Valentin Marquis

Ekaterina Smirnova

Stéfanie Graindorge

Pauline Delcros

Claire Villette

Julie Zumsteg

Dimitri Heintz

Thierry Heitz
email: thierry.heitz@ibmp-cnrs.unistra.fr

Broad-spectrum stress tolerance conferred by suppressing jasmonate signaling attenuation in Arabidopsis JASMONIC ACID OXIDASE (JAO) mutants

Keywords: basal defense, drought, jasmonate, JAO/JOX, metabolism, stress tolerance

Jasmonate signaling for adaptative or developmental responses generally relies on an increased synthesis of the bioactive hormone jasmonoyl-isoleucine (JA-Ile), triggered by environmental or internal cues. JA-Ile is embedded in a complex metabolic network whose upstream and downstream components strongly contribute to hormone homeostasis and activity. We previously showed that JAO2, an isoform of four Arabidopsis JASMONIC ACID OXIDASES, diverts the precursor jasmonic acid (JA) to its hydroxylated form HO-JA to attenuate JA-Ile formation and signaling. Consequently, JAO2-deficient lines have elevated defenses and display improved tolerance to biotic stress. Here we further explored the organization and regulatory functions of the JAO pathway. Suppression of JAO2 enhances the basal expression of nearly 400 JAregulated genes in unstimulated leaves, many of which being related to biotic and abiotic stress responses. Consistently, non-targeted metabolomic analysis revealed the constitutive accumulation of several classes of defensive compounds in jao2-1 mutant, including indole glucosinolates and breakdown products. The most differential compounds were agmatine phenolamides, but their genetic suppression did not alleviate the strong resistance of jao2-1 to Botrytis infection. Furthermore, jao2 alleles and a triple jao mutant exhibit elevated survival capacity upon severe drought stress. This latter phenotype occurs without recruiting stronger abscisic acid responses, but relies on enhanced JA-Ile signaling directing a distinct survival pathway with MYB47 transcription factor as a candidate mediator. Our findings reveal the selected spectrum of JA responses controlled by the JAO2 regulatory node and highlight the potential of modulating basal JA turnover to pre-activate mild transcriptional programs for multiple stress resilience.

INTRODUCTION

Jasmonates (JAs) constitute a conserved class of fatty acid derivatives endowed with regulatory functions that are recruited throughout the plant life cycle, from germination to reproduction. JAs contribute to the capacity of plants to cope with their interacting organisms, beneficial or pathogenic, and are central to a conserved antagonism between growth and defense (Campos et al., 2014;Guo et al., 2018;Wasternack and Hause, 2013). JAs were initially described as positive regulators of transcriptional responses to attacks by herbivore insects or microbial infections, but extensive research has assigned additional roles in responses to many abiotic stresses such as drought, salt, light, extreme temperatures or nutrient stress [START_REF] Ali | Jasmonic Acid Signaling Pathway in Response to Abiotic Stresses in Plants[END_REF]Kazan, 2015;Raza et al., 2020). Under such various threats, the JA pathway engages complex interactions with other hormonal pathways to coordinate adequate biochemical or anatomical changes resulting in enhanced tolerance.

Synthesis of jasmonic acid (JA), the name-giving compound and hormone precursor, is initiated in plastids when linolenic acid (C18:3) is oxygenated to an allene oxide intermediate and further cyclized to 12-oxo-phytodienoic acid (OPDA), the first jasmonate in the pathway. OPDA is quite abundant in Arabidopsis, and is partially converted to JA in the peroxisomes before being released in the cytosol [START_REF] Marquis | Stress-and pathway-specific impacts of impaired jasmonoyl-isoleucine (JA-Ile) catabolism on defense signalling and biotic stress resistance[END_REF]Schaller and Stintzi, 2009;Wasternack and Hause, 2013).

Although triggering massive transcriptional reprogramming and physiological responses when applied exogenously, JA is an inactive pro-hormone, and its endogenous activation occurs through JASMONATE RESPONSE 1 (JAR1)-catalyzed conjugation into jasmonoyl-isoleucine (JA-Ile) (Staswick and Tiryaki, 2004), one among many possible metabolic fates [START_REF] Marquis | Stress-and pathway-specific impacts of impaired jasmonoyl-isoleucine (JA-Ile) catabolism on defense signalling and biotic stress resistance[END_REF][START_REF] Miersch | Hydroxylated jasmonates are commonly occurring metabolites of jasmonic acid and contribute to a partial switch-off in jasmonate signaling[END_REF].

