B1-like (LOC105035238), transcript variant X2, JZ892723 cembSR019 ref|XM_010910721.1| mRNA 8e-32
------NA JZ892724 cembSR020
------NA JZ892805 cembSR021
Zea mays Sequence Zea mays cultivar B73 dicer-like protein 4 (dcl4) JZ892725 cembSR022 ID: gb|KR230386.1| mRNA, complete cds 1e-09 Populus trichocarpa Populus trichocarpa UBIQUITIN 11 family Sequence ID: protein (POPTR_0017s06450g) mRNA, complete ref|XM_006372884.1| cds JZ892726 cembSR023 9e-92
Theobroma cacao Theobroma cacao Calmodulin-like 11, putative Sequence ID: (TCM_004254) mRNA, complete cds JZ892806 cembSR024 ref|XM_007050401.1|
Glycine max Sequence Glycine max osmotic-stress inducible (SLTI629) JZ892727 cembSR025 ID: gb|GU992872.1| gene, promoter region
Elaeis guineensis PREDICTED: Elaeis guineensis 60S ribosomal Sequence ID: protein L36-3-like (LOC105056952), transcript JZ892728 cembSR026 ref|XR_833908.1| variant X2, misc_RNA
Phoenix dactylifera PREDICTED: Phoenix dactylifera protein Sequence ID: TOPLESS-like (LOC103723843), transcript JZ892729 cembSR027 ref|XM_008814907.1| variant X5, mRNA
Picea sitchensis Picea sitchensis clone WS0278_G04 unknown Sequence ID: mRNA JZ892730 cembSR028 gb|EF677916.1| 8e-04
Populus Sequence ID: Populus EST from mild drought-stressed leaves JZ892731 cembSR029 emb|CU231858.1| 1e-12
Solanum lycopersicum Solanum lycopersicum chromosome ch06, JZ892732 cembSR031 Sequence ID: complete genome 76
emb|HG975518.1|
Populus Populus EST from severe drought-stressed leaves Sequence ID: 3e-06 JZ892733 cembSR032 emb|CU226724.1|
Musa acuminata PREDICTED: Musa acuminatasubsp. malaccensis Sequence ID: uncharacterized LOC103978433 JZ892734 cembSR033 ref|XM_009394227.1| (LOC103978433), mRNA
Lupinus luteus Lupinus luteus mRNA for putative acid Sequence ID: phosphatase (acpase2 gene) JZ892735 cembSR034 emb|AJ505579.1|
Solanum demissum Solanum demissum chromosome 5 clone Sequence ID: PGEC160O2, complete sequence JZ892736 cembSR035 gb|AC150162.1|
Elaeis guineensis PREDICTED: Elaeis guineensis probable zinc Sequence ID: metalloprotease EGY1, chloroplastic JZ892737 cembSR036 ref|XR_830414.1| (LOC105035972), transcript variant X6, misc_RNA 1e-07 ------NA JZ892807 cembSR037
Elaeis guineensis PREDICTED: Elaeis guineensis uncharacterized Sequence ID: LOC105041658 (LOC105041658), mRNA JZ892738 cembSR038 ref|XM_010918633.1| 7e-07
Elaeis guineensis PREDICTED: Elaeis guineensis histone H1-like Sequence ID: (LOC105059363), mRNA JZ892739 cembSR039 ref|XM_010942636.1| 5e-13
Oryza sativa Japonica Oryza sativa Japonica Group genomic DNA, JZ892740 cembSR040 Sequence ID: chromosome 8, BAC clone:OSJNBb0005C03 dbj|AP005697.3| Cicer arietinum PREDICTED: Cicer arietinum putative Sequence ID: pentatricopeptide repeat-containing protein JZ892741 cembSR041 ref|XM_004490077.2| At1g69350, mitochondrial (LOC101494114), mRNA
Solanum lycopersicum Solanum lycopersicum chromosome ch05, Sequence ID: complete genome JZ892742 cembSR042 emb|HG975517.1| 8e-04
Elaeis guineensis PREDICTED: Elaeis guineensis universal stress JZ892743 cembSR043 Sequence ID: protein A-like protein (LOC105045049), mRNA ref|XM_010923208.1| 3e-16 Solanum lycopersicum Solanum lycopersicum chromosome ch05, JZ892744 cembSR044 Sequence ID: complete genome emb|HG975517.1| Oryza sativa Japonica Oryza sativa Japonica Group OsHAP2G mRNA JZ892745 cembSR045 Sequence ID: for HAP2 subunit of HAP complex, complete cds 77
dbj|AB288033.1| 2e-17
Cicer arietinum PREDICTED: Cicer arietinum alpha-1,3- Sequence ID: mannosyl-glycoprotein 2-beta-N- JZ892746 cembSR046 ref|XM_004500630.2| acetylglucosaminyltransferase (LOC101510931), transcript variant X2, mRNA
Solanum lycopersicum Solanum lycopersicum chromosome ch05, JZ892747 cembSR047 Sequence ID: complete genome emb|HG975517.1| Phoenix dactylifera PREDICTED: Phoenix dactylifera UDP- Sequence ID: glycosyltransferase 73C6-like (LOC103708808), JZ892748 cembSR048 ref|XM_008793899.1| mRNA 1e-09 Musa acuminata PREDICTED: Musa acuminata subsp. malaccensis Sequence ID: barley B recombinant-like protein D JZ892749 cembSR049 ref|XM_009401114.1| (LOC103983820), transcript variant X4, mRNA 7e-33 Cucumis melo Cucumis melo genomic chromosome, chr_4 JZ892750 cembSR050 Sequence ID: emb|LN713258.1| Musa acuminata PREDICTED: Musa acuminata subsp. malaccensis Sequence ID: 60S acidic ribosomal protein P2A-like JZ892808 cembSR051 ref|XM_009422856.1| (LOC104000738), transcript variant X2, mRNA 2e-12 Medicago truncatula Medicago truncatula CDK-activating kinase Sequence ID: assembly factor MAT1, putative mRNA JZ892809 cembSR052 ref|XM_003618225.2|
Medicago truncatula Medicago truncatula gibberellin receptor GID1c- Sequence ID: like protein mRNA JZ892810 cembSR053 ref|XM_003625279.2|
Medicago truncatula Medicago truncatula strain A17 clone mth2-67m8, Sequence ID: complete sequence JZ892811 cembSR054 gb|AC198008.3|
Phoenix PREDICTED: Phoenix dactylifera probable protein dactyliferaSequence Pop3 (LOC103698404), mRNA JZ892751 cembSR055 ID: 5e-50 ref|XM_008780403.1| Populus Populus EST from severe drought-stressed leaves Sequence ID: 6e-17 JZ892752 cembSR056 emb|CU226444.1|
Zea mays Sequence Zea mays GCN5 gene for histone acetyltransferase, JZ892753 cembSR057 ID: emb|AJ428542.2| complete cds 2e-10 Solanum pennellii Solanum pennellii chromosome ch10, complete Sequence ID: genome JZ892754 cembSR058 emb|HG975449.1|
Agave americana Agave americana isolate PDBK2012-0043 ATP JZ892755 cembSR059 Sequence ID: synthase CF0 subunit I (atpF) and ATP synthase
gb|KC704976.1| CF0 subunit III (atpH) genes, partial cds; plastid 78
2e-13 Elaeis guineensis PREDICTED: Elaeis guineensis macrophage Sequence ID: erythroblast attacher-like (LOC105052706), JZ892756 cembSR060 ref|XM_010933624.1| mRNA 8e-120 Phoenix dactylifera PREDICTED: Phoenix dactylifera uncharacterized JZ892757 cembSR061 Sequence ID: LOC103701424 (LOC103701424), mRNA ref|XM_008783459.1| Vitis vinifera Sequence Vitis vinifera, whole genome shotgun sequence, JZ892758 cembSR062 ID: emb|AM449524.1| contig VV78X047309.7, clone ENTAV 115
Vitis vinifera Sequence Vitis vinifera contig VV78X234451.2, whole JZ892759 cembSR063 ID: emb|AM423483.1| genome shotgun sequence
Cucumis sativus PREDICTED: Cucumis sativus NAD(P)H-quinone Sequence ID: oxidoreductase subunit T, chloroplastic JZ892760 cembSR064 ref|XM_011652407.1| (LOC101208302), transcript variant X2, mRNA
Catharanthus roseus Catharanthus roseus clone 42-166 putative JZ892761 cembSR065 Sequence ID: universal stress protein mRNA, complete cds gb|KJ634222.1| 6e-46 Hyacinthus orientalis Hyacinthus orientalis pathogenesis-related protein JZ892762 cembSR066 Sequence ID: mRNA, complete cds gb|AY389712.1| 6e-16
Arabidopsis thaliana Arabidopsis thaliana putative pyruvate kinase JZ892763 cembSR067 Sequence ID: (At3g22960) mRNA, partial cds gb|AY056196.1| Nicotiana sylvestris Nicotiana sylvestris Nsppc3 gene for JZ892764 cembSR068 Sequence ID: phosphoenolpyruvate carboxylase, partial cds dbj|AB026619.1| Citrus clementina Citrus clementina hypothetical protein JZ892765 cembSR069 Sequence ID: (CICLE_v10030902mg) mRNA, complete cds ref|XM_006435724.1| Cornutia obovata Cornutia obovata voucher 0118738342 psbA-trnH JZ892766 cembSR070 Sequence ID: intergenic spacer, partial sequence; chloroplast gb|KJ426682.1| Zea mays Sequence Zea mays cultivar inbred line B73 teosinte glume JZ892767 cembSR071 ID: gb|AY883559.2| architecture 1 (tga1) gene, complete cds
Glycine max Sequence PREDICTED: Glycine max disease resistance ID: RPP8-like protein 3-like (LOC102664161), JZ892768 cembSR072 ref|XM_006589287.1| transcript variant X2, mRNA
Taxus chinensis Taxus chinensis taxadiene synthase mRNA, JZ892769 cembSR073 Sequence ID: complete cds gb|AY007207.1| Lotus japonicus Lotus japonicus genomic DNA, clone: LjT34L14, JZ892770 cembSR074 Sequence ID: TM1967, complete sequence dbj|AP009779.1| Musa acuminata PREDICTED: Musa acuminata subsp. malaccensis JZ892771 cembSR075 Sequence ID: GPI-anchored protein LORELEI-like ref|XM_009417127.1| (LOC103996248), mRNA JZ892772 cembSR076 Brassica napus PREDICTED: Brassica napus transcription factor 79
Sequence ID: TCP15-like (LOC106446518), mRNA ref|XM_013888278.1| Elaeis guineensis PREDICTED: Elaeis guineensis transcription and Sequence ID: mRNA export factor SUS1 (LOC105048925), JZ892773 cembSR077 ref|XM_010928420.1| mRNA
Malus sylvestris Malus sylvestris ACL5 mRNA for ACAULIS5 JZ892774 cembSR078 Sequence ID: protein, complete cds dbj|AB204521.1| 3e-05 Medicago truncatula Medicago truncatula chromosome 7 BAC clone Sequence ID: mth2-75f4, complete sequence JZ892775 cembSR079 gb|AC195571.4|
Malus x domestica PREDICTED: Malus x domestica LON peptidase Sequence ID: N-terminal domain and RING finger protein 2-like JZ892776 cembSR080 ref|XM_008366416.1| (LOC103428311), mRNA
Dendrobium candidum Dendrobium candidum phenylalanine ammonia- Sequence ID: lyase mRNA, complete cds JZ892777 cembSR081 gb|JQ765748.1|
Populus Populus EST from mild drought-stressed leaves Sequence ID: JZ892778 cembSR082 emb|CU229903.1|
Theobroma cacao Sequence ID: Theobroma cacao Ubiquitin-protein ligase 1-like JZ892779 cembSR083 ref|XM_007020418.1| protein (TCM_030625) mRNA, complete cds
Beta vulgaris PREDICTED: Beta vulgaris subsp. vulgaris switch Sequence ID: 2-like (LOC104898934), transcript variant X4, JZ892780 cembSR084 ref|XR_790863.1| misc_RNA
Firmiana danxiaensis Firmiana danxiaensis microsatellite a6747_SSR89 Sequence ID: sequence JZ892781 cembSR085 gb|KF313540.1|
Phoenix dactylifera PREDICTED: Phoenix dactylifera uncharacterized Sequence ID: LOC103721151 (LOC103721151), mRNA JZ892782 cembSR086 ref|XM_008811225.1|
Elaeis guineensis PREDICTED: Elaeis guineensis microtubule- Sequence ID: associated protein 70-4-like (LOC105056048), JZ892783 cembSR087 ref|XM_010938109.1| mRNA
Citrus trifoliata Citrus trifoliata clone Y4-I15 hypothetical protein JZ892784 cembSR088 Sequence ID: mRNA, complete cds gb|HM596722.1| 4e-05 Chaunochiton kappleri Chaunochiton kappleri voucher D. Nickrent 3052 Sequence ID: small subunit ribosomal RNA gene, partial JZ892785 cembSR089 gb|DQ790106.1| sequence 2e-04 Alloteropsis semialata Alloteropsis semialata isolate MD 26S-18S JZ892786 cembSR090 Sequence ID: ribosomal RNA intergenic spacer, partial sequence; 80
gb|KT281168.1| 18S ribosomal RNA gene, internal transcribed spacer 1, 5.8S ribosomal RNA gene, and internal transcribed spacer 2, complete sequence; and 26S ribosomal RNA gene, partial sequence
Elaeis guineensis PREDICTED: Elaeis guineensis zerumbone Sequence ID: synthase-like (LOC105052461), mRNA ref|XM_010933280.1| JZ892787 cembSR091
Phoenix dactylifera PREDICTED: Phoenix dactylifera zerumbone Sequence ID: synthase (LOC103720715), mRNA JZ892788 cembSR092 ref|XM_008810554.1|
Musa acuminata PREDICTED: Musa acuminata subsp. malaccensis Sequence ID: zerumbone synthase (LOC103981080), mRNA JZ892789 cembSR093 ref|XM_009397672.1|
Nicotiana PREDICTED: Nicotiana tomentosiformis cell tomentosiformis division control protein 48 homolog C-like JZ892790 cembSR094 Sequence ID: (LOC104096525), mRNA ref|XM_009602911.1|
Lilium davidii Lilium davidii var. unicolor ADP-glucose Sequence ID: pyrophosphorylase small subunit (AGP2) mRNA, JZ892791 cembSR095 gb|KP179413.1| complete cds 1
Elaeis guineensis PREDICTED: Elaeis guineensis nucleobase- Sequence ID: ascorbate transporter 6-like (LOC105060258), JZ892792 cembSR096 ref|XM_010943883.1| transcript variant X2, mRNA
Vitis vinifera Sequence Vitis vinifera contig VV78X094631.6, whole JZ892793 cembSR097 ID: emb|AM461123.2| genome shotgun sequence
Ananas comosus Ananas comosus late-embryogenesis abundant JZ892794 cembSR098 Sequence ID: protein-like protein mRNA, partial cds gb|AY098519.1| Agave americana Agave americana chloroplast small heat shock Sequence ID: protein (sHSP) gene, complete cds; nuclear gene JZ892795 cembSR099 gb|JQ671429.1| for chloroplast product
Agave Agave americana chloroplast small heat shock cembSR100 americanaSequence protein (sHSP) gene, complete cds; nuclear gene JZ892796 ID: gb|JQ671429.1| for chloroplast product
Elaeis guineensis PREDICTED: Elaeis guineensis zerumbone Sequence ID: synthase-like (LOC105045554), mRNA JZ892797 cembSR101 ref|XM_010923886.1|
Trifolium pratense Trifolium pratense genome assembly redclover, JZ892798 cembSR102 Sequence ID: chromosome : chr2 emb|LN846350.1| JZ892799 cembSR103 Elaeis guineensis PREDICTED: Elaeis guineensis zerumbone 81
Sequence ID: synthase-like (LOC105052461), mRNA ref|XM_010933280.1| Elaeis guineensis PREDICTED: Elaeis guineensis zerumbone Sequence ID: synthase-like (LOC105052461), mRNA JZ892800 cembSR104 ref|XM_010933280.1|
Capsicum annuum Capsicum annuum Pvr9-like protein 2 gene, Sequence ID: complete cds JZ892801 cembSR105 gb|KM590986.1|
Sequence ID: Elaeis PREDICTED: Elaeis guineensis zerumbone guineensisref|XM_010 synthase-like (LOC105052461), mRNA JZ892802 cembSR106 933280.1|
Medicago truncatula Medicago truncatula acyl carrier protein mRNA Sequence ID: JZ892803 cembSR107 ref|XM_003624158.2|
No homology
JZ892804 cembSR108 ------
82
Table 9: Homology studiesof Agave sisalana L. ESTs with land plants (BLAST p) along with genbank accession numbers and user_ID.
Gen Bank Blast (p) with land plants Land Plant Acc. # User_ ID Species
JZ892707 hypothetical protein MTR_4g079620 Medicago JZ892707 cembSR001 [Medicago truncatula] truncatula
PREDICTED: uncharacterized protein LOC103638272 JZ892708 cembSR002 Zea mays [Zea mays] evalue 329 100% ------Non-significant homology JZ892709 cembSR003
Musa acuminata PREDICTED: 30S ribosomal protein S13, JZ892710 cembSR004 subsp. chloroplastic-like isoform X1 [Musa acuminata subsp. Malaccensis malaccensis] PREDICTED: tubulin alpha-3 chain isoform X2 JZ892711 cembSR005 Cucumis melo [Cucumis melo] ------Not Translated JZ892712 cembSR006
sedoheptulose-1,7-bisphosphatase, partial [Triticum JZ892713 cembSR008 Triticum aestivum aestivum]
hypothetical protein B456_001G025200 [Gossypium Gossypium JZ892714 cembSR009 raimondii] raimondii
PREDICTED: cytochrome P450 CYP72A219-like Nicotiana JZ892715 cembSR010 [Nicotiana tomentosiformis] tomentosiformis
Taxadien-5-alpha-ol O-acetyltransferase [Aegilops JZ892716 cembSR011 Aegilops tauschii tauschii]
------Not Translated JZ892717 cembSR013
Calcium-dependent protein kinase 34 [Triticum urartu] JZ892718 cembSR014 Triticum urartu
------Non-significant homology JZ892719 cembSR015
PREDICTED: CBL-interacting serine/threonine- protein kinase 12-like [Musa acuminata subsp. JZ892720 cembSR016 Musa acuminata malaccensis]
------Not Translated JZ892721 cembSR017
------Non-significant homology JZ892722 cembSR018
Phoenix ferredoxin, root R-B1 [Phoenix dactylifera] JZ892723 cembSR019 dactylifera ------Non-significant homology JZ892724 cembSR020
JZ892805 cembSR021 ------Non-significant homology 83
------Non-significant homology JZ892725 cembSR022
Populus ubiquitin extension protein 1 [Populustrichocarpa] JZ892726 cembSR023 trichocarpa RecName: Full=Putative terpenoid synthase 16; ------Short=AtTPS16 JZ892806 cembSR024
------Non-significant homology JZ892727 cembSR025
60S ribosomal protein L36-3-like [Musa acuminata JZ892728 cembSR026 Musa acuminata subsp. malaccensis]
Os06g0233200 [Oryza sativa Japonica Group] JZ892729 cembSR027 Oryza sativa
Non-significant homology ------JZ892730 cembSR028
PREDICTED: uncharacterized protein LOC103714481 Phoenix JZ892731 cembSR029 [Phoenix dactylifera] dactylifera
PREDICTED: methyl-CpG-binding domain-containing JZ892732 cembSR031 Pyrus species protein 9, partial [Pyrus x bretschneideri]
------Non-significant homology JZ892733 cembSR032
------Non-significant homology JZ892734 cembSR033
Not Translated ------JZ892735 cembSR034
------Non-significant homology JZ892736 cembSR035
Not Translated ------JZ892737 cembSR036
------Not Translated JZ892807 cembSR037
------Non-significant homology
------Non-significant homology JZ892738 cembSR038
Stress-inducible H1 histone-like protein [Nicotiana Nicotiana JZ892739 cembSR039 tabacum] tabacum
------Non-significant homology JZ892740 cembSR040
------Non-significant homology JZ892741 cembSR041
------Non-significant homology JZ892742 cembSR042
JZ892743 cembSR043 ------Non-significant homology JZ892744 cembSR044 Erythranthe PREDICTED: trihelix transcription factor GT-3b 84
guttatus [Erythranthe guttatus] PREDICTED: structural maintenance of chromosomes Erythranthe JZ892745 cembSR045 protein 3-like [Erythranthe guttatus] guttatus
------Non-significant homology JZ892746 cembSR046 ------Non-significant homology JZ892747 cembSR047
------Non-significant homology JZ892748 cembSR048
GAGA-binding transcriptional activator BBR/BPC6- JZ892749 cembSR049 Vitis vinifera like [Vitis vinifera]
------Non-significant homology JZ892750 cembSR050
hypothetical protein BVRB_5g115080 [Beta vulgaris JZ892808 cembSR051 Beta vulgaris subsp. vulgaris]
------Non-significant homology JZ892809 cembSR052
------Non-significant homology JZ892810 cembSR053
Not Translated ------JZ892811 cembSR054
Arabidopsis heat stable protein 1 [Arabidopsis thaliana] JZ892751 cembSR055 thaliana ------Non-significant homology JZ892752 cembSR056
------Non-significant homology JZ892753 cembSR057
------Non-significant homology JZ892754 cembSR058
JZ892755 ------Non-significant homology cembSR059
------Non-significant homology JZ892756 cembSR060
------Non-significant homology JZ892757 cembSR061
------Non-significant homology JZ892758 cembSR062
Not Translated ------JZ892759 cembSR063
------Non-significant homology JZ892760 cembSR064
JZ892761 universal stress family protein [Populus Populus JZ892761 cembSR065 trichocarpa] trichocarpa
------Non-significant homology JZ892762 cembSR066
Not Translated ------JZ892763 cembSR067
JZ892764 cembSR068 Nicotiana PREDICTED: zinc finger MYM-type protein 1-like 85
tomentosiformis [Nicotiana tomentosiformis] ------Non-significant homology JZ892765 cembSR069
------Non-significant homology JZ892766 cembSR070
Not Translated ------JZ892767 cembSR071
------Non-significant homology JZ892768 cembSR072
------Not Translated JZ892769 cembSR073
------Non-significant homology JZ892770 cembSR074
GPI-anchored protein LORELEI-like [Elaeis JZ892771 cembSR075 Elaeis guineensis guineensis]
------Non-significant homology JZ892772 cembSR076
PREDICTED: transcription and mRNA export factor JZ892773 cembSR077 [Elaeis guineensis SUS1 [Elaeis guineensis]
------Non-significant homology JZ892774 cembSR078
Not Translated ------JZ892775 cembSR079
------Non-significant homology JZ892776 cembSR080
------Non-significant homology JZ892777 cembSR081
hypothetical protein POPTR_0003s10270g [Populus Populus JZ892778 cembSR082 trichocarpa] trichocarpa
PREDICTED: cytochrome P450 89A2-like [Fragaria
Fragaria vesca vesca subsp. vesca] JZ892779 cembSR083
uncharacterized protein LOC103699496 [Phoenix Phoenix JZ892780 cembSR084 dactylifera] dactylifera
------Non-significant homology JZ892781 cembSR085
PREDICTED: uncharacterized protein LOC105053772 JZ892782 cembSR086 Elaeis guineensis [Elaeis guineensis]
------No homology JZ892783 cembSR087
------Non-significant homology JZ892784 cembSR088
------Non-significant homology JZ892785 cembSR089
Arabidopsis transcription factor bHLH122 [Arabidopsis thaliana] JZ892786 cembSR090 thaliana 86
PREDICTED: zerumbone synthase-like [Elaeis guineensis] ZSD1 is involved in secondary JZ892787 cembSR091 Elaeis guineensis metabolism, stress responses and phytosteroid biosynthesis
PREDICTED: zerumbone synthase-like [Setaria italica] ZSD1 is involved in secondary metabolism, JZ892788 cembSR092 Setaria italic stress responses and phytosteroid biosynthesis
Xanthoxin dehydrogenase [Triticum urartu] xanthoxin dehydrogenase (XanDH), as a functional marker to JZ892789 cembSR093 Triticum urartu modulate ABA levels
Not Translated ------JZ892790 cembSR094
Non-significant homology ------JZ892791 cembSR095
------Non-significant homology JZ892792 cembSR096
PREDICTED: probable E3 ubiquitin-protein ligase JZ892793 cembSR097 Malus domestica ARI2 [Malus domestica]
------Non-significant homology JZ892794 cembSR098
chloroplast small heat shock protein [Agave JZ892795 cembSR099 Agave americana americana]
cembSR100 PREDICTED: RING-H2 finger protein ATL57-like JZ892796 Musa acuminata [Musa acuminata subsp. malaccensis]
No homology JZ892797 cembSR101 ------
hypothetical protein PHAVU_L002400g [Phaseolus Phaseolus JZ892798 cembSR102 vulgaris] vulgaris
PREDICTED: nicastrin isoform X2 [Phoenix Phoenix JZ892799 cembSR103 dactylifera] dactylifera]
------Non-significant homology JZ892800 cembSR104
Not Translated ------JZ892801 cembSR105
PREDICTED: zerumbone synthase-like [Elaeis JZ892802 cembSR106 Elaeis guineensis guineensis]
Mitochondrial acyl carrier protein 2 isoform 2, partial JZ892803 cembSR107 Theobroma cacao [Theobroma cacao]
------Non-significant homology JZ892804 cembSR108
87
4.10 FUNCTINAL CHARACTERIZATION BY GENE ONTOLOGY
The Arabidopsis homologs of 105 Agave sisalana L. clone sequences are further divided on the basis of their molecular functions, biological processes and cellular components by means of gene ontology (GO) annotation (Table 10).
