MINISTRY OF EDUCATION MINISTRY OF AGRICULTURE AND TRAINING AND RURAL DEVELOPMENT VIET NAM ACADEMY OF AGRICULTURAL SCIENCES HA VAN CHIEN ROLES OF AUXIN RESPONSE FACTOR TRANSCRIPTION FACTOR (GmARF) IN SOYBEAN AND STRIGOLACTONE IN ARABIDOPSIS IN RESPONSE TO DROUGHT AND SALT STRESSES Major: Biotecnology Code: 62 42 02 01 SUMMARY OF THE DOCTORAL THESIS HA NOI - 2016 The doctoral thesis was completed in: VIETNAM ACADEMY OF AGRICULTURAL SCIENCE Supervisors: Assoc Prof Dr Nguyen Van Dong Dr Tran Phan Lam Son Reviewer 1: Reviewer 2: Reviewer 3: The doctoral thesis is defended at Council for thesis assessment at institutional level, held at: Vietnam Academy of Agricultural Science, at hours, day month year The thesis can be referred to at: Vietnam National Library Library of Vietnam Academy of Agricultural Science Library of Agriculture Genetics Institute INTRODUCTION Imperativeness of the thesis The rapidly increasing of the world population has made food security one of the most important global issues, including Vietnam In addition, the food productivity as well as the sustainable agriculture development is also burdened by climate change and environmental stresses (such as drought, flooding, unpredictable epidemics, soil erosion and environment pollutants ) Understanding the stress responses in plants is necessary to mitigate the problems via creating stress-tolerant crop cultivars It has been demontrated that transcription factors and phytohormones (such as Abscisic acid (ABA), auxin, cytokinins (CK), strigolactones (SLs)) play important roles in gene expression regulation and physiological activities in plant Therefore, our research is aimed to identify and characterize candidate genes, which can be used to engineer stress-tolerant transgenic crops, through approaches First, we address our self to study gene expression regulation mediating by transcription factors, namely auxin response factor transcription factors family (ARF); second, we concentrate on discovery of candidate genes involved in hormone metabolism and signaling in plant stress responses To achieve this goal, in this thesis, we conduct the experiments on model plant - Arabidopsis thaliana and an economically important crop – soybean (Glycine max) at the same time The thesis entiled: “Roles of auxin response factor transcription factor (GmARF) in soybean and strigolactone in Arabidopsis in response to drought and salt stresses” Objectivities - Identification and characterization of the potential auxin-response factor transcription factor genes in soybean for generating drought tolerance crops via genetic engineering - Phenotyping and study the molecular mechanisms of strigolactone in response to drought and salt stress conditions Contents 3.1 Roles of auxin response factor transcription factor in soybean in response to drought stress 3.2 Roles of strigolactone in response to drought and salt stress in Arabidopsis Scientific and practical significane 4.1 Scientific significance Our study is the first publication that provides the scientific data about the function of ARF TFs coding genes in soybean, as well as the essential role of SLs involved in environmental stress responses, especially drought condition Our results are considered as the reliable references for education and research | Page 4.2 Practical significance - This research allowed us to identify genetic components that contribute not only to improve drought tolerance of soybean, but also for in-depth functional analysis that ultimately leads to the development of soybean cultivars with improved tolerance to drought - This research also provided a promising approach to reduce the negative impact of abiotic stresses on crop productivity based on the modulation of SL content/response The novelty of the thesis - Characterization and functional analysis of GmARF genes under drought conditions - Our results classified some tissue-specific of GmARFs which are able to apply for genetic engineering to develop the drought tolerant cultivars - Our results also provided the roles of strigolactones in response to drought and high salinity in plant - Our results opened a promising application approach to enhance the drought/salt tolerance by strigolactone Structure of the thesis The main contents of the thesis are presented in 107 pages, including 28 figures and tables 185 literature references were used to cite for this thesis, including in Vietnamese