Under non-stressed conditions, JA-Ile levels are very low in most organs, particularly in leaves and roots, and target transcription factors (TFs) are kept silent by a suite of JASMONATE ZIM-DOMAIN (JAZ) repressor proteins and associated co-repressors [START_REF] Pauwels | The JAZ proteins: a crucial interface in the jasmonate signaling cascade[END_REF].

When JA-Ile formation occurs upon stress or endogenous signals, the hormone acts as a ligand to assemble co-receptors whose core components are various JAZ protein(s) and the F-box protein CORONATINE INSENSITIVE 1 (COI1). COI1-JAZ complexes are then recruited into E3 ubiquitin ligases that ubiquitinate JAZ and signal their subsequent proteolytical degradation, resulting in de-repression of responses (Chini et al., 2007;Thines et al., 2007). Specificity in responses to various stimuli can be achieved by a single hormone through combinatorial complexity at the co-repressor level, tissue-or cell-specific expression of components of the

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This article is protected by copyright. All rights reserved pathway, different sensitivities to variable hormone concentrations, or a combination of these different processes (Chini et al., 2016).

While the biochemical pathway leading to JA-Ile is well-defined [START_REF] Marquis | Stress-and pathway-specific impacts of impaired jasmonoyl-isoleucine (JA-Ile) catabolism on defense signalling and biotic stress resistance[END_REF]Wasternack and Song, 2017), several aspects of its regulation are still unclear. The JAs content in various plant organs is highly variable due to distinct expression patterns of genes encoding JA biosynthetic and modification activities [START_REF] Miersch | Hydroxylated jasmonates are commonly occurring metabolites of jasmonic acid and contribute to a partial switch-off in jasmonate signaling[END_REF]. Upon stress in vegetative tissues such as leaves, a coordinated activation of the pathway leads to the increased accumulation of JA and its derivatives; however, JA-Ile shows specific dynamics with rapid changes in its biosynthesis and turnover (Glauser et al., 2008;Heitz et al., 2012;[START_REF] Koo | Cytochrome P450 CYP94B3 mediates catabolism and inactivation of the plant hormone jasmonoyl-L-isoleucine[END_REF]. JA-Ile homeostasis is subjected to tight control by two catabolic JA-Ile pathways (Figure S1) that have been best characterized in Arabidopsis [START_REF] Koo | Metabolism of the plant hormone jasmonate: a sentinel for tissue damage and master regulator of stress response[END_REF], along with evidence in Nicotiana [START_REF] Luo | COI1-Regulated Hydroxylation of Jasmonoyl-Lisoleucine Impairs Nicotiana attenuata's Resistance to the Generalist Herbivore Spodoptera litura[END_REF] and rice (Hazman et al., 2019;[START_REF] Mao | Natural variation in the HAN1 gene confers chilling tolerance in rice and allowed adaptation to a temperate climate[END_REF]. In Arabidopsis, JA-Ile undergoes oxidation by three cytochromes P450 of the CYP94 subfamily, generating the less active 12OH-JA-Ile and the inactive 12COOH-JA-Ile derivatives (Heitz et al., 2012;Jimenez-Aleman et al., 2019;[START_REF] Kitaoka | Arabidopsis CYP94B3 encodes jasmonyl-L-isoleucine 12hydroxylase, a key enzyme in the oxidative catabolism of jasmonate[END_REF][START_REF] Koo | Cytochrome P450 CYP94B3 mediates catabolism and inactivation of the plant hormone jasmonoyl-L-isoleucine[END_REF]Poudel et al., 2019). JA-Ile is also prone to deconjugation by the amido-hydrolases (AH) IAR3 and ILL6 that also act on 12OH-JA-Ile to generate JA and 12OH-JA from these respective substrates (Widemann et al., 2013;Zhang et al., 2016) (Figure S1). The genetic inactivation of these catabolic pathways has profound metabolic impacts, as it strongly increases the stress-triggered JA-Ile pool and extends hormone half-life. The extensive characterization of various mutant lines further revealed that several abundant JAs accumulated after stress originated from dynamic catabolism of JA-Ile (Heitz et al., 2012;[START_REF] Koo | Cytochrome P450 CYP94B3 mediates catabolism and inactivation of the plant hormone jasmonoyl-L-isoleucine[END_REF][START_REF] Marquis | Stress-and pathway-specific impacts of impaired jasmonoyl-isoleucine (JA-Ile) catabolism on defense signalling and biotic stress resistance[END_REF]Widemann et al., 2013). Hence, a function of the AH and CYP94 pathways is to ensure a rapid clearance of JA-Ile pulses when the hormonal signal has been transmitted. Using higher order mutants in each pathway, [START_REF] Marquis | Stress-and pathway-specific impacts of impaired jasmonoyl-isoleucine (JA-Ile) catabolism on defense signalling and biotic stress resistance[END_REF] showed that unexpectedly, blocking JA-Ile catabolism had pathway-specific impacts on insect or fungal resistance, and that the outcome of the interaction with aggressors was more correlated with the transcriptional behavior (overinduced or not) of negative regulators such as JAZ or JAM than with actual JA-Ile levels. This means that the JA-Ile response circuitry integrates built-in negative feedback loops that prevent overwhelming defense, and that engineering impaired JA-Ile catabolism in Arabidopsis does not provide a trivial strategy to boost resistance to various pests. Nevertheless, natural variability in CYP94-mediated JA-Ile catabolism has been reported in rice and allowed adaptation of this crop species to a temperate climate [START_REF] Mao | Natural variation in the HAN1 gene confers chilling tolerance in rice and allowed adaptation to a temperate climate[END_REF].