4.10.1 Molecular Characterization
The Gene Ontology moleculer characterization of all the clone sequences showed that the maximum number of the reported sequences are engaged in transferase activity (18.59%) followed by other binding (16.026%), unknown molecular functions (13.462%), hydrolase activity (9.615%), other enzyme activity (7.692%), protein binding (7.051%), DNA or RNA binding (7.051%), Kinase activity (6.41%), nucleotide binding (5.769%), structural molecular activity (2.564), transcription factor activity (1.932%), transporter activity (1.282%), other molecular functions (1.282%), receptor binding or activity (0.641%) and nucleic acid binding (0.641%) respectively (Figure 28).
Figure 28: GO Molecular functions categorization by annotation.
88
4.10.2 Cellular Characterization
The GO characterization for cellular components of all the reported sequences of Agave sisalana L. showed that majority are present in other intracellular components (19.331%), followed by nucleus (15.613%), other cytoplasmic components (15.613%), chloroplast (8.922%), other membranes (8.922%), plasma membrane (4.833%), mitochondria (4.461%), cytosol (4.461%), extracellular (3.346%) plastid (2.974%), Golgi apparatus ( 2.602%), Endoplasmic Reticulum 2.602%, unknown cellular components (2.23%), ribosome (2.23%), other cellular components (1.487%) and cell wall (0.372%) respectively (Figure 29). 4.10.3 Biological Characterization
The biological process categorization by GO annotation revealed that major part of Agave sisalana L. homologs appeared in other metabolic processes (23.843%), followed by other cellular processes (22.776%), response to stress (7.473%), unknown biological processes (7.473%), response to abiotic or biotic stimulus (6.762%), protein metabolism (6.762%), other biological processes (4.626%), transcription DNA dependent (4.27%), transport (3.559%), DNA or RNA metabolism (3.559%), cell organization and biogenesis (3.203%), signal transduction (2.847%), developmental processes (2.491%) and electron transport or energy pathways (0.356%) respectively (Figure 30).
89
Figure 29: GO Cellular processes categorization by annotation.
Figure 30: GO Biological processes categorization by annotation.
90
Table 10: Gene function(s) of ESTs biological processes, molecular function & cellular components along with genbank accession numbers, user_ID and Arabidopsis genbank accession numbers
Agave Gen ArabidopsisG Bank User_ ID en Bank Acc Description Gene Function (s) / Location Acc # # Encodes an Dolichyl-phosphate-mannose- endoplasmic protein mannosyltransferase reticulum protein activity, cell wall mannoprotein SDF2 (stromal- biosynthetic process, chain derived factor-2) elongation of O-linked mannose Forms a complex residue, defense response to JZ892707 cembSR001 AT2G25110 SDF2-EFR. EFR is bacterium, defense response to involved in PAMP fungus, multicellular organismal (pathogen associated development molecular patterns) triggered immunity.
Starch synthase 4 Transferase activity, transferring JZ892708 cembSR002 AT4G18240 (SS4) glycosyl groups, protein binding
Somatic ATP binding, Protein kinase embryogenesis activity, transmembrane receptor JZ892709 cembSR003 AT2G13800 receptor-like kinase 5 protein serine/threonine kinase (SERK5) activity
Ribosomal protein rRNA binding, Structural S13/S18 family constituent of ribosome, JZ892710 cembSR004 AT5G14320 Ribosome biogenesis, translation
Alpha-tubulin GTP binding, GTPase activity, expressed primarily structural constituent of JZ892711 cembSR005 AT1G64740 in stamens and cytoskeleton, Microtubule-based mature pollen process, protein polymerization
Basic helix-loop- DNA binding, protein helix (bHLH) DNA- dimerization activity, binding superfamily transcription factor activity, JZ892712 cembSR006 AT4G16430 protein sequence-specific DNA binding, Regulation of transcription, DNA-templated, transcription, DNA-templated Organellar single- Single-stranded DNA binding, stranded DNA DNA replication JZ892713 cembSR008 AT5G44785 binding protein 3 (OSB3) Protein kinase Kinase activity, protein kinase JZ892714 cembSR009 AT3G57770 superfamily protein activity, Protein phosphorylation, ATP binding Gypsy-like Unknown JZ892715 cembSR010 AT5G33252 retrotransposon family 91
Encodes a defensin- Defense response to fungus, like (DEFL) family killing of cells of other organism, JZ892716 cembSR011 AT5G59105 protein Molecular function unknown
Ubiquinol- Molecular and biological process cytochrome C unknown JZ892717 cembSR013 AT5G51220 chaperone family protein Vacuolar protein Protein binding, transporter sorting-associated activity, JZ892718 cembSR014 AT4G21560 protein 28 homolog 1 (VPS28-1)
This gene encodes a Molecular and biological process small protein and has unknown either evidence of JZ892719 cembSR015 AT5G44065 transcription or purifying selection.
unknown protein Molecular and biological process JZ892720 cembSR016 AT5G01970 unknown
Encodes a component Chlorophyll binding, pigment of the light harvesting binding, Photosynthesis, light JZ892721 cembSR017 AT3G61470 antenna complex of harvesting in photosystem I, photosystem I response to light stimulus
Non-LTR Molecular and biological process JZ892722 cembSR018 AT3G43625 retrotransposon unknown family (LINE) DSEL is cytosolic Acylglycerol lipase activity, acylhydrolase that phosphatidylcholine 1- shows prefential acylhydrolase activity, lipase activity against triglyceride lipase activity, the sn-1 position of diacylglycerol catabolic process, JZ892723 cembSR019 AT4G18550 several classes of lipid metabolic process, lipid lipids, including 1,3- storage, monoacylglycerol diacylglycerols and catabolic process, negative 1-monoacylglycerols regulation of seed germination
Tetratricopeptide Molecular and biological process repeat (TPR)-like unknown JZ892724 cembSR020 AT2G27775 superfamily protein
Vacuolar sorting Calcium ion binding, Intracellular receptor 7 (VSR7) protein transport, protein JZ892805 cembSR021 AT4G20110 targeting to vacuole, protein transport
3-beta hydroxysteroid 3-beta-hydroxy-delta5-steroid dehydrogenase/isome dehydrogenase activity, sterol-4- rase family protein alpha-carboxylate 3- JZ892725 cembSR022 AT2G43420 dehydrogenase (decarboxylating) activity, oxidation-reduction, steroid biosynthetic process 92
Polyubiquitin gene Cellular protein modification containing 4 process, ubiquitin-dependent JZ892726 cembSR023 AT4G02890 ubiquitin repeats protein catabolic process, Molecular function unknown
Acyl-CoA N- N-acetyltransferase activity, acyltransferases transferase activity, metabolic JZ892806 cembSR024 AT4G28030 (NAT) superfamily process protein Nodulin MtN21-like Transmembrane transporter transporter family activity JZ892727 cembSR025 AT3G28100 protein
Unknown protein Molecular and biological JZ892728 cembSR026 AT5G10010 functions unknown
WUS-interacting Protein binding, Primary shoot protein 2 (WSIP2) apical meristem specification, JZ892729 cembSR027 AT3G15880 regulation of transcription, DNA- templated
C2 calcium/lipid- Molecular and biological binding plant functions unknown JZ892730 cembSR028 AT5G48060 phosphoribosyltransf erase family protein
Non-LTR Molecular and biological JZ892731 cembSR029 AT1G23990 retrotransposon functions unknown family (LINE) Autophagy 8b Microtubule binding, autophagy JZ892732 cembSR031 AT4G04620 (ATG8B) Unknown protein Molecular and biological JZ892733 cembSR032 AT3G54060 functions unknown
Unknown protein Molecular and biological JZ892734 cembSR033 AT4G38490 functions unknown
LATE MERISTEM DNA binding, chromatin binding, IDENTITY2 (LMI2) transcription factor activity, is a target of the sequence-specific DNA binding, meristem identity regulation of flower development, JZ892735 cembSR034 AT3G61250 regulator LEAFY regulation of transcription, DNA- (LFY) templated, response to jasmonic acid, response to salicylic acid
Leucine-rich repeat Kinase activity, Signal JZ892736 cembSR035 AT4G13820 (LRR) family protein transduction Pollen Ole e 1 Molecular and biological JZ892737 cembSR036 AT5G45880 allergen and extensin functions unknown family protein Unknown protein Molecular and biological JZ892807 cembSR037 AT4G21920 functions unknown SAUR-like auxin- Calmodulin binding, response to JZ892738 cembSR038 AT2G24400 responsive protein auxin family 93
RNA-binding Nucleic acid binding, nucleotide (RRM/RBD/RNP binding JZ892739 cembSR039 AT1G51520 motifs) family protein
TRAF-like family Molecular and biological JZ892740 cembSR040 AT3G58360 protein functions unknown
O-acyltransferase Diacylglycerol O-acyltransferase (WSD1-like) family activity, long-chain-alcohol O- JZ892741 cembSR041 AT3G49200 protein fatty-acyltransferase activity, triglyceride biosynthetic process
A member of the Metal ion binding, transferase Glycosyltransferase activity, transferase activity, Family 6 transferring glycosyl groups, transferase activity, transferring hexosyl groups, JZ892742 cembSR042 AT5G04500 glycosaminoglycan biosynthetic process, heparan sulfate proteoglycan biosynthetic process, protein glycosylation
Protein kinase Protein serine/threonine kinase superfamily protein activity, protein kinase activity, JZ892743 cembSR043 AT5G23170 kinase activity, ATP binding
Aldolase-type TIM tRNA dihydrouridine synthase barrel family protein activity, regulation of nitrogen JZ892744 cembSR044 AT5G47970 utilization, tRNA dihydrouridine synthesis
mRNA splicing Catalytic activity, mRNA factor, thioredoxin- splicing, via spliceosome, mitotic JZ892745 cembSR045 AT3G24730 like U5 snRNP nuclear division
F-box/RNI-like/FBD- Molecular and biological
cembSR046 AT5G44960 like domains- functions unknown JZ892746 containing protein Protein of unknown Transferase activity, transferring JZ892747 cembSR047 AT1G13000 function glycosyl groups
UDP-glucosyl UDP-glucosyltransferase activity, transferase 73B5 UDP-glycosyltransferase activity, (UGT73B5) flavonol 3-O-glucosyltransferase JZ892748 cembSR048 AT2G15480 activity, quercetin, defense response, response to other organism
Encodes a ferric Ferric-chelate reductase activity, chelate reductase metal ion binding, Ion transport, JZ892749 cembSR049 AT5G23980 oxidation-reduction process
94
Involved in Molybdenum ion binding, Mo- molybdenum cofactor molybdopterin cofactor JZ892750 cembSR050 AT5G20990 (Moco) biosynthesis biosynthetic process, auxin- activated signaling pathway
60S acidic ribosomal Structural constituent of protein family ribosome, Response to cold, JZ892808 cembSR051 AT2G27710 translational elongation
Encodes a xyloglucan Hydrolase activity, acting on endotransglucosylase glycosyl bonds, xyloglucan /hydrolase with only endotransglucosylase activity, only the xyloglucan:xyloglucosyl endotransglucosylase transferase activity, xyloglucan- (XET; EC 2.4.1.207) specific endo-beta-1,4-glucanase JZ892809 cembSR052 AT4G30290 activity towards activity, cell proliferation, cell xyloglucan and non- wall biogenesis, cell wall detectable organization, cellular response to endohydrolytic auxin stimulus, xyloglucan (XEH; EC 3.2.1.151) metabolic process activity
Gypsy-like Molecular and biological
retrotransposon functions unknown JZ892810 cembSR053 AT1G36795 family (Athila)
JZ892811 Catalytics Catalytic activity cembSR054 AT4G03200
Encodes a heat stable Metal ion binding protein with JZ892751 cembSR055 AT3G17210 antimicrobial and antifungal activity.
Encodes a putative Phosphoenolpyruvate phosphoenolpyruvate carboxykinase (ATP) activity, JZ892752 cembSR056 AT5G65690 carboxykinase (ATP- ATP binding, gluconeogenesis dependent).
Protein of unknown Molecular and biological JZ892753 cembSR057 AT5G16380 function functions unknown
beta glucosidase 19 Beta-glucosidase activity, (BGLU19) hydrolase activity, hydrolyzing JZ892754 cembSR058 AT3G21370 O-glycosyl compounds, carbohydrate metabolic process
Mitochondrial Double-stranded DNA binding, JZ892755 transcription regulation of transcription, DNA- cembSR059 AT4G19650 termination factor templated family protein LisH/CRA/RING-U- Molecular and biological JZ892756 cembSR060 AT3G55070 box domains- functions unknown containing protein Protein of unknown Molecular and biological JZ892757 cembSR061 AT5G66580 function functions unknown 95
RNA-directed DNA RNA-directed DNA polymerase polymerase (reverse activity, mRNA processing JZ892758 cembSR062 AT5G04050 transcriptase)
Phosphoinositide Phosphatidylinositol binding, JZ892759 cembSR063 AT4G14740 binding signal transduction
Dynein light chain Microtubule motor activity, JZ892760 cembSR064 AT4G15930 type 1 family protein microtubule-based process
Encodes gene that is Response to desiccation, induced in response Molecular function unknown JZ892761 cembSR065 AT2G21620 to dessication
NAD(P)-binding Oxidoreductase activity
JZ892762 Rossmann-fold cembSR066 AT2G29310 superfamily protein
Microtubule- Microtubule bindingCell associated protein 65- proliferation, cytokinesis, post- JZ892763 cembSR067 AT4G26760 2 (MAP65-2) embryonic root development
Ribosomal protein S3 Protein binding, Translation JZ892764 cembSR068 ATMG00090
Encodes a Mitochondrial mRNA pentatricopeptide modification, Molecular function repeat protein (PPR) unknown JZ892765 cembSR069 AT3G18970 protein involved in mitochondrial mRNA editing
Ankyrin repeat Molecular and biological JZ892766 cembSR070 AT5G54710 family protein functions unknown
Encodes one of two Protein binding, TOR signaling, Arabidopsis cell growth, embryo development JZ892767 cembSR071 AT3G08850 RAPTOR/KOG1 ending in seed dormancy, homologs regulation of growth
TLD-domain Calcium ion binding, N-terminal JZ892768 cembSR072 AT5G06260 containing nucleolar protein myristoylation protein UDP-glucosyl UDP-lycosyltransferase activity, transferase 76E2 quercetin 3-O-glucosyltransferase JZ892769 cembSR073 AT5G59590 (UGT76E2) activity, quercetin 7-O- glucosyltransferase activity
Homeodomain-like DNA binding, regulation of JZ892770 cembSR074 AT5G05090 superfamily protein transcription, DNA-templated
LORELEI-LIKE- Molecular and biological GPI-ANCHORED functions unknown JZ892771 cembSR075 AT5G56170 PROTEIN 1 (LLG1)
96
Protein of unknown Molecular and biological JZ892772 cembSR076 AT5G60060 function DUF295 functions unknown
Has 30201 Blast hits Transcription coactivator activity, to 17322 proteins in histone deubiquitination, mRNA 780 species export from nucleus, positive regulation of transcription, DNA- JZ892773 cembSR077 AT3G27100 templated, protein transport, transcription elongation from RNA polymerase II promoter
Leucine-rich repeat Defense response, Molecular JZ892774 cembSR078 AT5G66890 (LRR) family protein biological function unknown
Pseudogene, Molecular and biological JZ892775 cembSR079 AT4G06518 hypothetical protein functions unknown
Encodes a component RNA binding, RNA splicing, of the putative mRNA processing, mRNA JZ892776 cembSR080 AT5G42920 Arabidopsis transport THO/TREX complex
F-box family protein Protein ubiquitination, molecular JZ892777 cembSR081 AT5G49610 function unknown
Acyl-CoA-binding Fatty-acyl-CoA binding, protein phosphatidylcholine binding, lipid transport, response to absence of JZ892778 cembSR082 AT1G31812 light, response to cold, response to freezing, response to hypoxia
Encodes a member of Kinase activity, response to SNF1-related protein karrikin, response to osmotic
cembSR083 AT1G78290 kinase (SnRK2) stress JZ892779
Unknown protein NAD+ ADP-ribosyltransferase JZ892780 cembSR084 AT1G62520 activity
Cysteine/Histidine- Protein-disulfide reductase rich C1 domain activity, intracellular signal JZ892781 cembSR085 AT4G11540 family protein transduction, oxidation-reduction process
Unknown gene Molecular and biological JZ892782 cembSR086 AT1G58808 functions unknown Encodes a nuclear RNA binding, protein binding, protein that binds to AU-rich element binding, RNA RNA with a binding, mRNA stabilization JZ892783 cembSR087 AT2G22090 specificity for oligouridylates in vitro Disease resistance ADP binding, defense response, JZ892784 cembSR088 AT5G45230 protein (TIR-NBS- signal transduction LRR class) family 97
Encodes a ATP binding, protein Arabidopsis ortholog serine/threonine kinase of the ATR protein activity,response to gamma JZ892785 cembSR089 AT5G40820 kinase radiation, telomere maintenance in response to DNA damage, telomere maintenance via telomerase 18SrRNA Translation, molecular function JZ892786 cembSR090 AT3G41768 unknown
NAD(P)-binding Oxidoreductase activity, binding, Rossmann-fold catalytic activity, oxidation JZ892787 cembSR091 AT4G03140 superfamily protein reduction, metabolic process
InterPro DOMAIN/s: Ubiquitin-protein transferase Galactose activity oxidase/kelch, beta- JZ892788 cembSR092 AT5G01660 propeller (InterPro:IPR011043)
Pseudogene, Molecular and biological JZ892790 cembSR094 AT1G11806 hypothetical protein functions unknown
Transducin/WD40 Nucleotide binding, Signal JZ892791 cembSR095 AT3G06880 repeat-like transduction superfamily protein CONTAINS InterPro Molecular and biological DOMAIN/s: Dilute functions unknown JZ892792 cembSR096 AT5G20450 (InterPro:IPR002710)
Beta glucosidase 2 Beta-glucosidase activity, (BGLU2) hydrolase activity, hydrolyzing JZ892793 cembSR097 AT5G16580 O-glycosyl compounds, carbohydrate metabolic process
DNA polymerase V DNA binding, DNA-directed family DNA polymerase activity, DNA JZ892794 cembSR098 AT5G64420 replication, transcription, DNA- templated
Member of CYP81H Oxygen binding JZ892795 cembSR099 AT4G37310
COP1-interacting Transcription cofactor activity, protein 4, a nuclear- Regulation of nucleic acid- localized positive templated transcription, JZ892796 cembSR100 AT5G37190 regulator of regulation of photomorphogenesis arabidopsis photomorphogenesis BES1/BZR1 DNA binding, regulation of homolog 4 (BEH4) transcription, DNA-templated, JZ892797 cembSR101 AT1G78700 transcription, DNA-templated
Endonuclease/exonuc DNA-(apurinic or apyrimidinic JZ892798 cembSR102 AT4G36050 lease/phosphatase site) lyase activity, exonuclease 98
family protein activity, DNA repair
Encodes IAA-amino IAA-Ala conjugate hydrolase acid hydrolase activity, IAA-amino acid conjugate hydrolase activity, JZ892799 cembSR103 AT5G56660 metallopeptidase activity, auxin metabolic process, proteolysis
NAD(P)-binding Oxidoreductase activity, binding, JZ892800 cembSR104 AT4G03140 Rossmann-fold catalytic activity superfamily protein Leucine-rich repeat ATP binding, kinase activity, protein kinase family protein serine/threonine kinase JZ892801 cembSR105 AT5G65240 protein activity, protein phosphorylation
Exostosin family Catalytic activity JZ892802 cembSR106 AT5G37000 protein Encodes a member of ACP phosphopantetheine the mitochondrial attachment site binding involved acyl carrier protein in fatty acid biosynthetic process, (ACP) family protein binding, cobalt ion JZ892803 cembSR107 AT1G65290 binding, metal ion binding, fatty acid biosynthetic process, oxidation-reduction process
Molecular and biological functions unknown JZ892804 cembSR108 AT5G13560 Unknown protein
99
4.11 The cDNA MICROARRAY 4.12 TARGET PREPARATION (cDNA labeling with cy3 and cy5 probes)
The RNA required for cDNA probe labeling was of very fine quality. Total RNA extracted from control and drought stressed leaf epidermis samples of Agave sisalana L. was used for cDNA synthesis and then was indirectly labeled with fluorochromes cyanine-3 (Cy3) (182) and cyanine-5 (Cy5) (183). A program "microarray" on Nanodrop (ND-1000) finalizes the quality of labeled cDNA (Figure 31).
Figure 31: Qualitative and quantitative confirmation of labeled cDNA by nanodrop (ND-1000)
100
4.13 CHIP HYBRIDIZATION AND SCANNING
The labeled cDNAs (probes) made with control and stressed total RNA were hybridized with the Agave sisalana L. cDNA microarray platform. cDNA microarray chips hybridized with labeled probes were put in hybridizer for 18 hours. After hybridization, cDNA chips were carefully washed in different concentrations of SSC buffer. Scanning was done in UC4×4 (Genomic solution) scanner which generated the tiff image (Figure 32). The tiff image clearly indicates the grids, position of the spots, area between the sub-grids, morphology of spots and overall equal expression of spotted cDNAs.
