THE ROLE OF JAZ PROTEINS IN THE REGULATION OF PLANT GROWTH- DEFENSE TRADEOFFS By Qiang Guo A DISSERTATION Submitted to Michigan State University in partial fulfillment of requirements for the degree of Plant Biology - Doctor of Philosophy 2018 THE ROLE OF JAZ PROTEINS IN THE REGULATION OF PLANT GROWTH-DEFENSE ABSTRACT TRADEOFFS By Qiang Guo As sessile organisms, plants constantly experience challenges from the surrounding environment. In response to these biotic stresses, plants invest a prominent portion of their metabolic capacity in the production of defense-associated compounds and physical structures. However, expression of defense traits is often associated with growth restriction and ultimately reduces reproductive output. Although this growth-defense antagonism has a profound impact on plant biology and agricultural practice, the mechanisms that regulate tradeoffs between growth and defense are poorly understood. The plant hormone jasmonate (JA) plays a dual role in enhancing immune responses and inhibiting growth. The JA signaling cascade is switched on when the bioactive form of the hormone is recognized by the COI1-JAZ co-receptor complex, which leads to the degradation of JAZ repressors via the SCFCOI1-26S proteasome pathway and subsequent relief of JA-responsive transcription factors (TFs). In this dissertation research, I first show that JAZ proteins promote growth and reproductive fitness in the model plant Arabidopsis thaliana by suppressing metabolic pathways for defense. Characterization of a jaz decuple (jazD) mutant defective in 10 JAZ genes revealed that hyperactivation of JA signaling significantly increased resource allocation to defense pathways, thereby improving plant resistance to insect herbivores and necrotrophic pathogens. The elevated defense of jazD was linked to carbon starvation, curtailed seed production and, under extreme conditions, lethality. Secondly, I show that the allocation costs associated with heightened JA responses in jazD was largely dependent on the bHLH-type TFs MYC2, MYC3 and MYC4, and that MYC2/3/4 played overlapping and conserved roles in metabolic reprogramming in jazD. Characterization of jazD myc mutants further showed that the JAZ-MYC transcriptional module controls the production of endoplasmic reticulum (ER)-derived structures called ER bodies, which are implicated in plant immunity. Finally, the jazD mutant was employed as a parental line in a genetic suppressor screen aimed at identification of novel mutations that uncouple growth-defense antagonism. Characterization of these suppressor of jazD (sjd) mutants revealed that JA signaling interacts with the red light signaling pathway to influence growth-defense balance. One sjd mutant (sjd56) not affected in red light signaling was also shown to partially uncouple growth-defense antagonism in jazD. Taken together, results from this dissertation provide evidence that growth- defense tradeoffs at low to moderate levels of defense are controlled by hardwired transcriptional networks, whereas high levels of defense inhibit growth through metabolic competition (allocation costs) between primary and secondary metabolism. Consistent with this view, JAZ proteins promote growth and reproductive fitness by preventing the negative effects of an unrestrained immune responses. The findings described in this dissertation may benefit the development of crop plants that are optimized for both growth and defense. ACKNOWLEDGEMENTS There are many people to whom I want to express my thanks during my PhD career in Michigan State University. Research described in this dissertation could not be completed without the help from many wonderful people. My deepest gratitude goes to my advisor Dr. Gregg A. Howe, who has provided me with fantastic mentoring. I will always remember how Gregg spent time discussing research progress with me every Friday afternoon and helped me to resolve difficulties I met. Gregg’s patience, enthusiasm and integrity profoundly influence me. I appreciate all the time, ideas and support I received from Gregg. I am very fortunate to have a group of supportive and passionate committee members to guide me throughout my PhD studies. I would like to express my gratitude to Dr. Christoph Benning, Dr. Sheng Yang He, Dr. Jianping Hu, and Dr. Thomas Sharkey for their constructive suggestions and comments. Committee meetings and comprehensive exams with them have been enjoyable, and helped me gain insights into plant biology. The Howe lab has been a family to me since I joined in 2014. Thanks to Ian Major, who has taught me a number of lab techniques and who was always available when I was stuck with research or life problems. The knowledge and research ethics I learned from him will be with me wherever I go. Koichi Sugimoto has been a good friend to me and has given me much technical assistance. I am sure he will enjoy the food and research in his hometown. My research would not have been possible without the contributions from Yuki Yoshida, who constructed many of the higher-order jaz mutants described in the dissertation. His dedication to research has inspired me. Marcelo Campos was my supervisor when I did my rotation. It was fun to work with him. iv His smile and optimism left a deep impression on me. Yani Chen and Kyaw Aung gave me many tips on performing molecular experiments. I would like to thank them for “adopting” me during the trip to St. Louis for the 2017 ICAR conference. Nathan Havko has helped me with pathogen infection assays, and I am sure that he will come up with some exciting stories in the future. Leah Johnson, Caitlin Thireault, and Brian St. Aubin are talented graduate students I met in Howe lab. A significant portion of work described in Chapter Four was performed by Jinling Zhai, who was a visiting scholar from Hainan University in China. I also appreciate the efforts from my undergrads, including George Kapali, Alison Page, and Sam Heiler, who made many contributions to my project. Also thanks to Changxian Yang, Michael Das, and Julia Tu, who brought me with many joyful moments in the lab. The PRL, Plant Biology Department, and MSU plant science community have provided me with a friendly environment to grow. None of my work would be possible without the company of my friends and colleagues in MSU. My special thanks go to the PRL, DOE, and Plant Biology Department for continuous support of my studies at Michigan State University. Finally, I would like to say thanks to my fiancée Jing Yang, who has been by my side no matter what happens. I deeply appreciate her love, understanding and support. I am grateful to my parents and sister for their love and encouragement. v TABLE OF CONTENTS LIST OF TABLES..........................................................……………………………………….ix LIST OF FIGURES..................................................……………………………………………x CHAPTER ONE - LITERATURE REVIEW: RESOLUTION OF GROWTH-DEFENSE CONFLICT: MECHANISTIC INSIGHTS FROM JASMONATE SIGNALING.................1 Abstract............................................................................................................................................2 Introduction......................................................................................................................................3 Biosynthesis and metabolism of JA……………………………………………………………….4 JA signaling……………………………………………………….………………………………6 Redundancy and specificity of JAZ proteins……………………………………….……………..9 The bHLH MYC transcription factors…………………………………………………………...10 JA signaling reshapes the metabolic interface between growth and defense…………................11 The raison d’être of growth inhibition...........................................................................................14 Mechanisms of growth antagonism by JA.....................................................................................16 Modularity in JA signaling: conflict between too little and too much defense…….……………19 Summary and future perspectives: conflict resolution through phenotypic optimization….……21 APPENDIX………………………………………………………………………………………24 REFERENCES..............................................................................................................................33 CHAPTER TWO - JAZ REPRESSORS OF METABOLIC DEFENSE PROMOTE GROWTH AND REPRODUCTIVE FITNESS IN ARABIDOPSIS…………..……………46 Abstract..........................................................................................................................................47 Introduction....................................................................................................................................48 Results............................................................................................................................................52 Reduced growth and fertility of a jaz decuple mutant is associated with extreme sensitivity to jasmonate………..............................................................................................................52 Constitutive activation of jasmonate- and ethylene-mediated defense pathways in jazD plants……………………………………………………………………………..…….…54 Reprogramming of primary and secondary metabolism in jazD plants……………….......57 jazD plants exhibit symptoms of carbon starvation………………………………………59 A jaz1/2/3/4/5/6/7/8/9/10/13 undecuple mutant produces few viable seeds……………..60 Discussion......................................................................................................................................62 Methods…………….....................................................................................................................69 Plant material and growth conditions……………………………………………………..69 PCR analysis………………………………………………………………………………69 Growth measurements…………………………………………………………………….70 Root elongation assays……………………………………………………………………70 Coronatine treatment……………………………………………………………………..71 Insect and pathogen assays……………………………………………………………….71 Seed yield measurements………………………………………………………………….72 Germination assays………………………………………………………………………..72 vi RNA-seq analysis………………………………………………………………………….72 Quantitative proteomic analysis…………………………………………………………..73 Gas exchange measurements and 13C discrimination analysis……………………………75 Protein, lipid and cell wall measurements…………………………………………………75 Glucosinolate measurements………………………………………………………………76 Sucrose rescue assays……………………………………………………………………76 APPENDIX………………………………………………………………………………………78 REFERENCES............................................................................................................................114 CHAPTER THREE - MYC TRANSCRIPTION FACTORS PLAY OVERLAPPING AND DISTINCT ROLES IN REGULATING GROWTH -DEFENSE TRADEOFFS IN ARABIDOPSIS………………………………………………………………………………124 Abstract......................................................................................................................................125 Introduction................................................................................................................................126 Results.........................................................................................................................................131 JA hypersensitivity of jazD roots mainly depends on MYC2…………………………...131 MYC2 and MYC3 partially contribute to restricted growth of jazD ……………………133 MYC2/3/4 are required for the overaccumulation of defense compounds in jazD……....134 Constitutive formation of ER bodies in jazD is dependent on MYC TFs………………..134 Control of cellular respiration by the JAZ-MYC transcriptional module………………..137 MYC TFs are required for resistance of jazD to chewing insects and necrotrophic………… pathogens…………………………………………………………………………………137 Derepression of MYC TFs in jazD compromises reproductive fitness…………………..138 Discussion....................................................................................................................................140 Methods........................................................................................................................................147 Plant material and growth conditions…………………………………………………….147 Root and shoot growth measurements……………………………………………………147 Coronatine treatment and chlorophyll quantification…………………………………….148 Seed yield measurements………………………………………………………………148 Glucosinolate analysis………………………………………………………………….149 Insect and pathogen assays………………………………………………………………149 Confocal laser scanning microscopy…………………………………………………….150 SDS-polyacrylamide gel electrophoresis and mass-spectrometry analysis……………..150 Quantitative PCR………………………………………………………………………..151 Yeast two-hybrid assays…………………………………………………………………152 APPENDIX……………………………………………………………………………………154 REFERENCES............................................................................................................................182 CHAPTER FOUR – USE OF GENETIC SUPPRESSOR SCREENS TO UNCOUPLE GROWTH-DEFENSE ANTAGONISM……………………………………………………192 Abstract......................................................................................................................................193 Introduction................................................................................................................................194 Results..........................................................................................................................................197 Identification of suppressors of jazD…………………………………………………….197 One class of sjd mutants are insensitive to monochromatic red light……………………197 Apical hook formation of sjd10 is attenuated…………………………………................198 vii Growth-defense antagonism is partially uncoupled in sjd56…………………………….199 Genetic analysis of sjd56 and sjd78……………………………………………………...199 Discussion……………………………………………………………………..………………..201 Methods…………………………………………………………………………………….......205 jazD suppressor screen…………………………………………………………………..205 Genetic analysis of sjd mutants………………………………………………………….205 Hypocotyl elongation assays under monochromatic light………………………………206 Measurement of apical hook curvature………………………………………………….206 APPENDIX……………………………………………………………………………………207 REFERENCES……………………………………………………………………………….222 CHAPTER FIVE - SUMMARY AND FUTURE PERSPECTIVES....................................228 Summary of dissertation.............................................................................................................229 Future perspectives.....................................................................................................................234 REFERENCES...........................................................................................................................238 viii LIST OF TABLES Table 2.1. Seed and fruit production in jazQ and jazD plants......................................................79 Table 2.2. Biological processes in which proteins whose abundance in jazD leaves was increased or decreased in comparison to wild-type Col-0 based on gene ontology (GO) analysis………..80 Table 2.3. Mutants used for construction of jazD and jazU…………………………………….82 Table 2.4. Primers used for genotyping…………………………………………………………83 Table 2.5. Primers used for RT-PCR……………………………………………………………85 Table 3.1. Mutants used for construction of jazD myc mutants……………………………….155 Table 3.2. Primers used for genotyping jaz and myc mutants.………………………………..156 Table 3.3. Letters that denote significant differences according to Tukey’s HSD test (P < 0.05) for Figure 3.2B……………………………………………………………………………….158 Table 3.4. Letters that denote significant differences according to Tukey’s HSD test (P < 0.05) for Figure 3.3B……………………………………………………………………………….159 Table 3.5. Summary of proteins that were identified in the jazD-specific protein band in SDS- PAGE analyses……………………………………………………………………………….160 Table 4.1. List of sjd mutants identified in a suppressor screen.…………………………….208 Table 4.2. Segregation of rosette size in backcross populations of sjd56 and sjd78.………..209 ix LIST OF FIGURES Figure 1.1. Biosynthesis and metabolism of JA in Arabidopsis.……......…..…………………25 Figure 1.2. Connectivity between primary and specialized metabolism..........………………..26 Figure 1.3. Signaling networks and phenotypic space associated with growth-defense conflict.27 Figure 1.4. Speculative model of an evolutionary trajectory for JA-inducible defense…29 Figure 2.1. jazD pedigree……………………………………………………………………….87 Figure 2.2. Reverse transcription-PCR analysis of mutated JAZ genes in jazD………………..89 Figure 2.3. A jaz decuple mutant (jazD) is highly sensitive to JA and exhibits reduced growth and fertility……………………………………………….......…………………………91 Figure 2.4. Root growth inhibition in response to MeJA treatment…………………………….92 Figure 2.5. Vegetative growth and reproductive phenotypes of jazD plants……………………93 Figure 2.6. Bulk cell wall, protein, lipid, and dry mass content in higher-order jaz mutants…94 Figure 2.7. Fatty acid composition of seeds……………………………………………………95 Figure 2.8. jazD plants are highly resistant to insect herbivores and necrotrophic pathogens…96 Figure 2.9. Differential regulation in jazD of genes involved in growth, defense, and metabolism. …………………………………………………………………………………………………97 Figure 2.10. Upregulation of jasmonate pathway components in jazD………………………..99 Figure 2.11. Upregulation of ER body and indole glucosinolate defenses in jazD……………100 Figure 2.12. Reconfiguration of primary and secondary metabolism in jazD…………………102 Figure 2.13. Glucosinolate accumulation is elevated in jazD leaves………………………….104 Figure 2.14. Comparison of jazD “omics” data to jasmonate-responsive genes (JRGs) described by Sasaki-Sekimoto et al. (Sasaki-Sekimoto et al., 2005)……………………………………..105 Figure 2.15. jaz mutations increase respiration but do not affect resistance to CO2 diffusion through leaf mesophyll…………………………………………………………………………107 x Figure 2.16. jazD plants exhibit symptoms of carbon starvation………………………………108 Figure 2.17. Sorbitol does not promote biomass accumulation or root elongation in jaz mutants... ……….………………………………………………………………………………………….110 Figure 2.18. Vegetative growth and reproductive phenotypes of jazU plants…………………111 Figure 2.19. Genetic combination of jaz8-V and jazD further restricts growth and nearly abolishes seed production in the resulting undecuple mutant…………………………………..113 Figure 3.1. PCR-based genotyping of jazD mycT. …………………………………………….162 Figure 3.2. Sensitivity of jazD roots to JA is driven mainly by MYC2………………………..164 Figure 3.3. MYC2 is the major regulator of jazD sensitivity to coronatine.…………………165 Figure 3.4. Coronatine (COR)-induced chlorosis in jazD is partially dependent on light…….166 Figure 3.5. The growth deficiency of jazD is partially recovered by mycT.…………………..167 Figure 3.6. MYC2 and MYC3 play stronger roles in growth promotion compared to MYC4..168 Figure 3.7. The restricted growth of jazD cannot be restored by exogenous gibberellic acid (GA3) treatment…………………………………………………………………………..…………....169 Figure 3.8. Elevated accumulation of defense compounds in jazD is dependent on MYC TFs.170 Figure 3.9. Induction of ER body genes is mediated by MYC2/3/4………………………….172 Figure 3.10. MYC2/3/4 display additive effects on inducing the expression of ER body genes…. …………………………………………………………………………………………………..174 Figure 3.11. Increased respiration rates of jazD is dependent on MYC TFs.………………….176 Figure 3.12. MYC TFs account for increased resistance of jazD to insect herbivores and necrotrophic pathogens…………………………………………………………………………177 Figure 3.13. Compromised fertility of jazD is recovered by the myc2 myc3 myc4 triple mutation. ………………………………………………………………………………………………….179 Figure 3.14. Yeast two-hybrid analysis of NAI1-JAZ interactions……………………………181 Figure 4.1. Identification of suppressor of jazD (sjd) mutants .………………………….........210 Figure 4.2. Sensitivity of sjd mutants to red and far red light………………………………….212 xi Figure 4.3. sjd56 is insensitive to blue light…………………………………………………..213 Figure 4.4. Apical hook curvature of sjd10 is attenuated………………………………………..214 Figure 4.5. sjd56 and sjd78 partially recover the slow growth of jazD.………………………215 Figure 4.6. sjd56 maintains the elevated defense of jazD…………………………………….216 Figure 4.7. BC1F2 populations of sjd56 and sjd78…………………………………………..217 Figure 4.8. BC2F2 populations of sjd56 and sjd78…………………………………………..219 Figure 4.9. The blue light-insensitive phenotype of sjd56 is not associated with its growth phenotype……………………………………………………………………………………….221 xii CHAPTER ONE - LITERATURE REVIEW: RESOLUTION OF GROWTH-DEFENSE CONFLICT: MECHANISTIC INSIGHTS FROM JASMONATE SIGNALING Part of work presented in this chapter has been published: Guo, Q., Major, I.T., and Howe, G.A. (2018). Resolution of growth-defense conflict: mechanistic insights from jasmonate signaling. Current Opinion in Plant Biology 44, 72-81. 1 Abstract Induced plant resistance depends on the production of specialized metabolites that repel attack by biotic aggressors and is often associated with reduced growth of vegetative tissues. Despite progress in understanding the signal transduction networks that control growth-defense tradeoffs, much remains to be learned about how growth rate is coordinated with changes in metabolism during growth-to-defense transitions. Here, we highlight recent advances in jasmonate (JA) research to suggest how a major branch of plant immunity is dynamically regulated to calibrate growth-defense balance with shifts in carbon availability. We review evidence that diminished growth, as an integral facet of induced resistance, may optimize the temporal and spatial expression of defense compounds without compromising other critical roles of central metabolism. New insights into the evolution of JA signaling further suggest that opposing selective pressures associated with too much or too little defense may have shaped the emergence of a modular JA pathway that integrates primary and specialized metabolism through the control of repressor-transcription factor complexes. A better understanding of the mechanistic basis of growth-defense balance has important implications for boosting plant productivity, including insights into how these tradeoffs may be uncoupled for agricultural improvement. 2 Introduction Plant growth rate and reproductive output are intimately linked to the availability of photoassimilated carbon and other vital resources obtained from the environment. These same resources, however, are also used to produce defense compounds and physical structures that protect tissues from destruction by herbivores and pathogens. The notion that plant growth and immunity are antagonistically linked stems from the observation that elevated defense is commonly associated with growth inhibition and, of agricultural relevance, reduced yield. Given the importance of these traits for plant fitness in diverse environments, it is generally assumed that plants have evolved strategies to balance growth and reproductive output with the need for defense (Herms and Mattson, 1992; Heil and Baldwin, 2002; Stamp, 2003; Zust and Agrawal, 2017). A mechanistic appreciation of how growth and immunity intersect has important implications for understanding not only the diversity of defense strategies employed across the plant kingdom, but also for improving sustainable crop production. Significant progress has been made in understanding the molecular mechanisms of crosstalk between growth and immune signaling networks (Belkhadirl et al., 2014; Huot et al., 2014; Lozano-Duran and Zipfel, 2015; Havko et al., 2016). While it is now clear that gene regulatory networks exert major control over growth-defense balance, a better understanding of the inherent conflicts between these major physiological tasks is needed to accurately predict genotype-by-environment interactions that give rise to tradeoffs (Chae et al., 2016; Zust and Agrawal, 2017). Hormone-based defense systems in which broad-spectrum resistance is conferred by induced expression of specialized defense proteins and metabolites, with associated growth suppression, provide attractive experimental systems in which to address the underlying mechanisms of growth-defense tradeoffs (Havko et al., 2016). 3 Here we discuss growth-defense conflict from a mechanistic and metabolic perspective. We use the JA signaling pathway to highlight how reprogramming of the interface between primary and specialized metabolism may be linked to changes in carbon availability and re- calibration of growth rate. We also propose a framework for understanding the modular architecture of the JA signaling pathway in the context of opposing selective pressures associated with too much or too little defense, and how this signaling system integrates primary and specialized metabolism through control of repressor-transcription factor complexes. Finally, we consider how recent mechanistic insights into crosstalk between growth and immune signaling networks provide opportunities to uncouple growth-defense tradeoffs for agricultural benefit. Biosynthesis and metabolism of JA JA was first isolated from the essential oil of jasmine flowers in the form of methyl-JA (MeJA) (Demole et al., 1962). Since its identification, tremendous advances in JA research have been made to understand its function in regulating various physiological processes, especially its dual roles in inhibiting growth and promoting defense. The biosynthetic pathway of JA was characterized by many forward and reverse genetic screens (Wasternack, 2015). Biosynthesis of JA takes place in the chloroplast, peroxisome and cytosol (Howe, 2018). The first step of JA production is the release of α-linolenic acid (18:3) by the action of plastidic lipases, one of which is DEFECTIVE IN ANTHER DEHISCENCE 1 (DAD1) expressed in stamen filaments (Figure 1.1) (Ishiguro et al., 2001). Recently, Wang et al. showed that overexpression of two additional lipase genes PLASTID LIPASE 2 (PLIP2) and PLASTID LIPASE 3 (PLIP3) gives rise to the accumulation of JA and its derivatives in Arabidopsis leaves (Wang et al., 2018), suggesting that these two lipases also contribute to the accumulation of JA. Consistent with this hypothesis, the 4 restricted growth of PLIP2-OX and PLIP3-OX plants resembles the phenotype of mutants in which the JA pathway is constitutively activated, and blocking of JA perception in these PLIP- OX lines restores their growth phenotype (Wang et al., 2018). Once released from membrane lipids, α-linolenic acid is converted by 13-lipoxygenases (13-LOXs) to 13- hydroxyperoxylinolenic acid (13-HPOT) (Figure 1.1) (Bell et al., 1995; Bannenberg et al., 2009; Chauvin et al., 2013). In Arabidopsis, 13-LOXs are encoded by the LOX2, LOX3, LOX4 and LOX6 genes (Bannenberg et al., 2009; Chauvin et al., 2013; Chauvin et al., 2016). 13-HPOT is further metabolized to 12-oxo-phytodienoic acid (OPDA) in the chloroplast by the sequential action of ALLENE OXIDE SYNTHASE (AOS) (Song and Brash, 1991) and ALLENE OXIDE CYCLASE (AOC) (Figure 1.1) (Ziegler et al., 2000). OPDA is transported from chloroplast to peroxisome, most likely by a process involving the peroxisomal ATP-BINDING CASSETTE (ABC) transporter COMATOSE (CTS, also known as PXA1) (Figure 1.1) (Theodoulou et al., 2005). Within the peroxisome, OPDA is metabolized to 3-oxo-2(2' (Z)-pentenyl)-cyclopentane-1-octanoic acid (OPC-8:0) by OPDA REDUCTASE 3 (OPR3) (Stintzi and Browse, 2000) and then ligated to CoA by OPC-8:0 CoA LIGASE (OPCL) to produce OPC 8:0-CoA (Figure 1.1) (Schneider et al., 2005). OPC 8:0-CoA then goes through three cycles of β-oxidation to complete the production of JA (Figure 1.1) (Vick and Zimmerman, 1984; Li et al., 2005; Schilmiller et al., 2007). A recent study by Chini et al. revealed that an OPR3-independent pathway for JA biosynthesis exists in plants (Chini et al., 2018). They found that a mutant (opr3-3) defective in OPR3 is still resistant to insect herbivores and necrotrophic pathogens, and is able to activate the COI1-dependent JA signaling pathway under stressed conditions (Chini et al., 2018). This work also showed that, in the absence of 5 OPR3, OPDA can be converted to 4,5-didehydro-JA (ddh-JA) and that this compound can be reduced to JA by the enzyme OPDA REDUCTASE 2 (OPR2) (Figure 1.1) (Chini et al., 2018). Following its export from the peroxisome, JA is metabolized to a myriad of metabolites in the cytoplasm. For example, JA can be conjugated to isoleucine (Ile) by JASMONATE RESISTANT 1 (JAR1) to form JA-Ile, which is the major bioactive form of the hormone (Figure 1.1) (Staswick et al., 2002; Thines et al., 2007; Katsir et al., 2008; Fonseca et al., 2009). Metabolism of JA may also inactivate this hormone. Recent studies found that four paralogous 2- oxoglutarate/Fe(II)-dependent (2-OGD) oxygenases, named JASMONATE-INDUCED OXYGENASE (JOX) or JASMONIC ACID OXIDASE (JAO), hydroxylate JA to form 12-OH- JA in Arabidopsis (Figure 1.1) (Caarls et al., 2017; Smirnova et al., 2017). Mutation of four JOX genes in Arabidopsis led to overaccumulation of JA, and as a consequence, this quadruple mutant showed elevated resistance to the necrotrophic fungus Botrytis cinerea and the caterpillar Mamestra brassicae (Caarls et al., 2017). Genetic complementation of the quadruple mutant with individual JOX genes reduced the level of JA, indicating that all four JOXs contribute to the inactivation of the precursor form of JA-Ile (Caarls et al., 2017). JA signaling Perception of JA-Ile requires the F-box protein CORONATINE INSENSITIVE 1 (COI1), which is a component of the SCF (Skp/Cullin/F-box) E3-type ubiquitin ligase (Xie et al., 1998). The coi1 mutant was isolated in a screen for ethylmethanesulfonate (EMS)-mutagenized plants that were insensitive to coronatine, which is a molecular mimic of JA-Ile (Feys et al., 1994). Many phenotypes observed in coi1, including short anther filaments and male sterility, resemble phenotypes of mutants defective in JA biosynthesis (McConn and Browse, 1996). Likewise, a 6 screen for tomato mutants that are insensitive to MeJA identified the mutant jasmonate insensitive 1 (jai1), which is defective in the tomato ortholog of Arabidopsis COI1 (Li et al., 2004). Given the fact that F-box proteins provide specificity to the SCF ligase complex by recognizing particular targets for ubiquitination and degradation via the 26S proteasome, identification of COI1 as a F-box protein suggested that protein degradation is a key step in the JA signaling cascade (Xie et al., 1998). A decade after the discovery of COI1, JASMONATE ZIM-DOMAIN (JAZ) proteins were identified as the targets of this F-box protein (Chini et al., 2007; Thines et al., 2007; Yan et al., 2007). JAZ proteins belong to the TIFY protein family, which possesses a conserved TIFY motif within the ZIM domain (named for a zinc-finger protein expressed in the inflorescence meristem) (Vanholme et al., 2007; Bai et al., 2011). The main feature that distinguishes JAZ from other TIFY proteins is the 27-amino-acid Jas motif located near the C terminus (Howe et al., 2018). When cellular JA levels are low, the Jas motif interacts with the JAZ-interacting domain (JID) at the N terminus of the basic helix-loop-helix (bHLH) MYC transcription factors (TFs) (Zhang et al., 2015), which are the most intensively studied JA-responsive TFs. Structural, biochemical and in planta analyses indicate that JAZ proteins impose transcriptional repression by competitively impeding the binding of MEDIATOR 25 (MED25), which bridges TFs and RNA polymerase II to promote gene expression (Kazan and Manners, 2013; Zhang et al., 2015). JAZ proteins also attenuate TF activity by recruiting TOPLESS (TPL) proteins that suppress gene expression via epigenetic modification (Ke et al., 2015). TPL is recruited to JAZ either directly via an EAR motif (Shyu et al., 2012) or indirectly through the NOVEL INTERACTOR OF JAZ (NINJA) adaptor protein (Pauwels et al., 2010). 