and 176 in English and webpages | Page CHAPTER 1: OVERVIEW AND SCIENTIFIC BACKGROUND 1.1 Introduction Soybean is one the world’s leading economic oilseed crops, providing the largest source of vegetable oil, proteins, macronutrients and minerals for human consumption and animal feed Unfortunately, the low productivity of soybean is mainly attributed to evironmental stresses, in cluding drought Plants, especially soybean, activate various mechanisms to adapt with drought stress In the last 20 years, many genes, including both regulatory and functional genes, have been discovered in important crops, such as rice (Oryza sativa) and soybean (Glycine max), which are involved in defense mechanisms and functioned in increasing drought tolerance However, the detail information and the relationship between the regulation of TFs and gene expression have not been elucidated yet Therefore, identification and characterization of TFs family in soybean is necessary to understand plant stress responses On the other hand, high-salinity is also a typical stress that have influence to crop yield To elucidate plant responses mediated by the phytohormone – SLs signaling pathway to high-salinity and drought stress conditions, we conduct the experiment on model plant – Arabidopsis thaliana Because Arabidopsis has many advantage characteristics (such as its short life-cycle, small size and fully sequenced genome, easy to grow and transform, closely related to a major crop species) It has been shown that SLs play a typical role in regulation of many physiological processes in plant However, the involvement of SLs in plant drought and high-salinity stress responses has not been revealed yet So that to identify and study the relationship between SLs and drought and highsalinity stress responses is essential to compliment to the biological knowledge as well as the potential application in sustainable agriculture and cultivars improvement In short, to evaluate the good candidates for genetic engineering, in this study, we will focus on the auxin response factor transcription factor family in soybean (GmARF) and the pivotal role of SL in abiotic stress response in plant 1.2 The mechanisms of plant responses to environmental stresses Plants are always exposed to environmental stresses, such as drought, salt, cold, light or humidity, however, they are lack of movement ability, so that they have to respond and adapt to stresses to survive In response to environmental stresses, plants must activate plenty of complexity pathways and mechanisms (Manavalan et al.,, 2009) In term of phisiological, plants attempt to close the stomata, reduce respiration and photosynthesis frequency, water volume in tissues and plant growth, induce the root development to enhance the water-absorbance ability (Tran and Mochida, 2010) In term of molecular mechanisms, there are many genes that encoded for the stress responsive protein (Dorothea and Ramanjulu, 2005) Within the regulatory networks that control the signal transduction from | Page stress signal perception to stress-responsive gene expression, various transcription factors (TFs) and their DNA binding sites, the so-called cis-acting elements, act as molecular switches for stressresponsive gene expression, enabling plants adapt better to the adverse stressor Futhermore, phytohormone also play a typical role in plant abiotic stress responses and contribute to the adaptative mechanisms 1.3 Introduction of the auxin response factor transcription factor family in plant 1.3.1 Concept and classification of transcription factor 1.3.1.1 Concept Transcription factor is a specific DNA binding protein that binds to the promoter sequence and regulates the gene transcription (Latchman, 1997; Brivanlou and Darnell, 2002) 1.3.1.2 Classification Transcription factors can be classified based on their activity, fuction or the certain structure motif of their DNA-binding domain, DBD (Karin, 1990; Latchman, 1997; Brivanlou and Darnell, 2002) According to the identity in the DBD classification, TFs that share the similarity in DBD will be classified into one TFs family 1.3.2 Structure and Function of transcription factor 1.3.2.1 Structure The structure of TFs contain several specific domains including DNA-binding domain (DBD), trans-activating domain (TAD), and signal sensing domain (SSD) 1.3.2.2 Function Firsly, the basic function of TFs is the involvement in regulation of gene