Figure 32: Microarray image showing scanned image of hybridized slide
101
4.14 DATA NORMALIZATION The purpose of data normalization was to adjust data in order to avoid technical biological differences among the control and treated samples. There is always lacking of similarity between the replicates after hybridization process and these differences at the end lead to irregular fluorescence intensity among subarrays in single cDNA chip.
4.14.1 R-I Plot
GAPDH, along with lowess normalization was used to normalize the signal intensities of spots within the array and between the arrays. Total intensity in combination with lowess normalization was used to normalize the data between the cDNA arrays. Cy3 and Cy5 normalization intensities were alloted relative to fitted curve. The R-I plot intensities graph determined the overall expression and distribution of spots on the scale and was calculated by (log2 [/(b)/(a)] against log10[/(a)-/(b)]. a and b represented median intensities of labeled probes Cy5 and Cy3. LOWESS normalization data graph showed that most spots were present between -2 to +2 log ratios ranges. It indicated equal and quality expression of data spots between control and drought stressed samples (Figure 33A and Figure 33 B).
4.14.2 Z-SCORE HISTOGRAM
A histogram made from the array intensity levels was used to graphically distribute the unequal data set. It represented center, spread and skewness of data. It also indicated outliers and multiple modes' presence in the data. These characteristic features showed strong and proper distributional model for any data set. Most commonly used form of the histogram was obtained by dividing the total data range into half-sized bins known as classes. Then the numbers of points falling in to each class were counted. The x-axis or vertical axis determined the frequency signals intensity found in each array (probe density) and y-axis or horizontal axis determined Z score (probe intensity) and considered as response variable. The probe intensity graph for z histogram lie along x- axis varied from -5 to +4 before normalization and between range of -4 to +4 after data normalization. The Z-histogram cleared the picture of good quality data by a symmetric, moderate tailed distribution which was bell shaped. Linear normal probability plot also showed normal distribution among control and drought treated samples(Figure 34A and Figure 34B).
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Figure 33A: R-I plot for non-normalized data
103
Figure 33 B: R-I plot for normalized data
104
Figure 34A: Z-score histogram for non- normalized data
105
Figure 34B: Z-score histogram for normalized data
106
4.14.3 Box Plot
Box plots are very useful graphs that properly shape the distribution of the data, its central point (median), and determine the variability in terms of minimum and maximum values in inter-quartile range. In other words it is an excellent tool for determining the location and data variation in the data sets. Either end of the box shows the upper and lower range of quartile. The middle line of the box indicates the median point. Whiskers are the horizontal lines connected to the box representing the largest and smallest values not considered outliers. Graphically vertical axis represents signal intensity whereas horizontal axis represents the factor of interest (array). The box plot is an important quality tool for determining if a factor has a significant effect on the response with respect to either location or variation. Box plot graph showed that all the blocks in the array have significant effect on normalized intensity graph with respect to location than non-normalized data. In normalized data, the inter quartile range for normalized spots ranged from -1.0 to +1 (Figure 35A and Figure 35B).
4.15 SIGNIFICANCE ANALYSIS OF MICROARRAY (SAM)
For the analyses of differentially expressed genes SAM plot analysis was used. Each gene showed different score on the basis of its differential expression from the standard score. Those genes showing highly significant values were differentially expressed. Falsely identified genes percentage also helped in getting accuracy in SAM analysis and it was termed as false discovery Rate (FDR). SAM plot showed 126 significantly expressed genes with 1.09 % false discovery rate and 1.37% median value (Figure 36).
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Figure 35A: Box plot for non-normalized data
108
Figure 35B: Box plot for normalized data
109
Significant: 126 SAM Plotsheet Tail strength (%): 38 Median number of false positives: 1.37 se (%): 56.5 8 False Discovery Rate (%): 1.09
6
4
2
0
ObservedScore -4 -3 -2 -1 0 1 2 3 4
-2
-4
-6 Expected Score
Figure 36: SAM plot analyses of differentially expressed cDNA clones
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4.16 BIOINFORMATIC STUDIES OF DIFFERENTIALLY EXPRESSED cDNA
CLONES
The differentially expressed cDNA clones were subjected to Blast2Go for their functional categorization on the basis of cellular components, molecular functions and biological processes.The differentially expressed cDNA clones were homologous with blast top hit species Phoenix dactylifera followed by Arabidopsis thaliana, Populus euphratica and Elaeis guineesis respectively (Figure 37). The blast2GO molecular function categorization revealed that differentially expressed candidate ESTs were mostly involved in fatty acyl coA binding followed by phosphatidylcholine binding, hydrolase activity and alcohol dehydrogenase NAD activity respectiv0ely (Figure 38).The blast2GO hits for biological processes revealed that differentially expressed cDNA clones of Agave sisalana L. were involved in the cellular, metabolic, transport, DNA-dependent response to abiotic or biotic stimulus and unknown biological processes respectively (Figure 39).
Figure 37: Agave sisalana potential drought stress candidate ESTs distribution with top hit species
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Figure 38: Agave sisalana potential drought stress candidate ESTs molecular functional categorization
Figure 39: Agave sisalana potential drought stress candidate ESTs cellular component categorization
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4.17 MICROARRAY DATA ANALYSIS
Ten clones showed significant (P ≤ 0.05) mean expression ratio (log2) >1.5 fold expression differences in drought stressed epidermis leaves of Agave sisalana L. after microarray data analysis. These ten clones with upregulated gene expression showed homology with drought stressed genes of other land plants. Already sequenced ESTs were further used for real time analyses. The EST sequences of potential candidates for drought stressed Agave genes were BLAST to search for homology in NCBI GenBank against nucleotide, EST and protein data bases, using BLASTX and BLASTN. All ESTs showed significant homology to NCBI GenBank nucleotide and protein data bases. Six ESTs have shown homology in all three database whereas four ESTs have shown homology to only nucleotide database (Table 11).
4.18 K MEANS CLUSTERING AND EXPRESSION GRAPH
Clustering microarray data by k-means, SOM (self organizing maps) and hierarchical clustering helped in identification and final interpretation of the microarray data. For the quantification of signals processing data, k-means clustering was used. It separated and divided observations in to k clusters and at the end the mean of all the clusters serve as model to that particular number of n clusters. Heat map of these clusters showed differential expression pattern of Agave sisalana genes responsible for drought tolerance (Figure 40).
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Table 11: Agave sisalana L. drought stressed potential candidates ESTs, their accession numbers, and homology with NCBI genbank against nucleotide and protein data bases.
AT GenBank Clone Id EST blast Nucleotide blast Protein blast Accession Acc Barley EST library Populus trichocarpa UBIQUITIN Hordeum vulgare Sequence ID: EXTENSION protein 1 Sequence ID: ref|XM_006372884.1| [Populus trichocarpa] AT4G02890 JZ892726 CIPG374D28 gb|CV059814.1| Populus trichocarpa UBIQUITIN 11 family protein
Abiotic stressed Populus Sequence ID: PREDICTED: berries of Vitis emb|CU231858.1| uncharacterized protein vinifera var. Populus EST from mild LOC103714481 [Phoenix Chardonnay Vitis drought-stressed leaves dactylifera] AT1G23990 JZ892731 CIPG3710D76 vinifera cDNA clone. Sequence ID: gb|CD711691.1|
cDNA library Vitis Populus Non significant vinifera Sequence ID: homology Sequence ID: emb|CU226724.1| emb|FQ468049.1| Populus EST from severe AT3G54060 JZ892733 CIPG3710H80 drought-stressed leaves
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Eucalyptus Elaeis guineensis Sequence Non significant homology globulus C14 ID: ref|XM_010923208.1| clone root apex PREDICTED: Elaeis under water stress guineensis universal stress AT5G23170 JZ892743 CIPG11B210 Eucalyptus protein A-like protein globulus cDNA (LOC105045049), mRNA Sequence ID: gb|GW337404.1|
Embrapa_Musa_C Populus Non significant homology achaco_ABB_ Sequence ID: Stressed Musa emb|CU226444.1| ABB Group Populus EST from severe AT5G65690 JZ892752 CIPG122C11 cDNA, mRNA drought-stressed leaves sequence. Sequence ID: gb|FL668233.1|
Asparagus Agave americana Non significant homology officinalis cDNA Sequence ID: clone aof01- gb|KC704976.1| 11ms1-a03 5', Agave americana isolate
mRNA sequence. PDBK2012-0043 ATP AT4G19650 JZ892755 CIPG125H40 synthase CF0 subunit I
(atpF) and ATP synthase CF0 subunit III (atpH) genes, partial cds; plastid
Elaeis guineensis Catharanthus roseus JZ892761 universal stress AT2G21620 JZ892761 CIPG129D68 root Elaeis Sequence ID: family protein [Populus guineensis cDNA gb|KJ634222.1| trichocarpa] 115
clone Catharanthus roseus clone Sequence ID: 42-166 putative universal gb|EL691283.1| stress protein mRNA, complete cds
Solanum Populus hypothetical protein lycopersicum Sequence ID: POPTR_0003s10270g cDNA, mRNA emb|CU229903.1| [Populus trichocarpa] sequence. Populus EST from mild AT1G31812 JZ892778 CIPG267F54 Sequence ID: drought-stressed leaves gb|GT168496.1|
Asparagus Elaeis guineensis Sequence PREDICTED: zerumbone officinalis cDNA ID: ref|XM_010933280.1| synthase-like [Elaeis clone aof01-2ms2- PREDICTED: Elaeis guineensis] AT4G03140 g08 5', mRNA guineensis zerumbone JZ892787 CIPG182B10 sequence. synthase-like Sequence ID: (LOC105052461), mRNA gb|CV291903.1|
Agave americana PREDICTED: RING-H2 Sequence finger protein ATL57-like ID: gb|JQ671429.1| [Musa acuminata subsp. No homology Agave americana malaccensis] AT5G37190 JZ892796 CIPG1812E93 chloroplast small heat shock protein (sHSP) gene, complete cds; nuclear gene for chloroplast product
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Transmembrane receptor protein serine/threonine kinase activity
Single-stranded DNA binding, DNA replication
GTPase activity, structural constituent of cytoskeleton
Single-stranded DNA binding, DNA replication
Defense response to fungus, killing of cells of other organism
Figure 40: Heat map analysis showing the differential expression of up regulated genes in epidermal leaves of Agave sisalana L.
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4.19 MICROARRAY RESULTS VALIDATION STUDIES BY REAL TIME PCR
Agave sisalana‟s potential drought ESTs were further checked for their expression through real time PCR to reduce any false positive results. Six transcripts from differentially expressed genes were selected for real-time RT-PCR. GAPDH gene was taken as the reference control to normalize the final expression levels. Selected transcripts showed different level of expression in drought stressed leaves of Agave sisalana L. as compared to control and these results were the confirmation of microarray data.
Real time data analysis confirmed the overall significant expression of up-regulated EST‟s (JZ892726 and JZ892752) up to 1.9 folds expression whereas EST (JZ892743, JZ892761 and JZ892787) showed less than 0.5 fold expression level under abiotic stress conditions. EST JZ892778 showed no expression or upregulated activity in stressed leaves of Agave sisalana L. Similar expression of two up-regulated ESTs (JZ892726 and JZ892752) was observed in expression behaviour and fold change studied in K means cluster analyses of microarray (Figure 41).
4
3.5
3
2.5
2 Control 1.5 Treated
1
0.5
0 JZ892726 JZ892752 JZ892743 JZ892761 JZ892787 JZ892778 Drought stressed ESTs of Agave sisalana
Figure 41: Relative fold expression of candidate ESTs of Agave sisalana L. in control and droughted plants through real-time PCR 118
5. DISCUSSION
5.1 EFFECT OF DROUGHT STRESS ON EPIDERMAL TISSUE OF AGAVE SISALANA LEAVES
Under drought stressed conditions, plants experienced anatomical changes to save water in the leaves which are the main organ of controlling internal water balance. Such alterations mainly comprised an increase in cuticle thickness and density of stomata, epidermal and mesophyll cells. A striking anatomical change observed in the leaf epidermal tissues of Agave sisalana under water stress was partially closed and open stomata under control and treated (10 and 2% FC) conditions. The size and walls of the epidermal cells play an important role against cell collapsing and death in arid and semi-arid conditions according to Oertli et al., (1990). An important role linked with the survival of the plants under adverse drought conditions is played by plant leaf stomata. Many xerophytes including Agave sisalana save their internal water by developing depressions or crypts with in their leaf epidermis (Fahn and Cutler 1992). Closed stomata under drought stress also correlates decreased photosynthetic and transpiration rate and stomatal conductance.
5.2 EFFECT OF DROUGHT STRESS ON PHYSIOLOGICAL BEHAVIOUR OF AGAVE SISALANA
Drought stress has a major impact on the gas exchange characteristics of the plants and this is mainly due to the impaired photosynthetic machinery, stomatal closure to prevent the transpirational water loss, early leaf senescence, oxidation of chloroplast lipids and changes in structure of pigments and proteins (Vijayalakshmi et al., 2012).
Agave sisalana plants treated with 2 and 10% FC drought stress, when compared with control or well watered plants showed a decreased pattern in all the physiological parameters. The significant decrease in photosynthetic activity of treated plants under drought stress is in accordance with the previous studies conducted on maize plants as reported by Anjum et al. (2011a) and Jabeen et al. (2008). It was also reported earlier by many researchers that as photosynthetic rate reduced, it also caused reduction in transpiration rate and CO2 uptake in drought stressed plants. Photosynthetic activity in plants is greatly hampered by the 119 unavailability of water because of the combined effect of stomatal and no stomatal mechanisms. (Mc Michael and Hesketh, 1982; Turner et al., 1986). Drought stress decreased photosynthetic carbon assimilation because of the stomatal closure which cause an overall reduction in the internal leaf CO2 concentration (Ennahli and Earl2005).
Another study on cotton crop under drought stress conditions reported that net photosynthesis, stomatal conductance and transpiration rate started decreasing with the onset of water unavailability (Leidi et al., 1993). Decreasing trend of photosynthetic activity of plants under drought stress mainly occurs due to stomatal closure and low protoplasm activity. But when the adverse effects of drought become unavoidable these repetitive water stress cycles develop immunity in plant in the form of adaptability to that particular stressed environment. (Matthews et al.,1990). Our results are strongly supported by Matthews et al (1990) and Leidi et al. (1993).
Transpiration rate (E) of Agave sisalana was found lower in drought stressed plants as compared to control plants. It has been reported earlier that in many crops, transpirational activity declines when only one third part of the extractable soil moisture has been left in the root zone (Henson et al., 1989; Ameglio et al., 2000). On the other hand increase in transpiration rate under drought stress has also been reported in many crops (Jones, 1992), because of the fact that only partial stomatal closure under increased drought stress resulted in reduction in transpiration as compared to dry matter production (Nguyen et al., 1997; Nobel, 1999). Environmental abiotic stresses directly influence photosynthetic machinery by disrupting all important components of photosynthesis like thylakoid electron transport, carbon reduction cycle, stomatal control of CO2, with accumulation of carbohydrates, destruction of membrane lipids and overall disturbance of water balance (Allen and Ort, 2001). Any crop having tendency to cope with different environmental stresses is directly or indirectly linked with their ability to withstand at the level of photosynthesis, which in turn affects transpiration, stomatal conductance and overall growth of the plant (Chandra, 2003). In short water deficiency may lead to various physiological disorders and the most important among them are photosynthesis and transpiration (Saccardy et al., 1998). In order to prevent water loss, plants closed their guard cells (stomata) present on the leaf which ultimately 120 cause poor plant growth by lowering the photosynthetic and transpirational activity (Ashraf and Ibram, 2005).
Stomatal closure is another earlier response to drought which gives protection to plants from heavy water loss that progress to a noticeable decrease in stomatal and mesophyll conductance, increases intercellular CO2 concentration and decreases photosynthetic rate (Chaves et al., 2003). Plants respond differently in control and water deficit conditions for stomatal conductance. Our results are supported by Flexas and Medrano, (2002) as they reported that stomatal closure leads to decrease in photosynthetic rate, inadequate CO2 availability and Rubisco activity under water deficiency in plants. Our findings also revealed that all factors correlate one way or the other, which decreased CO2/O2 ratio in leaves and impaired photosynthesis process (Janson et al., 2004; Moussa, 2006). Considering the past findings and current information on drought-induced responses, it is obvious that stomata get closed with progressively increased drought stress. It is well documented that there is a good correlation between leaf water status and stomatal conductance and water deficiency inculcates root-to-leaf signaling, promoted by soil dehydration through the transpiration process thus resulting in stomatal closure. Therefore, stomatal closure reported in any crop in response to water deficit condition is the first step to control water loss and internal water balance for plant survival (Chaves, 1991; Cornic and Massacci, 1996). There are many causes of stomatal closure other than reduced water potential or leaf turgor and that is low humidity in the agroecosystem. Stomatal responses are closely linked with moisture content of soil rather than with leaf water status (Maroco et al., 1997).
However Agave species possess special morphological processes that include the changes in the stomata opening and adaptations like water holding capacity, the succulent leaves, and expanded vacuoles resulting in an increased accumulation of organic acids (Nobel, 1988). The accumulation of fructans and uncommon carbohydrate might also contribute for the apatation of agave plants to semi-arid and arid regions (Hendry, 1993). The fructans play a very important role in protecting the desert plant under adverse environmental conditions such as cold, heat and drought by stabilizing the cell membrane integrity (Ritsema and Smeekens, 2003; Saldana, 2006). All these factors seem to be 121 involved in the evolution of Agave plants in adverse environment conditions and their adaptation to the dry, arid and semi-arid habitats.
Water use efficiency increases with the increase in drought stress, but in this study the results showed contradictory values with a markable difference among control and 10 and 2% FC water stressed Agave sisalana plants. These results are supported by the work of Jabeen et al., (2008) as the water use efficiency differs significantly among various cultivars. Drought tolerant plants retain water-use efficiency by preventing the water loss. But in drought stressed conditions where plant experienced other physiological disorders, water-use efficiency also decreased significantly (Anjum et al 2011). Our results are also in accordance with the findings of Anjum et al., (2011). Various physiological parameters need to be studied when dealing with water use efficiency. These parameters include stomatal regulation for gaseous exchange, plant development and functional regulation, photosynthetic activity of the mesophyll, and increase in root hydraulic conductivity with osmotic adjustment (Bacon, 2004).
Water use efficiency mainly depends upon the morphological characteristics of plant i.e., leaf size, canopy structure and position (Krieg, 2000). It has been reported earlier that WUE is directly associated with photosynthesis (Radin, 1992) because stomatal closure is closely tied with photosynthetic ability of plant. Since the genes involved in stomatal mechanisms also regulates WUE (Chaves et al., 2004), hence discussion on WUE revolves around gas exchange characteristics of plants via the stomata.
5.3 WATER RELATED ATTRIBUTES AND LEAF SURFACE AREA OF AGAVE SISALANA L.
Relative water content is an indicator which reflects the plant‟s inner strength to carry out the metabolic activities in tissues and an index for dehydration tolerance. Our findings in this experiment are in accordance with Moussa & Abdel-Aziz (2008) who reported the decline in RWC in maize plants under drought stress. Another study by Yang and Miao, (2010) also reported that poplar species subjected to progressive water stress showed reduction of RWC in the drought stressed cuttings i.e., Populus cathayana 23.3% and Populus kangdingensis 16%. Nayyar and Gupta (2006) revealed that as the leaves progressed 122 to drought, they exhibited larger reductions in water potential, decreased the RWC, leaf water potential and transpiration rate with considerable change in leaf temperature and overall plant metabolic activities. Plants‟ exposure to severe water stress eventually decreased water turgor pressure and leaf water potential, transpiration rate, relative water content with significant increase in leaf temperature (Siddique et al., 2001). The maintenance of water turgor pressure above a particular level is key to success in many physiological processes taking place in the plants all the time such as photosynthesis, cell expansion, CO2 and oxygen exchange and activity of many enzymes required for growth and maintenance. These processes get affected by drought in the absence of water turgor pressure (Taiz and Zeiger, 2009) which is more likely to be associated with reduction in the plant growth ratio than leaf water potential (Silva et al., 2010).
Leaf surface area was also reduced in droughted plants when compared to the control. Our results have been supported by the findings of Sankar et al. (2007), as they reported the decrease in leaf area after 50 to 70 days of drought stress. Drought stress results in reduced number of leaves, individual leaf size and leaf life span when subjected to longer droughts. Expansion in leaf area mainly depends upon leaf temperature and water turgor pressure for supply and plant growth. Drought imposed reduction in leaf area always associated with reduction in photosynthetic and transpiration rate (Rucker et al., 1995). Clauw et al. (2015) also studied the plant responses exposed to drought stress in Arabidopsis thaliana. Mild drought stress decreased both leaf cell number and leaf cell area without disturbing the stomatal index.
5.4 EFFECT OF DROUGHT STRESS ON BIOCHEMICAL ATTRIBUTES OF AGAVE SISALANA L.
Proline and other osmolytes‟ accumulation protects the cell membranes and proteins in plants subjected to abiotic traumas. It also regulates mitochondrial functions, influences cell division or death and regulates specific gene expression required for immediate plants‟ recovery after stress (Szabados and Savoure´, 2009). They maintain the quaternary structure of proteins and membrane integrity under water deficit condition and cause photoinhibition (Demiral and Turkan, 2004). Furthermore, it helps in stabilizing sub-cellular structures, 123 scavenging free radicals, buffering cellular redox potential under drought stress conditions (Ashraf and Foolad, 2007). Increased concentration of proline reported in the present study has already been discussed in many researches related to drought-stressed wheat (Hamada, 2000), sorghum (Yadav et al.,2005), bell pepper (Nath et al., 2005) and maize (Anjum et al., 2011b). Generally, proline accumulation is higher in stress-tolerant plants as compared to stress susceptible due to variation in proline-oxidase production which may be an adaptability of the plants to combat the stress environment (Sankar et al., 2007). In current study proline content was significantly higher in droughted as comapred to control plants. Plant metabolites like proline produced in response to any stress also function as a molecular chaperone and compatible osmolyte which protect protein structures integrity and boost up the activities of different enzymes (Lopez et al. 1994; Abdel- Nasser and Abdel-Aal 2002). It has been stated that proline contents in the leaves of plants are produced by several abiotic stresses including drought, salt and cold stress (Lopez et al. 1994; Lee and Liu 1999; Hernandez et al. 2000; De Ronde et al. 2000; Parida et al. 2002; Abdel-Nasser and Abdel- Aal 2002). Thus, it is concluded that the drastic increase in proline contents under drought stressed condition is an adaptive mechanism in Agave sisalana L. This increased production of proline under stress in many plant cultivars has been linked with stress tolerance and plant adaptation and is generally higher in stress-tolerant rather than in stress-sensitive plants.