7 The accumulation of JA-Ile above a threshold concentration activates JA-mediated signal transduction. JA-Ile is perceived by a receptor complex consisting of the F-box protein COI1, JAZ repressors, as well as an inositol pentakisphosphate that interacts with both COI1 and JAZs (Sheard et al., 2010). The three-dimensional structure of the receptor complex shows that JA-Ile is recognized by an open pocket in COI1, which is docked in the α-helix formed by a bipartite degron sequence within the Jas motif of JAZ proteins (Sheard et al., 2010). In addition to the α- helix, this degron also consists of a loop region to trap the hormone to its binding pocket (Sheard et al., 2010). Recruitment of JAZ proteins to COI1 triggers polyubiquitination and subsequent degradation of JAZ by the 26S proteasome (Chini et al., 2007; Thines et al., 2007), resulting in the activation of TFs that drive JA-responsive genes. Recent studies have shown that JA-induced degradation of JAZ repressors is facilitated by the direct interaction between COI1 and MED25, which brings COI1 to the transcriptional start sites of MYC2 target genes (An et al., 2017). Furthermore, MED25 recruits HISTONE ACETYLTRANSFERASE 1 (HAC1), which promotes gene expression by acetylating histone (H) 3 lysine (K) 9 (H3K9) (An et al., 2017). Besides JAZ proteins, JA-Ile promotes the destruction of another repressor of the JA signaling, namely JASMONATE-ASSOCIATED VQ MOTIF GENE 1 (JAV1) (Hu et al., 2013). Despite the fact that JAV1 is degraded by the 26S proteasome upon JA-Ile elicitation, this protein does not directly interact with COI1 (Hu et al., 2013). However, JA-Ile-induced degradation of JAV1 is still dependent on COI1, as MeJA treatment of coi1 mutant does not spur JAV1 destruction (Hu et al., 2013). It is conceivable that COI1 may activate the production an unidentified E3 ligase that recognizes JAV1 for degradation by the 26S proteasome (Hu et al., 2013). 8 Redundancy and specificity of JAZ proteins The 13 JAZ genes (JAZ1-13) in Arabidopsis are classified into five phylogenetic groups (Group I-V) (Thireault et al., 2015; Howe et al., 2018). Most mutants harboring loss-of-function insertional alleles in single JAZ genes do not show strong JA-induced phenotypes, suggesting that JAZ proteins are functionally redundant (Chini et al., 2007; Thines et al., 2007; Thireault et al., 2015). One exception is jaz10, which displays increased sensitivity to exogenous JA (Demianski et al., 2012). A JAZ10 alternative splice variant called JAZ10.4 lacks the Jas motif, however, it retains the ability to repress JA responses and is highly resistant to JA-induced degradation (Chung and Howe, 2009). Thus, mutants defective in JAZ10 exhibit hypersensitivity to JA likely because they lose the ability to produce splice variants that are stabilized against degradation. Compared to jaz single mutants, the responsiveness of a jaz quintuple (jazQ) mutant deficient in five JAZ genes (JAZ1/3/4/9/10) to JA application is enhanced (Campos et al., 2016). This mutant also shows other JA-associated phenotypes, including overaccumulation of anthocyanin and increased defense responses (Campos et al., 2016). However, these phenotypes are mild compared to JA-elicited phenotypes (Campos et al., 2016), indicating that the remaining JAZs are still functional in jazQ. Despite apparent redundancy among JAZ genes, recent studies demonstrate that some JAZ proteins possess specific functions. Functional specialization among gene family members may be achieved through expression in particular tissues or cell types. For instance, JAZ2 is strongly expressed in stomatal guard cells and inhibits stomatal opening by constraining the activity of MYC TFs, which directly regulate the expression of three homologous NAC family TFs to modulate stomata aperture (Zheng et al., 2012; Gimenez-Ibanez et al., 2017). This COI1- JAZ2-MYC-NAC module can be hijacked by Pseudomonas syringae bacteria to facilitate 9 pathogen infection (Gimenez-Ibanez et al., 2017). Another mechanism to achieve functional specificity among JAZ family members is through differential JAZ binding to specific TFs. For example, only JAZ3 interacts with the YABBY (YAB) family transcription factor FILAMENTOUS FLOWER (FIL)/YAB1, which regulates disease resistance and the production of anthocyanin and chlorophyll (Boter et al., 2015). The bHLH MYC transcription factors The best characterized JAZ-interacting TFs are the subgroup IIIe bHLH proteins MYC2, MYC3, MYC4 and MYC5 (Fernandez-Calvo et al., 2011; Major et al., 2017). Mutants defective in MYC2, MYC3 or MYC4 display reduced resistance to insect herbivores (Lorenzo et al., 2004; Fernandez-Calvo et al., 2011; Chico et al., 2014; Major et al., 2017). It has been shown that MYC TFs promote the production of a myriad of defense compounds that are derived from terpenoid, alkaloid, phenylpropanoid and amino acid biosynthetic pathways (Goossens et al., 2017). For example, MYC2, MYC3 and MYC4 are involved in the production of glucosinolates (Schweizer et al., 2013), which are major anti-insect secondary metabolites in the Brassicaceae family. A myc2 myc3 myc4 triple mutant is almost completely devoid of glucosinolates and, as a consequence, is susceptible to insect attack (Schweizer et al., 2013). Molecular and biochemical analyses showed that MYC TFs physically interact with MYB TFs (i.e. MYB28/29/34/51/76/122) to synergistically control the expression of glucosinolate biosynthetic genes (Schweizer et al., 2013). In addition to governing the expression of defense traits, MYC TFs execute other JA- mediated physiological tasks. For example, MYC2 reduces the activity of the root meristem by inhibiting the expression of PLETHORA 1 (PLT1) and PLETHORA 2 (PLT2), which mediate 10 auxin-induced regulation of stem cell niche maintenance (Chen et al., 2011a). MYC TFs also affect biomass accumulation. A mutant lacking MYC2, MYC3 and MYC4 displayed increased shoot growth in comparison with WT (Major et al., 2017). Reproductive processes are also influenced by MYC TFs. MYC2, MYC3, MYC4 and MYC5 interact with MYB TFs MYB21 and MYB24 to cooperatively modulate stamen development (Qi et al., 2015). The myc2 myc3 myc4 myc5 quadruple mutant exhibits defects in stamen development and reduced seed yield (Qi et al., 2015). JA signaling reshapes the metabolic interface between growth and defense Induced plant defense is associated with the production of a vast array of specialized metabolites (SMs) that mediate plant interactions with associated biota. Biosynthetic pathways for the major classes of SMs, including phenylpropanoids, polyketides, terpenoids, and nitrogen-containing compounds, are often regulated in an inducible fashion by JA (De Geyter et al., 2012; Zhou and Memelink, 2016). Because SMs are derived from one or more primary metabolites, induced production of SMs must be coordinated with corresponding changes in appropriate sectors of primary metabolism (D'Auria and Gershenzon, 2005; Aharoni and Galili, 2011). Pathways that highlight some of the major interconnections between specialized and primary metabolism in Arabidopsis are depicted in Figure 1.2. For example, cinnamates generated by the phenylpropanoid pathway are precursors for monolignols and lignin production, as well as diverse phenylpropanoid and polyketide products. Large pools of proteinogenic amino acids are required for the biosynthesis of numerous defensive proteins that can accumulate to high levels in JA-elicited tissues. Similarly, various amino acid precursors such as indole provide building blocks for nitrogen-containing SMs, including glucosinolates. As the largest and most diverse 11 group of plant metabolites, terpenoids are produced from isoprene units and include primary metabolites (e.g., carotenoids) as well as a myriad of specialized mono-, sesqui-, di-, and triterpenes. Other plant species produce distinct groups of SMs that are also derived from intermediates of primary metabolism; examples include the synthesis of phenolic glycosides from cinnamate, stilbenes from cinnamate and malonyl-CoA, cyanogenic glycosides from tryptophan, benzoxazinoids from indole, and complex alkaloids from amino acids, polyamines, and purines. The reported effects of biotic stress on primary metabolism often vary depending on the experimental system under study (Schwachtje and Baldwin, 2008; Zhou et al., 2015; Papazian et al., 2016). Nevertheless, increasing evidence indicates that changes in primary metabolism may serve to save time and energy during the transition from growth to defense. A notable example is the effect of biotic challenge on photosynthetic metabolism. The commonly observed repressive effect of biotic stress on photosynthesis gene expression may reflect a strategy to reprogram the cell’s biosynthetic machinery without actual losses in photosynthetic efficiency; photosynthetic robustness in the face of genetic and environmental perturbations would ensure a continuous supply of carbon skeletons for the rapid production of defense proteins and metabolites (Schwachtje and Baldwin, 2008; Luo et al., 2009; Bilgin et al., 2010; Attaran et al., 2014; Zhou et al., 2015; Havko et al., 2016). Similarly, turnover of photosynthesis-related transcripts and proteins may increase the pool of resources needed to fuel induced defense responses (Attaran et al., 2014) and also increase the availability of ribosomes for translation of defense-related mRNAs. Optimization of ribosome capacity during the onset of defense responses may thus serve to mitigate the high cost of protein synthesis in relation to growth (Ishihara et al., 2017; Xu et al., 2017). 12 Changes to primary metabolism elicited by JA also include reductions in sugar and starch content that is associated with increased biosynthesis of SMs, suggesting depletion of resources to produce SMs (Machado et al., 2013). Direct evidence for the diversion of resources to SMs was obtained by N flux studies in N. attenuata, which showed that assimilated N was directed to N-rich SMs (e.g., phenolamides) instead of soluble proteins (Ullmann-Zeunert et al., 2013). Ancillary pools of primary metabolites are also affected by specialized metabolism and can dramatically alter nutrient distribution. Glucosinolate production, for instance, can influence plant sulfur content via demand for activated sulfate (Falk et al., 2007; Mugford et al., 2009). The production of SMs is tightly regulated by transcription factors, some of which also appear to coordinate upstream pathways of primary metabolism (Aharoni and Galili, 2011). For example, MYB8 directs phenolamide biosynthesis and, perhaps indirectly, protein pool sizes in N. attenuata (Ullmann-Zeunert et al., 2013). MYB34 and MYB51, which are principal regulators of indole glucosinolate biosynthesis, directly regulate expression of genes involved in tryptophan biosynthesis and sulfate metabolism, revealing coordinated regulation of primary metabolic pathways with specialized metabolism (Celenza et al., 2005; Gigolashvili et al., 2007; Yatusevich et al., 2010). Metabolic costs of SM production include not only precursors and cofactors required for biosynthesis, but also costs associated with transport, maintenance, and storage (Gershenzon, 1994; Bekaert et al., 2012; Nour-Eldin et al., 2012; Havko et al., 2016). Flux balance analysis of glucosinolate production in Arabidopsis, for example, indicates that photosynthetic output would need to increase by 15% to account for metabolic processes associated with the production of these compounds (Bekaert et al., 2012). Overall, the changes to primary and specialized metabolism observed during growth to defense transitions are likely coordinated to support the energy and resource demands of SM production without sacrificing 13 other key roles of primary metabolism. Given the costs of chemical defense and the direct linkages between primary and specialized metabolism, it is perhaps not surprising that SM production is often associated with reduced growth. The raison d’être of growth inhibition Two general hypotheses have been proposed to explain why plant growth is inhibited upon induced expression of defense responses. One common interpretation invokes a resource-based cost (also referred to as allocation costs) in which increased allocation of one or more resources to defense necessarily restricts resources that could otherwise be used for growth, reproductive development, or other physiological tasks (Heil and Baldwin, 2002; Havko et al., 2016; Zust and Agrawal, 2017). This hypothesis could apply to any limiting biochemical resource that is shared by primary and specialized metabolism, including amino acids and photoassimilated carbon skeletons (Figure 1.2). The resource-based tradeoff model is challenging to test because of the difficulty in defining (and therefore measuring) metabolic costs of specific defense compounds, and likely oversimplifies a highly complex relationship that is shaped by strategies to offset the costs of defense (Neilson et al., 2013; Havko et al., 2016; Kliebenstein, 2016; Karasov et al., 2017; Zust and Agrawal, 2017). That plants can be manipulated to grow and defend well at the same time (e.g., Campos et al., 2016) further indicates that growth-defense antagonism is not simply determined by resource limitation but rather is controlled at the transcriptional level by hard-wired regulatory circuits. Nevertheless, it is evident that high-level production of SMs, which is commonly observed in plants, must reduce the pool of resources that is used to support other physiological processes. It is possible that resource-based tradeoffs are difficult to detect because they occur in 14 a context-dependent manner, for example being manifested during specific stages of ontogeny or only when the flux of primary metabolites into defense pathways exceeds a certain (likely high) threshold (Zust and Agrawal, 2017). As discussed below, multi-tiered mechanisms to powerfully repress the expression of chemical defenses may serve to prevent deleterious effects of carbon depletion or metabolic imbalance during the growth to defense transition, which if true would make resource-based tradeoffs difficult to detect in wild-type plants grown under most laboratory conditions. A second general hypothesis to explain the antagonistic relationship between induced resistance and growth is that growth restriction is an adaptive response mediated by hardwired interactions between growth and immune signaling networks. This regulatory view of growth- defense tradeoffs is analogous to strategies used by microorganisms to cope with nutrient scarcity (Matin, 1991; De Virgilio, 2012). Among the key features of many microbial responses to nutrient starvation are: i) mechanisms to sense nutrient scarcity prior to complete depletion of the resource; ii) turnover and recycling of cellular components, including protein degradation in response to amino acid starvation; iii) transcriptional activation of genes encoding protective compounds to help ensure survival during the quiescent state; and iv) the onset of general resistance to stresses other than nutrient limitation. Analogous to these microbial strategies, the emerging view in plants is that growth inhibition is often not a direct consequence of depleting a critical nutrient but rather is a highly programmed response that prepares the organism for harsh environmental conditions, from which robust growth can resume when conditions improve (Campos et al., 2016; Kliebenstein, 2016; Karasov et al., 2017; Machado et al., 2017; Zust and Agrawal, 2017). 15 The notion that immune-triggered growth inhibition is a strategy to avoid starvation of essential metabolic intermediates is generally consistent with the acclimatory response hypothesis, which provides an explanation for how plant growth rate is adjusted in response to diurnal changes in carbon supply and demand (Smith and Stitt, 2007). In extending this hypothesis to induced chemical defense, it is conceivable that rapid flux of carbon intermediates into defense pathways may have effects similar to those observed in plants subjected to extended night or other conditions associated with carbon starvation. Specifically, it is envisioned that nutrient-sensing systems detect carbon limitation or energy imbalances to recalibrate (i.e., reduce) growth to the new level of available carbon, thus protecting against the deleterious effects of growth arrest upon exhaustion of assimilated carbon (Smith and Stitt, 2007). Empirical support for this idea comes from studies showing that JA elicitation depletes sucrose and starch content in several plant species (Babst et al., 2005; Hanik et al., 2010; Machado et al., 2015; Machado et al., 2017). There is also increasing evidence to link JA to various energy sensing systems, including the target of rapamycin (TOR) and sucrose non-fermenting kinase 1 (SnRK1) pathways, that influence growth-defense balance (Schwachtje et al., 2006; Liu et al., 2017; Song et al., 2017; De Vleesschauwer et al., 2018). That slow growth is a common phenotype among plant mutants affected in metabolism raises the additional possibility that metabolic imbalance during the growth-defense transition, rather than chemical defense production per se, is a general cue for growth attenuation. Mechanisms of growth antagonism by JA The signal transduction networks that control growth-defense conflict are highly complex in their ability to integrate extracellular cues with the action of various growth and defense hormones. 16 The function of JA in both promoting defense and inhibiting growth provides a focal point for understanding how a well-defined signal within this larger network contributes to growth- defense balance at a mechanistic level. Indeed, there is increasing evidence that the core JA pathway is hub for integrating diverse developmental and stress-related cues that collectively serve to optimize plant fitness in changing environments (Howe et al., 2018). A compelling example of this comes from studies showing that defense responses are directly influenced by changes in the activity of phytochrome B during the shade avoidance response (Moreno et al., 2009; Chico et al., 2014). That JA inhibits growth of both dicot and monocot species suggests that the mechanisms responsible for linking hormone action to the control of cell division are conserved (Yan et al., 2007; Zhang and Turner, 2008; Yang et al., 2012; Noir et al., 2013; Havko et al., 2016; Hibara et al., 2016). Time course studies in Arabidopsis indicate the rapid defense activation and restriction of shoot growth in response to JA are tightly coupled processes that occur in the absence of reductions in photosynthetic efficiency (Attaran et al., 2014). Genetic analyses further show that MYC transcription factors negatively regulate leaf growth, whereas JAZ proteins, as repressors of MYCs, promote growth (Campos et al., 2016; Major et al., 2017). These studies support a model in which elevated levels of bioactive JA-L-isoleucine (JA-Ile) lead to JAZ degradation and de-repression of MYC transcription factors, which in turn exert opposing effects on growth and defense. The JAZ-MYC transcriptional module may restrict leaf growth and biomass accretion by one or more of several mechanisms (Figure 1.3A). According to the acclimatory response hypothesis (Smith and Stitt, 2007), activation of defense metabolism by MYC and perhaps other JAZ-interacting transcription factors could generate a metabolic signal that tunes growth rate downward to match the new metabolic state in which fewer resources are available for growth. 17 JA-inducible transcription factors such as MYC may also attenuate leaf growth through negative regulation of genes involved in cell cycle control (Noir et al., 2013; Attaran et al., 2014; Gasperini et al., 2015; Major et al., 2017). This could involve the synergistic interaction of JA with other phytohormones such as ethylene, which signals through ERF (ETHYLENE RESPONSE FACTORS) transcription factors to control cell division (Dubois et al., 2018). A function for MYCs as negative regulators of leaf growth is analogous to the role of the JAZ- MYC module in inhibiting the activity of PLETHORA transcription factors that promote auxin- dependent control of cell proliferation in the root meristem (Chen et al., 2011b; Gasperini et al., 2015; Major et al., 2017). A third hypothesis is that JA-mediated growth-defense tradeoffs are controlled by antagonistic crosstalk between the JA-Ile and gibberellin (GA) signaling pathways (Navarro et al., 2008) (Figure 1.3A). The DELLA repressors of GA signaling have been implicated in wound- and JA-mediated growth inhibition of Arabidopsis roots (Hou et al., 2010) and hypocotyls (Yang et al., 2012), but as yet there is little evidence for this in leaves (Zhang and Turner, 2008). These findings suggest that different mechanisms of growth antagonism may operate in different tissues or that different members of the DELLA family exert differential effects on growth-defense antagonism, perhaps through specific DELLA-JAZ interactions. Studies with N. attenuata provide evidence that JA-mediated carbohydrate depletion and shoot growth inhibition occur independently of the production of JA-Ile-regulated defense compounds, arguing against a resource tradeoff model in this experimental system (Machado et al., 2017). Based on the analysis of plants treated with exogenous JA and GA, it was proposed that JA indirectly represses shoot growth by antagonizing the GA pathway, perhaps through down regulation of photosynthesis (Machado et al., 2017). These collective studies indicate that, 18 despite detailed insight into how JA-Ile perception in the nucleus is coupled to defense gene expression (Howe et al., 2018), a satisfactory explanation of how this hormone inhibits growth is far from complete. Modularity in JA signaling: conflict between too little and too much defense Theories to explain variable patterns of plant defense often invoke the existence of strategies to offset the costs of immunity (Heil and Baldwin, 2002; Neilson et al., 2013; Karasov et al., 2017; Zust and Agrawal, 2017). A recurring theme among these strategies, which encompass all forms of induced defense, is exquisite control over the spatial and temporal expression pattern of defense genes and the physiological traits they specify. The regulatory mechanisms that dictate these patterns of defense may provide a window into evolutionary trajectories that shaped the emergence of extant defense systems (Yang et al., 2012; Hibara et al., 2016; Major et al., 2017). As an example, we present a speculative model of how selective pressures imposed by too little or too much defense may have shaped the modular architecture of JA-Ile signaling in higher plants (Figure 1.4). A striking feature of the JA branch of immunity is the prevalence of molecular components involved in transcriptional repression of defense gene expression (Campos et al., 2014; Howe et al., 2018). These mechanisms operate at multiple temporal and spatial scales, and include: i) metabolic depletion of JA-Ile (Koo and Howe, 2012; Heitz et al., 2016); ii) increased stability of JAZ repressors through alternative splicing and variation in degron efficiency (Chung et al., 2010; Shyu et al., 2012; Thireault et al., 2015); iii) structurally distinct MYC-interaction domains within JAZ repressors (Moreno et al., 2013; Zhang et al., 2017); iv) competitive inhibition of MYC binding to promoters of target genes (Nakata et al., 2013; Song et al., 2013; 19 Fonseca et al., 2014); v) age-dependent termination of JA signaling (Mao et al., 2017); and vi) and other negative feedback loops (Zhou et al., 2016) (Figure 1.4). Why are JA-based defense responses subject to so many levels of negative regulation? The answer to this question likely lies in the observation that sustained de-repression of JA-Ile signaling, for example from continuous exposure to exogenous precursors (e.g., methyl-JA) of JA-Ile, results in growth arrest, extreme senescence-like symptoms, and lethality (Ueda and Kato, 1980; Zhang and Xing, 2008; Campos et al., 2016). This and other examples of the deleterious effects of autoimmunity (Chae et al., 2016) suggest that, under some conditions, the advantages of switching off defense outweigh the advantages of switching it on. The dual role of JAZ proteins in both JA-Ile perception and repression of transcription factor activity raises the question of which of these two functions first emerged during evolution of the pathway (Howe et al., 2018). Although it is generally assumed that JA signaling evolved as a strategy to activate defense in response to danger signals (Howe and Jander, 2008; Koo and Howe, 2009; Thaler et al., 2012), it is possible that JAZ repressors originated in response to selective pressures to mitigate the metabolic costs of constitutive (i.e., costly) defenses prior to the emergence of JA-Ile and its coreceptor COI1 (Figure 1.4). In support of this hypothesis, a wealth of genetic and biochemical data suggest that JAZ degradation is the main, if not exclusive, function of COI1 and JA-Ile in vascular plants (Howe et al., 2018). There is also recent evidence to indicate that COI1, as well as the capacity to synthesize JA-Ile, arose in early land plants (Bowman et al., 2017; Pratiwi et al., 2017; Howe et al., 2018). Future studies of JA signaling in the basal plant lineages promises to provide important insights into the evolutionary origins of this major branch immunity and its role in regulating growth-defense balance. As mentioned above, it will be particularly informative to determine whether ancestral JAZ repressors evolved 20 before or after the emergence of COI1 and the capacity to synthesize the COI1-associated ligand (Figure 1.4). Summary and future perspectives: conflict resolution through phenotypic optimization An increased understanding of growth-defense tradeoffs is expected to inform research aimed producing plants in which metabolic resources are optimally allocated to growth and defense, thereby enhancing productivity in a given environment (Figure 1.3B). The Pareto front concept has proven useful for analyzing the optimal allocation of resources to physiological tasks that trade off with each other in nature (Shoval et al., 2012). Given that the best plant phenotype for growth is usually a poor phenotype for defense (and vice versa), additional research is needed to determine how the relevant metabolic and signal transduction networks can be rewired to uncouple, or at least minimize, tradeoffs to produce plants that exhibit robust growth and defense at the same time. Genetic suppressor screens offer one approach to achieve this goal. Campos et al (Campos et al., 2016) started with a jaz quintuple mutant (jazQ) of Arabidopsis that lacks five JAZ repressors and, as a consequence, exhibits heightened defense against insect attack and accompanying growth restriction. A suppressor screen revealed that loss of the red light receptor phytochrome B (phyB) in the jazQ background reverts the low biomass phenotype without compromising resistance to chewing insects. Uncoupling of growth-defense tradeoffs in jazQ phyB plants was attributed in part to simultaneous activation of the MYC and PIF transcription factor modules, which in wild-type plants antagonize one another in part through direct interaction between JAZ and DELLA proteins (Hou et al., 2010; Yang et al., 2012) (Figure 1.3A). Remarkably, the unique combination of jazQ phyB results in a plant that is phenotypically superior to wild-type plants in terms of anti-insect defense in the absence of a growth penalty, at 21 least under ideal laboratory growth conditions (Figure 1.3C) (Shoval et al., 2012; Chae et al., 2016; Zust and Agrawal, 2017). Although these findings suggest that rational redesign of the underlying regulatory networks may be used to optimize growth-defense balance, it will ultimately be important to determine how such genetic changes influence plant fitness in diverse environmental conditions (Zust and Agrawal, 2017). There is additional evidence that constitutive activation or priming of JA-mediated defenses can be achieved with minimum effects on growth (Chen et al., 2006; Smirnova et al., 2017). One striking example comes from work showing that downregulation of the Arabidopsis JAV1 repressor results in increased resistance to both necrotrophic fungi and insect herbivores without affecting growth (Hu et al., 2013). In addition to genetic modifications, it may also be possible to use chemical approaches to break the antagonistic link between growth and defense. For example, application of a synthetic macrolactone analog of JA-Ile was sufficient to induce JA-regulated defense responses in N. attenuata without obvious diminution of growth or fitness (Jimenez-Aleman et al., 2017). Although the molecular basis of this effect remains to be determined, it is possible that JA-Ile macrolactones work through specific COI1-JAZ coreceptor subtypes to promote defense at a level that does not restrict growth. Finally, we note that strategies to optimize growth-defense tradeoffs extend beyond JA and include other components of growth and immune signaling networks. Plant breeders have long been engaged in efforts to reduce growth and yield penalties that accompany resistance (R) gene-mediated crop protection against pathogens and pests (Brown, 2002; Chae et al., 2016; Karasov et al., 2017; Ning et al., 2017). Recent molecular studies in rice provide compelling examples of how broad-spectrum resistance to Magnaporthe oryzae, the causal agent of rice blast disease, can occur in the absence of significant growth or yield penalties (Deng et al., 2017; 22 Li et al., 2017). These and other (Xu et al., 2017) recent studies highlight the utility of fine- tuning the expression of defense pathways as a strategy to maximize resistance while minimizing negative pleiotrophic effects on growth and yield. 23 APPENDIX 24 Figures Figure 1.1. Biosynthesis and metabolism of JA in Arabidopsis. JA biosynthesis involves two organelles: chloroplast and peroxisome. Intermediate products are highlighted in bold. Abbreviations: DAD1: DEFECTIVE IN ANTHER DEHISCENCE 1; PLIP2: PLASTID LIPASE 2; PLIP3: PLASTID LIPASE 3; 13-LOXs: 13-LIPOXYGENASEs; AOS: ALLENE OXIDE SYNTHASE; AOC: ALLENE OXIDE CYCLASE; CTS: COMATOSE; 25 JAO: JMT: JASMONIC ACID OXIDASES; Figure 1.1. (cont’d) OPR3: OPDA REDUCTASE 3; OPCL: OPC-8:0 COA LIGASE; OPR2: OPDA REDUCTASE 2; JAR1: JASMONATE RESISTANT 1; JOX: JASMONATE-INDUCED OXYGENASES; JA CARBOXYL METHYLTRANSFERASE. 26 Figure 1.2. Connectivity between primary and specialized metabolism. Core metabolites (grey) in primary carbon metabolism (Calvin-Benson cycle, pentose phosphate pathway, glycolysis) are precursors for a variety of metabolic pathways (black boxes) that produce diverse primary (blue) and specialized (yellow) metabolites. Metabolic intermediates that are shared by primary and specialized metabolism illustrate potential for resource-based tradeoffs via competition between pathways. Defense-associated compounds in Arabidopsis include coumarins (e.g., scopoletin), cinnamate esters (e.g., sinapoyl malate), phenolamides (e.g., coumaroylagmatine), non-protein amino acids (NPAAs; e.g., Nδ-acetylornithine), alkaloids (e.g., camalexin), glucosinolates (e.g., 4-methylthiobutyl-glucosinolate), flavonols (e.g., kaempferol glycosides), anthocyanins (e.g., cyanidin glycosides), proanthocyanidins (e.g., epicatechin polymers), monoterpenes (e.g., (E)-β-ocimene), sesquiterpenes (e.g., (E)-β-caryophyllene), diterpenes (e.g., rhizathalene), and triterpenes (e.g., thalianol). Not shown is the derivation of the polyamine moiety of phenolamides from aliphatic amino acids. Glycosylation (upper right) of metabolites, including coumarins, cinnamate esters, glucosinolates, flavonoids and terpenoids, serves multiple roles in defense. Whereas most alkaloids are derived from amino acids, some are generated from other precursors such as purines, terpenes, and polyketides. E4P, erythrose-4- phosphate; PEP, phosphoenolpyruvate, GAP, glyceraldehyde 3-phosphate; TCA, tricarboxylic 27 Figure 1.2. (cont’d) acid; MVA, mevalonate; MEP, methylerythritol 4-phosphate; IPP, isopentenyl pyrophosphate; DMAPP, dimethylallyl pyrophosphate. 