expression (Weinzierl, 1999) Then, the appearance of TFs can verify the specificity of the transcription from DNA to RNA as well as control the cell development (Lobe, 1992) One of the crucial role of TFs is the participation in biotic and abiotic stress responses (Fujita et al.,, 2005; He et al.,, 2005; Hu et al.,, 2006; Yamaguchi-Shinozaki and Shinozaki, 2006; Fang et al.,, 2008; Nakashima et al.,, 2009; Cutler et al.,, 2010; Fujita et al.,, 2011) 1.3.3 The research situation of transcription factor in response to enviroinmental stresses 1.3.4 The auxin response factor transcription factor 1.3.4.1 Concept and structure The phytohormone auxin has been known to regulate various aspects of plant growth and development (Kieffer et al., 2010; de Jong et al., 2011; Lau et al., 2011;Ha et al., 2012) Numerous genetic and biochemical studies in Arabidopsis have provided evidence that transcriptional regulation of auxin response genes are regulated by two large TF families, the auxin response factor (ARF) and the auxin/indole acetic acid (Aux/IAA) families.(Guilfoyle and Hagen 2007) | Page In Arabidopsis, there are 23 ARFs most of which contain a conserved N-terminal DNA-binding domain (DBD), a variable middle transcriptional regulatory region (MR) and a carboxy-terminal dimerization domain (CTD).(Perez-Rodriguez et al., 2010; Zhang et al., 2011) The DBD of ARFs specifically binds to the conserved auxin response element (AuxRE, TGTCTC) in promoter regions of primary or early auxin-responsive genes The structure of the TRR of each ARF determines whether the ARF acts as an activator or repressor Activation domain (AD) of ARFs is usually enriched in glutamine (Q), serine (S) and leucine (L), while repression domain (RD) is enriched in either S, L and proline (P); S, L and/or glycine (G) or S The ARF CTD is modular with amino acid sequence related to domains III and IV in Aux/IAA proteins, making it function as a dimerization domain among the ARF CTDs or with several Aux/IAA proteins (Guilfoyle and Hagen 2007) 1.3.4.2 Roles and research progress of the auxin response factortranscription factor In Arabidopsis, mutations in the paralogous AtARF01 and AtARF02 resulted in delayed leaf senescence and floral organ abscission (Ellis et al.,, 2005; Lim et al.,, 2010) Similarly, AtARF07 and AtARF19 were shown to play a positive role in regulation of lateral root development (Fukaki et al.,, 2006) Given the importance of ARF TFs in diverse biological and physiological processes, and their potential applications for the development of improved stress-tolerant transgenic crop plants, the ARF TF families have been identified and characterized in a number of crop species, such as maize (Zea mays) (Xing, Pudake et al., 2011; Wang, Deng et al., 2012), rice (Oryza sativa) (Jain and Khurana 2009; Song, Wang et al., 2009; Shen, Wang et al., 2010), sorghum (Sorghum bicolor) (Wang, Bai et al., 2010), tomato (Solanum lycopersicum) (Wu, Wang et al., 2011), Chinese cabbage (Brassica rapa) (Mun, Yu et al., 2012) and Citrus sinensis (Li et al.,, 2015) 1.3.5 Transcription factor in soybean There are 61 transcription factor families in soybean containing 5035 TFs However, 857 TF genes have not study in characterization, functional analysis and their roles in soybean plant Some TF families were determined the roles of them in response to environmental stresses, including GmNACs (Le et al.,, 2011), GmNFYAs (Ni et al.,, 2013), GmWRKYs (Lou et al.,, 2013) 1.4 Introduction of strigolactone 1.4.1 Concept and classification of strigolactone Strigolactones (SLs), a small class of carotenoid-derived compounds, were first characterized over 45 years ago as seed germination stimulants in root parasitic plants, such as Striga, Orobanche and Phelipanche species (Xie and Yoneyama 2010; Ruyter-Spira, Al-Babili et al., 2013) SL was later reported as a root-derived signal that can enhance symbiosis between plants and arbuscular mycorrhizal fungi (AMF) possibly through its ability to induce AMF hyphal branching (Akiyama, Matsuzaki et al., 2005) More recently, SL was reported to play an important | Page role in the suppression of shoot branching by inhibiting the outgrowth of axillary buds (Umehara, Hanada et al., 2008) Strigolactone genes were classified into two groups, strigolactone biosynthesis and strigolactone signaling genes 1.4.2 Structure of strigolactone To date, more than 19 natural SLs have been characterized