Another biochemical marker for drought stress is malondialdehyde (MDA) produced by lipid peroxidation damage by free radicals or generation of ROS (Farooq et al., 2009). These reactive oxygen species directly attack membrane lipids and increase lipid peroxidation and the content of MDA (Mittler, 2002). Our results are in accordance with the findings of Meloni et al., (2003) and Sakhanokho et al., (2004) who reported that MDA content has been increased in the leaves under drought intensity which results in poor membrane stability, decreased chlorophyll content and finally results in ion leakage. Chlorophyll content is another key indicator for determination of plant metabolic rate (Mohammed et al., 2013). It is a major chloroplast component for photosynthesis and is directly involved in the phosynthetic activity of plants. The decrease in chlorophyll content due to any abiotic stress factor cause oxidative stress and may result in chlorophyll degradation and pigment photo-oxidation. Chlorophyll is important to plants because it harvest light from sun to run photosynthetic machinery. Chlorophyll a and b both are 124 susceptible to soil dehydration (Farooq et al., 2009). In the present study, decrease in chlorophyll content in drought stressed plants is in agreement with already reported findings in Triticum aestivum cultivars (Nyachiro et al., 2001), various sunflower varieties (Manivannan et al., 2007b) and olive cultivars (Guerfel et al., 2009). But many researchers also reported decreased or sometimes unchanged chlorophyll content under drought stress conditions in many species depending on the longevity and severity of drought (Kypyoarissis et al., 1995; Zhang and Kirkham, 1996). Transcriptomic analysis of premature leaf tissues of Arabidopsis thaliana identified 354 genes that were expressed differentially under mild drought stress (Clauw et al., 2015). Their results reported the existence of quick responses with different genetic origin to mild drought imposition in developing leaves. These responses involved signaling by certain metabolites like abscisic acid and proline metabolism.
5.5 CORRELATION BETWEEN PHYSIOLOGICAL, BIOCHEMICAL AND WATER RELATED ATTRIBUTES
The physiological, biochemical and molecular responses generated at the expense of drought stress tolerance have been correlated in various crop plants. Plants subjected to stresses tend to restrict their growth, development and survival. Moisture unavailability affects almost every plant process right from photosynthesis, chloroplast organisation to every enzyme activity at cellular level. In other words, all biotic and abiotic factors correlate in an agro-ecosystem.
Reduction in photosynthesis, transpiration and stomatal conductance directly correlates with the production of plant osmolytes like proline and ROS under water deficit condition which help the plants to survive and sustain life even when the conditions are not favorable. This study on Agave sisalana also revealed that as the drought stress progressed, the Agave plants produced increased concentration of proline and MDA content with decreased photosynthesis, transpiration, stomatal conductance, water use efficiency, relative water content, reduced leaf surface area and closed and partially closed stomata.
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5.6 cDNA LIBRARY CONSTRUCTION AND EXPRESSION PROFILING OF AGAVE SISALANA L.
The aim of this project was to find new genes in Agave sisalana L. under drought stressed conditions. For this purpose progeny development, drought stress optimization and cDNA library construction of drought stressed epidermal tissue was done. Clones were amplified and sequenced to determine the quality of the cDNA library. After that, expression profiling of sequenced and non-sequenced cDNA clones was done with the help of microarray. Till to date no work has been reported on Agave sisalana L. So this project developed an effective stage for further expressed sequence tags acquisition and differentially expressed genes discovery. As mentioned by Seki et al., (2002), genome sequencing is necessary for the acquisition of full-length cDNAs and their final expressed products under abiotic stresses. In 2003, Wiemann et al., also considered cDNA library as useful tool for the identification and discovery of differentially expressed genes.
One hundred and five ESTs have been generated from the drought stressed Agave sisalana L. cDNA library. Maximum significant homology was found with another land plant Populus trichocarpa. The results also predicted the full potential of Agave sisalana plant to express upregulated drought tolerant genes under drought stress environment for future scientists.
EST JZ892707 shows significant homology with stromal cell-derived factor2 (SDF2)-type proteins. They are highly conserved throughout the plant kingdom. Plants under different environmental stresses showed a protective response known as UPR (Unfolded Protein Response) in the Endoplasmic Reticulum. In 2010, Schott et al., reported AtSDF2 as an important component of unfolded Protein Response in Arabidopsis thaliana and transgenic plants tend to produce SDF2 due to Endoplasmic Reticulum stress. Thus SDF2 tends to involve in evolution of plants but its precise and controlled molecular function is still unknown (Schott and Strahl, 2011).
EST JZ892708 shows similarity with Starch synthase 4 (SS4). This is an important component of a molecular process that is involved in granule formation when the leaf expanding and chloroplast division takes place resulting in discoid and flattened shape of leaf 126 starch granules (Crumpton-Taylor M et al., 2013). Starch synthase gene possessed the transferase activity of glycosyl groups and protein binding during granule formation.
EST JZ892709 resembles with somatic embryogenesis receptor-like kinase 5 (SERK5). SERK5 gene belongs to a family of plant receptor kinases that are involved in various signaling pathways, and work as crucial regulators in various physiological processes like brassinosteroid signaling, pathogenesis, cell death control and pollen development (Wangze Wu et al., 2015). Receptor-like kinases also caused initiation of many cellular responses under multiple environmental challenges (Catherine Albrecht et al., 2008).
Ribosomes are ribonucleoprotein complexes which are engaged in translation process and are essential for growth. EST JZ892710 shows high affinity with Arabidopsis ribosomal proteins S13/S18 family that are highly expressed under stressful environment of insufficient amount of phosphate and iron availability to plants causing alteration in ribosomal composition. (Jinyan Wang et al., 2013). Ribosomal proteins S13/S18 family regulates rRNA binding, ribosome biogenesis, structural constituent of ribosome and translation process.
EST JZ892711 closely correlates with Alpha-tubulin genes primarily expressed in stamens and in mature pollen. These genes play an important role in GTPase activity, GTP binding, cytoskeleton building, protein polymerization and microtubule-based process. Carpenter J.L. et al., (1992) reported multiple alpha-tubulin (TUA) and beta-tubulin genes expression of Arabidopsis thaliana in pollen. They provide evidence that TUA1 gene expressed primarily in pollen.
EST JZ892712 belongs to the Basic Helix–Loop–Helix protein family known as multigene family of transcription factors. In Arabidopsis thaliana genome, 133 bHLH genes have been discovered and expressed so far. But as compared with animal orthologs, relatively small number of plant bHLH proteins have functionally characterized. Based on limited characterization of plant bHLH proteins, Heim et al., (2003) predicted that transcription factors of this family played different roles in plant metabolism, cell and tissue development. Rice genome has also been investigated for the presence of these proteins and their functions in abiotic stresses. OsbHLH1 gene caused response to cold stress (Wang et 127 al., 2003) whereas RERJ1gene produced response against wound and drought (Kiribuchi et al., 2005).
EST JZ892713 correlates with organeller single stranded DNA binding protein 1 in Arabidopsis thaliana. OSB1 tends to act as a novel motif necessary for single strand DNA binding and DNA replication in plants (Vincent Zaegel et al., 2006).
Protein kinase superfamily CDPK-SnRK comprised seven different types of serine threonine protein kinases and EST JZ892714 is one of those kinase related proteins. These proteins are mainly involved in protein phosphorylation, protein kinase activity and ATP binding. CDPKs and SnRKs are present on all five chromosomes of Arabidopsis thaliana (Hrabak et al., 2003).
ESTs JZ892715 and JZ892810 shows homology with Gypsy-like retrotransposon family proteins but their molecular functionality is still unknown. Arabidopsis thaliana contains several retrotransposon elements in their mitochondrial genome. These elements originated from three classes of nuclear retrotransposons, non-LTR/LINE family, the Tyl/copia,and Ty3/gypsy. Out of these three families, members of the Ty3/gypsy group are still not identified in the nuclear genome of Arabidopsis. (Knoop et al., 1996).
EST JZ892716 encodes a defensin-like (DEFL) family protein. This is a secretary protein produced in response to fungus and killing cells of other organism. Matthew, W. et al. (2007) also reported defensing-like small secreted molecules and identified DEFL families of proteins. EST JZ892717 relates to Ubiquinol-cytochrome C chaperone family protein. Ubiquinol-cytochrome C belongs to the family of oxidoreductases, specifically those acting on diphenols and related substances as donor with a cytochrome as acceptor. This enzyme participates in oxidative phosphorylation and is involved in the biochemical generation of ATP.
EST‟s (JZ892718 and JZ892805) have resemblance with vacuolar protein sorting- associated protein 28 homolog 1 (VPS28-1). Its main functions include protein binding and transporter activity. In Arabidopsis thaliana, there are seven members in vacuolar sorting receptor (VSR) family. Many researchers suggest that vacuole sorting receptors get interacted with sorting signals from many different VSR proteins in vitro (Watanabe et al., 128
2002; Jolliffe et al., 2004; Fujiiet al., 2007). They are present at the trans-Golgi network (TGN), and PVC i.e pre-vacuolar compartment in Arabidopsis thaliana (Sanderfoot et al., 1998) and are involved in vacuolar cargo sorting (daSilva et al., 2005; Oliviusson et al., 2006; Niemes et al., 2010).
Abiotic factors such as temperature, drought, UV-light, salinity and irradiance affect photosynthesis in plants. Chloroplasts in plants have photosystem I and II present in thyllakoid membranes. Both systems PSI and II are made up of chlorophyll a/b-binding proteins which form light-harvesting antenna complexes (LHC) around these photosystems i.e. PSI (LHCI) and PSII (LHCII) respectively. EST JZ892721 is closely related to LHCA2 PSI Light Harvesting Complex Gene. Several findings have been reported on electron transport activities that took place under salt and light stress condition in the thyllakoid membranes.
Activation of plant retrotransposons by biotic and abiotic factors is common in eukaryotes specially plants. Their activity seems to be closely linked with the molecular pathways that are governed by cis-regulatory transcripts that function in plant defense mechanism. EST JZ892722 also relates to Non-LTR retrotransposon family (LINE). These retrotransposons are highly variable and get evolved just because of the changings in their regulatory features (Grandbastien, 1992).
EST JZ892723 belongs to DSEL which is seed establishment and storage related Lipase in Arabidopsis thaliana. This enzyme is cytosolic acylhydrolase which showed prefential lipase activity for the sn-1 position of many lipid classes that includes 1,3- diacylglycerols and 1-monoacylglycerols (Kim, E.Y.et al., 2011).
EST JZ892724 shows homology with Tetratricopeptide repeat (TPR)-like superfamily protein in Arabidopsis. A large number of TPR family proteins are found in nature composed up of Tetratrico Peptide Repeats TPRs. These TPR repeats or motifs are further involved in PPI (protein-protein interaction) module that worked in regulation of different plant cellular functions. Arnaldoet al., 2006 have reported TTL1, a protein having TPR motifs involved in abscisic acid production and water stress tolerance. Recent studies in past few years have revealed that these proteins play an essential role in particular stimuli 129 response against ethylene, cytokinin, gibberellin and auxin production in Arabidopsis. Thus TPR proteins are emerging as key determinants for signaling pathways controlled by most plant hormones.
EST JZ892725 seems to be homologue of 3-beta hydroxysteroid dehydrogenase/isomerase family protein. This protein family is involved in many oxidation- reduction processes, dehydrogenase activity, steroid and sterol biosynthesis. The role of 3-β- hydroxysteroid is considered to play defensive role in rice against R. solani incidence (Lee et al., 2006). EST JZ892806 shows homology with Acyl-CoA N-acyltransferases (NAT) superfamily protein. In 2012, Maryet al., also reported significant role of acyl-CoA acyltransferases in peroxisomal lipid synthesis and N-acetyltransferase activity in the metabolic process.
EST JZ..892727 resembles Nodulin MtN21-like transporter family protein. Recent studies have highlighted the importance of nodulin-like proteins for the transport of nutrients, solutes, amino acids or hormones and for major aspects of plant development (Nicolas Denanceet al., 2014). Members of a small family of nodulin-like genes are regulated under iron deficiency in roots of Arabidopsis thaliana (Gollhofer et al.,2011).
EST JZ892729 has found significant similarity with WUS interacting protein. Plants exhibit different characteristics and modulations throughout their life for survival and that basically is carried out by meristems. This WUS proteins carry genes that encodes homeodomain of transcription factor that keep stem cells in the undifferentiated state in the apical shoot meristem. The mechanism used by WUS genes to inhibit the differentiation of meristem is still unknown. Martin etal.,in 2006 reported this protein in Arabidopsis thaliana known as WUSCHEL gene (WUS). They also suggested that WUS gene recruits transcriptional factors or corepressors to control the target gene that promotes differentiation of apical meristem. Therefore, the main function of WUSCHEL gene is stem cell maintenance in Arabidopsis thaliana.
EST JZ892732 shows homology with Arabidopsis homologue of autophagy 8b. This gene in Arabidopsis is involved in leaf starch degradation. Land plants contain transitory starch in their leaves which is a major photosynthetic product found in chloroplast. This 130 starch gets accumulated during the day and is further hydrolyzed into maltose and Glc in the night to aid the process of respiration and metabolic pathways. Recent studies on Arabidopsis thaliana pointed out that the degradation of leaf starch is aided by another non-plasticidal process known as autophagy. Thus autophagy took an active part in transitory starch degradation by hiding the small starch granule-like structure (SSGL) placed outside the chloroplast (Wang. et al., 2013).
Leucine-rich repeats (LRRs) are quite versatile protein-ligand interaction repeats or motifs found in many proteins having diverse functions of innate immunity and nervous system development and disease resistance (Jackie et al., 2007). ESTs JZ892736, JZ892774 and JZ892801 shows significant homology with leucine rich repeats. Shaohong Q. et al., in 2006 identified rice blast resistant gene Pi9 having six tandemly arranged resistance gene containing leucine rich repeats and nucleotide binding sites. They also reported that Pi9 gene gives a starting point to investigate molecular basis of disease resistance and further mechanisms of blast resistance gene clusters containing nuclear binding sites and leucine rich repeats in rice.
EST JZ892737 shows significant similarity with Pollen Ole e 1 allergen and extensin family protein. The biological function of this protein is still unknown but insilico studies confirm its contribution in the events of hydration, pollen physiology, germination, pollen tube growth and other reproductive functions (Alché et al. 1999, 2004, Tang et al., 2000, Stratford et al., 2001.) Heterologous proteins with related homology have been reported in other Oleaceae family members like fraxinus, privet, lilac and jasmine. The proteins encoded for tomato by LAT52 gene and for maize pollens by Zmc13 gene also exhibit significant homology with „Ole e 1‟ gene (Twell et al., 1989, Hanson et al., 1989)
EST JZ892738 belongs to SAUR-like auxin-responsive protein family. Auxin serves as central hormone in the regulation of plant life. Auxin‟s response is found maximum in roots which ultimately provides positional cue for distal organization and cell fate determination (Sabatini et al., 1999). When plants respond to auxin, they produced auxin/indole-3-acetic acid (Aux/IAA) proteins that are very short lived, the auxin response factors (ARFs) and protein degradation pathway components (Dharmasiri and Estelle, 2004). 131
ARFs bind themselves to promoters of auxin response elements in early auxin responsive genes (Guilfoyle and Hagen, 2001). Both Aux/IAA proteins and ARFs regulate auxin- mediated transcriptional signaling. The biological function of Auxin responsive factors is poorly understood. Yoko and his colleagues in 2005 reported the characterization and identification of T-DNA insertion lines of 18 ARF family members in Arabidopsis thaliana.The data suggested that the ARF proteins played important roles in auxin-mediated plant cells development and maintenance by regulating the overlapping of sets of target genes. These findings provideed molecular insight into unique functions exhibited by ARF gene family members found in Arabidopsis thaliana.
TRAF proteins also known as tumor necrosis factor receptor-associated proteins play an important role in plant metabolism, development and abiotic stress responses. EST JZ892740 showed a close homology with these TRAF-like family proteins. Recent studies confirmed that SINA2, a TRAF family protein played a crucial role in ABA related drought stress signaling in Arabidopsis (Bao et al., 2014). In Arabidopsis, SINA2 was significantly induced by ABA and drought treatment. Reduced drought tolerance was observed with the loss of function of this TRAF protein whereas over expression increased stomatal closure and decline in water loss under drought stress conditions. Therefore, it is involved in improving drought resistance in transgenic plants. After ABA treatment, overall expression of ABA and stress-responsive genes decline in the SINA2 mutant but goes higher in SINA2- overexpression. Therefore, drought response produced by SINA2, a TRAF protein was correlated with ABA. Bao Y. et al also elaborated the SINA2 function and considered it a molecular link between ABA signaling and drought tolerance in Arabidopsis.
EST JZ892745 is closely related to mRNA splicing factor and Thioredoxin-Like Tetratricopeptide Repeat. It is involved in reducing osmotic and NaCl tolerance that is further characterized by disorganization of the meristem tissue, reduced root elongation and impaired osmotic responses in seedling development and seed germination in Arabidopsis thaliana (Rosado et al., 2006).
EST‟s (JZ892746 and JZ892777) showed high homology with F-box/RNI-like/FBD- like domains-containing protein. F-box, a subunit of SCF (CDC53/F-box protein) and E3 132 ubiquitin ligases play an essential role in plant growth, maintenance and development, (Deshaies, 1999). They are also involved in multiple phytohormone signaling mechanisms like auxin and ethylene production (Moon et al., 2004).
EST JZ892811 showed catalytic functionality with the homologues of Arabidopsis thaliana. PRT family proteins and their homologues are catalytic in function and their regulatory proteins showed activity in nucleotide synthesis. Recent findings on new crystal structures also revealed important features of PRT protein function, as well as picture of how protein folds evolved to conduct both regulatory and catalytic functions (Sangita and Janet, 2001).
EST JZ892756 belongs to LisH/CRA/RING-U-box domains-containing proteins. The U box is a modified RING finger that is a base domain involved in ubiquitination. This is an interesting group of regulatory proteins containing (RING) zinc finger domain genes involved in zinc binding. Studies on microarray analysis of Arabidopsis genome revealed that expression of RING zinc finger proteins was introduced in response to cold (Fowler and Thomashow, 2002), which also indicated that RING finger proteins might also be a part of other environmental (biotic or abiotic) stress-induced gene expression. Characterization of small plant RING zinc finger proteins add up the information regarding their key role in all biological processes including cold-responsive gene expression (Lee et al., 2001), seed development (Molnar et al., 2002) and in one pathogen defense (Guo et al., 2003, Serrano and Guzma´n 2004).
EST JZ892766 shows close resemblance with Arabidopsis Ankyrin repeat family protein. The Arabidopsis genes, which contain ankyrin repeats are named as AKR (Arabidopsis Ankyrin Repeat), and the protein encoded by these ankyrin repeats is known as Arabidopsis Ankyrin Repeat Protein (AKRP) (Zhang et al., 1992). Plant ANK proteins played a major role in cell signaling pathways in defense (Cao et al., 1997) and development processes (Hemsley etal., 2005). The ANK repeat containing protein is also involved in regulatory pathways of anti-oxidation and metabolism for stress response and disease resistance (Yan et al., 2002). Ankyrin repeats are diverse and present in a variety of proteins 133 of prokaryotes, viruses and eukaryotes and they also regulate and are involved in protein- protein interactions. (Cristian et al., 2004)
EST JZ892771 resembles LORELEI-like-GPI-anchored protein (LLG1). In plant fertilization, successful sperm reception by female gametophyte induced safe migration, acceptance and fusion of the two sperm cells within female gametes. A study was conducted by Tatsuya et al., in 2010 on LORELEI-like-GPI-anchored protein. Their results showed that these proteins were not only involved in transport, reception and successful fertilization but also played a key role in seed development.
EST JZ892779 showed significant similarity with a member of SNF1-related protein kinase (SnRK2) family. Yeast SNF1 protein kinase, plant SnRK protein and mammalian AMP-activated protein kinase (AMPK) are highly protective and conserved protein families and play crucial roles in growth, cell signaling pathways and metabolic responses to different stress levels. In yeast, SNF1 worked under limited nutrients availability and control growth and regulation of glucose responsive genes (Cullen and Sprague, 2009). Another study on SnRK2 (SNF-related protein kinase2) family showed its key functioning role involved in ABA signaling and drought stress responses (Boudsocq et al., 2004, 2007; Kobayashi et al., 2004). Under drought stress conditions, accumulation of solutes like glucose and soluble sugars takes place within plant cells that ultimately give signal to glucose responsive genes to deal with stress tolerance.
The cysteine/Histidine-rich zinc-binding motifs also known as the RING and B-box are present in various unrelated proteins. EST JZ892781 also belongs to Cysteine/Histidine- rich C1 domain family protein. These domain or motifs are directly involved in protein- protein interactions and this has been verified by their biological, structural and biochemical studies. Many reported RING-containing proteins include oncoproteins, and proapoptotic activities, in the form of conformational changes in motifs, are being observed on NMR spectroscopy. In 1998, Katherine reported that motifs undergo these changes on zinc ligation. EST JZ892785 encodes an Arabidopsis ortholog of the ATR (ataxia-telangiectasia and RAD3 related) protein kinase. These proteins or kinases are involved in DNA damage, 134 translation, repair and cell cycle progression in yeast and mammals (Hawkesford and Wray, 2000).
EST JZ892802 showed homology to exostosin family protein. This family contains heparan sulfates which are complex sulfated molecules present in large amount at the surface of cells and in extracellular matrix. They are involved in binding and influencing the activity of various molecules like growth factors, morphogens and proteases and are well involved in many cell to cell and cell to matrix interactions. However, their exact role in this process is still not clear. (Marta et al., 2014)
EST‟s JZ892793 and JZ892754 showed homology with Arabidopsis homologue of beta glucosidase. Plants produce certain kind of secondary metabolites known as phytoanticipins. When plant tissue containing these phytoanticipins disrupted get bioactivated by the quick action of beta glucosidases. With the breakup of this binary system, two sets of components get separated and provide plants immediate chemical defense against herbivores and plant pathogens. According to recent findings, activation of major classes of phytoanticipins (cyanogenic glucosides, venacosides, glucosinolates and benzoxazinoid glucosides) is done by beta glucosidases.
EST JZ892742 is similar to a member of the Glycosyltransferase family 6. Plants produce large number of diversified low molecular weight plant secondary metabolites through Glycosylation (i.e. conjugation to a sugar moiety). It is the key modification catalysed by an enzyme family called glycosyltransferases (UGTs). Information gathered through completion of many plant genome projects revealed complex modified enzymes such as glutathione-S-transferases, UGTs, acyltransferases and cytochromes P450. Glycosyltransferases encoded large multigene families containing several hundred genes like family 1 UGTs encoded 120 Ugt genes in Arabidopsis and 165 being reported in Medicago truncatula (Claire et al., 2005).
EST‟s JZ892769 and JZ892748 showed similarity with Arabidopsis homologue UDP-glucosyl transferase. The Arabidopsis Glucosyltransferase serves the function of plant defense and senescence modulated by Isoleucic acid. Plants communicate and regulate pathogen defense mechanisms by antagonistic salicylate and jasmonate controlled signaling 135 pathways. Studies made already predicted the role of uncharacterized glucosyltransferase is crutial player in Salicyclate-Jasmonate signaling communication (Veronica et al., 2011). This shows that amino acid–related molecules have a novel link with plant defense mechanism that is controlled by small molecules of glucosylation (Morant et al., 2008).
EST‟s JZ892741, JZ892744, JZ892798, JZ892799 and JZ892809 are involved in different enzymatic activities like acyltransferases, aldolases, phosphatases, hydrolases and polymerases. When subjected to TAIR, these small EST predicted to be the part of WSD1- like, Aldolase-type TIM barrel and Endonuclease/exonuclease/phosphatase family proteins. EST‟s (JZ892758, JZ892786, JZ892808, JZ892764 and JZ892783) are involved in RNA/DNA binding proteins, RNA-directed DNA polymerase (reverse transcriptase) activity, 18SrRNA and 60S acidic ribosomal protein family.