28 Figure 1.3. Signaling networks and phenotypic space associated with growth-defense conflict. (A) Possible mechanisms to explain how JA restricts leaf growth. (1) JA-induced defense responses reduce carbon availability by diverting resources to the production of secondary metabolites. Altered carbon status may be detected by energy-sensing systems to reduce growth rate to a level that matches carbon availability. (2) MYC transcription factors inhibit growth independently of JA-induced defense responses. In roots, for example, MYC2 decreases the activity of the root meristem by repressing the expression of AP2-domain PLETHORA (PLT) transcription factors. In leaves, MYCs repress the expression of photosynthesis genes and may also constrain growth through unidentified regulators that repress cell division or cell expansion. (3) Crosstalk between JA-Ile and GA signaling pathways modulates growth responses. JAZ degradation releases DELLA proteins, which negatively regulate PIF transcription factors to inhibit cell expansion-type growth. PIF transcription factors inhibit chlorophyll biosynthesis and stimulate auxin production as part of the shade avoidance growth response. Points of positive and negative regulation are indicated by arrows and perpendicular lines, respectively. Dashed lines denote connections for which there is little direct evidence. (B) Hypothetical relationship between growth and defense among individuals (grey circles) within a population. The dashed blue line denotes the so-called Pareto front (Shoval et al., 2012), which represents the most efficient allocations of resources to growth and defense within the physiological limits of the plant. Arrows denote evolutionary trajectories that give rise to 29 Figure 1.3. (cont’d) preferred genotypes that are closest to the Pareto front. Yellow arrows exemplify the hypothetical trajectory of a genotype having strong defense but less ability to compete in a given environment. Green arrows exemplify a hypothetical breeding selection for crop species having elevated growth (or yield) but less ability to defend; such tradeoffs are typically offset through the use of pesticides. (C) Illustration of phenotypic space in which growth-defense balance can be optimized by genetic manipulation of the JA-Ile and phytochrome B (phyB) signaling pathways. Circles denote individuals within a population that exhibit various allocations to growth and defensed in a given environment. In Arabidopsis, phyB (yellow) and jazQ (blue) mutations favor rapid cell extension-type growth (i.e., shade avoidance) and defense, respectively. jazQ phyB (green) “double” mutants perform both tasks well at the same time and may even outperform wild-type (WT) plants under certain growth conditions (Campos et al., 2016). Dashed arrows denote how the indicated mutations shift allocations between growth and defense. 30 Figure 1.4. Speculative model of an evolutionary trajectory for JA-inducible defense. The model proposes that JA-inducible defense evolved stepwise in response to selective pressure imposed by too little (e.g., susceptibility to biotic attackers) or too much (e.g., metabolic costs) defense. Initially, constitutive expression of neofunctionalized defense proteins or secondary metabolites derived from primary metabolism provided a low level of protection against plant consumers. Promoter mutations and recruitment of transcription factors (e.g., MYC2, green ovals) served to increase defense expression and plant fitness in environments where biotic aggressors were prevalent. In some conditions, the metabolic cost of heightened defense outweighed its benefit in a given environment (e.g., low frequency of biotic attack). In second step, selective pressure to reduce defense expression led to the recruitment of JAZ repressors (red octagon), perhaps from an ancestral TIFY protein, and associated NINJA-TOPLESS (TPL) co-repressors (pink rectangle). JAZ-mediated repression of MYC activity curtails the metabolic costs of high defense and, depending on the nature of the JAZ-MYC interaction, may promote growth at the expense of resistance in environments where biotic pressure was high or unpredictable. In a third major step, a JA-triggered ubiquitin-proteasome system emerged as a mechanism to degrade JAZ repressors and relieve repression on transcription factors. The F-box protein COI1 (blue oval) interacts with JAZ in the presence of JA-Ile (yellow star) to promote ubiquitination (yellow circles) and subsequent degradation of JAZ by the 26S proteasome. De- repression of defense gene expression in this manner could, under certain selective conditions, 31 Figure 1.4. (cont’d) incur other metabolic costs, including reduced carbon availability. In step 4 of this model, multiple mechanisms emerged to temporally and spatially restrain JA-regulated defense responses. Response termination includes catabolism of bioactive JA (yellow star to square), multiple mechanisms to increase the repressive activity of JAZ (red octagon), competitive inhibition by JAM transcription factors (red oval), and age-dependent decay of JA signaling. Dashed grey lines represent thresholds at which excessive metabolic costs and susceptibility to biotic aggressors impose selective pressure. CMID, cryptic MYC interaction domain. 32 REFERENCES 33 REFERENCES Aharoni, A., and Galili, G. (2011). Metabolic engineering of the plant primary-secondary metabolism interface. Curr Opin Biotech 22, 239-244. An, C., Li, L., Zhai, Q., You, Y., Deng, L., Wu, F., Chen, R., Jiang, H., Wang, H., Chen, Q., and Li, C. (2017). Mediator subunit MED25 links the jasmonate receptor to transcriptionally active chromatin. Proceedings of the National Academy of Sciences of the United States of America 114, E8930-E8939. 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Trade-Offs Between Plant Growth and Defense Against Insect Herbivory: An Emerging Mechanistic Synthesis. Annual Review of Plant Biology 68, 10.11-10.22. 45 CHAPTER TWO - JAZ REPRESSORS OF METABOLIC DEFENSE PROMOTE GROWTH AND REPRODUCTIVE FITNESS IN ARABIDOPSIS Work presented in this chapter has been published: Guo, Q., Yoshida, Y., Major, I.T., Wang, K., Sugimoto, K., Kapali, G., Havko, N.E., Benning, C., and Howe, G.A. (2018). JAZ repressors of metabolic defense promote growth and reproductive fitness in Arabidopsis. Proceedings of the National Academy of Sciences of the United States of America 115, E10768-E10777. 46 Abstract Plant immune responses mediated by the hormone jasmonoyl-L-isoleucine (JA-Ile) are metabolically costly and often linked to reduced growth. Although it is known that JA-Ile activates defense responses by triggering the degradation of JASMONATE ZIM DOMAIN (JAZ) transcriptional repressor proteins, expansion of the JAZ gene family in vascular plants has hampered efforts to understand how this hormone impacts growth and other physiological tasks over the course of ontogeny. Here, we combined mutations within the 13-member Arabidopsis JAZ gene family to investigate the effects of chronic JAZ deficiency on growth, defense, and reproductive output. A higher-order mutant (jaz decuple, jazD) defective in ten JAZ genes (JAZ1- 7, -9, -10, and -13) exhibited robust resistance to insect herbivores and fungal pathogens, which was accompanied by slow vegetative growth and poor reproductive performance. Metabolic phenotypes of jazD discerned from global transcript and protein profiling were indicative of elevated carbon partitioning to amino acid-, protein-, and endoplasmic reticulum body-based defenses controlled by the JA-Ile and ethylene branches of immunity. Resource allocation to a strong defense sink in jazD leaves was associated with increased respiration and hallmarks of carbon starvation but no overt changes in photosynthetic rate. Depletion of the remaining JAZ repressors in jazD further exaggerated growth stunting, nearly abolished seed production and, under extreme conditions, caused spreading necrotic lesions and tissue death. Our results demonstrate that JAZ proteins promote growth and reproductive success at least in part by preventing catastrophic metabolic effects of an unrestrained immune response. 47 Introduction As sessile organisms, plants continuously adjust their growth, development, and metabolism in response to environmental stress. Complex regulatory networks involving plant hormones play a central part in linking stress perception to transcriptional responses that permit acclimation to harsh environments (Pieterse et al., 2009; Santner et al., 2009). The lipid-derived hormone jasmonoyl- L-isoleucine (JA-Ile) and its metabolic precursors and derivatives, collectively known as jasmonates (JAs), perform a critical role in plant resilience to many environmental challenges (Wasternack and Hause, 2013; Howe et al., 2018). JAs are perhaps best known for orchestrating local and systemic immunity to organisms that exploit plants as a source of food and shelter (Campos et al., 2014). The hormone controls the expression of large sets of genes that specify a myriad of defense traits, including the biosynthesis of specialized metabolites that thwart attack by diverse organisms ranging from microbes to mammals (Howe and Jander, 2008; Wu and Baldwin, 2010; Chini et al., 2016). Interestingly, transcriptional responses triggered by JA-Ile also result in growth inhibition (Yan et al., 2007; Zhang and Turner, 2008; Attaran et al., 2014; Havko et al., 2016; Major et al., 2017; Bomer et al., 2018). The dual role of JA-Ile in promoting defense and restricting growth provides an attractive opportunity to better understand the antagonistic relationship between growth and immunity, with implications for improving crop productivity (Karasov et al., 2017; Zust and Agrawal, 2017). Many gaps remain, however, in understanding how defense hormones reconfigure metabolism within the constraints of available resources to achieve an optimal balance between immunity and other physiological tasks (Guo et al., 2018). In cells containing low JA-Ile levels, JASMONATE ZIM-DOMAIN (JAZ) proteins bind directly to and repress the activity of various transcription factors (TFs) (Chini et al., 2007; Thines et al., 2007; Yan et al., 2007). The most thoroughly studied JAZ-interacting TFs are MYC2 and 48 its closely related paralogs (Fernandez-Calvo et al., 2011; Kazan and Manners, 2013; Figueroa and Browse, 2015; Qi et al., 2015). JAZ proteins repress MYC activity by providing a scaffold on which to recruit corepressors such as NINJA and TOPLESS (Pauwels et al., 2010; Shyu et al., 2012), as well as by impeding the association of the coactivator protein MED25 with the transcription initiation complex (Katsir et al., 2008; Zhang et al., 2015; An et al., 2017). In addition to recruiting transcriptional repression complexes to the promoters of JA-responsive genes, JAZ proteins participate in the primary JA-Ile perception event leading to ubiquitin-dependent JAZ degradation. When intracellular levels of JA-Ile rise above a threshold concentration, the hormone promotes binding of JAZ to the F-box protein CORONATINE INSENSITIVE 1 (COI1), which is a component of the E3 ubiquitin ligase complex SCFCOI1 (Thines et al., 2007; Katsir et al., 2008; Yan et al., 2018). JAZ proteins tagged with polyubiquitin chains by SCFCOI1 are destined for proteolytic destruction by the 26S proteasome, thereby relieving repression on MYC activity. Genetic epistasis analyses in Arabidopsis are consistent with biochemical and structural studies showing that COI1 and JA-Ile comprise a functional module dedicated to JAZ degradation, and that JAZ depletion is sufficient to derepress the expression of target genes controlled by MYC and other TFs (Major et al., 2017). Positive regulators of the core JA-Ile signaling pathway in Arabidopsis, including MYC TFs and components (e.g., COI1) of the JAZ degradation machinery, have been thoroughly studied through characterization of the corresponding loss-of-function mutants (Browse, 2009). In contrast, an understanding of how JAZ proteins negatively regulate JA responses has been hindered by the multi-membered nature of JAZ gene families, which in Arabidopsis consists of 13 members (JAZ1-13) (Thireault et al., 2015; Chini et al., 2016; Howe et al., 2018). Although there is evidence that individual JAZ genes control JA responses in specific tissues and cell types 49 (Gimenez-Ibanez et al., 2017; Li et al., 2017), the absence of strong phenotypes in most jaz single mutants described to date suggests some degree of redundancy among JAZ family members (Thines et al., 2007; Campos et al., 2016; Chini et al., 2016; Gimenez-Ibanez et al., 2017). Analysis of Arabidopsis mutants defective in multiple JAZ genes supports this interpretation. For example, constitutive JA responses in a jaz quintuple (jazQ) mutant defective in JAZ1/3/4/9/10 are relatively mild in comparison to the effects of exogenous JA treatment, and are fully suppressed by mutations that block JA-Ile biosynthesis or perception (Campos et al., 2016; Major et al., 2017). Indeed, treatment of plants with methyl-JA (MeJA) and other precursors of JA-Ile has been used extensively to study short-term responses (hours to days) to the hormone. This approach, however, is limited in its ability to target specific JAZ proteins or the tissues in which they are expressed. Multiple negative feedback circuits involving JA-Ile catabolism and JAZ repressors that are recalcitrant to JA-Ile-mediated degradation further mask the full range of responses to the hormone (reviewed in (Howe et al., 2018)). These considerations provide a rationale for using extreme higher-order jaz mutants to investigate the physiological, metabolic, and developmental consequences of derepressing JA responses over the course of ontogeny. Here, we developed a series of higher-order jaz mutants with which to interrogate the effects of chronic overactivation of JA responses. Progressive mutation of JAZ genes was positively correlated with the strength of defense traits and inversely associated with growth and fertility. Detailed characterization of a jaz decuple (jazD) mutant defective in JAZ1/2/3/4/5/6/7/9/10/13 revealed constitutive activation of both JA and ethylene responses, leading to resistance to caterpillar feeding and infection by a necrotrophic fungal pathogen. Metabolic phenotypes of jazD were indicative of elevated carbon and sulfur partitioning to chemical defense traits controlled by the MYC and ethylene response factor (ERF) branches of 50 immunity. The strong defense sink in jazD leaves was also associated with increased cellular respiration and carbon starvation, but not reductions in photosynthetic rate. Introduction of a jaz8 mutation into the jazD background further exacerbated growth defects and nearly abolished seed production in the resulting jaz undecuple mutant. Similarly, elicitation of JA responses in the sensitized jazD background caused spreading necrotic lesions and tissue death. Collectively, our data indicate that JAZ proteins promote growth and reproductive success by attenuating the harmful metabolic effects of an unfettered JA response. 51 Results Reduced growth and fertility of a jaz decuple mutant is associated with extreme sensitivity to jasmonate We used insertion mutations to construct a series of higher-order jaz mutants with which to interrogate the biological consequences of chronic JAZ deficiency in Arabidopsis (Figure 2.1). The 13-member JAZ family in Arabidopsis is comprised of five phylogenetic groups (I-V) that are common to angiosperms (Figure 2.2A). The previously described jazQ mutant harbors mutations in the sole member (JAZ10) of group III, all three members of group V (JAZ3/4/9), and one member (JAZ1) of the largest group I clade. Building on the jazQ chassis, we used genetic crosses to introduce five additional mutations that target the remaining group I members (JAZ2/5/6) and two genes (JAZ7/13) within group IV (Figure 2.2). The resulting homozygous jaz1/2/3/4/5/6/7/9/10/13 decuple mutant, referred to hereafter as jazD, thus targets all JAZs except for JAZ8 and the two group II genes (JAZ11 and JAZ12). Cultivation of plants in the absence of exogenous JA showed that whereas jazQ roots and leaves grow more slowly than wild-type (WT) Col-0, growth of jazD was even slower than jazQ (Figure 2.3A and 2.3B). Soil-grown jazD plants displayed less leaf area and shorter petioles than jazQ, and also accumulated more anthocyanins (Figure 2.3B mock and 2.5). Leaf biomass measurements taken over a 20-d time course confirmed that the relative growth rate (RGR) of jazD rosettes during this developmental stage was significantly less than WT (Figure 2.3C). That the RGR of jazQ was comparable to WT, despite the reduced biomass of jazQ rosettes at later times in development, may reflect growth changes occurring prior to the first time point of sampling (11 d after sowing) or the lack of statistical power needed to resolve small differences in RGR that are compounded over time into larger differences in rosette size. Although bulk protein, lipid, and cell 52 wall content of rosette leaves was similar between all three genotypes under our growth conditions, the ratio of leaf dry weight to fresh weight was increased in jazD relative to WT and jazQ (Figure 2.6). The restricted growth of jazD roots and leaves was associated with changes in flowering time under long-day growth conditions. jazD plants were delayed in their time to flowering compared to jazQ but contained a comparable number of leaves at the time of bolting (Figure 2.5). We next compared the response of jazQ and jazD mutants to exogenous JA. Root growth assays showed that the extent of JAZ deficiency (jazD > jazQ > WT) inversely correlated with root length under a range of MeJA concentrations, with growth of jazD roots effectively arrested in the presence of 5 μM MeJA (Figure 2.3A and 2.4). Shoot responsiveness to the hormone was assessed by treating intact leaves with coronatine (COR), which is a potent agonist of the JA-Ile receptor (Katsir et al., 2008). WT and jazQ leaves showed visible accumulation of anthocyanin pigments at the site of COR application (i.e., midvein) within four days of the treatment with no apparent signs of chlorosis (Figure 2.3B). In contrast, jazD leaves exhibited visible chlorosis at the site of COR application within 2 d of treatment and, strikingly, near complete loss of chlorophyll and spreading of necrosis-like symptoms throughout the leaf 4 d after treatment, leading to tissue death (Figure 2.3B). These data indicate that progressive loss of JAZ genes in jazQ and jazD results in both quantitative (e.g., root growth inhibition) and qualitative (e.g., COR-induced tissue necrosis) differences in JA responsiveness, and are consistent with the notion that the hypersensitivity of jazD results, at least in part, from loss of JAZ-mediated negative feedback control of JA responses. Measurements of reproductive output showed that whereas the total seed yield of jazQ was only marginally affected, seed production by jazD plumented to about one-third of WT levels (Table 2.1). The reduced fecundity of jazD resulted from a combination of decreased average mass 53 per seed and lower total seed number per plant; mutant plants produced fewer seeds per silique, and the size and number of siliques per plant were reduced as well (Table 2.1). The reduced size of jazD seeds correlated with a reduction in total fatty acid per seed (Figure 2.3D). Analysis of seed fatty acid profiles showed that jazQ and jazD seeds contain less oleic acid (18:1) and more linoleic acid (18:2) (Figure 2.7), suggesting alterations in fatty acid metabolism during seed development. The effect of jazD on seed size and lipid abundance was associated with reduced rates of seed germination (Figure 2.3E). These findings indicate that constitutive JA responses resulting from JAZ depletion are associated with poor reproductive performance. Constitutive activation of jasmonate- and ethylene-mediated defense pathways in jazD plants Having established the effects of jazQ and jazD on growth and reproduction, we next assessed how these mutations impact JA-mediated signaling pathways for defense. Similar to results obtained with long day-grown plants, jaz-mediated leaf growth restriction was observed under short-day conditions (Figure 2.8A), which we used to promote leaf biomass and delay flowering in plants used for insect bioassays. In tests performed with the generalist herbivore Trichoplusia ni we found that the strength of host resistance to insect feeding positively correlated with the severity of jaz mutation (jazD > jazQ > WT), consistent with a role for JAZs in the negative regulation of defense (Figure 2.8A and 2.8B). Messenger RNA sequencing (RNA-seq) was used to investigate the molecular basis of the enhanced anti-insect resistance. Global transcript profiles revealed that the total number of differentially expressed genes in jazD leaves (relative to WT) was more than 10-fold greater than that in jazQ (2,107 and 186 for jazD and jazQ, respectively) (Figure 2.9). Among the 186 genes whose expression was statistically different in the jazQ vs. WT comparison, the majority (59%) of 54 these were also differentially expressed in jazD. Gene Ontology (GO) analysis of 1,290 genes expressed to higher levels in jazD than WT showed that “response to JA/wounding”, as well as “defense response”, were among the biological processes most statistically overrepresented in this comparison (Figure 2.9). These results, together with analysis of metabolic pathways that are differentially activated in jaz mutants (see below), indicate that the strength of anti-insect resistance correlates with the extent of JAZ deficiency and concomitant reprogramming of gene expression. Analysis of the RNA-seq data also revealed that ethylene-response genes were highly expressed in jazD but not jazQ. In particular, anti-fungal defense genes controlled by the synergistic action of JA and ethylene were modestly repressed in jazQ but highly induced in jazD (Figure 2.8C). Among these were genes encoding the AP2/ethylene-response factors (ERFs) ERF1 and ORA59, which integrate JA and ethylene signals to promote the expression of antimicrobial compounds, including various defensins (PDFs), pathogenesis-related (PR) proteins, and hydroxycinnamic acid amides (HCAAs) (Figure 2.8C) (Berrocal-Lobo et al., 2002; Pre et al., 2008; Li et al., 2018). Strikingly, several PDF transcripts (e.g., PDF1.2) were among the most abundant of all mRNAs in jazD leaves, with expression levels comparable to that of the most highly expressed photosynthesis transcripts. In agreement with the RNA-seq data, jazQ plants were slightly more susceptible than WT to the necrotrophic pathogen Botrytis cinerea, whereas jazD leaves were more resistant to the spread of disease lesions (Figure 2.8D and 2.8E). To determine whether jazQ and jazD differentially affect other ethylene responses, we assessed apical hook formation in ethylene-elicited seedlings. Consistent with studies showing that apical hook formation is attenuated by JA signaling (Song et al., 2014), we found that stimulation of hook curvature in response to treatment with the ethylene precursor 1-aminocyclopropane-1-carboxylic 55 acid (ACC) was reduced in jazD but not jazQ seedlings (Figure 2.8F). These data indicate that whereas jazQ moderately activates JA responses and increases resistance to insect feeding, jazD strongly induces both the JA and ethylene branches of immunity to confer robust resistance to insect feeding and infection by B. cinerea. To validate the RNA-seq results and gain additional insight how jazD promotes leaf defense, we used quantitative tandem mass spectrometry to quantify global changes in protein abundance in jazD vs. WT in leaves. Amongst a total of 4,850 unique proteins identified in both genotypes, 149 and 120 proteins accumulated to higher and lower levels, respectively, in jazD (threshold fold change > 1.2, P < 0.05). GO analysis of the 120 downregulated proteins revealed enrichment of functional categories related to cytokinin response, cold response, and various functional domains of photosynthesis (Table 2.2). Analysis of proteins that were more abundant in jazD showed there was good agreement with the corresponding mRNA levels determined by RNA-seq; transcripts encoding 78% of these 149 proteins were also induced in jazD plants. As expected, there was strong enrichment in this protein set of GO categories associated with response to JA, herbivore and fungal attack, among other defense-related processes (Table 2.2). For example, the proteomic analysis revealed that jazD coordinately upregulated the abundance of most JA biosynthetic enzymes, as well as canonical JA marker proteins such as VSP1 and VSP2 (Figure 2.10). jazD leaves exhibited high expression of an agmatine coumaroyltransferase (At5g61160) and associated transporter (At3g23550) involved in the production of anti-fungal HCAAs (Muroi et al., 2009; Dobritzsch et al., 2016). Transcripts encoding the acyl-CoA N- acyltransferase NATA1 (At2g39030), which catalyzes the formation of the defense compound N(δ)-acetylornithine (Adio et al., 2011), were 50-fold higher in jazD leaves compared to WT and jazQ and were accompanied by increased NATA1 protein abundance. Perhaps most striking was 56 the coordinate upregulation in jazD leaves, at both the mRNA and protein levels, of most known structural and enzymatic components of the endoplasmic reticulum (ER)-derived ER body (Figure 2.11), which is implicated in induced immunity (Yamada et al., 2011; Nakano et al., 2017). These findings establish a central role for JAZ proteins as negative regulators of diverse leaf defense traits. Reprogramming of primary and specialized metabolism in jazD plants To investigate how the activation of multiple defense pathways influences primary metabolism, we used the RNA-seq and proteomics data to infer metabolic pathways that are altered in jazD leaves. Mapping of differentially expressed genes to KEGG pathway databases showed that the tricarboxylic acid (TCA) cycle, oxidative pentose phosphate pathway (OPP), sulfur assimilation and metabolism, and various amino acid biosynthetic pathways were among the processes most highly induced in jazD, whereas photosynthesis components were generally downregulated (Figure 2.12). One prominent example of a metabolic pathway that was upregulated in jazD was the shikimate pathway for the biosynthesis of aromatic amino acids. Trp biosynthetic enzymes involved in the production of indole glucosinolates (IGs) showed particularly high expression at the mRNA and protein levels (Figure 2.12B). Consistent with this finding, genes encoding enzymes in the phosphoserine pathway that supplies Ser for the biosynthesis of Trp and Cys (Benstein et al., 2013) were highly upregulated in jazD, as was the abundance of the corresponding enzymes as determined from proteomics data (Figure 2.12B and 2.9). LC-MS analysis of leaf extracts showed that several IGs accumulate to high levels in jazD (Figure 2.12C and 2.13), thereby validating the omics data. In agreement with previous studies employing JA elicitation (Sasaki- 57 Sekimoto et al., 2005; Kruse et al., 2007; Yatusevich et al., 2010), we also found that pathways involved in sulfur assimilation and cysteine biosynthesis, as well as ascorbate and glutathione metabolic pathways that protect against oxidative stress, were strongly upregulated in jazD (Figure 2.12B and 2.14). These data indicate that genetic depletion of JAZ proteins recapitulates the transcriptional effects of exogenous JA, and demonstrate that JAZ proteins exert control over pathways that operate at the interface of primary and specialized metabolism. We next addressed the question of whether jazD modulates net carbon assimilation. Despite the downregulation of photosynthetic mRNAs and proteins in jazD, modeling of photosynthetic parameters derived from gas exchange data indicated that the leaf area-based photosynthetic rate of jazD plants was comparable to WT (Figure 2.12D, 2.15A and 2.15B). This finding was confirmed by 13C isotope discrimination measurements, which showed that the degree of CO2 resistance through mesophyll cells was similar in WT, jazQ, and jazD leaves (Figure 2.15C and 2.15D). In contrast to photosynthesis, the net loss of CO2 from jazD leaves in the dark exceeded that of WT by ~50% (Figure 2.12E). Increased cellular respiration in jazD was confirmed by experiments showing that the mutant had increased respiration in both the day and night portions of the photoperiod (Figure 15E and 2.15F). These findings are consistent with the notion that increased cellular respiration is associated with high-level production of defense compounds (Bolton, 2009). GO analysis of the 817 downregulated genes in jazD leaves showed enrichment for growth-related processes, including ‘response to light stimulus’, ‘cell wall organization’, ‘response to abiotic stimulus’, ‘carbohydrate biosynthetic process’, and ‘lipid biosynthetic process’ (Figure 2.9). 58 jazD plants exhibit symptoms of carbon starvation Increased respiration and partitioning of carbon to metabolic defense pathways, in the absence of compensatory changes in photosynthesis, raised the possibility that jazD plants have a carbon deficit. Time-course studies showed that the rates of starch accumulation (WT: 0.103 μmol Glc g- 1 DW h-1; jazD: 0.113 μmol Glc g-1 DW h-1) and degradation (WT: -0.220 g-1 DW h-1; jazD: -0.186 μmol Glc g-1 DW h-1) were comparable between WT and jazD (Figure 2.16A). However, starch levels in jazD leaves were slightly lower than WT at all times of the diel cycle except at the end of the night, when starch was mostly depleted but modestly elevated in jazD relative to WT. jazD leaves also had consistently lower sucrose levels (Figure 2.16B). We also found that genes involved in starch and sucrose metabolism were generally downregulated in jazD, including the mRNA and protein abundance of the plastidic starch biosynthetic enzyme phosphoglucomutase (PGM1, At5g51820). To test whether these changes in central metabolism are associated with carbon deficit, we used the RNA-seq data to query the expression of genes that are induced by conditions (e.g., prolonged darkness) leading to carbon starvation. We found that 42 of 278 (15%) sugar starvation marker (SSM) genes defined by (Baena-Gonzalez et al., 2007), including several DARK INDUCIBLE (DIN) genes that respond to reduced energy status (Fujiki et al., 2001), were expressed to much higher levels in jazD than WT and jazQ (Figure 2.16C). We also examined the expression of EIN3-regulated glutamate dehydrogenases (GDH) that replenish 2-oxoglutarate for the TCA cycle and are considered metabolic markers of carbon deficiency (Miyashita and Good, 2008; Gibon et al., 2009; Tsai et al., 2016). Both the transcript and protein abundance of GDH1 (At5g181700) and GDH2 (At5g07440) were statistically increased in jazD in comparison to WT, consistent with a carbon deficit in this mutant. 59 To test the hypothesis that carbon limitation contributes to the slow growth of jaz mutants, we compared the growth of WT, jazQ, and jazD seedlings on agar medium supplemented with sucrose. The data showed that although exogenous sucrose promotes increased biomass in all genotypes tested, the stimulatory effect on the growth of jazD shoots was statistically greater than that of WT and jazQ (Figure 2.16D and 2.16E). Exogenous sucrose also enhanced the root growth of jazD in comparison to WT and jazQ (Figure 2.16F). Control experiments with sorbitol showed that the growth-promoting effect of sucrose was not attributed to changes in osmotic strength of the growth medium (Figure 2.17). These data provide evidence that the reduced growth of jazD but not jazQ results in part from a limitation in carbon supply. A jaz1/2/3/4/5/6/7/8/9/10/13 undecuple mutant produces few viable seeds The ability of jazD plants to perceive and respond to exogenous JA suggested that the remaining JAZ proteins in the mutant can actively repress JA-responsive genes. We hypothesized that mutation of these remaining JAZ loci (i.e., JAZ8, JAZ11, and JAZ12) in the jazD background may further enhance the level of growth-defense antagonism. To test this, we focused on JAZ8 because of its established role in repressing JA responses (Shyu et al., 2012) and the availability of a naturally occurring jaz8 null allele (Thireault et al., 2015). Moreover, the increased expression of JAZ8 in jazD leaves (> 15-fold relative to WT) (Figure 2.10) was consistent with a role in negative feedback control of JA responses. Screening of progeny derived from genetic crosses between jazD and jaz8 resulted in the identification of an undecuple mutant (jazU) homozygous for mutations in JAZ1/2/3/4/5/6/7/8/9/10/13 (Figure 2.18A). Root growth assays showed that jazU roots were even shorter than jazD in the presence of very low concentrations (e.g., < 1 μM) of MeJA (Figure 2.19A). When grown on JA-free medium, jazU showed an even stronger 60 constitutive short-root phenotype than jazD (Figure 2.19A). Similarly, the rosette morphology of jazU confirmed the progressive effect of JAZ depletion on restriction of rosette growth, including reduced biomass, leaf area, and petiole length (Figure 2.19B and 2.18B-D). Most strikingly, jazU plants exhibited near complete loss of viable seed production (Figure 2.19C). We estimated that less than 3% of jazU flowers set fruit; although jazU pollen was viable in crosses, among flowers that produced fruit, most senesced and aborted during silique filling (Figure 2.18E). Among the few jazU flowers that did produce seeds, seed set per silique was severely reduced, with recovery of only a few viable seeds per plant (Figure 2.18F-H). The collective seed-yield phenotypes of jazQ, jazD, and jazU strongly support a key role for JAZ proteins in promoting reproductive vigor. 