from various plant species, and they all share a common four-cycle skeleton (A, B, C and D), with cycles A and B bearing various substituents and cycles C and D being lactone heterocyclic connected by an enol-ether bond (Fig 1.5) (+)-5-Deoxystrigol is thought to be the precursor of other strigolactones (Matusova, Rani et al., 2005) 1.4.3 Biosynthesis of strigolactone Strigolactone, a small class of carotenoid-derived compounds, were found in many plant species In Arabidopsis, MAX3 and MAX4 encode CCD7 (carotenoid cleavage dioxygenase 7) and CCD8, respectively, which catalyze sequential carotenoid cleavage reactions to produce an apocarotenone called carlactone, a proposed SL precursor (Alder, Jamil et al., 2012) MAX1 is a cytochrome P450 monooxygenase that is presumably involved in a catalytic step downstream of MAX3 and MAX4 (Ruyter-Spira, Al-Babili et al., 2013) 1.4.4 Signaling of strigolactone Strigolactone is transported and percepted by the specific system Two components of the sitrolactone signaling are α/β-fold hydrolase, D14(Arite, Iwata et al., 2007; Arite, Umehara et al., 2009; Hamiaux, Drummond et al., 2012; Waters, Nelson et al., 2012) and F-box protein, MAX2/D3/RMS4 (Dun, Hanan et al., 2009; Nelson, Scaffidi et al., 2011) 1.4.5 Roles of strigolactone Strigolactones (SLs), a small class of carotenoid-derived compounds, were first characterized over 45 years ago as seed germination stimulants in root parasitic plants, such as Striga, Orobanche and Phelipanche species (Xie and Yoneyama 2010; Ruyter-Spira, Al-Babili et al., 2013) SL was later reported as a root-derived signal that can enhance symbiosis between plants and arbuscular mycorrhizal fungi (AMF) possibly through its ability to induce AMF hyphal branching (Akiyama, Matsuzaki et al., 2005) More recently, SL was reported to play an important role in the suppression of shoot branching by inhibiting the outgrowth of axillary buds (GomezRoldan, Fermas et al., 2008; Umehara, Hanada et al., 2008; Xie and Yoneyama 2010) 1.4.6 Potential application of strigolactone Strigolactone is an important regulator for growth and development of plant Strigolactone and its functions could become a promising approach for developing the methods and new biotechnology for sustainable agriculture | Page CHAPTER 2: MATERIALS AND METHODS 2.1 MATERIALS, CHEMICALS AND MACHINES 2.1.1 Materials The model plant cultivar - Williams 82 was used for study the Auxin-response factor transcription factor family in soybean The max2-3 (SALK_092836), max2-4 (SALK_028336), max3-11 (SALK_023975), max312 (SALK_015785), max4-7 (SALK_082552) and max4-8 (SALK_072750) mutants on Arabidopsis thaliana Columbia-0 genetic background (Col-0, wild-type, WT) were used in this study These mutants are well-characterized by the previous study (Umehara, Hanada et al., 2008) 2.1.2 Chemicals 2.1.3 Machines 2.2 Period and Place 2.2.1 Period The research contents have been done for years (4/2012 to 3/2015) 2.2.2 Place The research contents have been done in Signaling Pathway Research Unit, RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro, Tsurumi, Yokohama, JAPAN 230-0045; and National key labolatory for plant cell technology, Agriculture Genetics Institute, Pham Van Dong road, Tu Liem, Ha Noi, Viet Nam 2.3 Methods 2.3.1 Plant growth, treatments and collection of tissues 2.3.1.1 Plant growth, treatments and collection of tissues for soybean 2.3.1.2 Plant growth, treatments and collection of tissues for Arabidopsis 2.3.2 Identification of the GmARF members and strigolactone-related genes in soybean All predicted GmARF TFs in soybean were collected for manual analysis from various plant TF databases, (Mochida, Yoshida et al., 2009; Mochida, Yoshida et al., 2010; Wang, Libault et al., 2010; Zhang, Jin et al., 2011) and only those GmARFs containing full open reading frames (ORFs), as predicted by Glyma v1.1 (http://www.phytozome.net/soybean), were used for further analyses Genes with threshold of ≥ 90% nucleotide sequence identity were considered as duplicated genes (Cheung, Estivill et al., 2003) Strigolactone biosynthetic and signaling genes in soybean were predicted and classified by BLAST method using the Arabidopsis homolog genes | Page 2.3.3 Phylogenetic analysis Sequence alignments of all identified ARFs from Arabidopsis and soybean were performed with a gap open penalty of 10 and a gap extension penalty of 0.2 using ClustalW implemented on MEGA