EST JZ892730 is close homologue of Arabidopsis C2 calcium/lipid-binding plant phosphoribosyltransferase family protein. Ca(2+) acts as an important second messenger in signal transduction of plants regulating stress-induced gene profiling and expression. Functional analysis of these calcium/lipid binding plant proteins reveals that Ca(2+)-binding domains (C2 domains) are involved behind the role of transcriptional regulators in the signaling pathways and crop genetic maintenance and improvement. Ca2+ signaling played a major role in plant responses to majority of abiotic stresses like high or low temperature, anoxia, osmotic and oxidative stress (de Silva et al.,2011).
Brassinosteroids (BRs) are steroid hormones that are indulged in many physiological processes of plants in their life cycle. EST JZ892797 showed significant similarity with BES1/BZR1 homolog 4 (BEH4). BES1 is involved in the regulation of brassino-steroid- induced gene expression. The regulatory mechanism that is behind the BR homeostasis is still unknown and not clearly understood.
Aldehydes which are biologically important get metabolized by NAD(P)C-dependent aldehyde dehydrogenases superfamily proteins. EST‟s JZ892762 and JZ892800 showed homology to Rossmann-fold superfamily protein that are NAD(P)Cdependent aldehyde dehydrogenases and produce the Rossmann fold coenzyme binding site upon sequence comparison of amino acid motifs. Aldehydes are mediators of fundamental biochemical 136 reactions and are produced during carbohydrates, steroids, vitamins, amino acids and finally lipids metabolism. They can also generate response to number of environmental stresses that disrupt metabolism including dehydration, salinity, dessication, high and low temperature shocks (Hans-Hubert et al., 2004).
In eukaryotic cells, microtubules, actin, and intermediate filaments coordinate to form the cytoskeletal interactions involved in the final confirmation of cell architecture, modification of surface receptors, transport, differentiation, mitosis and cell motility. Dynamics of Cytoskeletal interactions depend on self-associations of protein self and coordination with regulatory elements. These elements are known as microtubule-associated proteins. EST JZ892763 also showed homology to Microtubule-associated protein 65-2. These proteins basically controlled the microtubule organizing assembly. The MAP family includes large proteins as well as smaller components. They are widely spread among all the plant cells but many MAP‟s tend to be associated with specific cell types (Maccioni and Cambiazo, 1995).
EST JZ892765 showed homology to a pentatricopeptide repeat protein (PPR). These proteins are involved in mRNA editing in mitochondria and chloroplasts. The molecular function of these PPR proteins includes plant growth, development, organelle biogenesis, photosynthesis, respiration, and most importantly, combating the environmental stresses. PPR proteins are one of the major families reported on land plants having more than 400 members. Studies conducted elsewhere helped understanding of PPR proteins mechanism that how RNA sequences are being recognized by these proteins for modular base-specific interactions resulting in pathway required for potential binding sites (Barkan and Small, 2014). EST JZ892784 encodes disease resistance protein (TIR-NBS-LRR class) family. In Arabidopsis and other dicotyledonous plants, two families of disease resistant proteins are being reported by Meyerset al., (2002). These are TIR-X (Toll/interleukin-1 receptor- X) and TIR-NBS proteins. Their main function is to produce innate immune responses against various environmental stresses.
The process by which plants produce reproductive structures from vegetative structures is important developmental transition which will ultimately affect the reproductive 137 success of land plants. In Arabidopsis, meristem identity regulator LEAFY (LFY) controlled this process of transition. EST JZ892735 closely resembles LATE MERISTEM IDENTITY2 (LMI2) homologue of Arabidopsis thaliana. The molecular mechanisms used by LFY for flower formation is not clear but it shows crucial developmental transition with the rapid change in environmental conditions (Pastore, 2011).
Members of WD40 protein superfamily played a crucial role in controlled seed germination and growth by the ribosome-biogenesis and protein interactions found in Arabidopsis thaliana. The domains of this family have been found in many plant proteins and tend to act as mediators in scaffolding pattern and assist adjacent protein activities involved in multicellular processes. EST JZ892791 showed significant homology to Transducin/WD40 repeat-like superfamily protein. In Arabidopsis, members of this family regulate many plant-specific events which are biologically important in development and environmental stress signaling.
EST JZ892795 relates to member of CYP81H protein domain of Arabidopsis thaliana. The key roles played by CYP81H protein domain is heme binding, iron ion binding and oxygen binding in Arabidopsis thaliana. THO/TREX is a precise focused nuclear complex that regulates mRNP biogenesis and inhibits transcription-associated mechanisms. Its ubiquitous role in the plant genome is unpredictive. EST JZ892776 encodes a component of Arabidopsis THO/TREX complex homologue. Iron is required by the plant to regulate different bilogical processes involved in plants survival. Many plant species reduce iron in soil from Fe(III) to Fe(II) by the help of Fe(III)-chelate reductases present in the plasma membrane of plant roots epidermal cells. These reductases helped the plant to uptake Fe(II) by the help of transporter proteins. This happens when there is iron deficiency in the soil. EST JZ892749 also encodes a ferric chelate reductase already reported in Arabidosis thaliana.
EST JZ892750 is involved in biosynthesis of molybdenum cofactor (Moco). Research on Arabidopsis thaliana reported a locus LOS5/ABA3 that encodes a Molybdenum Cofactor Sulfurase that mediates cold and osmotic stress responsive gene expression. To understand the effects of abiotic environmental stresses and their signaling pathways Liming et al., 2001 138 characterized two allelic mutants of Arabidopsis i.e., los5-1 and los5-2, which get impaired in gene induction by these stresses. LOS5/ABA3 encodes a molybdenum cofactor (MoCo) sulfurase and is expressed ubiquitously in many plant parts. Expression level of this gene increases in response to salt, drought and ABA treatment. LOS5/ABA3 is found to be a key regulator of ABA biosynthesis and stress tolerance.
Inositol-containing phospholipids are present in all eukaryotic plant and animal cells. This set of proteins performs wide range of structural as well as cellular functions. Very little information is available for plant phosphoinositides than about their animal counterparts. EST JZ892759 is also involved in Phosphoinositide binding. These inositol containing lipids tend to play many important functional roles throughout the plant life.
Thirteen EST‟s (JZ892720, JZ892728, JZ892733, JZ892734, JZ892807, JZ892753, JZ892757,JZ892804, JZ892782,JZ892780, JZ892775, JZ892772 and JZ892747) subjected to TAIR database have no significant homologues found in Arabidopsis thaliana and these are considered as EST‟s with unknown protein function.
5.7 DIFFERENTIALLY EXPRESSED ESTs
Genome sequencing and expression profiling of Agave sisalana L. has not been reported so far. Present study is the first report on differentially expressed ESTs in Agave sisalana under drought stressed conditions. As there was no on report sequence of Agave sisalana L. under abiotic stresses for comparison therefore homology of reported sequences was cross checked with sequences reported in other land plants. Ten EST‟s (JZ892796, JZ892787, JZ892778, JZ892752, JZ892755, JZ892761, JZ892731, JZ892733, JZ892743 and JZ892726) were found to be differentially expressed in Agave sisalanaL. under drought stress.
Differentially expressed ESTs (JZ892726, JZ892731, JZ892752, JZ892778, JZ892733) showed maximum homology with Populus trichocarpa. These ESTs are reported in mild and severe drought stressed leaves of Populus trichocarpa and predicted hypothetical ubiquitinin and receptor kinases containing domain proteins. Polyubiquitin genes are a part of ubiquitin proteins which played a key role in selective proteolysis by the UPS i.e 139 ubiquitin-proteasome system. This system has been emerged as fundamental player in plant response to abiotic factors like drought, cold, nutrient deprivation and salinity and helped plant in the adaptability of any stressed environment. This regulatory polyubiquitinin gene also influences the production of stress-related hormones like abscisic acid (Sophia, 2014). Another diverse group of cell surface receptor-like protein kinases (RLK‟s) in land plants plays an important role in sensing external stimuli and regulating gene expression in response to environment (Stone and Walker, 1995; Lease et al., 1998). EST‟s JZ892755 and JZ892796 showed maximum homology with Agave americana plants. These EST‟s serves as the function of PDBK and small HSP RING FINGER proteins. Heat-shock proteins, also called as „„Stress-induced proteins‟‟ induce gene expression against various kinds of environmental abiotic factors (Morimoto et al., 1994; Gupta et al., 2010). In Arabidopsis and other landplants, drought stress tends to induce gene expression by the synthesis of such stress proteins (Swindell et al., 2007). EST JZ892761 showed significant similarity with catharanthus roseus and this EST also contained significant homologues with the domains of Universal Stress Protein. EST‟s JZ892743 and JZ892787 showed significant similarity with Elaeis guineesis and showed homology with the domain of zerumbone- synthase like protein. Real time data analysis showed highest expression in EST‟s JZ892752 followed by EST JZ892726 whereas EST‟s JZ892743, JZ892761 and JZ892787 showed mild expression of drought tolerance in Agave sisalanaL. The differentially expressed EST JZ892743 in microarray data didn‟t show any expression through real time PCR. Real time data analysis confirms the overall significant expression of up-regulated EST‟s (JZ892726 and JZ892752) up to 1.9 fold expression whereas EST JZ892743, JZ892761 and JZ892787 showed less than 0.5 fold expression level under abiotic stress conditions. EST JZ892778 showed no expression or upregulated activity in stressed leaves of Agave sisalana L. Similar upfold expression of two ESTs (JZ892726 and JZ892752) was observed in expression behaviour and fold change studied in K means cluster analysis of microarray. Developing drought transgenic plants to control drought stress is becoming main area of interest. The first report study on Agave sisalana L. will provide the potential drought related transcripts for the development of drought resistant genetically modified crops in future. 140
REFERENCES
Abdel-Nasser, L. E. and Abdel-Aal, A. E. (2002). Effect of elevated CO2 and drought on proline metabolism and growth of safflower (Carthamus mareoticus L.) seedlings without improving water status. Pak J Biol Sci., 5:523-528.
Ackerson, R. C. (1980). Stomatal response of cotton to water stress and abscisic acid as affected by water stress history. Plant Physiol., 69: 455-459.
Acquaah, G. (2009). Acquired resistance encodes a novel protein containing ankyrin repeats. Principles of plant genetics and breeding, John Wiley & Sons. Cell 88: 57-63.
Aharoni, A. and Vorst, O. (2002). DNA microarrays for functional plant genomics. Plant Mol. Biol., 48: 99-118.
Ahmad, P. and Prasad, M. (2012). Abiotic stress responses in plants, Springer.
Arita, H.T. (1991). Spatia segregation in long nosed bats, Leptonycteris nivalis and Leptonycteris curasoae in Maxico. J. of Mammalogy, 72: 706-714.
Alba, R., Fei, Z., Payton, P., Liu, Y., Moore, S. L., Debbie, P., Cohn, J., D'Ascenzo, M., Gordon, J. S., Rose, J. K. C., Martin, G., Tanksley, S. D., Bouzayen, M., Jhan, M. M and Giovannoni, J. (2004). ESTs, cDNA microarrays, and gene expression profiling: tools for dissecting plant physiology and development. The Plant J., 39: 697-714.
Alché, J. D., Castro, A.J., Olmedilla, A., Fernández, M.C., Rodríguez, R., Villalba, M. and Rodríguez-García, M.I.(1999). The major olive pollen allergen (Ole e I) shows both gametophytic and sporophytic expression during anther development, and its 141
synthesis and storage takes place in the RER. Journal of Cell Science. 112:2501- 2509.
Alché, J.D., M'rani-Alaoui, M., Castro, A.J and Rodríguez-García, M.I (2004). Ole e 1, the major allergen from olive (Olea europaea L.) pollen, increases its expression and is released to the culture medium during in vitro germination. Plant Cell Physiology., 45:1149-1157.
Allen, D. and Ort, D. (2001). Impacts of chilling temperatures on photosynthesis in warm- climate. Trends Plant Sci., 6:36-41.
Ameglio, T., Roux, X. L., Mingeau, M and Perrier, C. (2000). Water relations of highbush blueberry under drought conditions. Acta Hortic., 537: 273-279.
Anjum, S. A., Wang, L., Farooq, M., Khan, I. and Xue, L. (2011b). Methyl jasmonate- induced alteration in lipid peroxidation, antioxidative defense system and yield in soybean under drought. J. Agron and Crop Sci., 197 (4): 296-301.
Anjum, S.A., X. Xie, L.Wang, M.F. Saleem, C. Man and W. Lei, (2011). Morphological, physiological and biochemical responses of plants to drought stress. Afri. J. Agri. Res. 6(9): 2026-2032.
Araus, J.L., G.A. Slafer, M.P. Reynolds and C. Royo, (2002). Plant breeding and drought in C3 cereals: What should we breed for? Annal. Bot., 89: 925–940.
Arizaga, S. and Ezcurra, E. (1995). Insurance against reproductive faliuer in a semelparous plantbulbil formation in Agave macroacantha flowering stalks. Oecologia, 101: 329- 334. 142
Arizaga, S. and Ezcurra, E. (2002). Propagation mechanisms in Agave macroacantha (Agavaceae), a tropical arid-land succulent rosette. American J. of Bot., 89:632-641.
Arnaldo L. Schapire, Victoriano Valpuesta, Miguel A. Botella. (2006). TPR proteins in plant hormone signaling. Plant Sig. and Beh. 1(5):229-230.
Arnon, D and F. Whatley, (1949). Is chloride a coenzyme of photosynthesis? Sci., 2865: 554- 556.
Ashraf, M. and Ibram, A. (2005). Drought stress induced changes in some organic substances in nodules and other plant parts of two potential legumes differing in salt tolerance. Flora, 200: 535-546.
Ashraf, M. and Foolad, M. R. (2007). Roles of glycine-betaine and proline in improving plant abiotic stress resistance. Environ. Exp. Bot., 59: 206- 216.
Bacon, M.A. (2004). Water Use Efficiency in Plant Biology. Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK.
Badano, E. I. and Pugnaire F. I. (2004). Invasion of Agave species (Agavaceae) in southeast Spain: invader demographic parameters and impacts on native species. Diversity And Distributions, 10: 493-500.
Bahrani M. J., Bahrami H. and Haghighi, A.A.K. (2010). Effect of water stress on ten forage grasses native or introduced to Iran. Grassl. Sci. 56: 1–5.
Bakay, M., Chen, Y. W., Borup, R., Zhao, P., Nagaraju, K. and Hoffman, E. P. (2002). Sources of variability and effect of experimental approach on expression profiling data interpretation. BMC Bioinformatics, 3: 4. 143
Bao, Y., Cuiting, W., Chunmei, J., Jing, P., Guobin, Z., Hua, L. and Hongxia, Z. (2014).The tumor necrosis factor receptor-associated factor (TRAF)-like family protein SEVEN IN ABSENTIA 2 (SINA2) promotes drought tolerance in an ABA-dependent manner in Arabidopsis. New Phytologist, 202:174–187.
Barkan, A., Small, I. (2014). Pentatricopeptide repeat proteins in plants. Annu Rev Plant Biol., 65:415-42.
Barrs, H.D and P.E. Weatherley (1962). A re-examination of the relative turgidity technique for estimating water deficits in leaves. Aust. J. Bio Sci., 15: 413-428
Basal, H., Smith, C. W., Thaxton P. S. and Hemphill J. K. (2005). Seedling drought tolerance in upland cotton. Crop Science, 45: 2; 766-771
Bates L.S., R.P. Waldren and I.D. Teare (1973). Rapid determination of free proline for water stress studies. Plant Soil, 39: 205-207.
Beck, E. H., Fettig, S., Knake, C., Hartig, K. and Bhattarai, T. (2007). Specific and unspecific responses of plants to cold and drought stress. J. of Bios., 32: 501-510.
Bentham, G., and J.D. Hooker. (1883). Genera plantarum. Vol. III, part 2. London: Reeve.
Ben saad, R., Zouari, N., Ben Ramdhan, W., Azaza, J., Meynard, D., Guiderdoni, E. and Hassairi, A. (2010). Improved drought and salt stress tolerance in transgenic tobacco overexpressing a novel A20/AN1 zinc-finger "AlSAP" gene isolated from the halophyte grass Aeluropus littoralis. Plant Mol Biol., 72: 171-90.
144
Benjamin, J. G. and Nielsen, D.C. (2006). Water deficit effects on root distribution of soybean, fieldpea and chickpea. Field Crops Res., 97: 248-253.
Bhattacharjee, S and Mukherjee, A. K. (1998). T'he deleterious effects of high temperature during earlygermination on membrane integrity and subsequent germination of Amaranthus lividus. Seed Sci. Technol., 26: 1-8.
Biamonti, G. and Caceres, J. F. (2009). Cellular stress and RNA splicing. Trends Biochem. Sci. 34: 146-153.
Blanco, I. A. Del., Rajaram, S., Kronstad, W. E. and Reynolds, M. P. (2000). Physiological performance of synthetic hexaploid wheat-derived populations. Crop Sci. 40 (5): 1257-1263.
Bogler, D. J., and Simpson, B. B. (1995). A Chloroplast DNA study of the Agavaceae. Systematic Bot., 20: 191-205.
Bohnert , H.J. and Cushman, J.C.(2000). Genomic approaches to Plant Stress tolerance. Current Opinion in Plant Biology. 3:117–124
Bohnert, H. J., Nelson, D. E. and Jensen, R. G. (1995). Adaptations to environmental stress. Plant Cell, 7: 1099-1111.
Borel, C. and. Simonneau, T. (2002). Is the ABA concentration in the sap collected by pressurizing leaves relevant for analyzing drought effects on stomata? Evidence fromABA-fed leaves of transgenic plants with modified capacities to synthesize ABA. J. Exp. Bot., 53 (367): 287-296. 145
Boudsocq, M., Barbier-Brygoo, H and Lauriere, C. (2004). Identification of nine sucrose nonfermenting 1-related protein kinases 2 activated by hyperosmotic and saline stresses in Arabidopsis thaliana. J of Biol Chem., 279:41758-41766.
Bown, D. (1995). Encyclopaedia of Herbs and their Uses. Dorling Kindersley, London.
Boyer, J.S. (1982). Plant Productivity and the environment, Science, 218:443-448.
Brackenbury T.D. and Appleton C.C. (1997). A comprehensive evaluation of Agave attenuata, a candidate plant molluscicide in South Africa. Acta Trop. 68: 201-213.
Bray, E. A. (1997). Plant responses to water deficit. Trends Plant Sci., 2: 48-54.
Bray, E. A., Bailey-Serres, J. and Weretilnyk, E. (2000). Responses to abiotic stresses. In: Gruissem, W., Buchnnan, B. and Jones, R. (Eds.). Biochemistry and Molecular Biology of Plants. American Society of Plant Physiologists. Rockville. MD. 1158- 1249.
Cao, H., Glazebrook, J., Clarke, J. D., Volko, S. and Dong, X. (1997). The Arabidopsis NPR1 gene that controls system acquired resistance encodes a novel protein containing ankyrin repeats. Cell, 88: 57-63.
Carpenter, J.L., Ploense, S.E., Snustad, D.P. and Silflow, C.D. (1992). Preferential expression of an alpha-tubulin gene of Arabidopsis in pollen. Plant Cell. 4:557-71.
Catherine, A., Eugenia, R., Birgit, K., Mark, K. and Sacco, C. de Vries. (2008). Arabidopsis somatic embryogenesis receptor kinase proteins serve brassinosteroid-dependent and -independent signaling pathways. Plant Physiol., 148:611–619.
146
Chandra, S. (2003). Effects of leaf age on transpiration and energy exchange of Ficus glomerata, a multipurpose tree species of central Himalayas. Physiol. Mol. Biol. Plants, 9: 255-260.
Chaves, M. M. (1991). Effects of water deficit on carbon assimilation. J. Exp. Bot., 42: 1-16.
Chaves, M. M., Osório, J. and Pereira, J. S. (2004). Water use efficiency and photosynthesis. In: Bacon M, (ed). Water use efficiency in plant biology. Oxford: Blackwell Publishing, 42-74.
Chaves, M.M., Maroco J.P. and Pereira J.S. (2003). Understanding plant response to drought from common bean (P. vulgaris), J. Exp. Bot., 57:1391-1398.
Chen, J. J. W., Wu, R., Yang, P. C., Huang, J. Y., Sher, Y. P., Han, M. H., Kao, W. C., Lee, P. J., Chiu., T. F., Chang, F., Chu, W. Y and Peck, K. (1998). Profiling expression patterns and isolating differentially expressed genes by cDNA microarray system with colorimetry detection. Genomics. 51: 313-324.
Chevallier, A. (1996). The Encyclopedia of Medicinal Plants. Dorling Kindersley. London ISBN 9-780751-303148.
Chinnusamy, V., Ohta, M., Kanpar, S., Lee, B. H., Hong, X., Agarwal, M. and Zhu, J. K. (2003). ICE1: a regulator of cold-induced transcriptome and freezing tolerance in Arabidopsis. Genes and Development. 17:1043-1054.
Chinnusamy, V., Schumaker, K. and Zhu, J. K. (2004). Molecular genetic perspectives on crosstalk and specificity in abiotic stress signaling in plants. J. Exp Bot., 55: 225-236.
147
Chopra, R.N., Nayar, S.L. and Chopra, I.C. (1986). Glossary of Indian Medicinal Plants, Council of Scientific and Industrial Research, New Delhi.
Churchill, G. A. (2002). Fundamentals of experimental design for cDNA microarrays. Nature Genetics. 32: 490-495.
Claire, M.M., Mathilde, L.M. and Patrick, S. (2005). Plant secondary metabolism glycosyltransferases: the emerging functional analysis. Trends Plant Sci., 10:542-9.
Clarke, J. D. and Zhu, T. (2006) Microarray analysisof the transcriptome as a stepping stone towards understanding biological systems: practical considerations and perspectives. Plant Journal, 45:630-650.
Cleveland, W. S. and Devlin, S. J. (1988). Locally weighted regression: An approach to regression analysis by local fitting. J. American Statistical Association. 83: 596-610.
Colunga, G.P., and Maypat, F. (1993). Agave studies in Yucatan, Mexico-1. Past and present germplasm diversity and uses. Economic Botany 47:312-327.
Cominelli, E., Sala, T., Calvi, D., Gusmaroli, G and Tonelli, C. (2008). Over-expression of the Arabidopsis At MYB41 gene alters cell expansion and leaf surface permeability. The Plant J. 53: 53-64.
Conesa, A., Gotz, S., Garcia-Gomez, J., Terol, , J. , Talon, M. and Robles, M. (2005). National Centre for Biotechnology Information Blast2GO: A universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21:3674–3676. 148
Coram, T. E. and Pang, E. (2006). Expression profiling of chickpea genes differentially regulated during a resistance response to Ascochyta rabiei. Plant Biotech. J. 4: 647- 666.
Cornic, C. and Massacci, A. (1996). Leaf photosynthesis under drought stress. In: Photosynthesis and Environment. Baker, N.R.. Kluwer Ed. Acad. Publs, 347-366.
Cornic, G and Fresneau, C. (2002). Photosynthetic carbon reduction and carbon oxidation cycles are themain electron sinks for photosystem 2 activity during a mild drought. Ann. Bot., 89: 887-894.
Cornic, G. and Briantais, J. M. (1991). Partitioning of photosynthetic electron flow between
CO2 and O2 reduction in a C3 leaf (Phaseolus vulgaris L.) at different CO2 concentrations and during drought stress. Planta, 183: 178-184.