61 Discussion A major objective of this study was to employ higher-order jaz mutants as novel tools to achieve a deeper understanding of JA responses throughout the plant life cycle. Our data show that moderate and severe JAZ deficiency in jazQ and jazD, respectively, recapitulates many of the effects of exogenous JA on growth, defense, and metabolism. Comparison of leaf transcriptomes revealed that the degree of JAZ depletion correlated both with the extent of transcriptional reprogramming and the strength of growth-defense antagonism. The complexity of growth- and immune-related phenotypes in higher-order jaz mutant is thus consistent with the capacity of JAZ proteins to directly control the activity of diverse TFs (Howe et al., 2018). Based on current annotations of the Arabidopsis TF repertoire (Jin et al., 2017), we identified 218 (147 up- and 71 downregulated) and 20 (11 up and 9 downregulated) TF-encoding genes that are differentially expressed in jazD and jazQ, respectively. These findings support a general model in which JAZ proteins reside at the apex of a transcriptional hierarchy that promotes defense and simultaneously inhibits growth (Chini et al., 2016; Howe et al., 2018). jaz loss-of-function mutations may also indirectly influence gene expression through changes in the expression of TF-encoding genes that promote subsequent waves of transcription or compensatory responses. A future challenge will be to link specific phenotypes of jaz mutants to defined JAZ-TF regulatory modules that exert temporal and spatial control over JA responses (Gimenez-Ibanez et al., 2017; Li et al., 2017; Major et al., 2017). A significant finding of our work was that jazQ and jazD mutants show not only quantitative variation in JA-related phenotypes but also qualitative differences in select defense traits. This is exemplified by the observation that jazD constitutively activates the ethylene branch of immune signaling to increase resistance to B. cinerea, whereas jazQ moderately inhibits 62 ethylene-dependent defense responses to this pathogen. The elevated JA/ethylene-dependent resistance of jazD is consistent with the ability of some JAZ proteins to repress the activity of two master regulators of ethylene signaling, EIN3 and EIL1, which in turn activate the expression of TFs (e.g., ERF1) that mediate resistance to necrotrophic pathogens (Solano et al., 1998; Berrocal- Lobo et al., 2002; Pre et al., 2008; Zhu et al., 2011; Muller and Munne-Bosch, 2015). Thus, although jazQ moderately relieves repression on MYC TFs to enhance resistance to insect feeding, this combination of jaz mutations (jaz1/3/4/9/10) may be insufficient to derepress EIN3/EIL1. In this scenario, antagonistic interactions between the MYC2 and ERF1 branches of JA signaling (Lorenzo et al., 2004) would explain the increased susceptibility of jazQ to B. cinerea. By contrast, we propose that the severe JAZ deficiency in jazD simultaneously derepresses both the MYC2 and EIN3/EIL1 branches to confer strong resistance to chewing insects and necrotrophic pathogens. Given that EIN3 physically interacts with MYC2 to inhibit JA-regulated defense against insect herbivores (Song et al., 2014), robust activation of insect and fungal pathogen defenses in jazD suggests that MYC2-EIN3/EIL1 antagonism may require certain JAZ proteins to control the balance between transcriptional repression and activation (Howe et al., 2018). The distinct biotic stress phenotypes of jazQ and jazD may reflect a larger pool of JAZs in jazQ, or may be attributed specifically to one or more JAZ proteins (i.e., JAZ2/5/6/7/13) present in jazQ but absent in jazD. Complementation of jazD with wild-type JAZ genes may help to address this hypothesis. It is noteworthy that many phenotypes of jazD, including high expression of PDF genes and enhanced resistance to both caterpillar feeding and pathogen infection, are also observed in mutants defective in JA catabolism (Caarls et al., 2017; Smirnova et al., 2017). These findings suggest that changes in JA homeostasis may deplete JAZ abundance to phenocopy the effects of jaz mutants. 63 JAZ depletion in higher-order jaz mutants may propagate changes in protein-protein interaction networks that shape the diversity of JA responses and hormone crosstalk (Howe et al., 2018). The strong induction of IG biosynthesis in jazD is consistent with the role of MYC-MYB heterodimers in JA-mediated activation of IG biosynthetic genes (Gigolashvili et al., 2007; Schweizer et al., 2013), such that genetic depletion of JAZ favors MYC-MYB interaction. A similar argument applies to the role of JAZ-DELLA interactions in the control of growth-defense balance; JAZ depletion could restrict growth through increased DELLA activity and attenuation of gibberellin-mediated responses (Hou et al., 2010; Yang et al., 2012; Machado et al., 2017). It remains to be determined whether changes in DELLA abundance or other components of the gibberellin pathway contribute to the reduced growth of higher-order jaz mutants. In fact, the critical role of MYC2/3/4 in restricting leaf growth and biomass in jazQ (Major et al., 2017) suggests that these TFs contribute to the growth phenotype of jazD. Other potential factors contributing to the reduced growth rate of jazD include downregulation of genes involved in cell wall organization (Bomer et al., 2018), and perturbation in auxin levels resulting from altered Trp metabolism. Lifetime viable seed production is a reliable measure of the cost of defense. Consistent with studies showing that induced defense responses in the absence of herbivore pressure curtail seed production (Agrawal, 1998; Baldwin, 1998), we found that jazQ, jazD and jazU mutants have weak, moderate, and severe negative effects on seed production, respectively. It therefore appears that either too little (e.g., coi1 mutation) or too much (e.g., jazU mutation) JA response can lead to reproductive failure, albeit for different physiological reasons. Similarly, the reduction in seed size and quality in higher-order jaz mutants is consistent with the increased seed size in JA-deficient mutants (Farmer and Dubugnon, 2009). These findings suggest that unrestrained JA responses 64 give rise to tradeoffs in which increased partitioning of resources to defense in source tissues reduces nutrient availability in sink tissues. It has been shown, for example, that carbon starvation in leaves has direct negative effects on seed development and quality in Arabidopsis (Smith and Stitt, 2007). In demonstrating a critical role for JAZ proteins in promoting reproductive performance, our results provide a fitness-based explanation for the emergence of multi-tiered mechanisms to restrain JA responses, with implications for understanding the evolution of JA signaling systems (Karasov et al., 2017; Howe et al., 2018). Several features of higher-order jaz mutants, including constitutive production of defense compounds, slow growth, and reduced fecundity, are indicative of hyperactive immunity (Bomblies and Weigel, 2007). These effects were exaggerated under conditions designed to further deplete JAZ in the sensitized jazD background, either by treatment with exogenous hormone or addition of jaz8 mutation. The necrosis of COR-treated jazD leaves provides strong evidence that JAZ proteins protect against JA-mediated cell death resulting from a runaway immune response. Although the underlying cause of tissue necrosis remains to be determined, we note that JAs have long been known to promote senescence-like symptoms and to elicit the production of ROS (Ueda and Kato, 1980; Orozco-Cardenas et al., 2001; Shan et al., 2011; Qi et al., 2015). Moreover, silencing of the JAZh paralog in Nicotiana attenuata caused spontaneous necrosis at late stages of leaf development, which was associated with increased ROS production (Oh et al., 2012). It is possible that the growth inhibitory and senescence-like symptoms of jaz mutants reflects autotoxicity of defense compounds, as recently proposed for IGs in Arabidopsis (Chen et al., 2017). The emerging link between IG production and ER body formation (Nakano et al., 2017), coupled with our discovery that JAZ proteins suppress the expression of both IGs and ER body components, provides the impetus for future studies aimed at understanding how JA coordinates 65 the proliferation of specialized organelles with defense metabolism. The striking diversity of chemical defense pathways expressed in jazD indicates that jaz mutants, potentially from any plant species, may be useful tools for discovery of novel anti-microbial and anti-insect defense compounds. Our analysis of the effects of chronic JAZ deficiency provides new insights into how vegetative growth rate is coordinated with changes in primary and specialized metabolism. In general, our data support the acclimatory response hypothesis to explain how plant growth rate is modulated in response to changes in the supply and demand for assimilated carbon (Smith and Stitt, 2007; Guo et al., 2018). Several independent lines of evidence indicate that partitioning of resources to a strong defense sink in jazD leaves is associated with carbon starvation and downward adjustment of growth rate. First, the expression of genes and protein markers of carbon starvation were upregulated in jazD leaves. Consistent with the concept of resource allocation costs, exogenous sucrose partially restored the growth of jazD leaves and roots. Second, the area- based respiration rate of jazD leaves was increased without a corresponding change in photosynthetic rate, potentially contributing to an energy deficit. Third, the sucrose and starch content in jazD leaves was modestly depleted throughout most times of the diel cycle, consistent with studies showing that JA elicitation reduces photoassimilate levels (Machado et al., 2013). Given that the rates of starch synthesis and degradation were similar in jazD and WT leaves, it appears that the control mechanisms underlying the precise pacing of starch reserves (Smith and Stitt, 2007; Sulpice et al., 2014) are largely operational under conditions where JA signaling strongly diverts carbon to defense. These findings sugest that JAZ proteins flexibly adjust growth- defense balance to match anticipated changes in resource availability, thereby avoiding the detrimental effects of hyperimmunity. 66 In summary, our results demonstrate that JA-triggered immunity imposes major metabolic demands which, if not properly restrained, are detrimental to plant fitness. In environments where assimilated carbon, nitrogen, water, and other essential nutrients may be limiting, the bioenergetic and biosynthetic demands associated with increased defense must be tightly coordinated with other physiological tasks. We propose that JAZ proteins assist in balancing the growth-defense continuum not as a binary on-off switch but rather by matching the biotic stress level to available resources. In particular, our results indicate that growth and reproductive penalties of immunity become evident only at high levels of defense; a condition that is buffered by multiple negative feedback mechanisms. The intermediate level of anti-insect defense exhibited by jazQ does not appear to impose major allocation costs under laboratory growth conditions (Campos et al., 2016). Rather, the level of growth restriction exhibited by jazQ may reflect other adaptive roles of growth- defense antagonism. Downward adjustment of growth may, for example, provide a mechanism to concentrate defense compounds in affected tissues, promote cross resilience to potential future stress by reserving resources, or optimize the timing of vegetative-to-reproductive transition (Havko et al., 2016; Guo et al., 2018; Wang et al., 2018). In contrast to jazQ, severe JAZ depletion in jazD activates transcriptional programs that dictate much stronger allocation of central metabolites to defense, with significant negative effects on growth and reproduction. A high energetic expense associated with synthesis of defense proteins, provision of amino acid precursors and biosynthetic enzymes, transport, and storage of defense compounds in jazD is supported by hallmarks of carbon starvation. The diversion of resources to defense in jazD likely extends beyond carbon to other facets of intermediary metabolism. The induced production of defensins and other sulfur-rich defense compounds, for example, provides a plausible explanation for upregulation of enzymes involved sulfate assimilation and the biosynthesis of glutathione cysteine, consistent with 67 the importance of sulfur metabolism in plant defense (Sasaki-Sekimoto et al., 2005; Kruse et al., 2007; Yatusevich et al., 2010). A challenge for future studies will be to elucidate the mechanisms by which the status of carbon and other nutrients is sensed and adjusted during growth-to-defense transitions. 68 Methods Plant material and growth conditions The Columbia accession (Col-0) of A. thaliana was used as wild type for all experiments. jazD was constructed by crossing jazQ (Campos et al., 2016) to other transfer DNA (T-DNA) or transposon insertion mutants obtained from the Arabidopsis Biological Research Center (ABRC; Ohio State University). The following jaz single mutants were combined with jazQ as described in Figs. S1 and S14 and were named as follows: jaz2-3 (RIKEN_13-5433-1) (Gimenez-Ibanez et al., 2017), jaz5-1 (SALK_053775) (Thines et al., 2007), jaz6-4 (CSHL_ET30) (this study), jaz7-1 (WiscDsLox7H11) (Thines et al., 2007), jaz8-V (Thireault et al., 2015), and jaz13-1 (GK_193G07) (Thireault et al., 2015). Additional details on jaz single mutants and the breeding scheme used to obtain jazD are provided in Table 2.3 and Figure 2.1, respectively. Efforts were made to reduce chromosomal contributions from other accessions by testing multiple SSLP polymorphic markers over many generations, so that the majority of jazD genome is expected to be derived from Col-0 (1) (Figure 2.1). Following sowing of seeds in soil, potted plants were covered with a transparent plastic dome for 10 days. Soil-grown plants were maintained under a 16-h light (100 μE m-2 s-1) and 8-h dark photoperiod at 20 ºC unless otherwise noted. Immediately after seed harvest, small seeds were eliminated by passing bulk seed through a brass sieve with a 250 μm pore size. Seeds retained after sieving (referred to as “sieved seeds”) were dried for two weeks in 1.5 mL Eppendorf tubes containing Drierite desiccant. PCR analysis PCR-based genotyping of jazD and lower-order mutants was performed using primer sets flanking DNA insertion sites and a third primer recognizing the T-DNA border (Table 2.4). PCR reactions 69 were performed with the following condition: 95 ºC for 5 min, followed by 35 cycles of denaturation (30 s at 95 ºC), annealing (30 s at 56 ºC) and elongation (1.5 min at 72 ºC). Final elongation step was performed at 72 ºC for 10 min and completed reactions were maintained at 12 ºC. jaz8-V was distinguished from wild-type JAZ8 amplicons by digestion with AflII (New England Biolabs). The presence or absence of full-length JAZ transcripts in Col-0, jazQ, and jazD plants was determined by reverse transcription (RT) PCR. RNA was extracted from rosette leaves of soil-grown plants using an RNeasy kit (Qiagen). cDNA was reverse transcribed with a High- Capacity cDNA Reverse Transcription kit (Applied Biosystems, ABI). RT-PCR reactions were performed with primer sets designed to amplify target JAZ genes and the internal control ACTIN1 (At2g37620) by GoTaq Green Master Mix (Promega). Primer sets and additional details of the RT-PCR procedures are provided in Table 2.5. Growth measurements For relative growth rate (RGR) analysis, five plants per genotype were harvested every two days beginning and ending 11 and 29 days, respectively, after seed sowing. Excised shoots were lyophilized for determination of dry weight. RGR was calculated from the slope of the log(dry weight) over the duration of the time course (Hummel et al., 2010). Leaf area of 23-day-old plants was determined by photographing rosettes from the top with a Nikon D80 camera. The resulting images were used to measure projected leaf area with GIMP software (http://www.gimp.org). Root elongation assays Seeds were surface sterilized with 50% (v/v) bleach for three min, washed 10 times with sterile water and stratified in dark at 4 ºC for two days. Seedlings were grown on 0.7% (w/v) agar media 70 containing half-strength Linsmaier and Skoog (LS; Caisson Labs) salts supplemented with 0.8% (w/v) sucrose and the indicated concentration of MeJA (Sigma-Aldrich). Each square Petri plate (Fisher; 100 x 100 x 15 mm) contained five seedlings per genotype. Plates were incubated vertically in a growth chamber maintained at 21 ºC for eight days under 16-h-light (80 μE m-2 s- 1)/8-h-dark conditions. The length of primary roots was measured using ImageJ software (https://imagej.nih.gov/ij/). Coronatine treatment The eighth true leaf of 40-day-old plants grown under 12-h-light/12-h-dark conditions were spotted with 5 µL of sterile water (mock) or a solution containing 50 µM coronatine (Sigma- Aldrich, C8115) prepared in sterile water. Photographs were taken two and four days after treatment. Insect and pathogen assays Insect feeding assays were performed at 20 ºC under a short-day photoperiod of 8-h light and 16- h dark. Neonate Trichoplusia ni larvae (Benzon Research) were transferred to fully expanded rosette leaves of 9-week-old plants. Four larvae were reared on each of 12 plants for approximately 12 days, after which larval weights were measured (Herde et al., 2013). Botrytis cinerea bioassays were performed as described previously (Rowe and Kliebenstein, 2007), with minor modifications. Detached leaves from 10-week-old short-day-grown (8 h light/16 h dark) plants were placed in Petri dishes containing filter paper moistened with 10 mL sterile water, with petioles submerged in the water. Each leaflet was inoculated with a single 4 µL droplet of Botrytis cinerea spore suspension (5,000 spores/mL in 50% organic grape juice). Petri dishes were sealed with Micropore 71 surgical tape (3M Health Care) and kept under the same conditions used for plant growth. Photographs were taken after five days and lesion area was measured using the ImageJ software (https://imagej.nih.gov/ij/). Seed yield measurements Individual plants were grown in 6.5-cm square pots. An inverted plastic cone and plastic tube (Arasystem 360 kit; Arasystem) were fitted to each plant 23 days after seed sowing to collect all seeds from dehiscing siliques. Seeds collected from individual plants were harvested and dried with Drierite desiccant for two weeks, after which total seed mass per plant was measured. Average seed mass was determined by weighing dry seeds in batches of 200 (Jofuku et al., 2005). For each plant, the weights of three sample batches were measured and averaged. The silique length and number of seeds per silique were measured by sampling the fully-elongated seventh, ninth and eleventh siliques on the main stem (Roux et al., 2004). Germination assays Germination assays were performed on half-strength LS agar plates without sucrose. Unsieved seeds were surface sterilized and stratified in dark at 4 ºC for two days. Plates were incubated vertically under continuous light at 21 ºC and germination was scored daily for seven days by radicle emergence from the seed coat (Dekkers et al., 2004). RNA-seq analysis Global gene expression profiling was performed on the Illumina HiSeq 2000 platform at the Michigan State University Research Technologies Service Facility (https://rtsf.natsci.msu.edu/). 72 Rosettes of 23-day-old soil-grown Col-0, jazQ, and jazD plants were harvested for RNA extraction 6 h after the beginning of the light period. Three independent RNA samples (biological replicates) were used for each genotype, with each replicate derived from pooling rosette leaves from 20 plants. Raw sequencing reads were filtered with Illumina quality control tool FASTX-Toolkit (http://hannonlab.cshl.edu/fastx_toolkit/) and then mapped to TAIR10 gene models by RSEM (version 1.2.25) (Li and Dewey, 2011). mRNA abundances for all Arabidopsis genes were expressed as transcripts per million (TPM). DESeq2 (version 3.3) (Anders and Huber, 2010) was used to normalize expected counts from RSEM and to determine differential gene expression by comparing normalized counts in Col-0 to those in mutants. DAVID (version 6.8) (Huang et al., 2009) and MapMan (version 3.6.0) (Thimm et al., 2004) was used to perform gene ontology (GO) analysis of enriched functional categories. Over- and underrepresented GO categories among differentially expressed genes were assessed by hypergeometric test with Benjamini & Hochberg’s false discovery rate (FDR) correction at P < 0.05. Analysis of the induction or repression of metabolic pathways was performed by Kyoto Encyclopedia of Genes and Genomes (KEGG) Mapper (http://www.genome.jp/kegg/pathway.html) (Kanehisa and Goto, 2000). Data deposition: RNA sequencing data from this study have been deposited in the Gene Expression Omnibus (GEO) database, https://www.ncbi.nlm.nih.gov/geo (accession no. GSE116681). Quantitative proteomic analysis Quantitative proteomic analysis was performed with proteins extracted from leaf tissue of 23-day- old soil-grown Col-0 and jazD plants. Proteins from three biological replicates (20 plants/replicate) of each genotype were extracted with the following extraction buffer: 100 mM Tris-HCl (pH 6.8), 150 mM NaCl, 10% glycerol (v/v), 4% SDS (w/v), 200 mM DTT, and protease inhibitor (Sigma- 73 Aldrich, 1 tablet/10 mL buffer). Protein concentrations were determined by Bradford assay. Trypsin-digested peptides derived from these proteins were derivatized with a tandem mass tag (TMT) labeling kit (ThermoFisher) for quantification by mass spectrometry (MS) performed at the Michigan State University Proteomics Core Facility (https://rtsf.natsci.msu.edu/proteomics/). Briefly, protein samples were digested with trypsin using the Filter-Aided Sample Preparation (FASP) protocol according to Wisniewski et al. (Wisniewski et al., 2009). Samples were then labeled with TMTsixple Isobaric Label Reagents (ThermoFisher) according to manufacturer’s protocol. After labeling, all six samples were combined and dried by vacuum centrifugation. The combined peptide samples were separated over a pH gradient (pH 3-10) into six fractions using an Agilent OffGel 3100 fractionator (www.agilent.com) according to manufacturer’s protocol. Dried fractions were washed and eluted. Eluted peptides were sprayed into a ThermoFisher Q-Exactive mass spectrometer (www.thermo.com) using a FlexSpray nano-spray ion source. Survey scans were taken in the Orbitrap (70,000 resolution, determined at m/z 200) and the top ten ions in each survey scan were then subjected to automatic higher energy collision induced dissociation (HCD) with fragment spectra acquired at 35,000 resolution. Conversion of MS/MS spectra to peak lists and quantitation of TMT reporter ions was done using Proteome Discover, v1.4.1.14. Peptide-to- spectrum matching was performed with the Sequest HT and Mascot search algorithms against the TAIR10 protein sequence database appended with common laboratory contaminants (downloaded from www.arabidopsis.org and www.thegpm.org, respectively). The output from both search algorithms was then combined and analyzed using Scaffold Q+S (version 4.5.3) to probabilistically validate protein identifications and quantification. Assignments validated using the Scaffold 1% FDR confidence filter were considered true. 74 Gas exchange measurements and 13C discrimination analysis Plants grown under short-day photoperiod (8 h light/16 h dark) in ‘Cone-tainers’ (Steuwe and Sons, Tangent, OR, USA) were used for gas exchange analysis. The measurements were performed on LI-6400XT and LI-6800 systems (LI-COR Biosciences, Lincoln, NE, USA) as previously described (Campos et al., 2016). Daytime respiration was determined from slope-intercept regression analysis of the common intersection of five CO2 response curves (using intercellular CO2 below 10 Pa) measured at decreasing, sub-saturating irradiances (Walker and Ort, 2015). Leaf tissue was freeze-dried and used for the measurement of the ratio of 13CO2 to 12CO2 by mass spectrometry at the Stable Isotope Ratio Facility for Environmental Research, University of Utah (Salt Lake City, UT). Isotopic ratios and CO2 partial pressure at Rubisco were calculated as described (Farquhar et al., 1982; Farquhar et al., 1989; Weraduwagel et al., 2015). Protein, lipid and cell wall measurements For protein, lipid and cell wall measurements, leaf tissue was harvested from 23-day-old plants grown under our standard long-day conditions. Excised shoots were lyophilized to determine the dry weight. Total protein was extracted using a Plant Total Protein Extraction Kit (PE0230, Sigma- Aldrich) and quantified by Bradford assay. Lipid extraction, thin-layer chromatography (TLC) of polar and neutral lipids, transesterification, and gas chromatography were performed as described previously (Wang and Benning, 2011; Wang et al., 2018). For polar lipids, lipid separation was performed by activated ammonium sulfate-impregnated silica gel TLC plates (TLC Silica gel 60, EMD Chemical) with a solvent consisting of acetone, toluene, and water (91:30:7.5 by volume). Lipids were visualized by brief exposure to iodine vapor on TLC plates. Acyl groups of the isolated lipids were then converted to methyl esters, which were subsequently quantified by a gas 75 chromatography. Cell wall was extracted with a solution containing 70% ethanol, chloroform/methanol solution (1:1 v/v) and acetone as described (Foster et al., 2010). Starch was removed from the extracts using amylase and pullulanase (Sigma-Aldrich). Protein, lipid and cell wall content was normalized to leaf dry weight. Glucosinolate measurements Plants were grown under long-day conditions (16-h day and 8-h night) for 23 days. Rosette leaves were harvested and frozen in liquid nitrogen immediately. Two plants were pooled for each sample, with three biological replicates collected per sample. Frozen tissue was homogenized with a TissueLyser II (Qiagen) and glucosinolates were extracted following published procedures (Glauser et al., 2012), with minor modifications. Briefly, 80% methanol (v/v) was added to homogenized tissues and the mixture was vortexed for 5 min. Extracts were then centrifuged at 16,000 x g for 5 min and the supernatant was transferred to a 2-mL glass vial (RESTEK). Samples were analyzed in the MSU Mass Spectrometry Facility by ultrahigh pressure liquid chromatography (UPLC) coupled to quadrupole time-of-flight mass spectrometry (QTOFMS) using Waters Xevo G2-XS. Data analysis and processing were performed as described previously (Glauser et al., 2012). Sucrose rescue assays The effect of exogenous sucrose on leaf biomass and root growth was determined by growing seedlings on square Petri plates (Greiner Bio-One; 120 x 120 x 17 mm). In order to control for variation in seed quality, seeds were sieved after drying with desiccant for two weeks (see above). After sterilization and washing, seeds were sown without stratification on 0.7% (w/v) agar media 76 containing half-strength LS salts supplemented with sucrose or sorbitol. Each plate contained ten (for biomass) or five (for root growth) seeds of Col-0 and mutant lines. Plates were placed in dark at 4 ºC for four days and then incubated horizontally (for leaf biomass) or vertically (for root growth) in growth chambers maintained at 21 ºC under 16 h at a light intensity of 80 μE m-2 s-1 and 8 h dark. ImageJ was used to measure root length after 11 days. Plant biomass and projected leaf area were measured after 16 days. 77 APPENDIX 78 Tables and figures Table 2.1. Seed and fruit production in jazQ and jazD plants. Genotype Seed yield per Average seed Silique No. seed per No. silique plant1 (mg) mass2 (μg) length3 (cm) silique4 per plant5 Col-0 608.3 ± 103.8 21.6 ± 1.3 1.59 ± 0.07 63 ± 11 451 ± 77 jazQ 524.3 ± 98.5 17.3 ± 0.9* 1.70 ± 0.06 58 ± 6 533 ± 100 jazD 192.7 ± 70.0* 16.6 ± 0.7* 1.45 ± 0.08* 37 ± 4* 329 ± 119* Data show the mean ± SD of at least ten plants per genotype. Asterisks denote significant difference when compared to Col-0 plants according to Tukey’s HSD test (P < 0.05). 1Seed yield was determined by collecting all seeds from individual plants and drying seeds with Drierite desiccant for two weeks prior to weighing. 2Average seed mass was determined by weighing batches of 200 seeds. 3,4,5Fully elongated 7th, 9th, and 11th siliques were collected for measurements of silique traits. 79 Table 2.2. Biological processes in which proteins whose abundance in jazD leaves was increased or decreased in comparison to wild-type Col-0 based on gene ontology (GO) analysis. Upregulated in jazD GO ID GO description P value 0009695 jasmonic acid biosynthetic process < 0.0001 0055114 oxidation-reduction process 0009611 response to wounding 0009651 response to salt stress 0009753 response to jasmonic acid < 0.0001 < 0.0001 < 0.0001 < 0.0001 0008652 cellular amino acid biosynthetic process < 0.0001 0000162 tryptophan biosynthetic process < 0.0001 0050832 defense response to fungus < 0.0001 0006952 defense response 0019762 glucosinolate catabolic process 0006564 serine biosynthetic process 0080027 response to herbivore 0009414 response to water deprivation Downregulated in jazD GO ID GO description 0009735 response to cytokinin 0015979 photosynthesis 0009409 response to cold 0010207 photosystem II assembly 0019684 photosynthesis, light reaction 80 0.0002 0.0010 0.0113 0.0226 0.0336 P value < 0.0001 < 0.0001 < 0.0001 0.0001 0.0079 Table 2.2. (cont’d) 0042549 photosystem II stabilization 0042742 defense response to bacterium 0.0239 0.0257 Enriched functional categories were determined with DAVID (version 6.8) using the hypergeometric test with Benjamini & Hochberg’s false discovery rate (FDR) correction. 81 Table 2.3. Mutants used for construction of jazD and jazU. Mutant Original name Source Accession Mutagen Resistance1 jaz1-2 SM_3.22668 JIC SM Col-0 dSpm transposon jaz2-3 RIKEN_13- 5433-1 RIKEN No-0 Ds transposon jaz3-4 GK-097F09 GABI Kat Col-0 jaz4-1 SALK_141628 SALK Col-0 T-DNA (pAC161) T-DNA (pROK2) jaz5-1 SALK_053775 SALK Col-0 T-DNA (pROK2) Basta (confirmed) Hygromycin (confirmed) Sulfadiazine (confirmed) Kanamycin (silenced) Kanamycin (confirmed) jaz6-4 CSHL_ET30 CSHL Ler jaz7-1 WiscDsLox7H11 Wisconsin Col-0 Ds transposon (Enhancer trap GUS) Kanamycin (confirmed) T-DNA (pWiscDsLox) Basta (not tested) jaz8-V2 N/A ABRC Vash-1 SNP N/A jaz9-4 GK_265H05 GABI Kat Col-0 jaz10-1 SAIL_92_D08 SAIL Col-0 jaz13-1 GK_193G07 GABI Kat Col-0 T-DNA (pAC161) T-DNA (pCSA110) T-DNA (pAC161) Sulfadiazine (confirmed) Basta (confirmed) GUS Sulfadiazine (not tested) 1Resistance of the mutant line to the indicated selectable marker was tested and confirmed. 2The C-to-A nonsense mutation present in JAZ8 from accession Vash-1 was backcrossed four times to Col-0 to generate a line (#28-6-30) that was used for subsequent genetic crosses (Thireault et al., 2015). N/A, not applicable. 82 Table 2.4. Primers used for genotyping. Gene Locus Primer Sequence (5’-3’) JAZ1 AT1G19180 JAZ1_F ACCGAGACACATTCCCGATT JAZ1_R CATCAGGCTTGCATGCCATT JAZ1_border ACGAATAAGAGCGTCCATTTTAGAG JAZ2 AT1G74950 JAZ2_F TCTTCCTCGTGACAAAACGCA JAZ2_R CCAAACACAGAACCATCTCCACA JAZ2_border CCGGATCGTATCGGTTTTCG JAZ3 AT3G17860 JAZ3_F ACGGTTCCTCTATGCCTCAAGTC JAZ3_R GTGGAGTGGTCTAAAGCAACCTTC JAZ3_border ATAACGCTGCGGACATCTACATT JAZ4 AT1G48500 JAZ4_F TCAGGAAGACAGAGTGTTCCC JAZ4_R TGCGTTTCTCTAAGAACCGAG JAZ4_border TTGGGTGATGGTTCACGTAG JAZ5 AT1G17380 JAZ5_F GCTTATACCGAAAACCCGATTCCAG JAZ5_R GGCTCATTGAGATCAGGAAGAACCA JAZ5_border TTGGGTGATGGTTCACGTAG JAZ6 AT1G72450 JAZ6_F GACACACATCACTGTCACTTC JAZ6_R AGTTTCTGAGGTCTCTACCTTC JAZ6_border CCGTTTTGTATATCCCGTTTCCGT 83 Table 2.4. (cont’d) JAZ7 AT2G34600 JAZ7_F ATGCGACTTGGAACTTCGCC JAZ7_R GGAGGATCCGAACCGTCTG JAZ7_border ACGTCCGCAATGTGTTATTA JAZ8 AT1G30135 JAZ8_F TGTCCTAAGAGTCCGCCGTTGT JAZ8_R TTTGGAGGATCCGACCCGTTTG JAZ9 AT1G70700 JAZ9_F TACCGCATAATCATGGTCGTC JAZ9_R TCATGCTCATTGCATTAGTCG JAZ9_border CTTTGAAGACGTGGTTGGAACG JAZ10 AT5G13220 JAZ10_F ATTTCTCGATCGCCGTCGTAGT-3 JAZ10_R GCCAAAGAGCTTTGGTCTTAGAGTG JAZ10_border GTCTAAGCGTCAATTTGTTTACACC JAZ13 AT3G22275 JAZ13_F GCACGTGACCAAATTTGCAGA JAZ13_R TGAAGAGAGGAGGATGATGAGGA JAZ13_border AAACCTCCTCGGATTCCATTGC 84 Table 2.5. Primers used for RT-PCR. Gene Locus Primer Sequence (5’-3’) Annealing (ºC) PCR cycles JAZ1 AT1G19180 JAZ1_RT_F JAZ1_RT_R JAZ2 AT1G74950 JAZ2_RT_F JAZ2_RT_R JAZ3 AT3G17860 JAZ3_RT_F JAZ3_RT_R ATGTCGAGTTCTAT GGAATG 52 TCATATTTCAGCTGC TAAAC ATGTCGAGTTTTTCT GCCGA 52 TTACCGTGAACTGA GCCAAG ATGGAGAGAGATTT TCTCGGG 52 TTAGGTTGCAGAGC TGAGAGAAG JAZ4 AT1G48500 JAZ4_RT_F ATGGAGAGAGATTT TCTCGGGCTGG 64.7 JAZ4_RT_R JAZ5 AT1G17380 JAZ5_RT_F JAZ5_RT_R JAZ6 AT1G72450 JAZ6_RT_F JAZ6_RT_R JAZ7 AT2G34600 JAZ7_RT_F JAZ7_RT_R JAZ9 AT1G70700 JAZ9_RT_F JAZ9_RT_R TTAGTGCAGATGAT GAGCTGGAGGA ATGTCGTCGAGCAA TGAAAA 54 CTATAGCCTTAGAT CGAGAT ATGTCAACGGGACA AGCGC 54 CTAAAGCTTGAGTT CAAGGT ATGATCATCATCAT CAAAAACTG 58 CTATCGGTAACGGT GGTAAG ATGGAAAGAGATTT TCTGGG 52 TTATGTAGGAGAAG TAGAAG 85 30 30 30 40 35 35 40 40 Table 2.5. (cont’d) JAZ10 AT5G13220 JAZ10_RT_F ATGTCGAAAGCTAC 52 CATAGAAC JAZ10_RT_R GATAGTAAGGAGAT GTTGATACTAATCTC T JAZ13 AT3G22275 JAZ13_RT_F ATGAAGGGTTGCAG 56 CTTAGA JAZ13_RT_R TTAGAAATTATGAA ACTIN1 AT2G37620 Actin1_F Actin1_R GAGAGGAGG ATGGCTGATGGTGA AGACATTCAA 67.2 TCAGAAGCACTTCC TGTGAACAAT 40 35 40 86 Figure 2.1. jazD pedigree. 