software (Thompson, Gibson et al., 1997; Tamura, Dudley et al., 2007) The alignments were subsequently visualized using GeneDoc (http://www.nrbsc.org/gfx/genedoc/) as presented in Supplementary Fig S1 The sequence alignments were also used to construct the unrooted phylogenetic tree by the neighbor-joining method using MEGA The confidence level of monophyletic groups was estimated using a bootstrap analysis of 10,000 replicates Only bootstrap values higher than 50% are displayed next to the branch nodes 2.3.4 Expression analyses of GmARF genes using microarray data and soybean Illumina expression data For tissue-specific expression analysis of GmARF genes, microarray-based expression data for 68 types of tissues and organs housed in Genevestigator (https://www.genevestigator.com/) were used.(Hruz, Laule et al., 2008) Illumina transcriptome sequencing data provided by Libault et al.,(Libault, Farmer et al., 2010; Libault, Farmer et al., 2010) were also used to evaluate the expression of GmARF genes in tissues: nodules of 35-d-old soybean plants (harvested after 32 days of inoculation of the 3-d-old plants), 14-d-old shoot apical meristem (SAM), flowers (reproductive R2 stage), green pods (R6 stage), 18-d-old trifoliate leaves, roots (V2 stage), root tips and root hairs of 3-d-old seedlings For expression analysis of GmARF genes in soybean leaves at V6 and R2 stages under drought stress, which was imposed on the plants by withholding water from the pots until the volumetric soil moisture content reduced to below 5%, microarray data recently published by Le et al., was used.(Le, Nishiyama et al., 2012) At the V6 stage, soybean plants had six unrolled trifoliate leaves and seven nodes, while at R2 full bloom stage, open flowers were found on any of the top two nodes on the main stem 2.3.5 RNA isolation, DNaseI treatment and cDNA synthesis 2.3.5.1 RNA isolation, DNaseI treatment and cDNA synthesis for soybean 2.3.5.2 RNA isolation, DNaseI treatment and cDNA synthesis for Arabidopsis 2.3.5.3 qRT-PCR Primer design 2.3.6 Dehydration treatment and microarray analysis in Arabidopsis WT and max2-3 plants (30 plants/each) were grown in soil as described previously (Nishiyama, Watanabe et al., 2011) and in the drought tolerance assay Aerial portions of 24-d-old plants were detached and exposed to dehydration by placing them on paper towels on a lab bench At the indicated time points, RWC of treated samples was measured (n = 5) Rosette leaves of independent WT and | Page Figure 3.1 Chromosomal distribution of 51 soybean GmARF genes identified in this study and structural analysis of the GmARF proteins (A) Chromosomal distribution of GmARF genes with indication of percentages of GmARFs located on each chromosome (B) Graphical representation for chromosomal localization of GmARF genes Greek numbers indicate chromosome numbers (C) Graphical representation for domain organization of GmARF proteins A typical ARF contains a DNA-binding domain (DBD), which consists of a B3 subdomain and an auxin-response (ARF) subdomain, a middle region (MR) and a carboxy-terminal dimerization domain (CTD) 11 | Page Figure 3.2 Phylogenetic relationship of ARFs from Arabidopsis and soybean The unrooted phylogenetic tree was constructed using the full ORFs of ARF proteins The bar indicates the relative divergence of the sequences examined Bootstrap values higher than 50% are displayed next to the branch 3.1.3 Analysis of expression patterns of GmARF genes in different tissues and organs under well-watered conditions In the next line of our study, we have interest in gaining knowledge about tissue-specific expression of the GmARFs Because it enables us to identify the genes which are involved in defining the precise nature of individual tissues Moreover, identification of tissue-specific genes, for instance root-specific genes, provides a resource of root-specific promoters for improvement of drought tolerance by enhancement of root growth (Werner, Nehnevajova et al., 2010; Ha, Vankova et al., 2012) (Figure 3.1.3) The results showed that 18 genes were determined as tissue-specific 12 | Page genes, including shoot-specific genes (GmARF25, 29, 34, 35, 36, 48, 50) and 11 root-specific genes (GmARF02, 05, 09, 15, 18, 22, 27, 28, 32, 33, 49) Figure 3.3 Expression patterns of 51 putative GmARF genes in roots (black bars) and shoots (white bars) of 12-d-old soybean seedlings under normal conditions On the