Cramer, G. R. (2010). Abiotic stress and plant responses from the whole vine to the genes. Aus. J. Grape Wine Res., 16: 86-93.
Cristian, B., Torben, J., Pere, P. and Carlos, M.V. (2004). Ankyrin repeat-containing proteins in Arabidopsis: characterization of a novel and abundant group of genes coding ankyrin transmembrane proteins. Gene., 340:111-121.
Cronquist, A. (1981). An integrated system of classification of flowering plants. New York: Columbia Univ. Press.Current opinion in plant biology, 3:117-124.
149
Crumpton-Taylor, M.1., Pike, M., Lu, K.J., Hylton, C.M., Feil, R., Eicke, S., Lunn, J.E., Zeeman, S.C. and Smith, A.M. (2013). Starch synthase 4 is essential for coordination of starch granule formation with chloroplast division during Arabidopsis leaf expansion. New Phytol., 200:1064-75.
Cullen, P. J and Sprague, G. F. (2009). Glucose depletion causes haploid invasive growth in yeast. PNAS, USA 97:13619-13624.
DaCosta M.and Huang B. (2009). Physiological adaptations of perennial grasses to drought stress. In: Perspectives in biophysical plant ecophysiology. Barrera, E.D. and W.K. Smith, (Edi), Universidad Nacional Autónoma de México, México. 169–190. ISBN 987-0-578-00421-1.
Dahlgren, R.M., and P.F. Yeo. (1985). The families of the monocotyledons. Berlin: Springer- Verlag. da Silva B.P., de Sousa, A.C., Graziela, M.S., Tatiana, P.M. and Jose, P.P. (2002). A New Bioactive Steroidal Saponin from Agave attenuata. Verlag der Zeitschrift für Naturforschung. Tubingen pp. 423-428. daSilva, L.L., Taylor, J.P., Hadlington, J.L., Hanton, S.L., Snowden, C.J., Fox, S.J., Foresti, O., Brandizzi, F., and Denecke, J. (2005). Receptor salvage from the prevacuolar compartment is essential for efficient vacuolar protein targeting. Plant Cell, 17: 132- 148.
Davies, W., J. and Zhang, J. (1991). Root signals and the regulation of growth and development of plantin drying soil. Annu. Rev. Plant Physiol. Plant Mol. Biol., 42: 55-76.
150
Debnath, M., Pandey, M., Sharma, R., Thakur, G.S. and Lal, P. (2009). Biotechnological intervention of Agave sisalana: A unique fiber yielding plant with medicinal property. Journal of Medicinal Plants Research Vol. 4:177-187.
Demiral, T. and Turkan, I. (2004). Does exogenous glycinebetaine affect antioxidative system of rice seedlings under NaCl treatment? J. Plant Physiol., 161: 1089-1110.
Demirevska, K., Zasheva, D., Dimitrov, R., Stoilova, L. S., Stamenova, M. and Feller, U. (2009). Droughtstress effects on Rubisco in wheat: changes in the Rubisco large subunit. Acta Physiol. Plant, 31: 1129-1138.
De Ronde, J.A., Van Der Mescht, A. and Steyn, H.S.F. (2000). Proline accumulation in response to drought and heat stress in cotton. African J Crop Sci. 8:85-92.
de Silva, K., Laska, B., Brown, C., Sederoff, H.W. and Khodakovskaya, M. (2011). Arabidopsis thaliana calcium-dependent lipid-binding protein (AtCLB): a novel repressor of abiotic stress response. J Exp Bot., 62:2679-89
Deshaies, R. J (1999). SCF and Cullin/Ring H2-based ubiquitin ligases. Annu Rev Cell Dev Biol 15: 435-467
Dharmasiri, N., and Estelle, M. (2004). Auxin signaling and regulated protein degradation. Trends Plant Sci. 9: 302-308
Dinneny, J. R., Long, T. A., Wang, J. Y., Jung, J. W., Mace, D., Pointer, S., Barron, C., Brady, S. M., Schiefelbein, J., and Benfey, P. N. (2008) .Cell identity mediates the resp++++onse of Arabidopsis roots to abiotic stress. Sci., 320: 942-945. 151
Dionisio-Sese, M. L. and Tolbita, S. (1999). Antioxidative responses of shoots and roots of wheat increasing NaCl concentration. J. Plant. Physiol., 155: 274-80.
Dobbin, K. and Simon, R. (2002). Comparison of microarray designs for class comparison and class discovery. Bioinformatics, 18: 1438-1445.
Dobbin, K., Shih, J. H. and Simon, R. (2003). Statistical design of reverse dye microarrays. Bioinformatics, 19: 803-810.
Dodd, A. N., Borland, A. M., Haslam, R. P., Griffiths, H. and Maxwell, K. (2002). Crassulacean acid metabolism. J. of Experimental Bot., 53: 569-580.
Dombrowski, J. E. (2003). Salt stress activation of wound-related genes in tomato plants. Plant Physiology. 132: 2098-2107.
Draghici, S. (2003). Data Analyses tools for DNA Microarrays. Boca Raton, FL: Chapman & Hall/CRC.
Duan, B., Yang, Y., Lu, Y., Korpelainen, H., Berninger, F. and Li, C. (2007). Interactions between drought stress, ABA and genotypes in Picea during cold acclimation in addition to the CBF cold response pathway. Plant Cell, 14: 1675-1690.
Duggan, D. J., Bittner, M., Chen, Y., Meltzer, P. and Trent, J. M. (1999). Expression profiling using cDNA microarrays. Nature Genetics, 21: 10-14.
152
Duvall, M. R., Clegg, M. T., Chase, M. W., Clark, W. D., Kress, W. J., Hills, H. G., Eguiarte, L. E., Smith, J. F., Gaut, B. S., Zimmer, E. A. and Learn, G. H. (1993). Phylogenetic hypotheses for the 132 monocotyledons constructed from RBCL sequencing data. Ann. of the Miss. Bot. Gar. 80:607-619.
Eguiarte, L., Souza,V. and Silva-Montellano, A. (2000). Boletin de la Sociedad. Botanica de Mexico, 66: 131-150.
Eldridge, J. (1975). Bush medicine in the Exumas and Long Island, Bahamas; a field study. Econ. Bot. 29: 307-332.
Engler, A. and Prant, K. (1888). Endogenous ABA during drought stress, Abscisic acid Physiology and Biochemistry, Dia naturlichen Pflanzenfamilien. Teil 2, Abteil 5. Liepzig.
English-Loeb, G.M. (1990). Plant drought stress and outbreaks of spider mites: a field test. Ecology, 71: 1401-1411
Escamilla-Treviño, L.L. (2011). Potential of plants from genus Agave as bioenergy crops. Bio Ener. Res., 5:1-9
Ennahli, S., and Earl, H.J. (2005). Physiological limitations to photosynthetic carbon assimilation in cotton under water stress. Crop Sci. 45:2374-2382.
Fahn, A. and Cutler, D.F. (1992). Xerophytes, Gebrueder Borntraeger,Berlin, p. 167.
Farooq, M., Basra, A., Wahid, S.M., Ahmad, A. and Saleem, B.A. (2009). Improving the drought tolerance in rice (Oryza sativa L.) by exogenous application of salicylic acid. J. Agron. & Crop Sci., 195:237–246. 153
Faver, K. L., Gerik, T. J., Thaxton, P. M. and El-Zik, K. M. (1996). Late season water stress in cotton: II: leaf gas exchange and assimilation capacity. Crop Sci., 36: 922-928.
Feder, M. E. and Hofmann, G. E. (1999). Heat-shock proteins, molecular chaperones, and stress response: evolutionary and ecological physiology. Annu. Rev. Physiol., 61: 243-282.
Flexas, J. and H. Medrano (2002). Drought-inhibition of photosynthesis in C-3 plants: Stomatal and nonstomatal limitation revisited. Ann. Bot. 89: 183-189.
Flower, S. and Thomashow, M. F. (2002). Arabidopsis transcriptome profiling indicates that multiple regulatory pathways are activated during cold acclimation in addition to the CBF cold response pathway. The Plant Cell, 14: 1675-1690.
Flowers, T. J. (2004). Improving crop salt tolerance. J. Exp. Bot., 55: 307-319.
Foyer, C. H., Lopez-Delgado, H. J., Dat, H. and Scott, I. M. (1997). Hydrogen peroxide and glutathione associated mechanisms of acclamatory stress tolerance and signaling. Physiol. Plant., 100: 241-254.
Flores-Benitez, S., Jimenez-Bremont, J.F., Rosales-Mendoza, S., Arguello-Astorga, G.R., Castillo-Collazo, R.. and Alpuche-Solis, A.G. (2007). Genetic transformation of Agave salmiana by Agrobacterium tumefaciens and particle bombardment. Plant Cell Tissue Organ Cult., 91:215–224
154
Fujii, H., Paul, E., Verslues and Jian-Kang, Z. (2007). Identification of two protein kinases required for abscisic acid regulation of seed germination, root growth and gene expression in Arabidopsis. The Plant Cell., 19: 485–494.
Fujita, M., Fujita, Y., Maruyama, K., Seki, M., Hiratsu, K., Ohme‐Takagi, M., Tran, L. S. P., Yamaguchi‐Shinozaki, K. and Shonozaki, K. (2004). A dehydration‐induced NAC protein, RD26, is involved in a novel ABA‐dependent stress‐signaling pathway. The Plant J., 39: 863-876.
Faucon P (1998–2004) http://www.desert-tropicals.com/Plants/Agavaceae/Agave.html. Accessed 4 April 2011
Fujita, M., Fujita, Y., Noutoshi, Y., Takahashi, F., Narusaka, Y., Yamaguchi-Shinozaki, K. and Shinozaki, K. (2006). Crosstalk between abiotic and biotic stress responses: a current view from the points of convergence in the stress signaling networks. Curr Opin Plant Biol., 9: 436-42.
Garcia-Mendoza, A. and Chiang, F. (2003). The confusion of Agave vivipara L. and A. angustifolia Haw., two distinct taxa. Brittonia 55:82-87.
Gentry, H. S. (1982). Agaves from Continental North America. The University of Arizona Press,
Godfray, H. C., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., Pretty, J., Robinson, S., Thomas S. M. and Toulmin, C. (2010). Food security: the challenge of feeding 9 billion people. Sci., 327: 812-818.
Gollhofer, J., Schläwicke, C., Jungnick, N., Schmidt, W. and Buckhout, T.J. (2011). Members of a small family of nodulin-like genes are regulated under iron deficiency in roots of Arabidopsis thaliana. Plant Physiol. Biochem., 49:557-64. 155
Gong, Y., Rao, L. and YU, D. (2013). Abiotic Stress in Plants, InTech.Chemistry.
Good-Avila, S. V., Souza, V., Gaut, B. S. and Eguiarte, L. E. (2006). Timing and rate of speciation in Agave (Agavaceae). PNAS, USA, 103: 9124-9129.
Grandbastien, M.A. (1992). Retroelements in higher plants. Trends Genet., 8:103-108.
Greeff, C., M. Roux, J. Mundy and M. Petersen. (2012). Receptor-like kinase complexes in plant innate immunity. Front Plant Sci., 24(3):209.
Guerfel, M., Baccouri, O., Boujnah, D., Chaibi, W. and Zarrouk, M. (2009). Impacts of water stress on gas exchange, water relations, chlorophyll content and leaf structure in the two main Tunisian olive (Olea europaea L.) cultivars. Sci. Horticult., 119: 257-263
Guilfoyle, T.J., and Hagen, G. (2001). Auxin response factors. J. Plant Growth Regul. 20:281-291.
Guo, D. Y., Spetz, C., Saarma, M and Valkonen, J. P. T. (2003). Two potato proteins, including a novel RING finger protein (HIP1), interact with the potyviral multifunctional protein HCpro. Mol. Plant – Microbe Inter. 5:405-410
Guo, Y., Halfter, U., Ishitani, M. and Zhu, J. K. (2001). Molecular characterization of
functional domains in the protein kinase SOS2 that is required for plant salt tolerance. Plant Cell. 13: 1383-1400.
Gupta, S. C., Sharma, A., Mishra, M., Mishra, R. and Chowdhuri, D. K. (2010). Heat shock proteins in toxicology: how close and how far? Life Sci., 86: 377-384.
Hamada, A.M.(2000). Amelioration of drought stress by ascorbic acid, thiamine or aspirin in wheat plants. Ind. J. Plant Physiol., 5: 358-364. 156
Hans-Hubert, K., Dorothea, B., Yanling, W., Patrick, S.S. and Andrew, J.W. (2004). The ALDH gene superfamily of Arabidopsis. Trends in Pt. Sci., 9(8):371-377.
Hanson, D.D., Hamilton, D.S., Travis, J.L., Bashe, D.M. and Mascarenhas, J.P. (1998). Characterization of a pollen-specific cDNA clone from Zea mays and its expression. Plant Cell.,1:173–179
Hartung, W., Wilkinson, S. and. Davis. W. J. (1998). Factors that regulate abscisic acid concentrations at the primary site of action at the guard cell. J. Exp. Bot., 49: 361- 367.
Hasaegawa, P. M., Bressan, R. A., Zhu, J. K. and Bohnert, H. J. (2000). Plant cellular and molecular responses to high salinity. Ann. Rev. of Pt. Physiol. and Pt. Mol. Bio., 51: 463-499.
Havaux, M. (1992). Stress tolerance of photosystemII in vivo. Antagonistic effects of water, heat, and photo inhibition stresses. Plant Physiol., 100: 424-432.
Heim, M.A., Jakoby, M., Werber, M., Martin, C. and Biley,P. C. (2003). The basic helix- loop-helix transcription factor family in plants: A genome wide study of protein structure and functional diversity. Mol. Biol. Evol. 20. 735-747.
Hemsley, P. A., Kemp, A. C. and Grierson, C. S. (2005). The tip growth defective1S-acyl transferase regulates plant cell growth in Arabidopsis. Plant Cell. 17, 2554-2563.
Hendry, G. A. F. (1993). Evolutionary origins and natural functions of fructans- aclimatological, biogeographic and mechanistic appraisal. The New Phytologist,123:3-14.
157
Henson, I. E., Jensen, C. R., and Turner, N. C. (1989). Leaf gas exchange and water relations of lupins and wheat. I. Shoot responses to soil water deficits. Aus. J. Plant Physiol. 16: 401-413.
Hernandez, S., Deleu, C. and Larher, F. (2000). Proline accumulation by leaf tissues of tomato plants in response to salinity. Comptes Rendus LAcad. Des. Sci. Ser III: Sci La Vie-Life Sci 323:551-557.
Herppich, W. B. and Peckmann, K. (1997). Responses of gas exchange, photosynthesis, nocturnal acid accumulation and water relations of aptenia cordifoliato short-term drought and re-watering. J. Plant Physiol., 150: 467-474.
Hoekstra, F. A., Golovina, E. A. and Buitink, J. (2001). Mechanisms of plant desiccation tolerance. Trends Plant Sci., 6: 431-438.
Horvath, D. P., Schaffer, R., West, M. and Wisman, E. (2003). Arabidopsis microarrays identify conserved and differentially expressed genes involved in shoot growth and development from distantly related plant species. Plant J., 34: 125- 134.
Hrabak, E.M. (2003). The Arabidopsis CDPK-SnRK superfamily of protein kinases. Plant Physiol. 132: 666–680.
Hu, W., Hu, G., and Han, B. (2009). Genome-wide survey and expression profiling of heat shock proteins and heat shock factors revealed overlapped and stress specific response under abiotic stresses in rice. Plant Sci., 176: 583-590.
158
Huang D., Wu W., Abrams S.R. and Cutler A.J. (2008). The relationship of drought-related gene expression in Arabidopsis thaliana to hormonal and environmental factors. J. Exp. Bot. 11: 2991-3007.
Hutchinson, J. (1934). The families of flowering plants. Vol. II, Monocotyledons. Oxford: Clarendon Press.
Igathinathane, C., Pordesimo, L.O., Columbus, E.P. Batchelor, W.D. and Methuku, S.R. (2008). Shape identification and particles size distribution from basic shape parameters using Image J. Comput. Electron. Agric., 2: 168-182.
Ingram, J. and Bartels, D. (1996). The molecular basis of dehydration tolerance in plants. Annu Rev Plant Physiol Plant Mol Biol., 47:377-403.
Irish, M. (2003). Agaves. Available at http://search.epnet.com/login.aspx?direct= trueanddb =f5handan=11050720 accessed in May 2010.
Harper, J. F., Si-Ammour, A., Mauch-Mani, B., Heinlein, M., Kobayashi, K., Hohn, T., Dangl, J. L., Wang, X. and Zhu, T. (2002). Expression profile matrix of Arabidopsis transcription factor genes suggests their putative functions in response to environmental stresses. The Plant Cell. 14: 559-574.
Jaakola, L., Pirttila, A.M., Halonen, M. and Hohtola, A., (2001). Isolation of high quality RNA from bilberry (Vaccinium myrtillus L.) fruit. Mol. Biol. 19: 201–203.
Jabeen, F., M. Shahbaz and M. Ahraf (2008). Discriminating some prospective cultivars of maize (Zea mays L.) for drought tolerance using gas exchange characteristics and proline contents as physiological markers. Pak. J. Bot. 40: 2329-2343. 159
Jackie, D., Karen, W., Samantha, A., Karsten, H., Sean, O., Tatsuya, O., Suzanne, F.M., Guy, T. and Kevin, J.M. (2007).The extracellular leucine-rich repeat superfamily; a comparative survey and analyses of evolutionary relationships and expression patterns. BMC Genomics. 8:320-344.
Jajic, I., T. Sarna and K. Strzalka. (2015). Senescence, Stress, and Reactive Oxygen Species. Plants, 4(3): 393-411.
Jaleel, C. A., Manivannan, P., Sankar, B., Kishorekumar, A., Gopi, R., Somasundaram, R. and Panneerselvam, R. (2007). Induction of drought stress tolerance by ketoconazole in Catharanthus roseus is mediated by enhanced antioxidant potentials and secondary metabolite accumulation. Colloids and surfaces Biointerfaces, 60: 201- 206.
Jang, J. C. and Sheen, J. (1997). Sugar sensing in higher plants. Trends Plant Sci., 2: 208- 214.
Janson, J.G., Thomas, G.R. and Mason-pharr, D. (2004). Heat and drought influence photosynthesis, water relations, and soluble carbohydrates of two ecotypes of redbud (Cercis canadensis). J. Am. Soc. Hort. Sci., 129: 497-502.
Jewell, M. C., Campbell, B. C. and Godwin, I. D. (2010). Transgenic plants for abiotic stress resistance. Transgenic crop plants. Springer.
Ji, H., J. M. Pardo, G. Batelli, M. J. V. Oosten, R. A. Bressan and X. Li. (2013). The Salt Overly Sensitive (SOS) Pathway: Established and Emerging Roles. Molecular Plant, 6(2):275-286.
160
Jinyan, W., Ping, L., Huimin, G., Lu, Z., Wenfeng, L. and Wolfgang, S. (2013). Expression changes of ribosomal proteins in phosphate- and iron-deficient Arabidopsis roots predict stress-specific alterations in ribosome composition. BMC Genomics. 14:783.
Jolliffe, N.A., Brown, J.C., Neumann, U., Vicré, M., Bachi, A., Hawes, C., Ceriotti, A., Roberts, L.M. and Frigerio, L. (2004). Transport of ricin and 2S albumin precursors to the storage vacuoles of Ricinus communis endosperm involves the Golgi and VSR-like receptors. Plant J. 39: 821–833.
Jones, H. G. (1992). Plants and microclimate: A quantitative approach to environmental plant physiology. 2nd (ed), Cambridge University Press.
Jones, M. M., Osmond, C. B. and Turner, N. C. (1980). Accumulation of solutes in leaves of sorghum and sunflower in response to water deficits. Aus. J. Plant Physiol., 7: 193- 205.
Jones, M. M., Turner, N. C. and Osmond, C. B. (1981). Mechanisms of drought resistance in Plants. Academic Press, New York, 15-37.
Jung, Y., Lee, I., Nou, I., Lee, K., Rasotte, A. and Kang, K. (2013). BrRZFP1: a Brassica rapa C3HC4‐type RING zinc finger protein involved in cold, salt and dehydration stress. Plant Biol., 15: 274-283.
Kahn, T. L., Susan, E. F., Elizabeth, A.B., and Mary, A.C. (1993). Characterization of expression of drought and abscisic acid regulated tomato genes in the drought resistant species Lycopersicon pannellii. Plant Physiol.,103: 597-605
Katherine, L.B.B. (1998). RING fingers and B-boxes: zinc-binding protein-protein interaction domains. Biochem. Cell Biol., 76: 351–358. 161
Kaur, N. and Gupta, A. K. (2005). Signal transduction pathways under abiotic stresses in plants. Curr. Sci., 88: 1771-1780.
Kerr, M. K., Afshari, C. A., Bennett, L., Bushel, P., Martinez, J., Walker, N. J. and Churchill, G. A. (2002) Statistical analysis of a gene expression microarray experiment with replication. Statistica Sinica., 12: 203-217.
Kim, E.Y., Seo, Y.S. and Kim, W.T. (2011). AtDSEL, an Arabidopsis cytosolic DAD1-like acylhydrolase is involved in negative regulation of storage oil mobilization during seedling establishment. J. Plant Physiol., 168(14):1705-9.
Kiribuchi, K., Jikumaru, Y., Kaku, H., Minami, E., Hasegawa and Kodama. M. O. (2005). Involvement of the basic helix-loop-helix transcription factor RERJ1 in wounding and drought stress responses in rice plants. Biosci. Biotechnol. Biochem., 69:1042-1044.
Knoop, V., Unseld, M., Marienfeld, J., Brandt, P., Sünkel, S., Ullrich, H. and Brennicke, A. (1996). Copia-, gypsy- and LINE-like retrotransposon fragments in the mitochondrial genome of Arabidopsis thaliana. Genetics. 142:579-585.
Kobayashi, Y., Yamamoto, S., Minami, H., Kagaya, Y. and Hattori, T. (2004). Differential activation of the rice sucrose nonfermenting1-related protein kinase2 family by hyper osmotic stress and abscisic acid. The Plant Cell. 16:1163-1177.
Kodaira, K. S., Qin, F., Tran, L. S. P., Maruyama, K., Kidokoro, S., Fujita, Y., Shinozaki, K. and Yamaguchi-Shinozaki, K. (2011). Arabidopsis Cys2/His2 zinc-finger proteins 162
AZF1 and AZF2 negatively regulate abscisic acid-repressive and auxin-inducible genes under abiotic stress conditions. Plant physiol., 157: 742-756.
Kreps, J. A., Wu, Y., Chang, H. S., Zhu, T., Wang, X. and Harper, J. F. (2002). Transcriptome changes for Arabidopsis in response to salt, osmotic, and cold stress. Plant Physiol., 130: 2129-2141.
Krieg, D.R. (2000). Cotton water relations. pp. 7-15. In: D.M. Oosterhuis (ed). Proceedings 2000 Cotton Research Meeting and Summaries of Cotton Research. Arkansas Agric. Exp. Sta., Special Report 198.
Kuo, Y.C.,, Yang, L.M. and Lin, L.C. (2004). Isolation and immune modulatory effect of flavonoids from Syzygium samarangense. Planta Med. 70: 1237-1239.
Lawlor, D. W. (2002). Limitation to photosynthesis in water-stressed leaves: Stomatal metabolism and the role of ATP. Annals Hort. 89: 871-885.