87 Figure 2.1. (cont’d) Red ‘x’ and red ‘self’ indicate cross-pollination and self-pollination, respectively. jaz single mutants in blue shade have been reported previously or are newly characterized in this study (see Table S2 and Methods section). jaz2-1, jaz3-3, jaz9-1 were previously characterized (Chini et al., 2007; Thines et al., 2007) and jaz6-Wisc was characterized by the authors, but jaz2-3, jaz3-4, jaz6-4 and jaz9-4 were later selected as alternative alleles for construction of jazD. gl1-2 was included to study trichome development (Yoshida et al., 2009). Male sterility of coi1-1 mutants was exploited to assist in selection of rare recombination events between closely linked loci (Barth and Jander, 2006). 88 Figure 2.2. Reverse transcription-PCR analysis of mutated JAZ genes in jazD. 89 Figure 2.2. (cont’d) (A) Phylogenetic tree of 13 JAZ proteins in Arabidopsis. Blue and red asterisks denote JAZ genes that contain insertion mutations in jazQ and jazD, respectively. (B) Schematic diagrams of insertion mutations used for construction of jazQ and jazD. White and grey boxes represent untranslated regions (UTRs) and exons, respectively. The identity and position of each insertion mutation is shown. Red arrows show the position of primers used to assess expression of JAZ genes by RT-PCR. (C) RT-PCR analysis of expression of JAZ genes in wild-type Col-0 (WT), jazQ, and jazD. RNA was extracted from rosette leaves of 23-day-old plants grown under long-day conditions. The ACTIN1 gene (At2g37620) was used as a positive control. Red arrows denote PCR products that have the predicted size of full-length JAZ transcripts. 90 Figure 2.3. A jaz decuple mutant (jazD) is highly sensitive to jasmonate and exhibits reduced growth and fertility. (A) Root length of 8-d-old WT Col-0 (WT), jazQ, and jazD seedlings grown in the presence of 0, 5, or 25 μM MeJA. Data show the mean ± SD of 30 plants per genotype at each concentration. Capital letters denote significant differences according to Tukey’s honest significant difference (HSD) test (P < 0.05). (B) jazD leaves are hypersensitive to COR. The eighth leaf of 40-d-old plants grown under 12-h light/12-h dark photoperiod was treated with 5 μL water (mock) or 50 μM COR. Leaves were excised and photographed after 2 or 4 d of treatment. Arrows denote location of visible anthocyanin accumulation at the site of COR application. Inset, Right is enlargement of photograph of the COR-treated jazD. (Scale bars, 1 cm.) (C) RGR of soil-grownWT, jazQ, and jazD plants. (D) Total fatty acid content in seeds from the indicated genotype. Data show the mean ± SD of seeds obtained from five plants per genotype. (E) Time course of seed germination. Colored bars indicate the percentage of germinated seeds at various times after sowing on water agar: white, day 1; gray, day 2; black, day 3 and all later times; red, nongerminated seeds. 91 Figure 2.4. Root growth inhibition in response to MeJA treatment. The photographs show representative 8-day-old seedlings of the indicated genotype grown on 1/2 LS medium supplemented with 0, 5, or 25 μM MeJA. 92 Figure 2.5. Vegetative growth and reproductive phenotypes of jazD plants. (A) and (B) Rosette dry weight (A) and projected leaf area (B) was determined for 23-day-old soil- grown plants. Data show the mean ± SD of five plants per genotype. Capitalized letters denote significant differences according to Tukey’s HSD test (P < 0.05). (C) Petiole length of the third true leaf of 21-day-old soil-grown plants. Data show the mean ± SD of ten plants per genotype. (D) Anthocyanin levels in leaves of 23-day-old plants. Data show the mean ± SD of five rosettes per genotype. (E) and (F) The number of days to bolting (E) and opening of the first flower (F). Data show the mean ± SD of at least 18 plants per genotype. (G) The number of rosette leaves at the time bolting. Data show the mean ± SD of at least 18 plants per genotype. 93 Figure 2.6. Bulk cell wall, protein, lipid, and dry mass content in higher-order jaz mutants. (A-D) Rosette leaf tissue from 23-day-old plants of the indicated genotype was assessed for bulk cell wall (A), protein (B), lipid (C), and dry mass (D, as a ratio of dry weight to fresh weight) content. Data show the mean ± SD of five replicates per genotype. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). 94 Figure 2.7. Fatty acid composition of seeds. Values depict the relative abundance of major fatty acids in wild-type Col-0 (WT), jazQ, and jazD seeds. Asterisks denote significant differences in comparison to Col-0 seeds according to Tukey’s HSD test (P < 0.05). 95 Figure 2.8. jazD plants are highly resistant to insect herbivores and necrotrophic pathogens. (A) Representative short-day grown WT Col-0 (WT), jazQ, and jazD plants before and after challenge with four T. ni larvae for 12 d. (Scale bar: 3 cm.) (B) Weight gain of T. ni larvae reared on plants shown in A. Data show the mean ± SD of at least 30 larvae per genotype. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). (C) Heat map displaying the expression level of various jasmonate/ethylene-responsive genes in leaves of jazQ and jazD normalized to WT. ACT, agmatine coumaroyltransferase (At5g61160). (D) Representative leaf symptoms following 5 d treatment with B. cinerea spores or mock solution. (Scale bars: 2 cm.) (E) Disease lesion size on leaves of the indicated genotype. Data show the mean ± SD of at least 19 leaves per genotype. Capital letters denote significant differences (Tukey’s HSD test, P < 0.05). (F) Apical hook angle of seedlings grown in the presence of various concentrations of the ethylene precursor ACC. Data show the mean ± SD of at least 21 seedlings per genotype. Asterisks denote significant difference compared with WT (Tukey’s HSD test, P < 0.05). 96 Figure 2.9. Differential regulation in jazD of genes involved in growth, defense, and metabolism. 97 Figure 2.9. (cont’d) (A) and (B) The Venn diagrams show the numbers of differentially expressed genes in jazQ and jazD leaves based on analysis of RNA-seq data (threshold > 1.5 fold change and Benjamini-Hochberg corrected P value < 0.05). Gene ontology (GO) analysis (biological processes) was performed with genes that were either upregulated (A) and downregulated (B) in jazD leaves relative to Col-0. Enriched functional categories were determined with DAVID (version 6.8) using the hypergeometric test with Benjamini & Hochberg’s false discovery rate (FDR) correction. 98 Figure 2.10. Upregulation of jasmonate pathway components in jazD. Heat maps (left and middle) depict the expression level of select transcripts involved in JA biosynthesis, catabolism, and response. Transcript levels in jazQ and jazD were derived from RNA-seq data and are presented as fold-change (Log2) over wild-type Col-0 plants. Heat map on right depicts the abundance of the corresponding protein in jazD. Protein levels were determined by quantitative proteomic analysis and are presented as fold-change (Log2) over Col-0 plants. The indicated P value shows the statistical significance of the difference in protein levels between jazD and Col-0, evaluated using Permutation & Benjamini-Hochberg tests. ND, not detected in proteomic analysis. 99 Figure 2.11. Upregulation of ER body and indole glucosinolate defenses in jazD. 100 Figure 2.11. (cont’d) Heat maps (left and middle) depict the expression level of transcripts involved in endoplasmic reticulum (ER) body formation, aliphatic and indole glucosinolate metabolism, and select pathogen defense responses. Transcript levels in jazQ and jazD were derived from RNA-seq data and are presented as fold-change (Log2) over Col-0 plants. Heat map on right shows the abundance of the corresponding protein in jazD. Protein levels were determined by quantitative proteomic analysis and are presented as fold-change (Log2) over Col-0. The indicated P value shows the statistical significance of the difference in protein levels between jazD and Col-0, evaluated using Permutation & Benjamini-Hochberg tests. ND, not detected in proteomic analysis. 101 Figure 2.12. Reconfiguration of primary and secondary metabolism in jazD. (A) Mapping of differentially regulated genes in jazD to various metabolic pathways implicates elevated production of defense metabolites derived from amino acids. Mapped pathways include photosynthesis (Campos et al., 2016), pentose phosphate pathway (Gimenez-Ibanez et al., 2017), shikimate pathway (Thines et al., 2007), amino acids from pentose phosphate intermediates (Thireault et al., 2015), glycolysis (Hummel et al., 2010), amino acids from glycolysis 102 of tryptophan -2 -1 s from erythrose 4-phosphate biosynthesis Figure 2.12. (cont’d). intermediates (Herde et al., 2013), TCA cycle (Rowe and Kliebenstein, 2007), amino acids from TCA intermediates (Jofuku et al., 2005), sulfur metabolism (Roux et al., 2004), and defense metabolites from amino acids (Dekkers et al., 2004). Colored arrows denote the average foldchange of differentially expressed transcripts mapping to a particular pathway (P < 0.05). (B) Schematic (E4P), phosphoenolpyruvate (PEP), and 3-phosphoglycerate (3PG) illustrates up-regulation of genes and proteins in jazD. Each arrow represents an enzymatic reaction in the pathway. Boxes represent individual genes, colored by fold-change of jazD relative to WT according to RNA-seq data, whereas gray boxes denote genes with no significant change in expression. Gene names within boxes denote significantly increased protein levels according to proteomics data. Gene abbreviations: AnPRT, anthranilate phosphoribosyltransferase; AS, anthranilate synthase; CS, chorismate synthase; DHQS, 3-dehydroquinate synthase; DHS, 3-deoxy-7-phosphoheptulonate synthase; DQD/SDH, 3-dehydroquinate dehydratase/shikimate dehydrogenase; EPSP, 5- enolpyruvylshikimate-3-phosphate synthase; IGPS, indole-3-glycerol-phosphate synthase; IGs, indole glucosinolates; OAS, O-acetylserine lyase; PAI, phosphoribosylanthranilate isomerase; PGDH, phosphoglycerate dehydrogenase; PSAT, phosphoserine aminotransferase; PSP, phosphoserine phosphatase; SAT, serine acetyltransferase; SK, shikimate kinase; TSA, tryptophan synthase alpha subunit; TSB, tryptophan synthase β-subunit. (C) Indole glucosinolate levels in jazD leaves relative to that in WT leaves. Asterisks denote significant differences in comparison with WT (Student’s t test, P < 0.05). Abbreviations: (neoglucobrassicin); 4MOI3M, 4-methoxyindol-3- 1MOI3M, 1-methoxyindol-3-ylmethyl ylmethyl (glucobrassicin); OHI3M, 4- hydroxyindol-3-ylmethyl (hydroxyglucobrassicin). (D) and (E) Net gas exchange rate in WT and jazD rosette leaves measured at 400 μmol CO2 and 20 °C after acclimation in 500 μmol m (methoxyglucobrassicin); in light (D) or dark (E). I3M, indol-3-ylmethyl 103 Figure 2.13. Glucosinolate accumulation is elevated in jazD leaves. Glucosinolates were extracted from leaf tissue of 26-day-old jazD and Col-0 (WT) plants and measured by LC-MS. Peak area for the indicated glucosinolate compound in the WT sample was set to “1” and the peak area of the same compound in jazD was normalized to the WT sample. Asterisks denote significant difference in comparison to WT plants according to the Student’s t- test (P < 0.05). Abbreviations: 3MSOP, 3-methylsulphinylpropyl (glucoiberin); 4MSOB, 4- methylsulphinylbutyl (glucoraphanin); 5MSOP, 5-methylsulphinylpentyl (glucoalyssin); 6MSOH, 6-methylsulphinylhexyl (glucohesperin); 7MSOH, 7-methylsulphinylheptyl (glucoibarin); 3MTP, 3-methylthiopropyl (glucoiberverin); 8MSOO, 8-methylsulphinyloctyl (glucohirsutin); 4MTB, 4- methylthiobutyl (glucoerucin); I3M, indol-3-ylmethyl (glucobrassicin); OH-I3M, 4-hydroxyindol- 3-ylmethyl (hydroxyglucobrassicin); 5MTP, 5-methylthiopentyl (glucoberteroin); 2PE, 2- phenylethyl (gluconasturtiin); 4MOI3M, 4-methoxyindol-3-ylmethyl (methoxyglucobrassicin); 1MOI3M, 1-methoxyindol-3-ylmethyl (neoglucobrassicin); 7MTH, 7-methylthioheptyl. 104 Figure 2.14. Comparison of jazD “omics” data to jasmonate-responsive genes (JRGs) described by Sasaki-Sekimoto et al. (Sasaki-Sekimoto et al., 2005). 105 Figure 2.14. (cont’d) Authors of this previous study identified 46 JRGs differentially regulated by exogenous MeJA [38 upregulated genes and 8 downregulated genes (denoted by asterisks)]. These genes (Locus) were classified by Sasaki-Sekimoto et al. into the following functional categories using AraCyc as a tool for visualizing Arabidopsis biochemical pathways: I, jasmonic acid biosynthesis; II, tryptophan biosynthesis; III, indole glucosinolate biosynthesis; IV, serine biosynthesis; V, sulfur assimilation; VI, cysteine biosynthesis; VII, gluthathione biosynthesis; VIII, ascorbate biosynthesis; IX, ascorbate recycling; and X, not classified. The depicted heat maps (left and middle) show the expression level of these genes in jazQ and jazD as determined by our RNA- seq data and are presented as fold-change (Log2) over Col-0 plants. Heat map on right shows the abundance of the corresponding protein in jazD. Protein levels were determined by quantitative proteomic analysis and are presented as fold-change (Log2) over Col-0 plants. The indicated P value shows the statistical significance of the difference in protein levels between jazD and Col-0, evaluated using Permutation & Benjamini-Hochberg tests. ND, not detected in proteomic analysis. 106 Figure 2.15. jaz mutations increase respiration but do not affect resistance to CO2 diffusion through leaf mesophyll. (A) and (B) Nonlinear curve-fitting to model the maximum velocity of Rubisco (A) and the rate of photosynthetic electron transport (B) from photosynthetic rates in response to increasing CO2. Data show the mean ± SD of six replicates per genotype. (C) Comparison of the 13 C to 12 C isotopic ratio of leaf samples to the 13 12 13 C isotopic ratio of CVPDB (‰)) in wild-type Col-0 (WT), jazQ, C to the Vienna-Pee-Dee Belemnite (VPDB) standard (δ and jazD plants. (D) Comparison of CO2 partial pressure at Rubisco in WT, jazQ, and jazD plants. Data show the mean ± SD of five replicates per genotype. Capital letters denote the lack of significant differences according to Tukey’s HSD test (P < 0.05). (E) and (F) Daytime respiration (E) and nighttime dark respiration (F) on a leaf area basis. Daytime respiration was determined from the intersection of CO2 response curves measured at sub- saturating light intensities. Data show the mean ± SD of four replicates per genotype. 107 Figure 2.16. jazD plants exhibit symptoms of carbon starvation. (A) and (B) Time course of starch (A) and sucrose (B) levels in WT Col-0 (WT) and jazD plants during long-day photoperiod (16-h-light/8-h-dark). Leaf tissues of soil-grown plants were harvested after 23 days. Asterisks denote significant differences in comparison with WT (Student’s t test, P < 0.05). (C) Heat map showing the expression level of SSM genes in jazQ and jazD leaves. Gene- expression levels determined by RNA-seq are represented as fold-change (log2) over WT. (D) and (E) Photograph (D) and DW (E) of 16-d-old WT, jazQ, and jazD seedlings grown horizontally on MS medium containing the indicated concentration of sucrose. (Scale bar: D, 0.5 cm.) (F) Root length of 11-d-old WT, jazQ, and jazD seedlings grown vertically on MS medium lacking sucrose (open bar) or containing 23 mM sucrose (filled bar). Two-way ANOVA was used to test the effect of sucrose on growth (E and F) and showed that, whereas genotype (P < 0.001 for both WT vs. jazQ and WT vs. jazD) and sucrose (P < 0.001 for both WT vs. jazQ and WT vs. jazD) 108 Figure 2.16. (cont’d) significantly affect shoot and root growth, the genotype × sucrose interaction was significant only for jazD comparisons. 109 Figure 2.17. Sorbitol does not promote biomass accumulation or root elongation in jaz mutants. (A) Dry weight of 16-day-old wild-type Col-0 (WT), jazQ, and jazD seedlings grown horizontally on solid MS medium containing or not containing 23 mM sorbitol. (B) Root length of 11-day-old seedlings grown vertically on solid LS medium containing or not containing 23 mM sorbitol. Data show the mean ± SD of 80 seedlings per genotype. 110 Figure 2.18. Vegetative growth and reproductive phenotypes of jazU plants. 111 Figure 2.18. (cont’d) (A) jazU pedigree. Pedigree notations are as described in Fig. S1. Briefly, an introgressed jaz8-V mutant was crossed into the jazD background. Because the undecuple jazU mutant showed near sterility, jazU was maintained as a line segregating for the genetically linked jaz5 jaz1 mutations. (B-D) Rosette fresh weight (B), projected leaf area (C), and petiole length (third true leaf) (D) were determined for 28-day-old soil-grown plants. Data show the mean ± SD of eight plants per genotype. Capitalized letters denote significant differences according to Tukey’s HSD test (P < 0.05). (E) and (F) Photograph of inflorescence apices (E) and seeds (F) of wild-type Col-0 (WT), jazD, and jazU. Flower bud clusters are smaller in jaz mutants and after opening, most jazU flowers yellow and senesce without setting fruits (E). Many jazU seeds are not fully filled, consistent with silique abortion and senescence (F). Bars are 2 mm (E) and 0.5 mm (F). (G) Number of seeds per silique for WT, jazD, and jazU. Seeds were counted from each of 100 siliques from 10 plants per genotype. (H) Time course of seed germination. Colored bars indicate the percentage of germinated seeds at various times after sowing on water agar: white, day 1; grey, day 2; black, day 3 and all later times; red, non-germinated seeds. 112 Figure 2.19. Genetic combination of jaz8 and jazD further restricts growth and nearly abolishes seed production in the resulting undecuple mutant. 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Annual review of plant biology 68, 10.11-10.22. 123 CHAPTER THREE - MYC TRANSCRIPTION FACTORS PLAY OVERLAPPING AND DISTINCT ROLES IN REGULATING GROWTH-DEFENSE TRADEOFFS IN ARABIDOPSIS Contributions: The jazD myc mutants (jazD myc2, jazD myc3, jazD myc4, jazD myc23, jazD myc24, jazD myc34, and jazD myc234) utilized in this chapter were developed by Dr. Ian T. Major and George Kapali. Dr. Ian T. Major performed respiration measurements. 124 Abstract Innate immune responses triggered by the plant hormone jasmonate (JA) are often accompanied by constrained growth. MYC2 and two closely related proteins, MYC3 and MYC4, are among the best characterized transcription factors (TFs) involved in executing JA-mediated growth and defense responses. However, an understanding of the specific contributions of MYC2/3/4 in growth and defense processes remains unclear. Here, we combined a jaz decuple mutant (jaz1 jaz2 jaz3 jaz4 jaz5 jaz6 jaz7 jaz9 jaz10 jaz13; jazD) with myc single (myc2, myc3, and myc4), double (myc23, myc24, and myc34) and triple (myc234) mutants to investigate the overlapping and distinct impacts of MYC2/3/4 on plant growth, defense, and metabolism. We demonstrate that simultaneous loss of MYC2/3/4 completely or partially abolishes constitutive JA signaling phenotypes of jazD, including hypersensitivity to JA, growth stunting, and decreased fecundity. Among the three MYCs, MYC2 was the most prominent regulator of jazD sensitivity to JA, whereas MYC2 and MYC3 played essential roles in restricting biomass accumulation. Comparison of jazD and jazD myc mutants showed that the enhanced resistance of jazD to insect herbivores and necrotrophic pathogens require MYC TFs, and MYC3 was primarily responsible for the resistance of jazD to necrotrophic pathogens. The heightened defense of jazD was associated with overaccumulation of an endoplasmic reticulum (ER)-derived structure called the ER body, which contains a myriad of β-glucosidases that exhibit myrosinase activity. Further analysis showed that the biogenesis of ER bodies is dependent on MYC TFs, with MYC2 and MYC3 having a main role. In demonstrating that MYC TFs are a major target of the JAZ- repressible transcriptional hierarchy, our study establishes a central role for MYC TFs in the control of growth-defense balance. 125 Introduction Plants continuously integrate stress and other environmental cues to tailor their growth, development and metabolism. Coordination of plant responses to stress signals is largely dependent on the biosynthesis and action of various hormones (Pieterse et al., 2009; Santner et al., 2009). Among the hormones that control plant protection against biotic challengers is jasmonate (JA), a member of the larger group of oxylipin compounds derived from oxygenated lipids (Wasternack and Hause, 2013; Howe et al., 2018). The bioactive form JA, jasmonoyl-L-isoleucine (JA-Ile), controls transcriptional programs that modulate diverse chemical and morphological defense traits (Howe and Jander, 2008; Wu and Baldwin, 2010; Campos et al., 2014). JA-Ile- induced transcriptional reprogramming also retards plant growth and impairs reproduction (Yan et al., 2007; Zhang and Turner, 2008; Guo et al., 2018b). In the past decade, tremendous progress has been made in identifying the key components that connect JA-Ile perception with transcriptional outputs (Howe et al., 2018), as well as the multiple roles of JA in growth, development, and immunity (Campos et al., 2014; Huot et al., 2014; Havko et al., 2016; Guo et al., 2018a). However, little is known about the mechanisms by which JA signaling integrates growth and defense responses to optimize fitness in changing environmental conditions. The core JA signaling pathway involves JAZ transcriptional repressor proteins that block JA responses by inhibiting the activity of JA-responsive transcription factors (TFs) (Figure 3.2A) (Chini et al., 2007; Thines et al., 2007; Yan et al., 2007). When endogenous JA-Ile levels are below a certain threshold concentration, JAZ proteins interact with various TFs, the most thoroughly studied of which are MYC2 and its homologs MYC3 and MYC4 (Figure 3.2A) (Dombrecht et al., 2007; Fernandez-Calvo et al., 2011; Figueroa and Browse, 2015; Qi et al., 2015a). JAZ proteins inhibit MYC activity by recruiting the co-repressor TOPLESS (TPL), either through direct JAZ- 126 TPL interaction or indirectly via the NOVEL INTERACTOR OF JAZ (NINJA) adaptor protein (Pauwels et al., 2010; Shyu et al., 2012). In addition, binding of JAZ to MYC TFs prevents the association of MYC with the coactivator MED25 (Zhang et al., 2015; An et al., 2017; Howe et al., 2018). Upon the accumulation of JA-Ile, JAZ proteins associate with the CORONATINE INSENSITIVE 1 (COI1)-containing Skp1/Cullin/F-box (SCFCOI1) E3 ubiquitin ligase complex in a hormone-dependent manner, leading to JAZ ubiquitylation and degradation by the 26S proteasome (Figure 3.2A) (Xie et al., 1998; Chini et al., 2007; Thines et al., 2007; Katsir et al., 2008). Destruction of JAZ proteins in response to the JA-Ile signal thereby relieves the transcriptional repression on MYC and other TFs, such as EIN3 (Zhu et al., 2011), MYB (Qi et al., 2011; Song et al., 2011), and WRKY (Jiang et al., 2014) family TFs. JAZ proteins belong to the TIFY protein family. The C terminus of all JAZ proteins contains a Jas motif, which can be used to distinguish JAZ from other TIFY family members (Bai et al., 2011). Although there are 13 JAZ genes in the Arabidopsis genome, the number of JAZ genes in land plants is highly variable. The liverwort Marchantia polymorpha contains a single JAZ gene, whereas many higher plant species have more than 20 JAZ genes (Bai et al., 2011; Howe et al., 2018). Many JA-induced defense responses depend on MYC2, MYC3, and MYC4, which belong to subclade IIIe of the basic helix-loop-helix (bHLH) superfamily of TFs (Heim et al., 2003) and exhibit overlapping and conserved functions (Figure 3.2A). These three TFs promote the expression of chemical defense traits that confer resistance to insect herbivores. For example, myc2/3/4 triple mutants of Arabidopsis that lack these three TFs are deficient in the production of glucosinolates (Schweizer et al., 2013; Major et al., 2017), which are a prominent class of anti- insect compounds in the Brassicales order (Howe and Jander, 2008; Bednarek et al., 2009; Hopkins et al., 2009). Chromatin-immuno precipitation (ChIP) experiments have established that 127 at least some glucosinolate biosynthetic genes are direct targets of MYC2 (Schweizer et al., 2013). Consistent with their roles in promoting metabolic defense pathways, feeding assays performed with myc single (myc2, myc3, and myc4), double (myc23, myc24 and myc34) and triple (myc234) mutants showed that all three MYCs participate in resistance to non-adapted insect herbivores (e.g., Spodoptera littoralis), although MYC3 and MYC4 display stronger roles than MYC2 (Fernandez- Calvo et al., 2011). In addition to insect herbivores, MYC2, MYC3, and MYC4 are also involved in JA-dependent defense against necrotrophic pathogens, such as Botrytis cinerea (B. cinerea). Unlike anti-insect resistance, MYC2/3/4 perform distinct roles in regulating anti-fungal resistance. myc2 is more resistant to B. cinerea (Lorenzo et al., 2004), whereas myc234 is more susceptible to this pathogen (Chico et al., 2014). Thus, it is a question that which MYC plays a positive role in defending this fungal pathogen. In addition to their role as positive regulators of defense responses, MYC TFs exert negative control over growth. For example, mycT plants (defective in MYC2, MYC3, and MYC4) accumulate more biomass than WT plants, suggesting that one or more of these three JA-inducible TFs negatively regulate leaf growth (Major et al., 2017). However, the specific role of MYC2/3/4 in mediating growth traits remains unclear. Glucosinolates are spatially sequestered from activating myrosinase enzymes, which belong to the larger family of β-glucosidases (Wittstock and Burow, 2010). Disruption of plant tissues during insect chewing and other forms of biotic challenge allow myrosinases to mix with their glucosinolate substrates, thereby producing toxic thiocyanates, isothiocyanates, and nitriles (Bones and Rossiter, 2006). Recently, Nakano et al. reported that a β-glucosidase called PYK10/BGLU23, which is the major component of the endoplasmic reticulum (ER) body (Matsushima et al 2003), possesses myrosinase activity (Nakano et al., 2017). ER bodies are constitutively formed in epidermal cells of cotyledons, hypocotyls, and roots of Arabidopsis 128 seedlings, but are absent in rosette leaves under normal growth conditions (Matsushima et al., 2002; Ogasawara et al., 2009). In response to stress signals such as wounding and JA treatment, however, inducible-type ER bodies proliferate in mature leaves (Matsushima et al., 2002), suggesting that ER bodies are a component of the plant’s induced defense responses. However, the signal transduction pathway that links wound-induced JA biosynthesis to ER body formation remains unknown. Here, we employed a genetic approach to interrogate how JA-inducible MYC2/3/4 impact growth-defense balance. Our study took advantage of a jaz decuple (jazD) mutant that harbors mutations in ten JAZ genes (JAZ1/2/3/4/5/6/7/9/10/13), and exhibits strong constitutive JA responses and various JA-induced growth and defense phenotypes (Guo et al., 2018b). We introduced myc single (myc2, myc3, and myc4), double (myc23, myc24 and myc34) and triple (myc234 or mycT) mutations into jazD. Detailed comparison between jazD and the jazD myc mutants showed that the increased sensitivity of jazD to JA is mainly mediated by MYC2, whereas MYC2 and MYC3 but not MYC4 partially accounted for stunted leaf growth of jazD. Further analyses suggest that the growth restriction of jazD does not involve the antagonistic interaction between JAZ and DELLA proteins, but rather is directly linked to the activity of MYC TFs. MYCs stimulate defense responses by promoting secondary metabolism, including the biosynthesis of secondary metabolites, as well as the production of ER bodies. Among the three MYCs, MYC3 appears to play a main role in governing jazD resistance to B. cinerea. Comparison of the transcript and protein levels of ER body components in jazD and jazD myc mutants indicate that MYC2 and MYC3 play stronger roles than MYC4 in inducing ER body components. In addition to leaf growth, the increased production of defense compounds triggered by MYC TFs is also associated with curtailed reproduction of jazD plants. Our collective data suggest that MYC TFs restrain leaf 129 growth and reproduction by reprograming of plant metabolism to defense pathways, and that MYC2, MYC3, and MYC4 perform overlapping and distinct roles in mediating growth-defense tradeoffs. 130 Results JA hypersensitivity of jazD roots mainly depends on MYC2 To dissect the biological roles of individual MYC TFs in mediating JA-inducible responses in Arabidopsis, we constructed a series of jazD myc mutants using T-DNA and transposon insertion mutations (Table 3.1 and 3.2; Figure 3.1).The previously described jazD mutant carries mutations in ten members (JAZ1/2/3/4/5/6/7/9/10/13) of the JAZ gene family (Guo et al., 2018b). Various combinations of myc2, myc3, and myc4 were introduced into jazD by genetic crosses between jazD and a previously constructed jaz myc octuple mutant (jazQ mycT) (Major et al., 2017) harboring mutations in five JAZ (JAZ1/3/4/9/10) and three MYC (MYC2/3/4) genes (Figure 3.2A) (see Methods). The resulting undecuple (jazD myc2, jazD myc3, and jazD myc4), duodecuple (jazD myc23, jazD myc24, and jazD myc34), and treducuple (jazD myc234; referred to as jazD mycT) mutants were initially used to assess the role of MYC2/3/4 in the extreme sensitivity of jazD to exogenous JA. Root growth assays performed on JA-free medium showed that jazD roots were constitutively shorter than WT Col-0 (WT), whereas the root length of mycT seedlings was indistinguishable from WT seedlings (Figure 3.2B; Table 3.3). All jazD myc mutant combinations retained the constitutive short root of jazD (Figure 3.2B; Table 3.3), consistent with the idea that this trait is expressed independently of the canonical JA signaling pathway (Major et al., 2017). Assays performed on media supplemented with JA showed that mycT seedlings have reduced sensitivity to JA in comparison to WT (Figure 3.2B; Table 3.3). The JA sensitivity of jazD myc3, jazD myc4 and jazD myc34 was similar to jazD, indicating that MYC3 and MYC4 do not promote root growth sensitivity to the hormone in the presence of MYC2. The myc2 mutation alone significantly reduced the heightened sensitivity of jazD to JA, which was further reduced in mutant combinations that combined myc3 and/or myc4 with myc2 (Figure 3.2B; Table 3.3). These results 131 suggest that MYC2 plays a major role in mediating the JA hypersensitivity of jazD roots but that MYC3 and MYC4 can also contribute to the phenotype in the absence of MYC2. Shoot responses to JA were evaluated by treatment of fully-expanded leaves with coronatine (COR), which is a structural and functional mimic of JA-Ile. As previously reported (Guo et al., 2018b), anthocyanin accumulation was observed in WT leaves within four days of COR treatment (Figure 3.3A). Compared to WT, COR-treated mycT leaves showed little if any symptoms of anthocyanin accumulation (Figure 3.3A). jazD leaves displayed chlorosis within two days (Figure 3.4A), and within four days of COR application necrosis-like symptoms spread throughout the treated leaves in a manner that was largely dependent on light (Figure 3.3A, 3.4A and 3.4B). Consistent with a critical role for MYC2/3/4 in mediating JA-induced chlorosis, COR- treated jazD mycT leaves did not exhibit chlorosis or necrosis-like symptoms (Figure 3.3A). To further investigate the distinct roles of MYC2/3/4 in mediating the hypersensitivity of jazD leaves to COR, we applied COR to jazD myc2, jazD myc3, and jazD myc4 undecuple mutants as well as jazD myc23, jazD myc24, and jazD myc34 duodecuple mutants. The results showed that COR- induced chlorosis of jazD leaves is greatly alleviated by myc2 and partially relieved by myc3, whereas myc4 appeared to have little or no effect on COR-triggered chlorosis (Figure 3.3A). Similar to jazD mycT, jazD myc23 leaves did not display visible signs of chlorosis (Figure 3.3A). COR-induced chlorosis was observed on jazD myc24 leaves, and was further intensified on jazD myc34 leaves (Figure 3.3A). These findings suggest that MYC2 makes the major contribution to COR-induced leaf chlorosis and that MYC3 also plays a discernable role, with little if any role attributed to MYC4. These conclusions based on qualitative analysis of visible symptoms were validated by quantitative measurements of leaf chlorophyll in mock- and COR-treated plants (Figure 3.3B; Table 3.4). 