basis of their expression levels, the GmARF genes were classified into six groups (A-F) Data represent the means and standard errors of three independent biological samples Asterisks indicate significant differences as determined by Student’s t-test (*P< 0.05; **P< 0.01; ***P< 0.001) Relative expression was calculated based on the expression level of the target gene versus the level of the 60s reference gene 3.1.4 Analysis of expression patterns of the GmARF genes in roots and shoots during dehydration stress using qRT-PCR Expression of 51 GmARF genes under drought stress condition was examined by RT-qPCR analysis The evaluations of expression patterns in roots and shoots separately rather than in whole plants, might provide helpful information on the mode of action of stress-responsive GmARF genes in these individual tissues 13 | Page Figure 3.6 Expression of GmARF genes in roots (black bars) and shoots (white bars) of soybean plants under dehydration stress (A) Upregulated GmARF genes in shoots by at least 2fold (B) Downregulated GmARF genes in shoots by at least 2-fold Data represent the means and standard errors of three independent biological samples Asterisks on the top of bars indicate significant differences as determined by Student’s t-test (*P< 0.05; **P< 0.01; ***P< 0.001) Relative expression was calculated based on the expression level of the target gene versus the level of the 60s reference gene 14 | Page Figure 3.7 Expression of GmARF genes in roots (black bars) and shoots (white bars) of soybean plants under dehydration stress (A) Upregulated GmARF genes in roots by at least 2-fold (B) Downregulated GmARF genes in roots by at least 2-fold (C) Venn diagram analysis of differentially expressed GmARF genes in shoots and roots of soybean seedlings Data represent the means and standard errors of three independent biological samples Asterisks on the top of bars indicate significant differences as determined by Student’s t-test (*P< 0.05; **P< 0.01; ***P< 0.001) Relative expression was calculated based on the expression level of the target gene versus the level of the 60s reference gene 15 | Page The qRT-PCR analysis (Figure 3.6 and 3.7) showed that many GmARF genes were induced by stress Whereas, upregulated genes (GmARF12, 50) and downregulated gene (GmARF20, 26, 34, 35, 41, 43, 51) in both roots and shoots On the other hand, out of 30 GmARF genes that were downregulated in roots, 12 genes (GmARF09, 10, 15, 18, 21, 27, 28, 33, 37, 38, 44 and 49) were found to be upregulated in shoots Additionally, GmARF33 and GmARF50 were the most induced genes by dehydration in shoots and roots, respectively Therefore, these two genes would be excellent candidates for further in planta studies in soybean 3.1.5 Differential expression analysis of the GmARF genes in drought-stressed V6 and R2 soybean leaves and dehydrated shoots and roots of young soybean seedlings As previously shown, dehydration stress altered expression of many GmARF genes in roots and shoots of 12-d-old soybean seedlings Recently, using the 66 K Affymetrix Soybean Array GeneChip, we have carried out genome-wide expression profiling of soybean leaves at V6 and R2 stages under drought stress.(Le, Nishiyama et al., 2012) This microarray data set allowed us to assess the drought-responsive expression patterns of the GmARF genes in the leaves of mature soybean plants 3.2 Roles of strigolactone in response to drought and salt stress in Arabidopsis 3.2.1 Phenotyping of the strigolactone mutant plants under drought and salt stress conditions To determine the potential involvement of SL in the response of Arabidopsis to abiotic stress, the ability of the Arabidopsis max mutant and wild-type (WT) plants to survive drought and high salinity was examined The results were showed in Figure 3.9 and 3.10 These data indicate that max mutants are hypersensitive to drought and salt stresses Thus, SL plays an important role in the regulation of plant responses to abiotic stress 16 | Page Figure 3.9: Hypersensitivity of SL-deficient and SL-signaling max mutant plants to drought stress (A) Three-week-old WT and SL-deficient max3-11 and max4-7 and SL-signaling max2-3 mutant plants prior to being subjected to a drought stress (B) WT and mutant plants subjected to a drought stress and then rewatered for three days Inflorescences were removed from the surviving plants prior to photographing (C) Unstressed (control) WT and max plants grown in parallel with the drought test (D) Percent survival rates of WT and mutant plants Data represent the mean and standard error from data pooled from three independent experiments (n = 30/genotype/experiment) Asterisks indicate significant differences as determined by a Student’s ttest (***P[...]