Lease, K., Ingham, E., and Walker, J.C. (1998). Challenges in understanding RLK function. Curr. Opin. Plant Biol. 1: 388-392.
Lee, H. J., Xiong, L. M., Gong, Z. Z., Ishitani, M., Stevenson, B. and Zhu, J. K. (2001) The Arabidopsis HOS1 gene negatively regulates cold signal transduction and encodes Ring finger protein that displays cold regulated nucleo cytoplasmic partitioning. Genes & Dev.15: 912-924
Lee, M. L. T., Kuo, F. C., Whitmore, G. A. and Sklar, J. (2000). Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations. PNAS, USA. 97: 9834-9839. 163
Lee, T. M. and Liu, C. H. (1999). Correlation of decreases calcium contents with proline accumulation in the marine green Macroalga ulva fasciata exposed to elevated NaCl contents in seawater. J. Exp., Bot. 50:1855-1862.
Lee, J., Bricker, T.M., Lefevre, M., Pinson, S.R.M. and Oard, J.H. (2006). Proteomic and genetic approaches to identifying defence-related proteins in rice challenged with the fungal pathogen Rhizoctonia solani. Mol. Pl. Pathol., 7:405–416.
Leidi, E.O., Lopez, J. M., Lopez, M. and Gutierrez, J.C. (1993). Searching for tolerance to water stress in cotton genotypes: photosynthesis, stomatal conductance and transpiration. Photosynthtica, 28:383-390.
Leung, Y. F. and Cavalieri, D. (2003). Fundamentals of cDNA microarray data analyses. Trends in Genetics, 19: 649-659.
Levitt, J. (1980). Responses of Plants to environmental stresses; water, radiation, salt and other stresses. New York: Academic Press. 2: 93-128.
Levitt, J. (1982). Stress terminology. In: N. C. Turner and P. J. Kramer (Eds.). pp. 437-439. Adaptation of plants to water and high temperature stress. Wiley-Interscience. New York.
Likhitwitayawuid, K, Sawasdee K, Kirtikara K (2002). Flavonoids and stibenoids with COX- 1 and COX-2 inhibitory activity from Dracaenaloureiri. Planta Med. 68: 841-843.
Liming, X., Manabu, I., Hojoung, L. and Jian-Kang, Z. (2001). The Arabidopsis LOS5/ABA3 locus encodes a molybdenum cofactor sulfurase and modulates cold stress– and osmotic stress–responsive gene expression. The Plant Cell. 13:2063- 2083. 164
Lippold, F., Sanchez, D. H., Musialak, M., Schlereth, A., Scheible, W. R., Hincha, D. K. and Udvardi, M. K. (2009). AtMyb41 regulates transcriptional and metabolic responses to osmotic stress in Arabidopsis. Plant Physiol., 149: 1761-1772.
Lopez, F., Vansuyt, G., Fourcroy, P. and Casse-Delbart, F. (1994). Accumulation of a 22- kDa protein and its mRNA in the leaves of Raphanus sativus in response to salt stress or water deficit. Physiologia Plantarum. 91: 605-614.
Hawkesford, M.J. and Wray, J.L. (2000). Molecular genetics of sulphate assimilation. Advances in Botanical Research. 33:159-223.
Maccioni, R.B. and Cambiazo, V. (1995). Role of microtubule-associated proteins in the control of microtubule assembly. Physiol Rev., 75:835-64.
Mackill, D. J. A. (2007). A marker assisted backcross approach for developing submergent tolerant rice cultivars. Theor. Appl. Genet., 115: 767-776.
Mafakheri, A., Siosemardeh, B., Bahramnejad, P., Struik, C. and Sohrabi, Y. (2010). Effect of drought stress on yield, proline and chlorophyll contents in three chickpea cultivars. Aust. J. Crop Sci., 4:500-585.
Maguire, T. L., Grimmond, S., Forrest, A., Iturbe-Ormaetxe, I., Meksem, K. and Gresshoff, P. (2002). Tissue-specific gene expression in soybean (Glycine max) detected by cDNA microarray analyses. J. Plant Physiol., 159: 1361-1374.
Mahajan, S. and Tuteja, N. (2005). Cold, salinity and drought stresses: an overview. Arch. of Biochem. and Biophy., 444: 139-158. 165
Maio, A. D. (1999). Heat shock proteins: facts, thoughts, and dreams. Shock (Augusta, Ga.) 11(1): 1-12.
Manivannan P., Jaleel, C.A., Sankar, B., Kishorekumar, A., Somasundaram, R..,. Alagu Lakshmanan, G.M. and Panneerselvam, R. (2007b). Growth, biochemical modifications and proline metabolism in Helianthus annuus L. as induced by drought stress. Colloids Surf. B: Biointerf., 59: 141-149.
Marta, B.W., Krzysztof, B.W. and Marion, K.G. (2014). The extostosin family: Proteins with many functions. Matrix Biology., 35:25–33.
Martin, K., Yaniv, S., Holly, C., Elena, C., Christoph, M., Thomas, L. and Brendan, D. (2006). Analyses of the transcription factor WUSCHEL and its functional homologue in antirrhinum reveals a potential mechanism for their roles in meristem maintenance. The Plant Cell. 18:560–573.
Maroco, J. P., Pereira, J. S. and Chaves, M. (1997). Stomatal responses to leaf-to-air vapour pressure deficit in Sahelian species. Aust. J. Plant Physiol., 24: 381-387.
Martiınez, J. P., Lutts, S., Schanck, A., Bajji, M. and Kinet, J. M. (2004). Is osmotic adjustment required for water stress resistance in the Mediterranean shrub Atriplex halimus L.? J. Plant Physiol., 161: 1041-1051.
Mary, C.H., Marina, I.S. and Stefan, E.H.A. (2012). The emerging role of acyl-CoA thioesterases and acyltransferases in regulating peroxisomal lipid metabolism. Bioch. et Biophys. Acta., 1822:1397–1410. 166
Massaci, A., Nabiev, S. M., Petrosanti, L., Nematov, S. K., Chernikova, T. N., Thor, K. and Leipner, J. (2008). Response of the photosynthetic apparatus of cotton (Gossypium hirsutum L.) to the onset of drought stress under field conditions studied by gas- exchange analysis and chlorophyll fluorescence imaging. Plant Physiol. Biochem., 46: 189-195.
Matsui, A., Ishida, J., Morosawa, T., Mochizuki, Y., Kaminuma, E., Endo, T. A., Okamoto, M., Nambara, E., Nakajima, M. and Kawashima, M. (2008). Arabidopsis transcriptome analyses under drought, cold, high-salinity and ABA treatment conditions using a tiling array. Plant and Cell Physiol., 49: 1135-1149.
Matthews, R.B., Azam, A. and Peacock, J.M. (1990). Response of four sorghum lines to mid-season drought: II. Leaf characteristics. Field Crops Res., 25: 297-308.
Matthew, W., Jones R., Justin, O.B. and Daphne, P. (2007). Genome-wide expression profiling of the Arabidopsis female gametophyte identifies families of small, secreted proteins. Plos Genet., 3:171.
Maury, P., Berger, M. F., Mojayad and Planchon, C. (2000). Leaf water characteristics and drought acclimation in sunflower genotypes. Plant and Soil, 223: 153-160.
Mccord, J. M. (2000). The evolution of free radicals and oxidative stress. The Amer. J. medicine, 108: 652-659.
Mc Michael, B.L. and Hesketh, J.D. (1982). Field investigations of the response of cotton to water deficits. Field Crops Res., 5:319–333.
167
Meloni, D.A., Olivamartinez, M.A. and Cambraia, J. (2003). Photosynthesis and activity of superoxide dismutase, peroxidase and glutathione reductase in cotton under salt stress. Environt. Exp. Bot., 49:69-76.
Meyers, B.C., Morganteand, M. and Michelmore, R. W. (2002). TIR-X and TIR-NBS proteins: two new families related to disease resistance TIR-NBS-LRR proteins encoded in Arabidopsis and other plant genomes. The Plant Journal, 32: 77–92
Miller, M., and Taube, K. (1993). The Gods and Symbols of Ancient Mexico and the Maya: An Illustrated Dictionary of Mesoamerican Religion. London: Thames and Hudson.
Miller, G., Shulaev, V. and Mittler, R. (2008). Reactive oxygen signaling and abiotic stress. Physiol. Plant, 133: 481-489.
Ming, R., R. Van-Buren, C. M. Wai, H. Tang, M. C. Schatz, J. E. Bowers, E. Lyons, Ming-Li Wang, J. Chen, E. Biggers, J. Zhang, L. Huang, L. Zhang, W. Miao, J. Zhang, Z. Ye, C. Miao, Z. Lin, H. Wang, H. Zhou, W. C. Yim, H. D. Priest, C. Zheng, M. Woodhouse, P. P. Edger, R. Guyot, H.Guo, H. Guo, G. Zheng, R. Singh, A. Sharma, X. Min, Y. Zheng, H. Lee, J. Gurtowski, F. J. Sedlazeck, A. Harkess, M. R. McKain, Z. Liao, J. Fang, J. Liu, X. Zhang, Q. Zhang, W. Hu, Y. Qin, K. Wang, L. Chen, N. Shirley, Y. Lin, L. Liu, A. G. Hernandez, C. L. Wright, V. Bulone, G. A. Tuskan, K. Heath, F. Zee, P. H. Moore, R. Sunkar, J. H. Leebens-Mack, T. Mockler, J. L. Bennetzen, M. Freeling, D. Sankoff, A. H. Paterson, X. Zhu, X. Yang, J. Andrew, C. Smith, J. C. Cushman, R. E. Paull and Q. Yu. (2015). The pineapple genome and the evolution of CAM Photosynthesis. Nature Genetics., 47:1435–1442.
Mittler, R.. (2002). Oxidative stress, antioxidants and stress tolerance. Trends Plant Sci., 7: 405-410.
168
Mohammadi, M., Kav, N. N. K. and Deyhols, M. K. (2007). Transcriptional profiling of hexaploid wheat (Triticum aestivum L.) roots identifies novel dehydration-responsive genes. Plant Cell Environ., 30: 630-645.
Mohammed, B., Gabel, M. and Karlsson, L.M. (2013). Nutritive values of the drought tolerant food and fodder crop. .Afri. J. Agri Res., 8: 2326-2333.
Molnar, G., Bancos, S., Nagy, F. and Szekeres, M. (2002). Characterization of BRH1, a brassinosteroid-responsive RING-H2 gene from Arabidopsis thaliana. Planta 215: 127-133.
Moon, J., Parry, G. and Estelle, M. (2004). The ubiquitin-proteasome pathway and plant development. Plant Cell 16: 3181-3188
Morant A.V., Jørgensen K., Jørgensen C., Paquette, S.M., Sánchez-Pérez, R. Mølle, B.L. and Bak, S. (2008). Beta-glucosidases as detonators of plant chemical defense. Phytochem., 69:1795-813.
Morimoto, R. I., Tissieres, A. and Georgopoulos, C. (1994). Heat Shock Proteins: Structure, function and regulation. Cold Spring Harbor Lab. Press, Cold Spring Harbor, NewYork.
Moussa, H.R. and Abdel-Aziz, S.M. (2008). Comparative response of drought tolerant and drought sensitive maize genotypes to water stress. Aust. J. Crop Sci., 1: 31-36.
Moussa, H.R. (2006). Influence of exogenous application of silicon on physiological response of salt-stressed maize (Zea mays L.). Int. J. Agric. Biol., 8: 293-297.
169
Nakashima, K., Ito, Y. and Yamaguchi-Shinozaki, K. (2009). Transcriptional regulatory networks in response to abiotic stresses in Arabidopsis and grasses. Plant Physiol., 149: 88-95.
Nath, A.K., Kumari, S., and Sharma, D.R. (2005). In vitro selection and characterization of water stress tolerant cultures of bell pepper. Ind. J. Plant Physiol., 10:14-19
Navari-Izzo, F., Quartacci, M. F. and Izzo, R. (1990). Water-stress induced changes in protein and free aminoacids in field grown maize and sunflower. Plant Physiol Biochem., 28: 531-537.
Nayyar, H. and Gupta, D. (2006). Differential sensitivity of C3 and C4 plants to water deficit stress: association with oxidative stress and antioxidants. Environ. Exp. Bot. 58: 106-113.
Neill, S.J. and Burnett. E.C. (1999). Regulation of gene expression during water deficit stress. Plant Growth Regulation, 29: 23-33.
Nguyen, H. T., Babu, R. C. and Blum, A.(1997). Breeding for drought resistance in rice: Physiology and molecular genetics considerations. Crop Sci., 37: 1426-1434.
Niemes, S., Langhans, M., Viotti, C., Scheuring, D., San Wan Yan, M., Jiang, L., Hillmer, S., Robinson, D.G., and Pimpl, P. (2010). Retromer recycles vacuolar sorting receptors from the trans-golgi network. Plant J. 61: 107–121.
Nicolas, D., Boris, S. and Laurent, D.N. (2014). Emerging functions of nodulin-like proteins in non-nodulating plant species. Plant Cell Physiol., 55:469-74 170
Nobel, P. S. (1988). Environmental biology of Agaves and Cacti. Sci., 242: 948-949.
Nobel, P. S. (1991). Achievable productivities of certain CAM plants - Basis for high values
compared with C3 and C4 plants. New Phytologist, 119: 183-205.
Nobel, P. S. (2010). Desert wisdom/agaves and cacti: CO2, water, climate change. Universe, Inc., Bloomington.
Nobel, P. S., Garciamoya, E. and Quero, E. (1992). High annual productivity of certain agaves and cacti under cultivation. Plant Cell and Environ., 15: 329-335.
Nobel, P.S. (1977). Water relations of flowering of Agave Desert, Botanical Gazette. 138:1- 6.
Nyachiro, J.M.. Briggs, K.G., Hoddinott, J. and Johnson-Flanagan, A.M. (2001). Chlorophyll content, chlorophyll fluorescence and water deficit in spring wheat. Cereal Res. Commun. 29: 135–142.
O‟Connell, M.A. and Rodriguez-uribe, L. (2006).A root specific bZIP transcription factor is responsiv to water deficit stress in Tepary bean (Phaseolus acutifolius) and common bean (P. vulgaris), Journal of Experimental Botany, 57:1391-1398.
Oertli, J. J., Lips, S. H. and Agami, M. (1990). The strength of sclerophyllous cells to resist collapse due to negative turgor pressure. Acta Oecol. 11: 281–289.
Oliviusson, P., Heinzerling, O., Hillmer, S., Hinz, G., Tse, Y.C., Jiang, L., and Robinson, D.G. (2006). Plant retromer, localized to the pre-vacuolar compartment and microvesicles in Arabidopsis, may interact with vacuolar sorting receptors. Plant Cell., 18: 1239–1252. 171
Olsen, A. N., Ernst, H. A., Leggio, L. L. and Skriver, K. (2005). NAC transcription factors: structurally distinct, functionally diverse. Trends Plant Sci., 10: 79-87.
Ooka, H., Satoh, K., Doi, K., Nagata, T., Otomo, Y., Murakami, K., Matsubara, K., Osato, N., Kawai, J. and Carninci, P. (2003). Comprehensive analysis of NAC family genes in Oryza sativa and Arabidopsis thaliana. DNA res., 10: 239-247.
Oosterhuis, D.M. and Wullschleger, S.D. (1987). Osmotic adjustment in cotton (Gossypium hirsutum L.) leaves and roots in response to water stress. Plant Physiol., 84: 1154- 1157.
Oosterhuis, D. M. and Wullschleger, S. D. (1988). Drought tolerance and osmotic adjustment of various crops in response to water stress. Arkansas Farm Res., 37: 12.
Palomino, G., Dolezel, J., Mendez, I. and Rubluo, A. (2003). Nuclear genome size analyses of Agave tequilana Weber. Caryologia, 56: 37-46.
Panaretou, B. and Zhai, C. (2008). The heat shock proteins: their roles as multi-component machines for protein folding. Fungal biol. rev., 22: 110-119.
Parida, A., Das, A.B. and Das, P. (2002). NaCl stress causes changes in photosynthetic pigments, proteins and other metabolic components in the leaves of a true mangrove, Bruguiera parviflora, in hydroponic cultures. J. Plant Biol. 45:28–36.
Parimala, P. and Muthuchelian, K. (2010). Physiological response of non-Bt and Bt cotton to short-term drought stress. Photosynthetica. 48: 630-634.
172
Pastore, J. (2011). "A role for LATE MERISTEM IDENTITY2 in the reproductive development of Arabidopsis" Dissertations available from ProQuest. Paper AAI3485718. http://repository.upenn.edu/dissertations/AAI3485718
Penna, S. (2003). Building stress tolerance through over-producing trehalose in transgenic plants. Trends in Plant Sci., 8: 355-357.
Pinheiro, C., Chaves, M. M. and Ricardo, C. P. (2001). Alterations in carbon and nitrogen metabolism induced by water deficit in the stems and leaves of Lupinus albus L. J. Exp. Bot., 52: 1063-1070.
Praba, M. L., Cairns, J. E., Babu, R. C. and Lafitte, H. R. (2009). Identificatio n of physiological traits underlying cultivar differences in drought tolerance in rice and wheat. J. Agron Crop Sci., 195: 30-46.
Prat, H. (1948). General features of the epidermis in Zea mays. Ann. Missouri Bot. Gard., 35:341-351.
Price, N.D., Famili, I., Beard, D. A., and Palsson, B. O. (2002). Extreme pathways and Kirchhoff‟s second law. Biophysics J., 83: 2879-2882.
Quisenberry, J. E., Roark, B. and McMichael, B. L. (1982). Use of transpiration decline curves to identify drought-tolerant cotton germplasm. Crop Sci., 22: 918-922.
Rabbani, M., Maruyama, K., Abe, H., Khan, M., Katsura, K., Ito, Y., Yoshiwara, K., Seki, M., Shinozaki, K. and Yamaguchi-Shinozaki, K. (2003). Monitoring expression profiles of rice genes under cold, drought, and high-salinity stresses and abscisic 173
acid application using cDNA microarray and RNA gel-blot analyses. Plant Physiol., 133: 1755-1767.
Radin, J.W. (1992). Reconciling water-use efficiency of cotton in field and laboratory. Crop Sci. 32:13-18.
Ramamoorthy, R., Jiang, S. Y., Kumar, N., Venkatesh, P. N. and Ramachandran, S. (2008). A comprehensive transcriptional profiling of the WRKY gene family in rice under various abiotic and phytohormone treatments. Plant Cell Physiol., 49: 865-879.
Ramanjulu S. and Bartels D. (2002). Drought and dessication induced modulation of gene expression in plants. Plant Cell Environ. 25(2):141-151.
Rao, I. and Cramer. G. (2003). Plant nutrition and crop improvement in adverse soil conditions, In M. Chrispeels and D. Sadava (eds). Plants, genes, and crop Biotechnology. American Society of Plant Biologists and ASPB Education, 270-303.
Rascio, A., Platani, C., Scalfati, G., Tonti, A. and Di Fonzo, N. (1994). The accumulation of solutes and water binding strength in durum wheat. Physiologia Plantarum, 90:715- 721.
Ren, X., Chen, Z., Liu, Y., Zhang, H., Zhang, M., Liu, Q., Hong, X., Zhu, J. K. and Gong, Z.
(2010). ABO3, a WRKY transcription factor, mediates plant responses to abscisic acid and drought tolerance in Arabidopsis. Plant J., 63: 417-429.
174
Rensink, W. A. and Buell, C. R. (2005). Microarray expression profiling resources for plant genomics. Trends in Plant Sci., 10: 603-609.
Ritsema, T., and S. Smeekens. (2003). Fructans: beneficial for plants and humans. Current Opinion in Plant Biology 6:223-230.
Roche J., Hewezi T., Bouniols A. and Gentzbittel L. (2009). Real-time PCR monitoring of signal transduction related genes involved in water stress tolerance mechanism of sunflower. Plant Physiol. Biochem. 47: 139-145.
Rodriguez-Uribe, L. and O‟Connell, M.A. (2006). A root-specific bZIP transcription factor is responsive to water deficit stress in tepary bean (Phaseolus acutifolius) and common bean (P. vulgaris).J. Exp. Bot., 57:1391-8.
Rontein, D.G., Basset, G. and Hanson, A. (2002). Metabolic engineering of osmoprotectant accumulation in plants. Metab. Eng., 4: 49-56.
Saeed, F., Hagemann, S. and Jacob, D. (2009). Impact of irrigation on the South Asian summer monsoon. Geophysical Research Letters, 36.
Saeed, M., Kheir, A. and Al-Sayed, A. (2005). Supperssive effect of some amino acids against Meloidogyne incognita on Soybeans. J. Agric. Sci. Mansoura Univ., 30: 1097-1103.
Saibo, N. J., Lourenco, T. and Oliveira, M. M. (2009). Transcription factors and regulation of photosynthetic and related metabolism under environmental stresses. Ann Bot., 103:609-23.
175
Saldana, O. I. (2007). Carbohydrate metabolism in the leaf of the Agave tequilana (Weber) plant. uk.bl.ethos.443993
Samarah, N. H., Alqudah, A. M., Amayreh, J. A. and McAndrews, G. M. (2009). The effect of late-terminal drought stress on yield components of four barley cultivars. J. Agron. Crop Sci., 195: 427-441.
Sánchez-Díaz M., Tapia C. and Antolín M.C. (2008). Abscisic acid and drought response of Canarian laurel forest tree species growing under controlled conditions. Environ. Exp. Bot. 64: 155-161.
Sanderfoot, A.A., Ahmed, S.U., Marty-Mazars, D., Rapoport, I., Kirchhausen, T., Marty, F. and Raikhel N.V. (1998). A putative vacuolar cargo receptor partially colocalizes with AtPEP12p on a prevacuolar compartment in Arabidopsis roots. Proc. Natl. Acad. Sci. USA 95: 9920–9925.
Sangita, C.S. and Janet, L.S. (2001). The PRT protein family. Current Opinion in Structural Biology. 11:733–739.
Sankar, B., Jaleel, C.A., Manivannan, P., Kishorekumar, A., Somasundaram, R. and Panneerselvam, R. (2007). Drought-induced biochemical modifications and proline metabolism in Abelmoschus esculentus (L.) Moench. Acta Bot. Croat., 66(1): 43-56
Savchenko, G. E., Klyuchareva, E. A., Abramck, L. M. and Serdyuchenko, E. V. (2002). Effect of periodic heat shock on the inner membrane system of atioplasts. Russ. J. Plant Physiol., 49: 349-359.
176
Saccardy, K., Pineau, B., Roche, O. and Cornic, G. (1998). Photo chemical efficiency of photosystem and xanthophyll cycle components in Zea mays L. leaves exposed to water stress and high light. Photosynthesis. Res., 56: 57-66.
Scheideler, M., Schlaich, N. L., Fellenberg, K., Beissbarth, T., Hauser, N. C., Vingron, M., Slusarenko, A. J. and Hoheisel, J. D. (2002). Monitoring the switch from housekeeping to pathogen defense metabolism in Arabidopsis thaliana using cDNA arrays. J. Biol. Chem., 277: 10555-10561.
Schena, M., Shalon, D., Davis, R. W. and Brown, P. O. (1995). Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Sci., 270: 467-470.
Schott, A., Ravaud, S., Keller, S., Radzimanowski J., Viotti, C., Hillmer, S., Sinning, I. and Strahl, S. (2010). Arabidopsis stromal-derived Factor2 (SDF2) is a crucial target of the unfolded protein response in the endoplasmic reticulum. J. Biol. Chem., 285:18113-21.