132 MYC2 and MYC3 partially contribute to restricted growth of jazD We next determined whether MYC2/3/4 are involved in suppressing shoot growth of jazD by comparing soil-grown WT Col-0 (WT), mycT, jazD, and jazD mycT plants with respect to various leaf growth traits, including shoot biomass, projected leaf area, and rosette diameter. Loss of MYC2/3/4 in mycT resulted in moderate (but not statistically significant) increases in leaf growth parameters relative to WT (Figure 3.5), as previously reported (Major et al., 2017). mycT partially restored the growth phenotype of jazD rosettes, such that the size and weight of jazD mycT leaves were intermediate between WT and jazD (Figure 3.5). To assess the relative contribution of MYC2/3/4 to growth inhibition, we measured the biomass and projected leaf area of WT, mycT, jazD, jazD myc undecuple mutants, and jazD mycT. jazD myc2 and jazD myc3 showed increased growth compared to jazD, whereas jazD myc4 plants were indistinguishable from jazD (Figure 3.6). Furthermore, the biomass of jazD myc2 was slightly greater than jazD myc3 (Figure 3.6A). These data provide evidence that MYC2 and MYC3 both contribute to leaf growth restriction of jazD, whereas MYC4 does not. In addition to MYC TFs (Zhang and Turner, 2008; Major et al., 2017), among the regulatory factors implicated in JA-mediated growth repression are DELLA repressors in the GA response pathway (Yang et al., 2012; Huot et al., 2014). It has been reported that JAZ proteins antagonistically interact with DELLA proteins (Figure 3.7A), and that treatment of Arabidopsis seedlings with MeJA increases the level of a DELLA protein RGA (Yang et al., 2012). Thus, removal of JAZ proteins in higher-order jaz mutants may increase the level of DELLA proteins, which suppress elongation growth by restraining the activity of PHYTOCHROME- INTERACTING FACTOR (PIF) TFs (Figure 3.7A). To test this hypothesis, WT, jazQ, and jazD seedlings were grown on medium supplemented with different concentrations of GA, which 133 triggers the degradation of DELLAs. The results showed that GA promoted hypocotyl elongation of all three genotypes to a similar extent (Figure 3.7B; two-way ANOVA analysis). Western blot analysis of RGA protein levels showed that WT, jazQ, and jazD leaves accumulated comparable levels of RGA protein (Figure 3.7C). These findings suggest that growth restriction of jazD is unlikely ascribed to increased DELLA protein levels. MYC2/3/4 are required for the overaccumulation of defense compounds in jazD To assess whether the elevation of Trp flux mediated by MYC TFs gives rise to increased production of IGs, we compared the level of glucosinolates in leaves of 23-day-old WT, mycT, jazD, and jazD mycT plants. Our data showed that the levels of most aliphatic glucosinolates did not differ between WT and jazD leaves (Figure 3.8A). However, jazD leaves accumulated much higher levels of indole glucosinolates, including I3M, OH-I3M, 4MOI3M, and 1MOI3M (Figure 3.8A). mycT mutation clearly compromised IGs production in jazD, such that the levels of these compounds in jazD mycT were similar to WT (Figure 3.8A). In addition to glucosinolates, the mycT mutation weakly but consistently reduced the basal level of anthocyanin accumulation in WT leaves, although this difference was not statistically significant (P = 0.78, Figure 3.8B). The anthocyanin content in jazD mycT leaves was intermediate between WT and jazD (Figure 3.8B), consistent with the notion that TFs in addition to MYC2/3/4 promote anthocyanin production in response to JA (Qi et al., 2011; Major et al., 2017). These collective data demonstrate a key role for MYC2/3/4 in activation of specialized metabolism in response to depletion of JAZ repressors. Constitutive formation of ER bodies in jazD is dependent on MYC TFs ER bodies are repositories for several myrosinase enzymes involved in the breakdown of glucosinolates into toxic defense compounds (Nakano et al., 2014). The elevated expression of ER 134 body-associated mRNAs and proteins in jazD (Guo et al., 2018b) suggested that ER body structures, which in WT leaves are induced in response to wounding and JA treatment (Matsushima et al., 2002), might constitutively proliferate in jazD leaves. To address this question, we used Agrobacterium-mediated transformation to express an ER-localized yellow fluorescent protein (ER-YFP) (Nelson et al., 2007) in either a WT or jazD genetic background. Confocal imaging of jazD leaves expressing the ER-YFP marker revealed the constitutive presence of rod- shaped structures having size dimensions of typical ER bodies (Figure 3.9A and 3.9B) (Matsushima et al., 2003b; Nakano et al., 2014). That these structures were not observed in ER- YFP-expressing WT leaves (Figure 3.9A) indicate that JAZ proteins negatively regulate the wound- and JA-induced formation of ER bodies. We next used jaz myc polymutants to determine whether the induction of the ER body genes in jazD leaves is mediated by MYC TFs. Quantitative real-time PCR (qRT-PCR) was used to measure the accumulation of BGLU18 and TSA1 transcripts that encode proteins residing in inducible ER bodies (Ogasawara et al., 2009; Yamada et al., 2009; Nakano et al., 2014; Geem et al., 2018), as well as NAI1, NAI2 and PYK10 mRNAs that encode components associated with constitutive ER bodies (Matsushima et al., 2003a; Matsushima et al., 2004; Yamada et al., 2008; Nakano et al., 2014). The results showed that mycT had only a modest negative effect on BGLU18 and TSA1 transcript levels in comparison WT (Figure 3.9C). Strikingly, however, the mycT mutation eliminated the elevated expression of these genes in the jazD genetic background (Figure 3.9C). In contrast to the strong dependence in jazD of BGLU18 and TSA1 expression on MYC2/3/4, the basal expression of NAI1, NAI2 and PYK10 in WT leaves was not affected by mycT (Figure 3.9C). Moreover, mycT only partially reduced the accumulation of these marker genes in the jazD background (Figure 3.9C). 135 The results obtained from qRT-PCR experiments were validated by SDS-PAGE analyses showing that jazD leaves hyperaccumulate myrosinases known to reside in ER bodies. Specifically, we found that jazD accumulates a 60-kD polypeptide that is largely absent in leaf protein from WT, mycT, and jazD mycT plants (Figure 3.9D). Mass-spectrometry (MS) analysis identified the BGLU18 myrosinase as the major protein component of the 60 kD band, with lower levels (based on spectral counts) of the PKY10 myrosinase also detected (Table 3.5). BGLU18 and PYK10 have previously been identified as abundant resident proteins in inducible and constitutive ER bodies, respectively (Matsushima et al., 2003a; Ogasawara et al., 2009). Using SDS-PAGE as a semi- quantitative measure of protein abundance, we tested jaz myc polymutants for the presence of these ER body myrosinases. The results showed that the 60-kD protein accumulated in jazD but not in WT, mycT, or jazD mycT leaves (Figure 3.9D). In support of these data, confocal microscopy of jazD mycT plants stably expressing the ER-YFP marker showed that the proliferation of ER bodies in jazD is largely dependent on MYC2/3/4 (Figure 3.9A). Collectively, these data indicate that MYC2/3/4 positively regulate the induction of ER body genes and proteins, as well as the formation of ER body structures. We then assessed the contribution of MYC2, MYC3, and MYC4 to the expression of ER body genes. The relative transcript levels of BGLU18, TSA1, NAI1, NAI2, and PYK10 in rosette leaves of jazD myc undecuple and duodecuple mutants were quantified by qRT-PCR. As shown in Figure 3.10A, the expression of ER body genes in these mutants was either similar to jazD or intermediate between jazD and jazD mycT (Figure 3.10A). Among the jaz myc polymutants tested, jazD myc23 displayed the greatest reduction of ER body transcripts compared to jazD (Figure 3.10A). SDS-PAGE analysis of leaf protein extracts confirmed that the jazD myc23 mutant combination had the greatest effect on reducing the abundance of the 60-kD band corresponding 136 to the BGLU18/PYK10 myrosinases (Figure 3.10B). Taken together, our results indicate that MYC2/3/4 additively activate ER body genes, and that MYC2 and MYC3 appear to exert a stronger positive control on ER body components. Control of cellular respiration by the JAZ-MYC transcriptional module The increased production of plant defense compounds is often associated with elevated cellular respiration, which is required to generate the metabolic precursors of defense compounds (Bolton, 2009). Consistent with this notion, both day and night respiration rates in jazD leaves were significantly increased compared to WT (Figure 3.11), in agreement with previous results (Guo et al., 2018b). Analysis of the jazD mycT polymutant showed that the stimulatory effect of jazD on day and night respiration rates was largely reduced in the absence of MYC2/3/4 (Figure 3.11). Moreover, control experiments showed that mycT mutant alone had little or no effect on respiration (Figure 3.11). These findings demonstrate that metabolic defenses controlled by the JAZ-MYC transcriptional module are linked to changes in cellular respiration. MYC TFs are required for resistance of jazD to chewing insects and necrotrophic pathogens The ability of the mycT triple mutation to eliminate the accumulation of defense-related glucosinolates and associated ER body structures in jazD suggests that MYC2/3/4 TFs are also important for the previously reported resistance of jazD plants to chewing insects and necrotrophic pathogens (Guo et al., 2018b). To test this hypothesis, we compared the resistance of WT, mycT, jazD, and jazD mycT plants to insect challenge. Bioassays performed with neonate cabbage looper (Trichoplusia ni) larvae showed that the hyper-resistance of jazD to this generalist insect was strictly dependent on MYC2/3/4 (Figure 3.12A and 3.12B). The larval weight gain on both mycT and jazD mycT plants was significantly greater than that on WT plants (Figure 3.12A and 3.12B), 137 highlighting the importance of MYC TFs in anti-insect resistance. These results also indicate that MYC2/3/4 activity is epistatic to JAZ, consistent with current models of JA signaling in which JAZ proteins repress the activity of MYC TFs. We also investigated the response of jaz myc polymutants to infection by the necrotrophic fungal pathogen Botrytis cinerea (B. cinerea). Consistent with previous reports, mycT leaves were more susceptible to B. cinerea than WT (Figure 3.12C and 3.12D) (Chico et al., 2014), whereas jazD leaves were highly resistant to the pathogen (Figure 3.12C and 3.12D) (Guo et al., 2018b). Lesion area on jazD myc2 and jazD myc4 leaves was comparable to that on jazD leaves (Figure 3.12C and 3.12D). However, the robust resistance of jazD leaves was partially compromised in jazD myc3 and jazD mycT leaves (Figure 3.12C and 3.12D). These data suggest that MYC3 performs a more important function than MYC2 and MYC4 in promoting the high level of resistance of jazD to B. cinerea. Derepression of MYC TFs in jazD compromises reproductive fitness Induced defense responses are often associated with decreased seed quality and yield (Agrawal, 1998; Baldwin, 1998). We previously reported that seed production in jazD plants is less than half of that in WT on a per plant basis, and that the size and quality of jazD seeds is reduced as well (Guo et al., 2018b). To test whether MYC TFs contribute to this apparent tradeoff between defense and reproductive output, we compared the fecundity of WT and jazD plants to that of mycT and jazD mycT plants. Whereas jazD plants produced far fewer seeds than WT as previously observed (Guo et al., 2018b), the seed yield of mycT and jazD mycT plants grown under identical conditions was comparable to WT (Figure 3.13A). We also found that mycT was epistatic to jazD with respect 138 to seed size, silique length, and seed number per fruit (Figure 3.13B-D). Thus, the decreased fertility of jazD can be largely attributed to the activity of MYC2/3/4 TFs. 139 Discussion A key innovation of our study was the development of a series of jazD myc mutants, including jazD myc2, jazD myc3, and jazD myc4 undecuple, jazD myc23, jazD myc24, and jazD myc34 duodecuple, as well as the jazD mycT tredecuple mutants, which allowed us to dissect specific functions of MYC2/3/4. Our results suggest that MYC2 is the major MYC TF that determines root sensitivity of jazD to exogenous JA, which is consistent with previous findings showing that MYC2 performs a dominant role in root responses to JA (Fernandez-Calvo et al., 2011; Niu et al., 2011). Sub-functionalization of MYC isoforms may reflect differences in the spatiotemporal accumulation pattern of MYC2/3/4 (Chini et al., 2016). For example, MYC2 is expressed in most cell types of the root, whereas the expression of MYC3 (elongation and maturation zones) and MYC4 (root cap) is limited to certain regions of the root (Gasperini et al., 2015). In contrast to roots, it is unclear why MYC2 is the principle regulator of jazD shoot sensitivity to COR. It has been reported that JA-mediated leaf senescence and chlorophyll degradation is attenuated by myc2 but not by myc3 or myc4 (Qi et al., 2015b), suggesting that MYC2 plays a critical role in regulating JA-induced senescence. It is thus plausible that MYC2 promotes the expression of genes involved in senescence and chlorophyll depletion in COR-treated jazD leaves. Another possible explanation for the necrosis-like symptoms of COR-treated jazD is that overaccumulation of indole glucosinolates or other defense compounds exerts autotoxic effects in the leaf (Chen et al., 2017). Results from the current and previous studies (Schweizer et al., 2013) have shown that MYC TFs perform essential roles in indole glucosinolate biosynthesis. However, whether MYC2 is the major activator of the biosynthesis of indole glcuosinolates or other defense compounds in jazD remains to be assessed. The unique role of MYC3 in controlling jazD resistance to B. cinerea agrees with previous studies showing that MYC3 promotes the expression of PDF genes (Niu et al., 2011), 140 which encode anti-fungal peptides (Penninckx et al., 1996). This interpretation is also consistent with previous studies showing that MYC2 and MYC4 negatively regulate PDF expression (Boter et al., 2004; Lorenzo et al., 2004; Niu et al., 2011). MYC3 may also confer fungal resistance by specifically inducing the biosynthesis of other anti-fungal compounds, such as hydroxycinnamic acid amides (HCAAs) (Muroi et al., 2009) and camalexin (Khare et al., 2017). Additional work, however, is needed to address this hypothesis. Our previous studies suggested that the strong defense sink in jazD is associated with changes in carbon sensing and metabolism, which may link to restricted leaf growth of jazD (Guo et al., 2018b). In this study, we show that myc mutations concomitantly reduce resource allocation to metabolic defense and partially restore the slow growth of jazD. These data support the conclusion that the growth inhibitory effect of JA is obligately linked through MYC TFs to increase investment of resources in defense, as previously observed in a study of the relationship between MYC TFs and jazQ (Major et al., 2017). Recent studies suggest that MYCs may also inhibit growth directly by blocking the expression of genes involved in cell division or cell expansion (Pauwels et al., 2008; Zhang and Turner, 2008; Noir et al., 2013). In roots, MYC2 binds directly to and inhibits the promoter activity of genes encoding PLETHORA (PLT) TFs, which regulate auxin-induced root stem cell niche maintenance (Chen et al., 2011). It is thus conceivable that MYCs perform similar roles in leaf tissues as well. MYC2 has also been shown to hamper the activity of PIFs (Zhang et al., 2018), which are positive regulators of elongation growth (de Lucas and Prat, 2014; Leivar and Monte, 2014) and auxin responses (Nozue et al., 2011; Hornitschek et al., 2012). In addition to leaf growth, our data also demonstrate that activation of MYC TFs in response to JAZ depletion by jazD curtails reproductive output (Figure 3.13). Many studies have shown that induction of defense responses impedes reproductive fitness (Agrawal, 1998; Baldwin, 141 1998) but the underlying reasons remain largely unknown. It is conceivable that MYC TF- regulated production of defense metabolites reduces the amount assimilated carbon and other nutrients available for seed production. Alternatively, MYC TFs may impede fertility directly by targeting genes involved in seed development. Seed storage proteins and triacylglycerols (TAGs) account for approximate 40% of the seed weight (Baud et al., 2002). It has been reported that MYC2/3/4 redundantly inhibit Arabidopsis seed mass by constraining the production of seed storage proteins (Gao et al., 2016). It was proposed that MYC TFs adjust the content of seed storage proteins by modulating the expression seed storage protein biosynthetic genes (Gao et al., 2016). Whether MYC TFs directly control the expression of genes involved in TAG biosynthesis remains to be determined. The stunted growth of jazQ was completely recovered upon disruption of MYC2/3/4 activity in a jazQ mycT mutant (Major et al., 2017). In contrast, we report here that mycT mutation does not fully restore the slow growth phenotype of jazD (Figure 3.5 and 3.6). Given that GA treatment failed to recover jazD growth and that the level of the RGA DELLA protein was not elevated in jazD leaves (Figure 3.7), the incomplete growth recovery of jazD mycT mutant cannot likely be ascribed to increased activity of DELLA proteins. The incomplete recovery of jazD mycT may also be attributed to MYC5, which belongs to the same subfamily of bHLH TFs as MYC2, MYC3, and MYC4 (Figueroa and Browse, 2015; Qi et al., 2015a). It has been reported that mycT (myc2 myc3 myc4) and a myc2 myc3 myc4 myc5 quadruple (mycQ) mutant showed no difference in petiole length and leaf number (Major et al., 2017), indicating that MYC5 performs negligible roles in leaf growth in an otherwise wild-type genetic background. Additional studies are needed to test the possibility that MYC5 participates in restricting leaf biomass in the jazD genetic background. 142 Another interpretation for partial growth recovery of jazD mycT mutants is that other regulators in addition to MYCs contribute to the production of defense compounds in jazD. Although it is well established that MYC TFs promote the accumulation of anthocyanin (Niu et al., 2011), it is increasingly recognized that the biosynthesis of these compounds is controlled by a complex network of TFs. For instance, the WD-repeat/bHLH/MYB transcriptional complex, consisting of the WD-repeat protein TRANSPARENT TESTA GLABRA 1 (TTG1), bHLH TFs TRANSPARENT TESTA 8 (TT8), GLABRA 3 (GL3) or ENHANCER OF GLABRA 3 (EGL3), and R2R3 MYB transcription factors MYB75, MYB90, MYB113, or MYB114 (Qi et al., 2011), is a positive regulator of anthocyanin production. JAZ proteins interact with several components of this complex, including all three bHLH TFs (TT8, GL3 and EGL3) and one MYB TF (MYB75) to suppress anthocyanin accumulation (Qi et al., 2011). In addition, JAZ3 indirectly inhibits MYB75 expression by targeting a YAB family TF called FILAMENTOUS FLOWER (FIL), which binds to the promoter of MYB75 to stimulate anthocyanin biosynthesis (Boter et al., 2015). Thus, incomplete elimination of anthocyanin in jazD by mycT likely reflects the involvement of additional JAZ-regulated TFs in promoting anthocyanin biosynthesis. Consistent with the idea that JAZ proteins regulate the activity of diverse TFs involved in specialized metabolism, a recent study provided evidence that the expression of spatially clustered triterpenoid biosynthetic genes in Arabidopsis are repressed by JAZ independently of MYC2/3/4 (Major et al., 2017). Gene ontology (GO) analysis performed with upregulated genes in jazD showed that triterpenoid metabolic process (GO ID: 0006722) is also induced in jazD (Guo et al., 2018b). Based on the results of Major et al. (Major et al., 2017), it is likely that MYC TFs do not promote the induction of triterpenoid biosynthetic genes in jazD as well. In future studies it may be informative to measure triterpene levels in jazD and jazD myc mutants, particularly in root tissues where these 143 genes are most highly expressed. Given the complex genetic background of jazD (Guo et al., 2018) and the partial growth recovery by mycT, we cannot exclude the possibility that unknown genetic changes contribute to the growth phenotype of this mutant line. Reconstruction of the jaz decuple mutant using CRISPR technology may help to test this hypothesis. ER bodies were first discovered in epidermal and cortical cells of radish roots (Bonnett and Newcomb, 1965). Currently, it is generally recognized that these ER membrane-derived compartments are restricted to the order of Brassicales in which glucosinolates are found (Iversen, 1970; Behnke and Eschlbeck, 1978; Jorgensen, 1981). ER bodies are increasingly recognized as a repository for a large variety of β-glucosidases (Matsushima et al., 2003a; Ogasawara et al., 2009). That at least some of these enzymes (i.e. PYK10/BGLU23) display myrosinase activity suggests that ER bodies serve to physically separate myrosinases from their glucosinolate substrates until the tissue is disrupted by an appropriate biotic stress (Nakano et al., 2014; Nakano et al., 2017). Although there is evidence showing that JA treatment induces the formation of ER bodies (Matsushima et al., 2002), the mechanism by which JA triggers ER body accumulation has remained unclear. Our results significantly advance insight into this question by demonstrating that ER body biogenesis is positively regulated by the JAZ-MYC transcriptional module (Figure 3.9 and 3.10). Consistent with the emerging link between ER body formation and indole glucosinolates production, the extent of ER body formation in jazD and jazD mycT positively correlates with their indole glucosinolate levels (Figure 3.8A and 3.9A). Direct measurements of total myrosinase activity in jaz myc polymutants may be useful to identify specific JAZ and MYC proteins that control ER body function (Nakano et al., 2017). Interestingly, ER bodies are repositories not only for β-glucosidases but also for anti-fungal defensins such as PDF1.2 (Watanabe et al., 2013). That these low-molecular weight, cysteine-rich peptides deter a wide 144 variety of fungal pathogens is consistent with a role for ER bodies in anti-fungal defense (Penninckx et al., 1996; Campos et al., 2018). Recent studies indicate that PDFs are localized to ER bodies before fungal attack but that during pathogen invasion the peptides are secreted to apoplastic space (Watanabe et al., 2013). Given that PDF expression is highly elevated in jazD (Guo et al., 2018b), it will be interesting to determine whether ER bodies in jazD leaves serve as sites for PDF storage. We found that the expression of genes associated with both constitutive and inducible ER bodies are positively regulated by MYC2/3/4 (Figure 3.9C and 3.10A). However, our results also indicate MYC TFs exert differential control over the expression of these two types of ER body genes. The expression of inducible ER body genes (BGLU18 and TSA1) was strictly dependent on MYCs, whereas the expression of constitutive ER body genes (NAI1, NAI2, and PYK10) was only partially controlled by MYCs (Figure 3.9C and 3.10A). These results are consistent with previous studies showing that the biogenesis of constitutive ER bodies requires another bHLH TF called NAI1; among the constitutive ER body genes directly regulated by NAI1 are PYK10, NAI2, MEB1, MEB2, and several JACALIN-RELATED LECTINs (JALs) (Nakano et al., 2014). Loss of NAI1 completely disrupts ER body formation in seedlings (Matsushima et al., 2004). Thus, it is plausible that NAI1 is targeted by JAZ proteins and depressed in jazD to induce the expression of constitutive ER body genes, as well as the biogenesis of these structures. To test this hypothesis, we performed a yeast-two-hybrid (Y2H) analysis to determine whether NAI1 interacts with members of the Arabidopsis JAZ protein family. With the possible exception of a very weak interaction between NAI1 and JAZ8, robust interaction between NAI1 and other JAZs was not observed (Figure 3.14). This finding does not support the hypothesis that JAZ proteins inhibit ER body formation through physical interaction with NAI1. The mechanisms by which the biogenesis 145 of constitutive and inducible ER bodies is controlled in a different manner remain to be elucidated. In this context, it is interesting to note that MYC and MYB TFs co-activate the expression of glucosinolate biosynthetic genes via direct binding to their promoters, and that these two types of TFs physically interact with each other (Schweizer et al., 2013; Frerigmann et al., 2014; Frerigmann, 2016). We found that the induction of BGLU18 and PYK10 is dependent on MYC2/3/4 (Figure 3.9C and 3.10A). Examination of the BGLU18 promoter showed that it contains putative binding sites for both MYC and MYB TFs. Based on the increasing evidence for a link between glucosinolates and ER bodies (Nakano et al., 2017; Wang et al., 2017), we speculate that MYC and MYB TFs act synergistically to promote the formation of inducible ER bodies. Additional studies are needed to test whether and how MYC and MYB TFs directly target the promoters of ER body genes. 146 Methods Plant material and growth conditions Arabidopsis thaliana ecotype Columbia-0 (Col-0) was the wild-type (WT) genetic background for all experiments. Soil-grown plants were maintained at 20 ⁰C (± 1 ⁰C) in a growth chamber with a 16-h day (100 µE m-2 s-1) and 8-h night unless otherwise noted. For experiments involving growth of seedlings on agar plates, seeds were surface-sterilized in 50% bleach (v/v) for 3 min, washed 8 times with sterile water and then stratified in dark at 4 ⁰C for two days. Seeds were then sown on 0.7% (w/v) phytoblend agar (Caisson Labs) media containing half-strength Linsmaier and Skoog (LS; Caisson Labs) salts supplemented with 0.8% (w/v) sucrose. Construction of the jazD decuple and the jazQ mycT octuple mutants has been described previously (Major et al., 2017; Guo et al., 2018b). The jazD mycT tredecuple mutant was generated by combining jazD and jazQ myT. PCR- based genotyping of mutants was performed using primer sets flanking T-DNA insertion sites, together with a third primer specific for the T-DNA border (Campos et al., 2016; Major et al., 2017). Root and shoot growth measurements Root growth inhibition assays were performed by growing seedlings on square Petri plates (Thermo Fisher Scientific) containing half-strength LS salts, 0.8% (w/v) sucrose and 0.7% (w/v) phytoblend agar supplemented with the indicated concentration of methyl-JA (MeJA; Sigma- Aldrich) (Shyu et al., 2012). Plates were incubated vertically in a growth chamber maintained at 20 ⁰C with an 16 h : 8 h, day (80 µE m-2 s-1) : night photoperiod for 7 days. Primary root length was determined using the ImageJ software (https://imagej.nih.gov/ij/). WT and mutant lines were grown the same plate to avoid plate-to-plate variation. Measurement of growth parameters, 147 including leaf fresh weight, projected leaf area and rosette diameter, was performed as described previously (Campos et al., 2016). Coronatine treatment and chlorophyll quantification The fifth true leaves of 26-day-old soil-grown plants were spotted with 5 µL of sterile water (mock) or 50 µM coronatine (prepared in sterile water). Treated leaves were scanned 2 and 4 days after treatment. For whole-rosette treatment, similar plants were sprayed with sterile water or 5 µM coronatine, as described previously (Attaran et al., 2014). Rosettes were scanned after 3 and 4 days of coronatine treatment. For chlorophyll measurement, leaves of 25-day-old plants were sprayed with 5 µM coronatine or water (mock), and harvested three days after spray. Chlorophyll was extracted by 80% acetone buffered by 2.5 mM sodium phosphate solution (pH 7.8), and absorbance at 646 nm, 663 nm, and 750 nm was determined by spectrophotometer (Beckman Coulter DU-800) (Porra et al., 1989). The following equation was used for estimation of chlorophyll concentration (µg/mL): Chlorophyll a + b = (17.76 x (A646 - A750)) + (7.34 x (A663 - A750)) (Porra et al., 1989). Seed yield measurements Inspection of seed yield was performed as described previously (Guo et al., 2018b). An inverted plastic cone and plastic tube (Arasystem 360 kit; Arasystem) were fitted to each plant 23 days after seed sowing to collect all seeds from dehiscing siliques. Seeds collected from individual plants were dried with Drierite desiccant for two weeks, after which total seed mass per plant was measured. Average seed mass was determined by weighing dry seeds in batches of 100 (Jofuku et al., 2005). For each plant, the weights of five sample batches were measured and averaged. The 148 silique length and number of seeds per silique were determined by sampling the fully-elongated seventh, ninth and eleventh siliques on the main stem (Roux et al., 2004). Glucosinolate analysis Plants were grown under long-day conditions (16-h day and 8-h night) for 23 days. Rosette leaves were harvested and frozen in liquid nitrogen immediately. Two plants were pooled for each sample, with three biological replicates were collected per sample. Glucosinolates were extracted with 80% methanol as described previously (Glauser et al., 2012; Guo et al., 2018b). Samples were analyzed by Waters Xevo G2-XS ultrahigh pressure liquid chromatography (UPLC) coupled to quadrupole time-of-flight mass spectrometry (QTOFMS) in the MSU Mass Spectrometry Facility. Data analysis and processing were performed as described before (Glauser et al., 2012). Insect and pathogen assays Insect-feeding assays were performed with soil-grown plants maintained at 20 ⁰C in a growth chamber with a photoperiod of 8 h light (100 µE m-2 s-1) and 16 h dark. Four neonate Trichoplusia ni larvae (Benzon Research) were reared on each of 8 plants (10-week-old) for nine days, after which larval weights were measured (Herde et al., 2013). Botrytis cinerea inoculation assays were performed as described previously (Rowe and Kliebenstein, 2007), with minor modifications. Detached leaves from 10-week-old short-day-grown (8 h light/16 h dark) plants were placed in Petri dishes containing filter papers moistened with 10 mL of sterile H2O, with petioles embedded in the H2O. Each leaflet was inoculated with a single 4 µL droplet of B. cinerea spore suspension (5,000 spores/mL in 50% organic grape juice). Petri dishes were sealed with microspore surgical tapes (3M Health Care) and kept under the same conditions used for plant growth. Photographs 149 were taken after five days and lesion area was measured using the ImageJ software (https://imagej.nih.gov/ij/). Confocal laser scanning microscopy To express the ER luminal marker protein ER-YFP in plants, the coding sequence of ER-YFP, which includes the signal peptide of WALL-ASSOCIATED KINASE 2 (WAK2), YFP and HDEL ER retention signal (Nelson et al., 2007), was subcloned into the pYL436 binary vector which contains the 35S promoter sequence (Rubio et al., 2005). Transformation of WT and jazD plants with Agrobacterium tumefaciens (strain GV3101) was performed using the floral dip method (Clough and Bent, 1998). Seedlings (T1 generation) of transformed lines were screened on LS plates containing gentamycin (100 µg/mL) and transferred into soil. Homozygous lines were selected by testing the T3 progeny for resistance to gentamycin. jazD mycT plants overexpressing ER-YFP was obtained by crossing jazD mycT to jazD plants harboring 35S:ER-YFP. The fifth rosette leaves of 30-day-old homozygous lines were inspected by confocal laser scanning microscopy with a Nikon A1Rsi microscope. NIS-Elements Advanced Research (Nikon) and Photoshop (Adobe) software were used for image processing. SDS-polyacrylamide gel electrophoresis and mass-spectrometry analysis Crude proteins were extracted from leaves of 23-day-old soil-grown Arabidopsis plants with an extraction buffer consisting of 100 mM Tris-HCl pH 6.8, 150 mM NaCl, 10% glycerol, 4% SDS, 200 mM DTT, and one tablet of Complete Mini EDTA-free proteinase inhibitors (one tablet per 10 mL; Roche) (Schilmiller et al., 2010). Lipophilic contaminants that would interfere with electrophoresis were removed by chloroform-methanol extraction of the solubilized protein. 