... plants 3.2 Roles of strigolactone in response to drought and salt stress in Arabidopsis 3.2.1 Phenotyping of the strigolactone mutant plants under drought and salt stress conditions To determine the potential involvement of SL in the response of Arabidopsis to abiotic stress, the ability of the Arabidopsis max mutant and wild-type (WT) plants to survive drought and high salinity was examined The results... Exogenous strigolactone improve salt tolerance in soybean To evaluate the environmental stress tolerant soybean variety, we identifed the SL biosynthesis and SL response genes in soybean On the other hand, we also analyzed the role of SL in response to salt stress in soybean Our results showed that the SL-treated soybean exhibited promising salt stress tolerance as same as the examination in Arabidopsis. .. Assessment of drought, salt, and osmotic Sstress tolerance 2.3.7.1 Drought stress tolerance assay in Arabidopsis 2.3.7.2 Salt stress tolerance assay 2.3.7.3 Germination assay for salt stress for Arabidopsis: 2.3.7.4 Root growth assay under salt and osmotic stress conditions in Arabidopsis 2.3.7.5 Stomatal closure assay and measurement of stomatal density in Arabidopsis 2.3.7.6 Assay for sensitivity to ABA in. .. localization of GmARF genes Greek numbers indicate chromosome numbers (C) Graphical representation for domain organization of GmARF proteins A typical ARF contains a DNA-binding domain (DBD), which consists of a B3 subdomain and an auxin- response (ARF) subdomain, a middle region (MR) and a carboxy-terminal dimerization domain (CTD) 11 | Page Figure 3.2 Phylogenetic relationship of ARFs from Arabidopsis and soybean. .. Stomatal Closure, and Stomatal Density in the max Mutant and WT Plants Figure 3.15: Relative water content (RWC), relative size of the stomatal aperture, and stomatal density of the WT and SL- deficient and SL-signaling max mutant plants (A) Time course of RWC of WT and SL- deficient max3-11 and max4-7 and SL-signaling max2-3 plants exposed to drought stress Data represent the mean and standard error (n... found to be upregulated in shoots Two genes (GmARF33, 50) are potential for application to generate the drought tolerant soybean by genetic engineering 4 Strigolactones was found as a positive regulator to drought and salt stress responses Howerver, the shoot traits were more important than the root traits 5 Strigolactone- mediated genes involved in drought stress were discovered The results also indicated... is to alter root-related traits, such as root physiology and growth (Manavalan, Guttikonda et al., 2009; Galvan-Ampudia and Testerink 2011) To gain insight into mechanisms that render max mutant 20 | Page plants more sensitive to abiotic stress, we examined root growth in max and WT plants under salt and osmotic stresses In our experimental design, various concentrations of mannitol were used to induce... results were showed in Figure 3.9 and 3.10 These data indicate that max mutants are hypersensitive to drought and salt stresses Thus, SL plays an important role in the regulation of plant responses to abiotic stress 16 | Page Figure 3.9: Hypersensitivity of SL-deficient and SL-signaling max mutant plants to drought stress (A) Three-week-old WT and SL-deficient max3-11 and max4-7 and SL-signaling max2-3 mutant... mutant plants prior to being subjected to a drought stress (B) WT and mutant plants subjected to a drought stress and then rewatered for three days Inflorescences were removed from the surviving plants prior to photographing (C) Unstressed (control) WT and max plants grown in parallel with the drought test (D) Percent survival rates of WT and mutant plants Data represent the mean and standard error from... transcriptome analysis of leaves of WT and SL-signaling max2-3 plants under both normal and dehydrative stress conditions was conducted using the Arabidopsis 44K DNA oligo microarrays (Figure 3.16) This was done to identify genes involved in the downstream pathways affected by SL-mediated responses to drought stress The microarray data displayed an interaction between SL, ABA and CK in response to drought