Schott, A. and Strahl, S. (2011). Methods to study stromal-cell derived factor 2 in the context of ER stress and the unfolded protein response in Arabidopsis thaliana. Methods Enzymol., 490:295-319.
Schroeder, J. I., Allen, G. J., Hugouvieux, V., Kwak, J. M. and Waner, D. (2001). Guard cell signal transduction. Ann. Rev. Plant Physio. and Plant Mol. Bio., 52: 627-658.
177
Seki, M., Kamei, A., Yamaguchi-Shinozaki, K.and Shinozaki, K. (2003). Molecular responses to drought, salinity and frost: common and different paths for plant protection. Current Opinion in Biotechnol., 14: 194-199.
Seki, M., Narusaka, M., Abe, H., Kasuga, M., Yamaguchi-Shinozaki K., Carninci, P., Hayashizaki, Y. and Shinozaki, K. (2001). Monitoring the expression pattern of 1300 Arabidopsis genes under drought and cold stresses using full-length cDNA microarray. The Plant Cell. 13: 61-72.
Seki, M., Narusaka, M., Kamiya., A, Ishida, J., Satou, M., Sakurai, T., Nakajima, M., Enju, A., Akiyama, K., Oono, Y., Muramatsu, M., Hayashizaki, Y., Kawai, J., Carninci, P., Itoh, M., Ishii, Y., Arakawa, T., Shibata, K., Shinagawa, A. and Shinozaki K. (2002). Functional annotation of a full-length Arabidopsis cDNA collection. Sci., 296:141- 145.
Selote, D.S. and Chopra, R.K. (2004). Drought induced spike sterility is associated with an inefficient antioxidant defense in rice plants. Physiol. Plant., 121(3):462-471.
Serrano, M. and Guzma´n, P. (2004) Isolation and gene expression analyses of Arabidopsis thaliana mutants with constitutive expression of atl2, an early elicitor-response RING-H2 zinc-finger gene. Genet., 167: 919-929.
Shaohong, Q., Guifu, L., Zhou, B., Maria, B., Lirong, Z., Liangying, D., Bin, H. and Guo- Liang W. (2006).The broad-spectrum blast resistance gene pi9 encodes a nucleotide- binding site–leucine-rich repeat protein and is a member of a multigene family in rice. Genetics. 172:1901–1914.
Shao, H, H. Wang and X. Tang. (2015). NAC transcription factors in plant multiple abiotic stress responses: progress and prospects. Front Plant Sci., 6: 902.
178
Shao, H. B., Chu, L. Y., Jaleel, C. A., Manivannan, P., Panneerselvam, R. and Shao, M. A. (2009). Understanding water deficit stress-induced changes in the basic metabolism of higher plants-biotechnologically and sustainably improving agriculture and the eco-environment in arid regions of the globe. Crit. Rev. Biotechnol., 29: 131-151.
Sharaf, A. and Zahran, M. (1967). Pharmacological investigation on Agave Sisalana with special study of its ecbolic effect. Plant Foods Hum.Nutr. 14: 345-351.
Sheldon, S. (1980). Ethnobotany of Agave-lecheguilla and yucca-carnerosana in mexico zona ixtlera. Economic Botany 34:376-390.
Shen, B., Jensen, R. G. and Bohnert, H. J. (1997). Increased resistance to oxidative stress in transgenic plants by targeting mannitol biosynthesis to chloroplasts. Plant Physiol., 113: 1177-1183.
Shinozaki, K. and Shinozaki, Y. K. (2000). Molecular responses to dehydration and low temperature: differences and cross-talk between two stress signaling pathways. Curr. Opin. Plant Biol., 3: 217-223.
Shinozaki, K., Shinozaki, Y. K. and Seki, M. (2003). Regulatory network of gene expression in the drought and cold stress responses. Curr Opin Plant Biol., 6: 410-417.
Yamaguchi-Shinozaki K. and Shinozaki K. (2005). Organization of cis-acting regulatory elements in osmotic- and cold-stress-responsive promoters. Trends Plant Sci. 10: 88- 94.
Shinozaki. K., and Yamaguchi-Shinozaki, K. (2006). Gene networks Involved in drought stress response and tolerance, J. Exp. Bot., 58:221-227.
179
Siddique, M. R. B., Hamid, A. and Islam, M. S. (2001). Drought stress effects on water relations of wheat. Bot. Bull. Acad. Sin., 41: 35-39.
Silva, J. M. D. and Arrabaca, M. C. (2004). Contributions of soluble carbohydrates to the
osmotic adjustment in the C4 grass Setaria sphacelata: A comparison between rapidly and slowly imposed water stress. J. plant physiol., 161: 551-555. Silva, E.C., Silva, M.F.A., Nogueira, R.J.M.C. and Albuquerque, M. B. (2010). Growth evaluation and water relations of Erythrina velutina seedlings in response to drought stress. Brazilian J. Plant Physiol., 22:225-233.
Slauson, L. A. (2001). Insights on the pollination biology of Agave (Agavaceae). Haseltonia. 8:10-23.
Smirnoff, N. (1993). Tansley Review No. 52. The role of active oxygen in the response of plants to water deficit and desiccation. New Phytologist, 27-58.
Smith, J. A. C. and Nobel, P. S. (1986). Water movement and storage in a desert succulant- anatomy and rehydration kinetics for leaves of Agave deserti. J. Exp. Bot., 37: 1044- 1053.
Sophia, L.S. (2014). The role of ubiquitin and the 26S proteasome in plant abiotic stress signaling. Front Plant Sci., 5:135.
Sreenivasulu N., Sopory S. K., Kavi Kishor P. B. (2007). Deciphering the regulatory mechanisms of abiotic stress tolerance in plants by genomic approaches. Gene 388:1–1310-1016
Stewart, C. R. and Larher, F. (1980). Accumulation of amino acids and related compounds in relation to environmental stress. In: Miflin, B. J. (ed). The Biochemistry of Plants: a comprehensive treatise, New York: Academic Press 5.609-635. 180
Stone, J.M. and Walker, J.C. (1995). Plant protein kinase families and signal transduction. Plant Physiol., 108:451-457.
Stratford, S., William, B., Diane, L.H., Jason, G.S., Robyn, C., Alice, G., Allan, M.S., Sheila, M., and Patricia, B. (2001). A leucine-rich repeat region is conserved in pollen extensin-like (Pex) proteins in monocots and dicots. Plant Mol. Biol. 46:43–56.
Sunkar, R., Bartels, D. and Kirch, H. H. (2003). Over expression of a stress-inducible dehydrogenase gene from Arabidopsis thaliana in transgenic plants improves stress tolerance. The Plant J., 35:452-64
Swamy, P. and Smith, B. (1999). Role of abscisic acid in plant stress tolerance. Current Sci., 76: 1220-1227.
Swindell, W. R., Huebner, M. and Weber, A. P. (2007). Transcriptional profiling of Arabidopsis heat shock proteins and transcription factors reveals extensive overlap between heat and non-heat stress response pathways. BMC Genomics 8: 125.
Szabados, L. and Savoure, A. (2009). Proline: a multifunctional amino acid. Trends Plant Sci., 15: 89-97.
Taiz, L and Zeiger, E. (2009). Physiological and biochemical responses of semi arid plants subjected to water stress plant physiology. Sinauer Associates, ISBN 978- 0878938230,Sunderland
Takasaki, H., Maruyama, K., Kidokoro, S., Ito, Y., Fujita, Y., Shinozaki, K., Yamaguchi- Shinozaki, K. and Nakashima, K. (2010). The abiotic stress-responsive NAC-type 181
transcription factor OsNAC5 regulates stress-inducible genes and stress tolerance in rice. Molecular Genetics and Genomics, 284: 173-183.
Tang, B., Banerjee, B., Greenberger, P.A., Fink, J.N., Kelly, K.J. and Kurup, V.P. (2000). Antibody binding of deletion mutants of Asp f 2, the major Aspergillus fumigatus allergen. Biochem. Biophys. Res. Comm. 270:1128-1135
Tatsuya, T., Yuan, Q., Yiding, H., Damayanthi, D. and Ravishankar, P. (2010). A role for LORELEI, a putative glycosylphosphatidyl inositol anchored protein, in Arabidopsis thaliana double fertilization and early seed development The Plant J., 62:571–588.
Tattersall, E. A., Grimplet, J., Deluc, L., Wheatley, M. D., Vincent, D., Osborne, C., Ergul, A., Lomen, E., Blank, R. R., Schlauch, K. A., Cushman, J. C. and Cramer, G .R. (2007). Transcript abundance profiles reveal larger and more complex responses of grapevine to chilling comparedto osmotic and salinity stress. Funct. Integr. Genomics. 7: 317-33.
Tester, M. and Bacic, A. (2005). Abiotic stress tolerance in grasses. From model plants to crop plants. Plant Physiol., 137: 791-793.
Tester, M. and Langridge, P. (2010). Breeding technologies to increase crop production in a changing world. Science 327:818-822.
Thomashow, M. F. (1999). Plant cold acclimation: freezing tolerance genes and regulatory mechanisms. Annual Rev.Plant Biol., 50: 571-599.
Thomashow, M. F. (2001). So what's new in the field of plant cold acclimation? Lots! Plant Physiology, 125: 89-93.
182
Tissue, D. T. and Nobel, P. S. (1988). Parent ramet connections in Agave deserti- influences of carbohydrates on growth. Oecologia .75:266-271
.
Todaka, D., Nakashima, K., Shinozaki, K. and Yamaguchi-Shinozaki, K. (2012). Toward understanding transcriptional regulatory networks in abiotic stress responses and tolerance in rice. Rice, 5: 1-9.
Toker, C., Lluch, C., Tejera, N. A., Serraj, R. and Siddique, K. H. M. (2007). Abiotic Stresses. In Chickpea Breeding and Management (Yadav, S.S., Redden, R., Chen, W. and Sharma, B., (eds). UK: CABI, pp. 474-496.
Tran, L. S., Nakashima, K., Sakuma, Y., Osakabe, Y., Qin, F., Simpson, S. D., Maruyama, K., Fujita, Y., Shinozaki, K. and Yamaguchi-Shinozaki, K. (2007). Co-expression of the stress-inducible zinc finger homeodomain ZFHD1 and NAC transcription factors enhances expression of the ERD1 gene in Arabidopsis. The Plant J., 49: 46-63.
Tripp, J., Mishra, S. K. and Scharf, K. D. (2009). Functional dissection of the cytosolic chaperone network in tomato mesophyll protoplasts. Plant Cell Environ., 32: 123- 133.
Trouverie, J., The‟venot, C., Rocher, J. P., Sotta, B. and Prioul, J. L. (2003). The role of abscisic acid in the response of a specific vacuolar invertase to water stress in the adult maize leaf. J. Exp. Bot., 54: 2177-2186.
183
Tseng, G. C., Oh, M. K., Rohlin, L., Liao, J. C. and Wong, W. H. (2001). Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects. Nucleic Acids Res., 29: 2549-2557.
Tuberosa, R. and Salvi, S. (2006). Genomics-based approaches to improve drought tolerance in plants. Trends Plant Sci., 11:405-12.
Turner, P.R., Jaffe, L.A., and Fein, A. (1986). Regulation of cortical vesicle exocytosis in sea urchin eggs by inositol 1,4,5-trisphosphate and GTP-binding protein, J. Cell Biol., 102:70. Twell, D., Wing, R., Yamaguchi, J. and McCormick, S. (1989). Isolation and expression of an anther-specific gene from tomato. Mol. General Genetics., 217:240–245.
Tuteja, N. and Sopory, S. K. (2008). Chemical signaling under abiotic stress environment in plants. Plant Signal Behav., 3: 525-536.
Uno, Y., Furihata, T., Abe, H., Yoshida, R., Shinozaki, K. and Yamaguchi-Shinozaki, K. (2000). Arabidospsis basic leucine zipper transcription factors involved in an abscisic acid-dependent signal transduction pathway under drought and high salinity conditions. PNAS, USA. 97:11632-11637.
Valenzuela-Zapata, A. G. (1997). El Agave Tequilero, su cultivo e industria. Lıtteris Editores, Mexico. pp 1–204.
Valenzuela-Zapata, A. G. and Nabhan, G. P. (2003). Tequila. A natural and cultural history. The University of Arizona Press, Tuscon, Arizona.
184
Velculescu, V. E., Zhang, B., Vogelstein, B. and Kinzler, K. (1995). Serial analysis of gene expression. Sci., 270: 484-487.
Verastegui, M. A., Sanchez, C. A., Heredia, N. L. and Garcia Alvarado J. S. (1996). Antimicrobial activity of extracts of three major plants from the Chihuahuan desert. J. Ethnopharmacology, 52: 175-177.
Veronica, S.P., Wei, Z., Basem, K., Birgit, G., Theresa, F.K., Philippe, S.K. and Anton, R.S. (2011). The Arabidopsis glucosyltransferase UGT76B1 conjugates isoleucic acid and modulates plant defense and senescence. The Plant Cell. 23:4124–4145.
Vij, S. and Tyagi, A. K. (2006). Genome-wide analysis of the stress associated protein (SAP) gene family containing A20/AN1 zinc-finger (s) in rice and their phylogenetic relationship with Arabidopsis. Molecular Genetics and Genomics. 276: 565-575.
Vij, S. and Tyagi, A. K. (2007). Emerging trends in the functional genomics of the abiotic stress response in crop plants. Plant Biotech J., 5: 361-380.
Vijayalakshmi, T., Varalaxmi, Y., Jainender, S., Yadav, S.K., Vanaja, M., Jyothilakshmi, N. and Maheswari, M. (2012). Physiological and biochemical basis of water-deficit stress tolerance in pearl millet hybrid and parents. J. Am. Plant Sci., 3:1730-1740.
Vincent, Z. Benoıˆt, G., Monique L.R., Charles, A., Denise, M., Mathieu, E., Jean, C., Jose´, M.G. and Patrice, I. (2006). The plant-specific ssDNA binding protein osb1 is involved in the stoichiometric transmission of mitochondrial DNA in Arabidopsis. The Plant Cell. 18:3548–3563.
Wahid, A., Gelani, S., Ashraf, M and Foolad, M.R., (2007). Heat tolerance in plants: an overview. Environ. Exp. Bot. 61:199-223. 185
Wang, M., Zheng, Q., Shen, Q. and Guo, S. (2013). The critical role of potassium in plant stress response. Int. j. Mol. Sci., 14: 7370-7390.
Wang, Y., Yu, B., Zhao, J., Jiangbo Guo,Ying, L., Shaojie, H., Lei, H., Yumei, D., Yiguo, H., Dingzhong, T. and Yule, L. (2013). Autophagy contributes to leaf starch degradation, Plant Cell., 25:1383–99.
Wang, R. C., Guegler, K., Labrie, S. T. and Crawford, N. M. (2000). Genomic analysis of a nutrient response in Arabidopsis reveals diverse expression patterns and novel metabolic and potential regulatory genes induced by nitrate. Plant Cell. 12: 1491- 1509.
Wang, R., Okamoto, M., Xing, X. and Crawford, N. M. (2003a). Microarray analysis of the nitrate responsein Arabidopsis roots and shoots reveals over 1,000 rapidly responding genes and new linkages to Glucose, Trehalose-6-Phosphate, Iron, and Sulfate metabolism. Plant Physiol., 132: 556-567.
Wang, W. X., Barak, T., Vinocur, B., Shoseyov, O. and Altman, A. (2003 b). Abiotic resistance and chaperones: possible physiological role of SP1, a stable and stabilizing protein from Populus. In: Vasil IK (ed.) Plant biotechnology 2000 and beyond. Kluwer, Dordrecht, p.439-43.
Wang, W., Vinocur, B. and Altman, A. (2003 c). Plant responses to drought, salinity and extreme temperatures: towards genetic engineering for stress tolerance. Planta. 218: 1-14.
Wangze, W., Yujun, W., Yang, G., Meizhen, L., Hongju, Y., Minghui, L., Jianxin, Z., Jia, L. and Kai, H. (2015). Somatic embryogenesis receptor-like kinase 5 in the ecotype Landsberg erecta of Arabidopsis is a functional RD LRR-RLK in regulating brassinosteroid signaling and cell death control. Plant Sci. 6:852. 186
Watanabe E., Shimada T., Kuroyanagi M., Nishimura M., Hara-Nishimura I. (2002). Calcium-mediated association of a putative vacuolar sorting receptor PV72 with a propeptide of 2S albumin. J. Biol. Chem. 277: 8708–8715
Wen-yue, S., Hui, W. and Jic-chang, H. (2001). The effect of external betaine on membrane lipid peroxidation of wheat seedlings under water stress. Xibel Zhiwu Xueb. 21: 487- 491.
Wiemann, S., Mehrle, A., Bechtel, S., Wellenreuther, R., Pepperkok, R. and Poustka A. (2003). cDNAs for functional genomics and proteomics: the German cDNA Consortium. C.R. Biol. 326:1003-1009.
Wikstrom, N., Savolainen, V. and Chase, M. W. (2001). Evolution of the angiosperms: calibrating the family tree. Proceedings of the Royal Society of London Series B- Biological Sciences 268: 2211-2220.
Wilhite, D.A., M.D. Svoboda, and H.J. Hayes, (2007). Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparedness. Water Resour. Managm., 21:763–774.
Winter, K., and Smith. J.A.C. (1996). An introduction to crassulacean acid metabolism., biochemical principles and ecological diversity, p. 1-13, In K. Winter and J. A. C. Smith, (eds). Crassulacean Acid Metabolism - Biochemistry, Ecophysiology and Evolution, Vol.114.
Xiong, L. and Yang, Y. (2003). Disease resistance and abiotic stress tolerance in rice are inversely modulated by an abscisic acid-inducible mitogen-activated protein kinase. Plant Cell. 15: 745-759. 187
Xiong, L. and Zhu, J. K. (2001). Abiotic stress signal transduction in plants: Molecular and genetic perspectives. Physiol. Plant., 112: 152-66.
Xiong, L., Schumaker, K. S. and Zhu, J. K. (2002). Cell signaling during cold, drought, and salt stress. The Plant Cell Online. 14:165-183.
Xu, D. Q., Hunag, J., Guo, S. Q., Yang, X., Bao, Y. M., Tang, H. J. and Zhang, H. S. (2008). Over-expression of TFIIIA type zinc finger protein gene ZFP252 enhance drought and salt tolerant in rice (Oryza sativaL.). FBBS. Lett., 582: 1037-1043.
Yadav, S.K., Jyothilakshmi, N., Maheswari, M. , Vanaja, M. and Venkateswarlu, B. (2005).
Yan, J., Wang, J. and Zhang, H. (2002) An ankyrin repeat-containing protein plays a role in both disease resistance and antioxidation metabolism. Plant J. 29:193-202.
Yang, F. and Miao, L.F. (2010). Adaptive responses to progressive drought stress in two poplar species originating from different altitudes. Silva Fennica. 44: 23-37.
Yang, Y.H. and Speed, T. (2002) Design issues for cDNA microarray experiments. Nature Reviews in Genetics. 3: 579-588.
Yang, Y., Dudoit, S., Luu, P. and Speed, T. P. (2001) Normalization for cDNA microarray data. SPIE proceedings series, 4266: 141-152.
Yanhui, C., Xiaoyuan, Y., Kun, H., Meihua, L., Jigang, L., Zhaofeng, G., Zhiqiang, L., Yunfei, Z., Xiaoxiao, W. and Xiaoming, Q. (2006). The MYB transcription factor 188
superfamily of Arabidopsis, expression analysis and phylogenetic comparison with the rice MYB family. Plant Mol. Biol., 60: 107-124.
Yi, N., Kim, Y. S., Jeong M. H., Oh, S. J., Jeong, J. S., Park, S. H., Jung, H., Do Choi, Y. and Kim, J. K. (2010). Functional analyses of six drought-inducible promoters in transgenic rice plants throughout all stages of plant growth. Planta, 232: 743-754.
Yoko, O., Paul, J.O., Kazunari, A., Jose, M.A., April, C., Charlie, C., Joseph, R.E., Beth, H., Amy, L., Diana, N., Courtney, O., Hong, Q., Alison, S., Guixia, Y., and Athanasios, T. (2005). Functional genomic analysis of the auxin response factor gene family members in Arabidopsis thaliana unique and overlapping functions of ARF7 and ARF19. The Plant Cell., 17:444–463.
Yordanov I., Velikova V. and Tsone, V. (2000). Plant response to drought, acclimatation and stress tolerance. Photosynthetica. 30: 171-186.
Zhang J, Kirkham MB (1996). Antioxidant response to drought in sunflower and sorghum seedlings. New Phytol. 132: 361-373. Zhao, Z., Chen, G. and Zhang, C. (2001). Interaction between reactive oxygen species and nitric oxide in drought-induced abscisic acid synthesis in root tips of wheat seedlings. Aus. J. Plant Physiol., 28: 1055-1061.
Zhou, Q. Y., Tian, A. G., Zou, H. F., Xie, Z. M., Lei, G., Huang, J., Wang, C. M., Wang, H. W., Zhang, J. S. and Chen, S. Y. (2008). Soybean WRKY-type transcription factor genes, GmWRKY13, GmWRKY21, and GmWRKY54, confer differential tolerance to abiotic stresses in transgenic Arabidopsis plants. Plant Biotechnol J., 6:486-503.
Zhou, W.Z., Zhang, Y.M., Lu, J.Y. and Li, J.F. (2012). Construction and evaluation of normalized cDNA libraries enriched with full-length Sequences for rapid discovery 189
of new genes from Sisal (Agave sisalana Perr.) at different developmental stages. Int. J. Mol. Sci.13: 13150-13168.
Zhu, J. K. (2002). Salt and drought stress signal transduction in plants. Ann. Rev. of Plant Bio., 53: 247-273.
Zhu, T. and Wang, X. (2000). Large-scale profiling of the Arabidopsis transcriptome. Plant Physiol., 124: 1472-1476.
APPENDICES
APPENDIX-I
RNA extraction buffer
Hexadecyltrimethylammonium bromide (CTAB) 2% Polyvinylpyrrolidone (PVP) 2% Tris HCl (pH8) 100 mM EDTA 25mM Spermidine 5g/L Mercaptoethanol 2% NaCl 2M
APPENDIX II
SSTE buffer NaCl 1M SDS 0.5% Tris HCl (pH: 8) 10mM EDTA (pH: 8) 1mM
APPENDIX III
TAE buffer (50X) Tris base 242g Glacial acetic acid 57.1ml O.5M EDTA (pH: 8) 100ml
APPENDIX IV
T.E. Buffer 10mM Tris-HCl 1.0mM EDTA
APPENDIX V
Cell Resuspension Solution (Solution 1) Tris HCl (pH.8) 25mM EDTA 10mM Glucose 50Mm
APPENDIX VI Cell Lysis Solution (Solution 2) NaOH 0.2M SDS 1%
APPENDIX VII Neutralization Solution (Solution 3) 3M Potassium Acetate (pH 3.8)
APPENDIX VIII Pre hyb buffer (100 ml). 5 X SSC 25 ml 20 X SSC 0.1% SDS 1 ml 10% SDS 1% BSA 1 g BSA (Sigma A-9647) fill to 100 ml.
APPENDIX IX 2X Hybridization buffer: 50% Formamide 5 ml 10X SSC 5 ml 20X SSC 0.2% SDS 200 ul 10% SDS