150 Protein pellets from the chloroform-methanol extraction were resuspended in the buffer containing 100 mM Tris-HCl pH 6.8, 150 mM NaCl, 10% glycerol, 1% SDS, and 200 mM DTT, and protein concentrations were determined by the Bradford assay (Bio-Rad). The isolated proteins were then separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE) and stained with Coomassie Brilliant Blue R-250. The jazD-specific band, which was in the 70-kd region of the gel, was cut out and subjected to mass-spectrometry analysis at the Michigan State University Proteomics Core Facility (https://rtsf.natsci.msu.edu/proteomics/). Quantitative PCR For quantitative PCR (qPCR) analysis, rosette leaves of two 23-day-old soil-grown plants were pooled together for each sample, with three biological replicates collected per sample. Harvested tissues were immediately frozen in liquid nitrogen and stored at -80 ⁰C until processing. Frozen tissues were homogenized with a TissueLyser II (Qiagen) and RNA was extracted using an RNA extraction kit (Macherey-Nagel), as per the manufacturer’s instructions. RNA quality was assessed by A260/A280 ratios using an ND-1000 UV Nanodrop spectrophotometer (Thermo Scientific). Complementary DNA (cDNA) was reverse transcribed using the High Capacity cDNA Reverse Transcription kit (Applied Biosystems, ABI) as per the manufacturer’s protocols, and cDNA was diluted to 15 ng/µL with nuclease-free water. Quantitative real-time PCR reactions consisted of 2 µL of diluted cDNA template (30 ng in total), 5 µL of 2 x Power SYBR Green Master Mix (ABI), 1 µL of 5 µM forward and reverse primers, and 2 µL of nuclease-free water for a final reaction volume of 10 µL. The forward and reverse primers used were as follows: PP2A, 5’- AAGCAGCGTAATCGGTAGG-3’ and 5’- GCACAGCAATCGGGTATAAAG-3’; BGLU18, 5’-CGACAACGGAAAGAAAGCTC-3’ and 5’-GCAGTTTCTGAATGCGTCAA-3’; TSA1, 5’- 151 AATGCTCTTCAAGGCAAGGA-3’ and 5’-TGATCCAACAGACTCGAACG-3’; PYK10, 5’- CAATGAGCCATGGGTTTTCT-3’ and 5’-CAACTGCTTCTGCGTGAGAG-3’; NAI2, 5’- CCGAATTTCGATGCGATTAT-3’ and 5’-CCGAGTCTACGGTTCTCTGC-3’; and NAI1, 5’- GGTTCTCGCACGTCACAAGT-3’ and 5’-CTTCCTCCATTGTTAACACAATCTT-3’. Reactions were run on an ABI 7500 Fast qPCR instrument with the following conditions: 50 ⁰C for 2 min, 95 ⁰C for 10 min, then 40 cycles of 15 s at 95 ⁰C for denaturation and 60 s at 60 ⁰C for annealing and polymerization. A dissociation curve was performed at the end of each reaction using default parameters (15 s at 95 ⁰C, 60 s at 60 ⁰C-95 ⁰C in 1 ⁰C increments, and 15 s at 95 ⁰C), which confirmed a single peak for each set of primers. All reactions were run with three technical replicates, which typically did not differ by more than 0.2 to 0.5 cycle threshold. Target gene expression was normalized to the expression of PROTEIN PHOSPHATASE 2A (PP2A), which is stable under JA-inducing conditions (Attaran et al., 2014). The efficiencies for each primer set were determined by LinRegPCR. Yeast two-hybrid assays Yeast two-hybrid (Y2H) assays were performed with the Matchmaker LexA system (Clontech) as previously described (Melotto et al., 2008; Chung and Howe, 2009). Full-length JAZ cDNAs were subcloned into the pGILDA vector to generate fusions of the bait protein with the LexA DNA binding domain. Full-length cDNAs encoding MYC2 and NAI1 were subcloned into the pB42AD vector to generate fusions of the prey protein with the B42 activation domain. Bait and prey vectors were cotransformed into yeast (Saccharomyces cerevisiae) strain EGY48 using the frozen-EZ yeast transformation II kit (Zymo Research). Transformants were selected for colorimetric 152 detection (β-galactosidase) of protein-protein interaction as described by Chung and Howe (Chung and Howe, 2009). Y2H plates were scanned after six days of incubation at 30 ⁰C. 153 APPENDIX 154 Tables and figures Table 3.1. Mutants used for construction of jazD myc mutants. Mutant Original name Source Accession Mutagen jaz1-2 SM_3.22668 JIC SM Col-0 dSpm transposon jaz2-3 RIKEN_13- 5433-1 RIKEN No-0 Ds transposon jaz3-4 GK-097F09 GABI Kat Col-0 jaz4-1 SALK_141628 SALK Col-0 jaz5-1 SALK_053775 SALK Col-0 T-DNA (pAC161) T-DNA (pROK2) T-DNA (pROK2) Resistance1 Basta (confirmed) Hygromycin (confirmed) Sulfadiazine (confirmed) Kanamycin (silenced) Kanamycin (confirmed) jaz6-4 CSHL_ET30 CSHL Ler Ds transposon (Enhancer trap GUS) Kanamycin (confirmed) jaz7-1 WiscDsLox7H11 Wisconsin Col-0 jaz9-4 GK_265H05 GABI Kat Col-0 jaz10-1 SAIL_92_D08 SAIL Col-0 jaz13-1 GK_193G07 GABI Kat Col-0 myc2-1 SALK_040500 SALK Col-0 myc3-1 GK-445B11 GABI Kat Col-0 T-DNA (pWiscDsLox) T-DNA (pAC161) T-DNA (pCSA110) T-DNA (pAC161) T-DNA (pROK2) T-DNA (pAC161) myc4-1 GK-491E10 GABI Kat Col-0 T-DNA (pAC161) Basta (not tested) Sulfadiazine (confirmed) Basta (confirmed) GUS Sulfadiazine (not tested) Kanamycin (silenced) Sulfadiazine (confirmed) Sulfadiazine (confirmed) 1Resistance of the mutant line to the indicated selectable marker was tested and confirmed. 155 Table 3.2. Primers used for genotyping jaz and myc mutants. Gene Locus Primer Sequence (5’-3’) JAZ1 AT1G19180 JAZ1_F ACCGAGACACATTCCCGATT JAZ1_R CATCAGGCTTGCATGCCATT JAZ1_border ACGAATAAGAGCGTCCATTTTAGAG JAZ2 AT1G74950 JAZ2_F TCTTCCTCGTGACAAAACGCA JAZ2_R CCAAACACAGAACCATCTCCACA JAZ2_border CCGGATCGTATCGGTTTTCG JAZ3 AT3G17860 JAZ3_F ACGGTTCCTCTATGCCTCAAGTC JAZ3_R GTGGAGTGGTCTAAAGCAACCTTC JAZ3_border ATAACGCTGCGGACATCTACATT JAZ4 AT1G48500 JAZ4_F TCAGGAAGACAGAGTGTTCCC JAZ4_R TGCGTTTCTCTAAGAACCGAG JAZ4_border TTGGGTGATGGTTCACGTAG JAZ5 AT1G17380 JAZ5_F GCTTATACCGAAAACCCGATTCCAG JAZ5_R GGCTCATTGAGATCAGGAAGAACC A JAZ5_border TTGGGTGATGGTTCACGTAG JAZ6 AT1G72450 JAZ6_F GACACACATCACTGTCACTTC JAZ6_R AGTTTCTGAGGTCTCTACCTTC JAZ6_border CCGTTTTGTATATCCCGTTTCCGT JAZ7 AT2G34600 JAZ7_F ATGCGACTTGGAACTTCGCC JAZ7_R GGAGGATCCGAACCGTCTG JAZ7_border ACGTCCGCAATGTGTTATTA JAZ9 AT1G70700 JAZ9_F TACCGCATAATCATGGTCGTC JAZ9_R TCATGCTCATTGCATTAGTCG JAZ9_border CTTTGAAGACGTGGTTGGAACG 156 Table 3.2 (cont’d) JAZ10 AT5G13220 JAZ10_F ATTTCTCGATCGCCGTCGTAGT-3 JAZ10_R GCCAAAGAGCTTTGGTCTTAGAGTG JAZ10_border GTCTAAGCGTCAATTTGTTTACACC JAZ13 AT3G22275 JAZ13_F GCACGTGACCAAATTTGCAGA JAZ13_R TGAAGAGAGGAGGATGATGAGGA JAZ13_border AAACCTCCTCGGATTCCATTGC MYC2 AT1G32640 MYC2_F GCTACAACCAACGATGAATC MYC2_R TCATCAACAGCGTCATCCGA MYC2_border TTGGGTGATGGTTCACGTAG MYC3 AT5G46760 MYC3_F GTTAGATCAGCTGCGAATGATTCGG MYC3_R CTCCGACTTTCGTCATCAAAGCAAC MYC3_border ATAACGCTGCGGACATCTACATT MYC4 AT4G17880 MYC4_F GGATCCATGTCTCCGACGAATGTTC AAGTA MYC4_R TCTCTCACAACTTGATCCAGCTAA MYC4_border ATAACGCTGCGGACATCTACATT 157 Table 3.3. Letters that denote significant differences according to Tukey’s HSD test (P < 0.05) for Figure 3.2B. Genotype WT mycT jazD jazD myc2 jazD myc3 jazD myc4 jazD myc23 jazD myc24 jazD myc34 jazD mycT 0 µM A A BCD BCD D CD AB DE DE ABC MeJA 5 µM IJ FG O IJK O O GH HI O GH 1 µM FG EF JKLM FG IJKL JKLM F FGH KLM EF 25 µM LMN GH O N O O KLMN MN O IJKL 158 Table 3.4. Letters that denote significant differences according to Tukey’s HSD test (P < 0.05) for Figure 3.3B. Treatment Genotype Mock Col-0 COR Col-0 mycT Mock mycT COR jazD Mock jazD COR jazD myc2 Mock jazD myc2 COR jazD myc3 Mock jazD myc3 COR jazD myc4 Mock jazD myc4 COR jazD mycT Mock jazD mycT COR Chlorophyll a Chlorophyll b Chlorophyll a + b ABC ABC B ABC ABC D C E ABC F ABC D C ABC A AB AB AB B C AB D AB E B C AB B A A A A A B A C A D A B A A 159 Table 3.5. Summary of proteins that were identified in the jazD-specific protein band in SDS-PAGE analyses. Spectral counts, percent amino acid coverage Protein ID Beta glucosidase 18 NADP-malic enzyme 2 Beta glucosidase 23 Succinate dehydrogenase 1-1 FtsH extracellular protease family Sulfite reductase 10-formyltetrahydrofolate synthetase Glucoside glucohydrolase 2 Leucine-rich repeat protein kinase family protein Lipoxygenase 2 26S proteasome regulatory subunit (putative) Phosphoglycerate mutase (2,3- bisphosphoglycerate-independent) Vacuolar ATP synthase subunit A Transducin family protein/WD-40 repeat family protein AICARFT/IMPCHase bienzyme family protein Nuclear transport factor 2 family protein with RNA binding domain P-loop containing nucleoside triphosphate hydrolases superfamily protein RNAse l inhibitor protein 2 Winged-helix DNA-binding transcription factor family protein Nuclear transport factor 2 family protein with RNA binding domain Apoptosis inhibitory protein 5 Translation elongation factor EF1A/initiation factor IF2gamma family protein Ribulose-bisphosphate carboxylases Transducin/WD40 repeat-like superfamily protein U5 small nuclear ribonucleoprotein helicase (putative) 160 GeneBank accession no. AT1G52400 AT5G11670 AT3G09260 AT5G66760 AT2G30950 AT5G04590 AT1G50480 AT5G25980 AT2G01210 Mr 60 64 60 70 74 72 68 63 78 WT ND ND ND ND ND ND ND 3, 4.2 1, 1.1 AT3G45140 AT5G57950 102 ND 24 1, 3.5 AT1G09780 61 ND AT1G78900 AT2G19520 69 56 ND ND AT2G35040 65 ND AT3G25150 53 ND AT3G53110 55 ND AT4G19210 AT4G35890 68 56 ND ND AT5G60980 49 ND AT2G34040 AT1G18070 62 59 ND ND ATCG00490 AT3G05090 53 82 5, 11.1 2, 3.1 AT1G20960 247 1, 0.4 jazD 25, 37.5 8, 18.4 4, 0 2, 1.6 2, 3.7 2, 3.1 2, 1.6 1, 1.8 1, 1.1 1, 1.6 1, 3.5 1, 2.0 1, 1.9 1, 3.4 1, 1.7 1, 2.1 1, 2.4 1, 1.5 1, 2.5 1, 2.4 1, 2.0 1, 1.7 ND ND ND Table 3.5. (cont’d) LC-MS/MS was used to identify proteins in the 60-kD region of the WT and jazD SDS-PAGE gel. The number of spectral counts (i.e., the number of times the mass spectrometer detected a peptide corresponding to a particular protein) and the percent of the full- length protein sequence that was covered by the peptides (percent amino acid coverage) are shown. ND, not detected. 161 Figure 3.1. PCR-based genotyping of jazD mycT. 162 Figure 3.1. (cont’d) (A) and (B) Genotyping of jazD mycT for JAZ1/2/3/4/5/6/7/9/10/13 (A) and MYC2/3/4 (B) was performed using primer sets flanking DNA insertion sites and a third primer recognizing the T-DNA border (Table 3.1 and 3.2). NC, negative control. 163 Figure 3.2. Sensitivity of jazD roots to JA is driven mainly by MYC2. (A) Perturbations (shown in red) used in this study to manipulate JA responses involve treatment with exogenous methyl-JA (MeJA) or coronatine (COR), as well as loss-of-function mutations of ten JASMONATE ZIM-DOMAIN (JAZ) repressors (jazD) or MYC transcription factors (myc2, myc3, myc4, myc23, myc24, myc34, and myc234). The Venn diagram at right depicts that three MYC TFs (pink: MYC2, blue: MYC3, and yellow: MYC4) may play independent or overlapping roles in mediating JA outputs. (B) Root length of 10-day-old WT Col-0 (WT), mycT, jazD, jazD myc2, jazD myc3, jazD myc4, jazD myc23, jazD myc24, jazD myc34, and jazD mycT seedlings grown in the presence of 0, 1, 5 or 25 µM MeJA. Data show the mean ± SD of 13-20 seedlings per genotype. Letters that denote significant differences according to Tukey’s HSD test (P < 0.05) are shown in Table 3.3. 164 Figure 3.3. MYC2 is the major regulator of jazD sensitivity to coronatine. th (A) Photographs of leaves after coronatine (COR) treatment. The 5 rosette leaves of 24-day-old plants grown under 16-h-light/8-h-dark photoperiod were spotted with 5 μL of water (mock) or 50 μM COR. Leaves were excised and photographed after four days of COR treatment. Scale bars, 0.5 cm. (B) Chlorophyll content (chlorophyll a + b) in COR-sprayed leaves. Soil-grown plants (25-day- old) were sprayed with either water (mock) or 5 μM COR. Leaves were harvested three days after spray and subjected to chlorophyll extraction. Data show the mean ± SD of three samples per genotype. Chlorophyll content was log2 transformed according to Box-Cox Normality Plot for statistical tests. Letters that denote significant differences according to Tukey’s HSD test (P < 0.05) are shown in Table 3.4. 165 Figure 3.4. Coronatine (COR)-induced chlorosis in jazD is partially dependent on light. th (A) Photographs of leaves after COR or COR/dark treatment. The 5 rosette leaves of 25-day-old plants grown under LD conditions were spotted with 5 μL of water (mock) or 50 μM COR. Plants were either maintained under LD conditions or transferred into dark conditions (LD to dark) after COR treatment. Leaves were excised and photographed after two or four days of COR treatment. Scale bars, 0.3 cm. (B) Enlarged photographs of COR- or COR/dark-treated jazD leaves in Panel A. 166 Figure 3.5. The growth deficiency of jazD is partially recovered by mycT. (A) Photograph of WT Col-0 (WT), mycT, jazD, and jazD mycT rosettes of 23-day-old plants grown under 16-h-light/8-h-dark photoperiod. Scale bars, 0.5 cm. (B-D) Rosette fresh weight (B), projected leaf area (C) and rosette diameter (D) of WT, mycT, jazD, and jazD mycT plants shown in Panel A. Data show the mean ± SD of five plants per genotype. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). 167 Figure 3.6. MYC2 and MYC3 play stronger roles in growth promotion compared to MYC4. (A) Fresh weight of 28-day-old WT Col-0 (WT), mycT, jazD, jazD myc2, jazD myc3, jazD myc4 and jazD mycT plants grown under long-day conditions (16-h-light/8-h-dark). Data show the mean ± SD of five plants per genotype. Fresh weight was log2-transformed according to Box-Cox Normality Plot for statistical tests. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). (B) Projected leaf area of 53-day-old WT, mycT, jazD, jazD myc2, jazD myc3, jazD myc4 and jazD mycT plants grown under short-day conditions (8-h-light/16-h-dark). Data show the mean ± SD of five plants per genotype. Projected leaf area was log2-transformed according to Box-Cox Normality Plot for statistical tests. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). 168 Figure 3.7. The restricted growth of jazD cannot be restored by exogenous gibberellic acid (GA3) treatment. (A) Schematic diagram illustrating the interaction between JA and GA signaling pathways. (B) Hypocotyl length of WT Col-0 (WT), jazQ and jazD seedlings grown on half-strength LS medium supplemented with different concentrations (0, 1 or 10 µM) of GA3. Seedlings were -2 -1 s grown under 16-h-light (10 μE m )/8-h-dark photoperiod at 20 ºC for seven days. Data show the mean ± SD of ten seedlings per genotype. Two-way ANOVA was performed to test the effect of GA3 on hypocotyl elongation (E and F) and showed that the GA3 x genotype interaction was insignificant for WT vs. jazQ or WT vs. jazD comparisons (P < 0.05). (C) Detection of RGA protein in WT, jazQ, jazD and rga seedlings by western blot. Seedlings were grown on half-strength LS medium containing 0.8% (w/v) sucrose under long-day conditions for 16 days. Western blot was performed with anti-RGA antibody. Coomassie brilliant blue staining of the PVDF membrane was used as loading control. The region of the gel corresponding to the large subunit of Rubisco (RbsL) is shown. Duplicate samples (biological replicates) were loaded for each genotype. 169 Figure 3.8. Elevated accumulation of defense compounds in jazD is dependent on MYC TFs. 170 Figure 3.8 (cont’d) (A) Comparison of glucosinolate levels in leaves of WT Col-0 (WT), mycT, jazD and jazD mycT plants. Glucosinolates were extracted from leaf tissues of 26-day-old plants and quantified by LC-MS. Peak area for the indicated glucosinolate compound in the WT sample was set to “1” and the peak area of the same compound in other genotypes was normalized to the WT sample. Abbreviations: 3MSOP: 3-methylsulphinylpropyl, glucoiberin; 4MSOB: 4- methylsulphinylbutyl, glucoraphanin; 5MSOP: 5-methylsulphinylpentyl, glucoalyssin; 6MSOH: 6-methylsulphinylhexyl, glucohesperin; 7MSOH: 7-methylsulphinylheptyl, glucoibarin; 3MTP: 3-methylthiopropyl, glucoiberverin; 8MSOO: 8-methylsulphinyloctyl, glucohirsutin; 4MTB: 4- methylthiobutyl, glucoerucin; I3M: indol-3-ylmethyl, glucobrassicin; OH-I3M: 4-hydroxyindol- 3-ylmethyl, hydroxyglucobrassicin; 5MTP: 5-methylthiopentyl, glucoberteroin; 2PE: 2- phenylethyl, gluconasturtiin; 4MOI3M: 4-methoxyindol-3-ylmethyl, methoxyglucobrassicin; 1MOI3M: 1-methoxyindol-3-ylmethyl, neoglucobrassicin; 7MTH: 7-methylthioheptyl. Asterisks denote glucosinolates that were upregulated in jazD but not in jazD mycT compared to WT according to Tukey’s HSD test (P < 0.05). (B) Anthocyanin levels in 23-day-old WT, mycT, jazD and jazD mycT leaves. Data show the mean ± SD of five rosettes per genotype. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). 171 Figure 3.9. Induction of ER body genes is mediated by MYC2/3/4. (A) Confocal images of the fifth rosette leaves of 30-day-old plants grown under long-day conditions (16-h-light/8-h-dark). The endoplasmic reticulum (ER) luminal marker protein ER- YFP, which includes the signal peptide of WALL-ASSOCIATED KINASE 2 (WAK2), YFP and HDEL ER retention signal, was overexpressed in WT Col-0 (WT), jazD and jazD mycT plants. White arrows depict ER body structures. Scale bars, 10 µm. (B) Enlargement of ER bodies at the surface of ER network in jazD. Scale bars, 10 µm. 172 Figure 3.9. (cont’d) (C) Relative expression levels of ER body genes regulated by stress signals (BGLU18 and TSA1) or developmental cues (NAI1, NAI2 and PYK10) in WT, mycT, jazD and jazD mycT leaves. PP2A (At1g13320) was used for qPCR normalization. Data show the mean ± SD of three biological replicates per genotype. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). (D) SDS-PAGE analyses of total rosette proteins show that a band in the 60-kD region (black arrows) appears in jazD but not in WT, mycT or jazD mycT. Duplicate samples (biological replicates) were loaded for each genotype. 173 Figure 3.10. MYC2/3/4 display additive effects on inducing the expression of ER body genes. 174 Figure 3.10. (cont’d) (A) Relative expression levels of ER body genes in WT Col-0 (WT), jazD and jazD myc leaves. Plants were grown under long-day (16-h-light/8-h-dark) conditions for 25 days. PP2A (At1g13320) was used for qPCR normalization. Data show the mean ± SD of three biological replicates per genotype. Black and blue asterisks denote significant differences when comparing indicated genotypes to jazD or jazD mycT respectively according to Tukey’s HSD test (P < 0.05). (B) Removal of one or two MYC TFs in the jazD background fails to deplete the 60-kD protein band. 175 Figure 3.11. Increased respiration rates of jazD is dependent on MYC TFs. (A) and (B) Respiration rates of WT, mycT, jazD, and jazD mycT plants measured at 400 μmol CO2 in light (A) or dark (B). Plants were grown under short-day (8-h-light/16-h-dark) conditions for eight weeks. Data show the mean ± SD of three plants per genotype except for mycT in Panel A, which represents one plant. 176 Figure 3.12. MYC TFs account for increased resistance of jazD to insect herbivores and necrotrophic pathogens. (A) Average weight of T. ni larvae after nine days of feeding on WT Col-0 (WT), mycT, jazD and jazD mycT leaves. Plants were grown under short-day conditions (8-h-dark/16-h-light). Data show the mean ± SD of at least 26 larvae per genotype. Larval weight were log2 transformed according to Box-Cox Normality Plot for statistical tests. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). (B) Representative short-day grown plants before and after challenged with T. ni larvae. Scale bars, 2 cm. (C) Necrotic lesion area measured after six days of Botrytis cinerea (B. cinerea) infection of WT, mycT, jazD, jazD myc2, jazD myc3, jazD myc4, and jazD mycT leaves. Data show the mean ± SD of 13-15 leaves per genotype. Lesion area was log2 transformed according to Box-Cox Normality 177 Figure 3.12. (cont’d) Plot for statistical tests. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). (D) Representative Arabidopsis leaves after infection with B. cinerea for six days. Scale bars, 1 cm. 178 Figure 3.13. Compromised fertility of jazD is recovered by the myc2 myc3 myc4 triple mutation. (A) and (B) Seed yield (A) and seed mass (B) of WT Col-0 (WT), mycT, jazD, and jazD mycT plants. Plants were grown under long-day conditions (16-h-light/8-h-dark) until they stop generating new flowers. Seed yield was determined by collecting all seeds from individual plants and drying seeds with Drierite desiccant for two weeks prior to weighing. Average seed mass was determined by weighing batches of 100 seeds. Data show the mean ± SD of at least five plants per genotype. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). 179 Figure 3.13. (cont’d) (C) and (D) Silique length and number of seeds per silique of WT, mycT, th th th , 9 and 11 jazD and jazD mycT plants. Fully elongated 7 siliques were collected for examination of silique traits. Data show the mean ± SD of at least four plants per genotype. 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Derepression of ethylene-stabilized transcription factors (EIN3/EIL1) mediates jasmonate and ethylene signaling synergy in Arabidopsis. Proceedings of the National Academy of Sciences of the United States of America 108, 12539-12544. 191 CHAPTER FOUR - USE OF GENETIC SUPPRESSOR SCREENS TO UNCOUPLE GROWTH-DEFENSE ANTAGONISM 192 Abstract Plants deter biotic aggressors with innate immune responses that are energetically demanding and that are often accompanied by growth restriction. Despite the impact of growth-defense tradeoffs on many aspects of plant development and productivity, the molecular mechanisms connecting defense with growth are not well understood. Here, we used a genetic suppressor screen to identify EMS-induced mutants in which the slow-growth phenotype of a jaz decuple mutant (jazD) is rescued without apparent disruption of defense traits. Hypocotyl elongation assays performed with monochromatic light showed that ten of 13 suppressors of jazD (sjd) were insensitive to red light, suggesting that the underlying causal mutations are associated with red light signaling, such as PHYTOCHROME B (PHYB). Assessment of apical hook formation of the 13 sjd lines revealed that the hook curvature of sjd10 was attenuated. Comparison between jazD and two non-red-light- insensitive suppressors (sjd56 and sjd78) showed that whereas both mutants exhibited increased growth, only sjd56 retained the defense phenotypes of jazD. Subsequent characterization of these suppressors promises to identify mechanisms that uncouple growth-defense tradeoffs in plants. 193 Introduction As a consequence of their sessile nature, plant growth and development are subject to restraint by resource limitations in the microenvironment. In response to attack by biotic aggressors that consume plant tissues as a food source, plants mount various defense responses that require acquisition of photoassimilates and other nutrients (Havko et al., 2016; Guo et al., 2018a). Considerable resources are required for the biosynthesis, modification, transport and storage of defense compounds, which are largely derived from precursors in primary metabolism (Gershenzon, 1994). Therefore, defense induction is presumed to generate allocation costs that reflect partitioning to defense pathways at the expense of growth and other physiological processes (Zust and Agrawal, 2017). In addition to allocation costs, immune responses can also incur ecological costs (Simms, 1992; Karasov et al., 2017; Zust and Agrawal, 2017). For instance, high defense levels may unintentionally repel mutualists (e.g., pollinators) required for seed production (Strauss et al., 1999). Owing to the tradeoffs between growth and immunity, efforts to improve crop productivity through breeding may select against robust expression of defense traits (Chen et al., 2015). Thus, advances in understanding the molecular mechanisms that govern the antagonistic relationships between growth and defense may help to boost the development of crop varieties having both high yield and resilience to biotic stresses. Jasmonic acid and its derivatives (JAs) constitute a class of lipid-derived compounds that regulate plant immunity against insect herbivores and necrotrophic pathogens, and also play important roles in growth and reproduction (Wasternack and Hause, 2013; Guo et al., 2018a; Guo et al., 2018b; Howe et al., 2018). The bioactive form of JA, JA-Ile, is perceived by the receptor protein CORONATINE INSENSITIVE 1 (COI1) (Xie et al., 1998; Katsir et al., 2008), which is part of the Skp1/Cullin/F-box (SCFCOI1) E3 ubiquitin ligase complex that ubiquitinates 194 JASMONATE ZIM DOMAIN (JAZ) transcriptional repressors upon JA perception (Thines et al., 2007; Chini et al., 2016). Ubiquitinated JAZs are degraded by the 26S proteasome, followed by the release of JA-responsive transcription factors (TFs), the best examples of which are bHLH MYC TFs (Major et al., 2017; Howe et al., 2018). Although the mechanisms by which JA deploys immune responses against insect herbivores and pathogens have been intensively studied, it is still poorly understood how JA restricts growth. In a previous study, Campos et al. combined mutations in five JAZ genes to construct a jaz quintuple (jazQ) mutant that displays constitutive activation of JA signaling and growth-defense antagonism (Campos et al., 2016). Visual screening of jazQ mutagenized with ethyl methanesulfonate (EMS) identified suppressors that restored the slow growth of jazQ without impairing defense (Campos et al., 2016). Among these suppressors was suppressor of jazQ 11 (sjq11), which carries a null mutation in PHYTOCHROME B (PHYB), a red light receptor that inhibits the activity of growth-promoting PHYTOCHROME-INTERACTING FACTORS (PIFs) (Campos et al., 2016). Genetic reconstruction of jazQ phyB confirmed that removal of phyB in the jazQ background is sufficient to recover the growth phenotype of jazQ without compromising defense, and suggested that rewiring of JA and red light signaling pathways can allow simultaneous growth and defense (Campos et al., 2016). Despite this progress, much remains to be learned about how plant growth is impacted by various levels of defense; the constitutive defense responses exhibited by jazQ are relatively modest and do not appear to have allocation costs under the growth conditions employed (Campos et al., 2016; Guo et al., 2018b). It thus remains to be determined whether growth-defense antagonism can also be uncoupled when higher levels of defense traits generate allocation costs. 195 In this study, we exploited a recently developed jaz decuple (jazD) mutant in which growth- defense tradeoffs are much stronger than those observed in jazQ plants as a consequence of more severe depletion of JAZ repressors (Guo et al., 2018b). Screening of an EMS-mutagenized population of jazD plants identified 13 suppressors of jazD (sjd) that partially recovered the stunted growth of jazD while retaining high levels of anthocyanin accumulation as a proxy for defense traits. Most of the sjd mutants were insensitive to red light, suggesting defects in red light signaling like loss of phyB function. Among the three (sjd10, sjd56 and sjd78) non-red-light- insensitive sjd mutants, one (sjd10) displayed an attenuated apical hook phenotype. Examination of growth and defense traits revealed partial uncoupling of growth-defense antagonism in sjd56. These collective findings highlight the effectiveness of using genetic suppressor screens to uncouple growth-defense tradeoffs. 196 Results Identification of suppressors of jazD To better understand the mechanisms by which activation of plant defense pathways antagonize vegetative growth, we devised a genetic screen to identify plants that exhibit enhanced defense responses without growth penalties. We previously showed that a jaz decuple (jazD) mutant defective in ten JAZ genes (JAZ1/2/3/4/5/6/7/9/10/13) displays not only robust resistance to insect herbivores and necrotrophic pathogens, but also stunted vegetative growth and development (Guo et al., 2018b). We exploited these phenotypes of jazD as a tool to dissect the molecular components involved in growth-defense antagonism. To this end, we mutagenized jazD seeds with EMS and visually screened approximately 30,000 M2 plants for individuals that showed recovery of the slow-growth phenotype but retention of anthocyanin accumulation, a marker of JA-regulated defense (Figure 4.1A). A total of 13 suppressor of jazD (sjd) lines were identified (Table 4.1 and Figure 4.1B-G). One class of sjd mutants are insensitive to monochromatic red light Among the 13 sjd mutants identified, 11 (sjd1, sjd2, sjd4, sjd40, sjd56, sjd83, sjd93, sjd109, sjd110, sjd111 and sjd113) of them displayed similar phenotypes, including long petioles and elongated hypocotyls under white light. These phenotypes were confirmed in the M3 generation and were reminiscent of phenotypes displayed by photomorphogenic mutants. It has been shown that a null mutation of the photoreceptor gene PHYB in the jazQ background recovers the growth of jazQ without altering its defense traits (Campos et al., 2016). Thus, we hypothesized that this group of morphologically similar sjd mutants may be impaired in light signaling. To test this possibility, the hypocotyl elongation response of sjd seedlings (M3 generation) to monochromatic light was 197 compared to well-characterized photoreceptor mutants. We found that ten sjd mutants (sjd1, sjd2, sjd4, sjd40, sjd83, sjd93, sjd109, sjd110, sjd111 and sjd113) were insensitive to red light like phyB, but responded normally to both far red and blue light (Figure 4.2 and 4.3), suggesting that these suppressors carry mutations in components of red light signaling. One mutant (sjd56) responded normally to red and far red light but was insensitive to blue light like the blue light receptor mutant cry1 (Figure 4.3). The identification of multiple suppressor mutants insensitive to light perception suggests a potentially important role of light signaling pathways in JA-driven growth-defense decisions. Apical hook formation of sjd10 is attenuated The growth inhibitory properties of ethylene (Dubois et al., 2018), together with constitutive activation of ethylene responses in jazD (Guo et al., 2018b), raised the possibility that sjd mutants are impaired in ethylene signaling. To test this, we compared the apical hook curvature of dark- grown wild-type and sjd seedlings, which is a well characterized ethylene response (De Paepe and Van Der Straeten, 2005; Li and Guo, 2007). One mutant, sjd10, displayed a clearly attenuated apical hook (Figure 4.4A and 4.4B), suggesting that sjd10 may be defective in ethylene signaling. In addition to the attenuated apical hook formation, sjd10 also produced leaves that were broader than those of the jazD parental line (Table 4.1 and Figure 4.1C). However, analysis of a segregating F2 population from a sjd10 to jazD backcross showed that the broad-leaf phenotype did not co-segregate with the increased size of sjd10 rosettes (Figure 4.4C). 198 Growth-defense antagonism is partially uncoupled in sjd56 We next examined the growth and defense phenotypes of the sjd56 and sjd78 mutants, which had normal light sensitivities. Measurements of leaf biomass and projected leaf area showed that the slow-growth phenotype of jazD was partially rescued in sjd56 and sjd78 (Figure 4.5). These two suppressor mutants also accumulated leaf anthocyanins to a similar level as parental jazD (Figure 4.6A). To assess whether sjd56 and sjd78 retained resistance to necrotrophic pathogens, we inoculated leaves with Botrytis cinerea spores. Whereas sjd56 was as resistant to this pathogen as jazD, the disease lesion area on sjd78 was much larger, comparable to that of WT leaves (Figure 4.6B). Feeding assays performed with Trichoplusia ni larvae showed that sjd56, but not sjd78, maintained elevated resistance to this generalist insect herbivore (Figure 4.6C and 4.6D). These results demonstrate that sjd56 partially suppressed the growth-restriction phenotype of jazD without impairing several defense traits. In contrast to sjd56, the partial growth restoration of sjd78 was associated with loss of defense. Genetic analysis of sjd56 and sjd78 As an initial step toward identification of causal mutations in sjd56 and sjd78, sjd56 and sjd78 were each backcrossed to jazD (using jazD as the female parent), and the resulting BC1F2 populations showed segregation of rosette size for both mutants (Figure 4.7). The segregation ratios for sjd56 and sjd78 were approximately 1:7 and 1:3, respectively, and generally consistent with Mendelian inheritance (Table 4.2), suggesting that the increased growth of each mutant was caused by a single recessive mutation in each suppressor line. A second backcross used to generate BC2F2 populations validated the conclusion that increased rosette size in each mutant was likely caused by a single recessive mutation (Table 4.2 and Figure 4.8). 199 To determine whether the blue light-insensitive phenotype of sjd56 was linked to the growth phenotype, BC1F3 seeds from 15 independent BC1F2 plants exhibiting increased growth were used for hypocotyl elongation assays under blue light. The results revealed a wide range of hypocotyl lengths in these lines (Figure 4.9), indicating that blue light insensitivity of sjd56 does not appear to be linked to the increased rosette growth phenotype. 200 Discussion JA is a key modulator of plant defense responses (Wasternack, 2015). In contrast to its positive role in fending off herbivorous insects and pathogens, this hormone often negatively affects growth and reproductive fitness (Baldwin, 1998; Yan et al., 2007; Zhang and Turner, 2008; Gao et al., 2016; Guo et al., 2018a; Guo et al., 2018b), giving rise to growth-defense antagonism in plants. Elucidation of the mechanisms that mitigate JA-mediated growth inhibition may benefit agricultural practices to develop crop species with desirable growth and defense traits. A previous study using jazQ as a tool to screen for suppressors that uncouple growth-defense tradeoffs showed that rewiring of the JA and phyB signaling pathways allows plants to maintain robust growth and defense at the same time (Campos et al., 2016). However, the JA responses in jazQ are moderate, and thus the expression of defense traits in jazQ does not represent situations when defense traits are activated to an extreme extent. Here, we performed a genetic suppressor screen using jazD, in which defense responses are highly activated in comparison to jazQ (Guo et al., 2018b). Our study showed that mutations in components of the red light signaling pathway reduced the intensity of growth restriction by jazD. Comparison of growth and defense traits in jazD and sjd56 demonstrated that mutations in sjd56 partially recovered the growth traits of jazD while retaining its enhanced defense. Our findings build on previous studies (Campos et al., 2016) showing that genetic suppressor screens provide a powerful approach to better understand the antagonistic relationship between growth and JA-mediated defense. Further characterization of the sjd mutants described here should provide insight into the molecular mechanisms by which resource allocation to growth and defense pathways is regulated. Among the 13 sjd mutants identified in this study, ten were insensitive to red light (Figure 4.2A). The ratio of red (R) light to far red (FR) light is detected by the phytochrome photoreceptors, 201 including phyB (Ballare, 2014). When the ratio of R:FR is high, phyB is in its active form and inhibits the activity of PIF TFs (Bae and Choi, 2008; Fiorucci and Fankhauser, 2017), which promote cell elongation (de Lucas and Prat, 2014; Leivar and Monte, 2014). Under shading conditions when the R:FR ratio is low, phyB is inactivated and increased PIF activity enhances growth (Bae and Choi, 2008; Fiorucci and Fankhauser, 2017). Thus, simultaneous removal of phyB and JAZ may promote growth and defense at the same time by relieving repression of growth (i.e. PIFs)- and defense (i.e. MYCs)-promoting TFs. Given the previous identification of phyB as a mutation that uncouples growth-defense tradeoffs in jazQ (Campos et al., 2016), it seems likely that phyB mutations are also responsible for reverting the growth phenotype of some red light- insensitive sjd mutants described here. Genetic complementation tests and sequencing of PHYB in these mutants are needed to test this hypothesis. It will also be important to genetically reconstruct jazD phyB with a null phyB allele to exclude the possibility that spurious mutations resulting from EMS mutagenesis contribute to the phenotypes of these sjd mutations. Blue light is perceived by the cryptochrome photoreceptors (CRY1 and CRY2) (Chaves et al., 2011). Recent studies demonstrate that CRY1 and CRY2 physically interact with PIF4 and PIF5, suggesting that CRYs suppress elongation growth (Pedmale et al., 2016). However, although sjd56 was insensitive to blue light, subsequent analyses demonstrated that cry1 or cry2 (data not shown) were unlikely to be the causal mutations in this suppressor mutant. Reoccurrence of red light insensitivity but no other monochromatic light insensitivity suggests that red light signaling may perform special roles in regulating plant growth. Further studies are needed to reveal the underlining mechanisms and to verify the causal mutations in sjd56. Inspection of the apical hook revealed attenuated apical hook curvature for sjd10 (Figure 4.4A and 4.4B). The apical hook protects cotyledons and meristem tissues during seedling 202 emergence from the soil, and is mediated by a number of plant hormones, including auxin, ethylene, gibberellins, and brassinosteroids (Bleecker et al., 1988; Guzman and Ecker, 1990; Lehman et al., 1996; Achard et al., 2003; Li et al., 2004; Vriezen et al., 2004; De Grauwe et al., 2005; Vandenbussche et al., 2010). Among these hormones, previous studies have shown that JA antagonizes ethylene signaling to inhibit apical hook formation (Turner et al., 2002). MYC2 physically interacts with ETHYLENE-INSENSITIVE3 (EIN3) to attenuate its transcriptional activity in promoting apical hook curvature (Song et al., 2014). Consistent with these studies, hook curvature of jazD in response to treatment with the ethylene precursor 1-aminocyclopropane-1- carboxylic acid (ACC) is reduced (Guo et al., 2018b). The ethylene signaling cascade is activated when ethylene is recognized by members of the cognate receptor family, which in Arabidopsis consists of ETHYLENE RESPONSE 1 (ETR1), ETR2, ETHYLENE RESPONSE SENSOR 1 (ERS1), ERS2 and ETHYLENE INSENSITIVE 4 (EIN4) (Merchante et al., 2013). Perception of ethylene activates EIN2 and subsequently stabilizes EIN3 and EIN3-LIKE 1 (EIL1) TFs to induce various ethylene responses (Merchante et al., 2013). Mutants deficient in the ethylene signaling pathway (i.e. ein2-1 and ein3-1 eil1-3) exhibit reduced hook curvature in the absence of ACC (Song et al., 2014). Thus, altered apical hook formation in sjd10 raises the possibility that the ethylene signaling pathway is disrupted in this mutant. However, we cannot exclude the possibility that the attenuated hook curvature of sjd10 results from mutations of components in other hormone signaling pathways. For example, the establishment of an auxin gradient in the hypocotyl is essential for proper hook development (Schwark and Schierle, 1992). A recent study showed that a mutant defective in the auxin influx carrier LAX3 displayed reduced hook curvature without ACC treatment (Vandenbussche et al., 2010). Therefore, sjd10 could also harbor a mutation in auxin-related genes. In an F2 population derived from a cross between sjd10 and jazD, we 203 observed that rosette size and morphology did not segregate in a manner consistent with a single recessive mutation (Figure 4.4C). In future studies, it will be necessary to determine whether the attenuated apical hook formation co-segregates with the large-rosette phenotype. In addition to altered apical hook formation, ethylene retards leaf growth by suppressing cell division and cell elongation (Dubois et al., 2018). For example, one of the ethylene response factors (ERFs) BOLITA activates type II TEOSINTE BRANCHED 1/CYCLOIDEA/PCF (TCP) genes, which in turn induce RETINOBLASTOMA RELATED 1 (RBR1) (Marsch-Martinez et al., 2006). RBR1 encodes a protein that represses E2Fa by phosphorylation, and consequently inhibits progression of cell cycle into the S-phase (Marsch-Martinez et al., 2006). Another ethylene response factor ERF6 induces the gibberellin-degrading enzyme GIBBERELLIN 2-OXIDASE 6, leading to the stabilization of DELLA repressors (Dubois et al., 2013), which are associated with the inhibition of cell expansion (Claeys et al., 2014). Therefore, it is conceivable that mutations of ethylene signaling components in jazD may result in growth recovery. If the causal mutation in sjd10 is related to ethylene signaling, this mutant may be a good candidate to dissect how JA and ethylene signaling pathways act together to control growth and defense. 204 Methods jazD suppressor screen Approximately 30,000 jazD seeds were mutagenized by immersion in a solution of 0.1% or 0.2% (v/v) EMS (Sigma-Aldrich) for 16 h at room temperature, with constant agitation (Campos et al., 2016). Seeds (M1 generation) were thoroughly washed with H2O, stratified in the dark at 4 ⁰C for two days and then immediately sowed on soil. M2 seed was collected from 24 pools of self- pollinated M1 plants (approximately 1,000 M1 plants/pool). Soil-grown M2 plants were visually screened for individuals with a larger rosette size than jazD and accumulation of anthocyanin. Putative sjd (suppressor of jazD) mutants were rescreened in the M3 generation to confirm heritability of phenotypes. Genetic analysis of sjd mutants sjd mutants (M3 generation) were used as the recurring male parent for backcrossing to the jazD parental line. For segregation analysis of BC1F2 and BC2F2 populations, seeds were sowed on half-strength Linsmaier and Skoog (LS; Caisson Labs) plates supplemented with 0.8% (w/v) sucrose and stratified at 4 ⁰C in dark for four days. Plates were then transferred to a growth chamber maintained at 20 ºC and incubated for eight days under 16-h-light/8-h-dark conditions (80 μmol m-2 s-1). Seedlings were transferred to soil, in square pots containing four seedlings per pot. Potted plants were covered with a transparent plastic dome for two days and were maintained under a 16- h light (100 μmol m-2 s-1) and 8-h dark photoperiod at 20 ºC until photographed. 205 Hypocotyl elongation assays under monochromatic light WT (Col-0), jazD and sjd (M3 generation) seeds were sowed on half-strength LS plates supplemented with 0.8% (w/v) sucrose and stratified at 4 ⁰C in dark for four days. Plates were then transferred to monochromatic LED chambers outfitted to emit blue (470 ± 20 nm, 25 μmol m-2 s- 1), red (670 ± 20 nm, 50 μmol m-2 s-1) or far-red (740 ± 20 nm, 5 μmol m-2 s-1) light. As controls, the light-sensing mutants cry1-400, phyA-75 and phyB-9 and were included (Reed et al., 1993; Reed et al., 1994; Ruckle et al., 2007). WT and mutant lines were grown on the same plate to control for plate-to-plate variation. Following seven days of growth under the specified monochromatic light conditions, seedling hypocotyls were placed between transparent films and scanned for length measurement using the ImageJ software (https://imagej.nih.gov/ij/). Measurement of apical hook curvature Seedlings were grown on 0.7% (w/v) agar media containing half-strength LS salts supplemented with 0.8% (w/v) sucrose. After stratification at 4 ⁰C in the dark for three days, plates were incubated horizontally in the dark at 20 ⁰C for four days. Images of apical hook were photographed. The angle of apical hook curvature was measured by ImageJ software (https://imagej.nih.gov/ij/). The angle of apical hook curvature is defined as 180° minus (when the hook is not exaggerated) or plus (in the case of hook exaggeration) the angle between the apical part and the lower part of the hypocotyl (Vandenbussche et al., 2010). 206 APPENDIX 207 Tables and figures Table 4.1. List of sjd mutants identified in a suppressor screen. Name Suppressed jazD phenotypes Elevated defense Additional phenotypes sjd1 sjd2 sjd4 Small rosette, short petiole Small rosette, short petiole Small rosette, short petiole sjd10 Small rosette sjd40 Small rosette, short petiole ND1 ND ND ND ND Elongated hypocotyl Elongated hypocotyl Elongated hypocotyl Broad leaf Elongated hypocotyl sjd56 Small rosette, short petiole Yes Elongated hypocotyl sjd78 Small rosette sjd83 Small rosette, short petiole sjd93 Small rosette, short petiole sjd109 Small rosette, short petiole sjd110 Small rosette, short petiole sjd111 Small rosette, short petiole sjd113 1 ND, not detected. Small rosette, short petiole No ND ND ND ND ND ND ND Elongated hypocotyl Elongated hypocotyl Elongated hypocotyl Elongated hypocotyl Elongated hypocotyl Elongated hypocotyl 208 Table 4.2. Segregation of rosette size in backcross populations of sjd56 and sjd78. Mutant Backcross population1 sjd-like jazD-like Segregation ratio (sjd-like : jazD-like) P value (Chi-squared test) sjd56 sjd78 sjd56 sjd78 BC1F2 95 BC1F2 BC2F2 BC2F2 125 120 114 657 370 579 348 1:7 1:3 1:5 1:3 < 0.001 0.897 < 0.001 0.872 1 Segregating F2 populations derived from crossing the indicated sjd mutants to jazD were visually scored for rosette size (small jazD-like rosettes or larger sjd-like rosettes). 209 Figure 4.1. Identification of suppressor of jazD (sjd) mutants. 210 Figure 4.1. (cont’d) (A) Schematic diagram of suppressor screens of jazD. jazD seeds were mutagenized by EMS and visually screened for mutants (M2 generation) that partially recovered the slow-growth phenotype of jazD while retaining elevated anthocyanin levels. (B-G) Photographs of WT, jazD and sjd plants (M3 generation) grown under long-day (16-h- light/8-h-dark) conditions. Sets of plants were photographed at different ages: (A) 34-day-old; (B- C) 30-day-old; (D-E) 34-day-old; and (F) 36-day-old. Scale bars, 1 cm. 211 Figure 4.2. Sensitivity of sjd mutants to red and far red light. (A) and (B) Hypocotyl lengths of sjd mutants grown under red (A; 50 μmol m -2 -1 s ) and far-red (B; -2 -1 s 5 μmol m ) light. Seedlings were grown for seven days on half-strength LS agar plates supplemented with 0.8% (w/v) sucrose. Data show the mean ± SD of at least ten seedlings per genotype. Asterisks denote significant differences compared to jazD according to Student’s t-test (P < 0.05). 212 Figure 4.3. sjd56 is insensitive to blue light. Hypocotyl lengths of sjd mutants grown under blue (25 μmol m ) light. Seedlings were grown for seven days on half-strength LS agar plates supplemented with 0.8% (w/v) sucrose. Data show the mean ± SD of at least ten seedlings per genotype. Asterisks denote significant differences compared to jazD according to Student’s t-test (P < 0.05). s -2 -1 213 Figure 4.4. Apical hook curvature of sjd10 is attenuated. (A) Representative apical hooks of WT, jazD and sjd10 seedlings grown for four days in dark on half-strength LS agar plates supplemented with 0.8% (w/v) sucrose. (B) Angles of WT, jazD and sjd10 apical hooks measured by ImageJ. Data show the mean ± SD of at least ten seedlings per genotype. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). (C) Photograph of sjd10 (M3 generation), jazD and a BC1F2 population of sjd10. Seedlings were started on half-strength LS agar plates supplemented with 0.8% (w/v) sucrose for eight days followed by 14 d growth under a 16 h light/8 h dark photoperiod after transferring to soil. The blue arrows denote F2 plants that show the broad-leaf phenotype without recovery of rosette size. The red arrows denote F2 plants that display the large-rosette phenotype without changes in leaf morphology. Scale bars, 1 cm. 214 Figure 4.5. sjd56 and sjd78 partially recover the slow growth of jazD. (A) and (B) Dry weight (A) and projected leaf area (B) were determined for 30-day-old plants grown under long-day conditions. Data show the mean ± SD of at least eight plants per genotype. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). 215 Figure 4.6. sjd56 maintains the elevated defense of jazD. (A) Anthocyanin levels of 23-day-old WT, jazD, sjd56 and sjd78 plants. Data show the mean ± SD of five plants per genotype. Capital letters denote significant differences according to Tukey’s HSD test (P < 0.05). (B) Necrotic lesion area measured five days after infection with Botrytis cinerea. Data show the mean ± SD of at least eight leaves per genotype. (C) Photograph of representative T. ni larvae after ten days of feeding on WT, jazD, sjd56 and sjd78 plants. Scale bars, 0.5 cm. (D) Weights of T. ni larvae reared on WT, jazD, sjd56 and sjd78 plants. Data show the mean ± SD of at least 30 larvae per genotype. 216 Figure 4.7. BC1F2 populations of sjd56 and sjd78. 217 Figure 4.7. (cont’d) (A) and (B) Photographs of sjd56 (A) and sjd78 (B) mutants (M3 generation), jazD and their BC1F2 populations. Seedlings were started on half-strength LS agar plates supplemented with 0.8% (w/v) sucrose for eight days followed by 28 d growth under a 16 h light/8 h dark photoperiod. Scale bars, 1 cm. 218 Figure 4.8. BC2F2 populations of sjd56 and sjd78. 219 Figure 4.8. (cont’d) (A) and (B) Photographs of wildtype Col-0 (WT) with sjd56 (A) and sjd78 (B) mutants (M3 generation), jazD and their BC2F2 populations. Seedlings were started on half- strength LS agar plates supplemented with 0.8% (w/v) sucrose for eight days followed by 22 d growth under a 16 h light/8 h dark photoperiod. Scale bars, 1 cm. 220 Figure 4.9. The blue light-insensitive phenotype of sjd56 is not associated with its growth phenotype. 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Identification of JA signaling components, including the receptor CORONATINE INSENSITIVE 1 (COI1) (Xie et al., 1998), the transcriptional repressor JASMONATE ZIM-DOMAIN (JAZ) proteins (Thines et al., 2007; Yan et al., 2007; Chini et al., 2018), and the bHLH MYC and other JA-responsive transcription factors (TFs) (Chini et al., 2007; Thines et al., 2007; Howe et al., 2018), marked key steps to reveal the mechanisms by which JA reprograms gene expression. Among the major tasks performed by JA is activation of defense gene expression in response to challenge by biotic aggressors (Farmer and Ryan, 1990; Howe et al., 1996). Interestingly, JA-induced expression of defense traits is often accompanied by growth restriction (Havko et al., 2016). One theory to explain the growth inhibition imposed by JA is that transcriptional networks are hardwired to restrict growth upon activation of JA signaling cascade (Campos et al., 2016). This notion is supported by the successful unlocking of growth-defense tradeoffs through relief of transcriptional repression of the JA and phyB signaling pathways (Campos et al., 2016). Detailed characterization of the jaz quintuple (jazQ) mutant has shown that the strength of growth-defense antagonism in the mutant is relatively weak, which may explain the ability of a phyB mutation to completely rescue the growth defect of jazQ without compromising defense (Campos et al., 2016). It was therefore of interest to develop higher-order jaz mutants in which severe JAZ depletion strongly activates defense responses. Towards this goal, a major focus of this dissertation was detailed physiological, and biochemical characterization of higher-order jaz mutants. 229 Another interpretation of JA-mediated growth-defense tradeoffs is that investment of metabolic resources in defense restricts the allocation of resources to vegetative and reproductive growth (Zust and Agrawal, 2017). At the time this dissertation research was initiated, there was little direct evidence to support this “metabolic tradeoff” hypothesis (Coley et al., 1985; Herms and Mattson, 1992; Heil and Baldwin, 2002; Stamp, 2003; Havko et al., 2016; Kliebenstein, 2016). The investigation of how JA affects resource allocation has been hindered by functional redundancy within the JAZ protein family (Chini et al., 2016). To help resolve the question, we constructed a jaz decuple (jazD) mutant defective in ten JAZ genes (JAZ1/2/3/4/5/6/7/9/10/13), as described in Chapter Two of this dissertation. Characterization of this higher-order jaz mutant showed that the JA signaling pathway is constitutively activated upon JAZ depletion. Correspondingly, jazD exhibits increased resistance to insect herbivores and necrotrophic pathogens compared to WT and jazQ. Global transcript and protein profiling suggested that resource allocation to defense-related metabolic pathways is highly elevated in jazD. Results obtained from these omics analyses were supported by direct measurements of defense compounds (e.g., indole glucosinolates) and increased rates of cellular respiration. The enhanced expression of defense traits in jazD leaves appeared to be linked to depletion in carbon reserves, as determined by a modest reduction in starch and sucrose levels. The slow growth of jazD leaves and roots was also associated with symptoms of sugar starvation and defects in reproductive fitness. My findings suggest that JAZ proteins function to fine-tune the expression level of defense traits. In the absence of biotic attack, JAZ proteins repress the JA signaling cascade to limit resource allocation to defense pathways. Under these conditions, the plant appears 230 to prioritize the use of photoassimilates and other resources for growth and seed production. When plants experience mild attack from insects or microbes, elevated JA levels lead to JAZ degradation, which in turn triggers immune responses. The rapid induction of JAZ genes in JA-elicited cells likely leads to de novo synthesis of JAZ repressors that exert negative feedback control on the pathway. In this way, JAZ proteins play an important role in mitigating the high cost of induced defense responses, and growth restriction mainly comes from rewiring of signaling networks connected with JA, which is similar to the situation in jazQ. However, as the biotic stress escalates past a threshold level, more JAZs are depleted and defense traits are expressed to an extreme extent that starves plants for carbon and other nutrients. It is conceivable that this signal is sensed by unknown mechanisms, and that plants adjust their growth rates accordingly. JAZ proteins execute JA outputs by targeting various JA-responsive TFs, the most intensively studied of which are the basic helix-loop-helix (bHLH) MYC TFs, including MYC2, MYC3 and MYC4 (Chini et al., 2007; Thines et al., 2007; Fernandez-Calvo et al., 2011). To determine whether MYC TFs are required for defense responses observed in jazD, we introduced T-DNA insertion mutations that disrupt one, two or three members among MYC2, MYC3 and MYC4 in the jazD genetic background. Comparison of the resulting jazD myc mutants to WT, jazD, and mycT lines showed that the defense traits of jazD, including elevated resistance to insect and pathogen attack, are dependent on MYC2/3/4. Among the three MYCs, MYC3 plays dominant roles in driving tryptophan flux and plant resistance to necrotrophic pathogens. Interestingly, we discovered that the formation of endoplasmic reticulum (ER)-derived structures called ER bodies, which are repositories for defense-related β-glucosidases, is constitutively activated in jazD leaves. 231 Further analyses showed that the induction of ER body genes in jazD is mediated by MYC TFs, especially MYC2 and MYC3. These results indicate that MYC TFs largely account for the allocation of resources to defense-related processes in jazD, and that MYC2/3/4 perform overlapping and distinct functions in metabolic reprogramming. However, we found that loss of MYC2/3/4 does not fully restore the slow-growth phenotype of jazD. It is possible that additional JAZ-interacting factors contribute to the growth phenotype of jazD. Given the fact that defense responses are strongly and constitutively activated in jazD, this mutant provides a tool to investigate the antagonistic relationship between growth and defense without having to impose actual biotic stress. Chapter Four of this dissertation describes an ethyl methanesulfonate (EMS)-based genetic screen to identify suppressors of jazD in which growth is partially recovered without impeding defense. The screen identified 13 suppressors of jazD (sjd) that display increased growth while accumulating similar levels of anthocyanin compared to jazD. Hypocotyl elongation assays performed under monochromatic light showed that ten sjd mutants are insensitive to red light, suggesting that they carry mutations in components of the red light signaling pathway. Evaluation of apical hook formation of sjd mutants showed that one red light-sensitive mutant (sjd10) exhibits attenuated formation of apical hook. Therefore, we speculate that sjd10 may harbor mutations in genes involved in regulating hook formation (i.e. genes in auxin- and ethylene-signaling pathways). Finally, measurement of growth and defense parameters showed that the red light-sensitive sjd56 mutant partially recovers the stunted growth of jazD while maintaining enhanced resistance to insect herbivores and necrotrophic pathogens. Thus, our screen of EMS-mutagenized jazD successfully 232 identified mutants that uncouple growth-defense tradeoffs. Characterization of theses mutants in the future may shed light on the molecular mechanisms that govern plant growth and immunity. To summarize, research in this dissertation demonstrates that JAZ proteins promote growth and fertility by preventing detrimental metabolic processes triggered by unrestrained JA responses. The bHLH MYC TFs play a key role in mediating resource allocation to defense pathways, and also appear to mediate growth restriction. The use of suppressor screens further showed that growth-defense tradeoffs observed in jazD can be uncoupled. 233 Future perspectives In the past five years, many discoveries have advanced our understanding of JA biology and how this hormone impacts plant performance. The crystal structure has been resolved for JAZ proteins interacting with MYC TFs, revealing how JAZ proteins switch between the repressor function and the co-receptor function (Zhang et al., 2015). MED25 was found to physically interact with COI1 and facilitate COI1-dependent degradation of JAZ repressors (An et al., 2017). Uncoupling of growth and defense antagonism was achieved through genetic removal of JAZ and phyB proteins (Campos et al., 2016). The role of MYC TFs in modulating growth-defense balance was also elucidated (Major et al., 2017). Furthermore, a number of novel interactions between JAZ proteins and TFs were identified (Hu et al., 2013b; Zhao et al., 2013; Jiang et al., 2014; Boter et al., 2015; Zhai et al., 2015), and these findings greatly expanded the scope of physiological processes regulated by JA. Collectively, these findings establish JAZ proteins as an integrative hub of JA signaling that exerts master control over growth, defense and various other physiological processes. However, many interesting questions remain to be answered. Although it is known that JA signaling switches on the production of defense compounds, the quantitative analyses showing how JA reconfigures carbon distribution among diverse metabolic pathways remain an open question. Isotopic labelling is one way to directly measure the incorporation of carbon into different metabolites. For example, 14CO2 labeling was employed to track assimilated carbon in both source and sink tissues of Arabidopsis (Kolling et al., 2015). In another study, Hanik et al. used 11CO2 labeling to track carbon partitioning into several metabolite pools in Nicotiana tabacum upon MeJA treatment (Hanik et al., 2010). They revealed that MeJA increased carbon partitioning into 234 aromatic amino acids (i.e. tryptophan) in the shikimate acid pathway (Hanik et al., 2010). In Chapter Two of this dissertation, changes of carbon allocation to growth and defense pathways in higher-order jaz mutants were discerned from global transcript and protein profiling. These mutants are good candidates for isotopic carbon labeling to better understand how JA remobilizes carbon during the growth to defense transition. Much of the research aimed at understanding JA-mediated resource tradeoffs has concerned tradeoffs imposed by biotic stresses. However, increasing evidence has implicated JA in the control of abiotic stress responses, including those triggered by low temperature, drought and high salinity. A subgroup of JAZ proteins physically interact with INDUCER OF CBF EXPRESSION (ICE) TFs that regulate plant resilience to cold stress (Hu et al., 2013b). This study showed that exogenous JA enhances plant tolerance to cold (Hu et al., 2013b). In addition, several lines of evidence suggest that the JA-responsive TF MYC2 is involved in abscisic acid (ABA) signaling (Kazan and Manners, 2013), which is triggered by water deficiency and high salinity (Osakabe et al., 2014). The expression of MYC2 can be induced by ABA and drought stress, and MYC2 overexpressing plants displayed increased ABA sensitivity (Abe et al., 2003). However, the role of MYC2 in drought tolerance is not conclusive. Transgenic plants overexpressing both MYC2 and MYB2, another drought-inducible MYB TF, exhibited decreased electrolyte leakage upon mannitol treatment, suggesting that MYC2 positively regulates plant resilience to drought (Abe et al., 2003). By contrast, the myc2 mutant has been reported to be more tolerant to drought (Harb et al., 2010). Our preliminary data showed that jazD exhibited increased sensitivity to exogenous ABA treatment with respect to seed germination, and this hypersensitivity was not observed in jazD mycT (data now shown). Therefore, the higher- 235 order jaz mutants may be valuable tools to study how JA contributes to drought tolerance. Further studies are needed to provide more information about how these mutants perform under abiotic stresses and how JA remodels resource allocation to growth and resilience under abiotic stresses. ER bodies are ER-derived structures that contain several defense proteins, including β-glucosidases and plant defensins (Watanabe et al., 2013; Nakano et al., 2014). Although the induction of ER body formation by exogenous MeJA was demonstrated more than 15 years ago (Matsushima et al., 2002), the mechanisms by which JA triggers the proliferation of this specialized structure remain unclear. We provide evidence in Chapter Three that the JAZ-MYC transcriptional module regulates the expression of ER body genes. However, molecular and biochemical analyses (e.g. chromatin immunoprecipitation sequencing) are required to determine whether MYC TFs induce ER body genes through direct binding to their promoters. It also remains to be determined how ER bodies are disrupted upon insect attack to release stored defense proteins. Advances in understanding growth-defense tradeoffs raise the possibility that these two physiological processes can be uncoupled. Suppressor screens starting with jazQ identified a mutant exhibiting heightened growth and defense traits as a result of phyB mutation (Campos et al., 2016). Likewise, screens for suppressors of jazD (Chapter Four) are expected to reveal new mechanisms that unlock growth-defense tradeoffs. Future studies will search for the causal mutations in sjd mutants and explore the molecular mechanisms that disconnect growth and defense. In addition to rewiring distinct signaling pathways, an alternative to uncouple JA-mediated growth-defense antagonism is to manipulate components of JA metabolism or signaling pathways. Loss-of-function 236 mutations that impair enzymes (e.g. JAO2/JOX) involved in JA catabolism were shown to promote plant resistance against fungal pathogens while retaining normal growth rates (Caarls et al., 2017; Smirnova et al., 2017). In another study, RNAi lines of JASMONATE- ASSOCIATED VQ MOTIF GENE 1 (JAV1), which also functions to repress JA signaling, displayed increased resistance to insect attack without obvious changes in growth traits (Hu et al., 2013a). Application of this collective knowledge to develop agricultural crops that maintain optimal growth and defense is an important direction for future research. The development of CRISPR technology to modify genomes in a timely manner will facilitate this process. Taken together, characterization of the physiological roles of JAZ proteins have ushered in a new era of understanding how plants manage their resource balance in harsh environments. Large-scale omics analyses, mathematical modeling and novel genetic modification tools will assist the quest to uncover how JA exerts control over various physiological traits to maximize plant fitness in response to dynamic environmental cues. 237 REFERENCES 238 REFERENCES Abe, H., Urao, T., Ito, T., Seki, M., Shinozaki, K., and Yamaguchi-Shinozaki, K. (2003). Arabidopsis AtMYC2 (bHLH) and AtMYB2 (MYB) function as transcriptional activators in abscisic acid signaling. Plant Cell 15, 63-78. 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