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Upstream of JA-Ile in the biochemical pathway, the metabolic fate of precursor JA is also a potential regulatory node for JA-Ile signaling (Heitz et al., 2019). JA can be converted to numerous derivatives by hydroxylation, sulfation, glucosylation, decarboxylation or various conjugations (Heitz et al., 2016;Wasternack and Strnad, 2018). The enzymes responsible for many of these modifications and their physiological significance remain unclear. In early investigations, the potential for diverting JA metabolic flux was demonstrated by ectopically expressing Arabidopsis JA methyl-transferase (JMT) in Nicotiana attenuata. Basal jasmonate levels did not differ from wild-type (WT) but upon insect challenge, the JA pool was strongly directed towards methyl-JA with an associated reduction in JA-Ile-dependent direct and indirect defenses, and an increase in insect herbivory (Stitz et al., 2011). However, it was not determined if suppression of JMT affected JA-Ile homeostasis and signaling. Likewise, hydroxylation of free JA and further decoration by sulfation into HSO 4 -JA or glycosylation is a common modification conserved in many plant species [START_REF] Miersch | Hydroxylated jasmonates are commonly occurring metabolites of jasmonic acid and contribute to a partial switch-off in jasmonate signaling[END_REF]. Only recently was the elusive enzymatic JA hydroxylation pathway characterized in plants. Besides the deconjugation of 12OH-JA-Ile providing an indirect route for 12OH-JA formation (Widemann et al., 2013), a direct hydroxylation activity has been assigned to an Arabidopsis subclade of four 2-oxoglutarate-dependent dioxygenases named JASMONIC ACID OXIDASES (JAO1 to 4) (Smirnova et al., 2017)) or JASMONATE-INDUCED OXYGENASES (JOX) [START_REF] Caarls | Arabidopsis JASMONATE-INDUCED OXYGENASES down-regulate plant immunity by hydroxylation and inactivation of the hormone jasmonic acid[END_REF] (Figure S1). JAO/JOX readily hydroxylate JA in vitro, and their genes are co-induced with the JA pathway upon stress situations including leaf wounding or fungal infection. We previously showed by genetic analysis that, despite of having no obvious impact on steady-state JA-Ile levels, suppression of JAO2 expression results in elevated expression of antimicrobial defense markers and strong resistance to Botrytis cinerea infection (Smirnova et al., 2017). JAO2 identifies an important metabolic regulatory mechanism that represses some basal JA defense responses in WT plants by diverting JA from JA-Ile formation. In addition, a quadruple joxQ mutant was also characterized for enhanced tolerance to insect attacks and reduced growth [START_REF] Caarls | Arabidopsis JASMONATE-INDUCED OXYGENASES down-regulate plant immunity by hydroxylation and inactivation of the hormone jasmonic acid[END_REF]. Recently, it was reported that silencing JA hydroxylases in N. attenuata enhances JA-Ile-mediated defenses and resistance against Spodoptera litura larvae (Tang et al., 2020).

Here we further investigated the architecture of AtJAO2 action at the whole plant level and the spectrum of responses that are affected in leaves by its genetic suppression. We show that although JAO2 displays below-and above-ground sites of expression, only its suppression in leaves de-represses defenses in this organ. We determined through global transcriptome and non-targeted metabolomic analysis that JAO2 deficiency derepresses a subset of JA-regulated genes with subsequent overaccumulation of different classes of defensive compounds. A number

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This article is protected by copyright. All rights reserved of transcription factors associated with abiotic stress tolerance are also upregulated in jao2-1 mutant, suggesting a broader impact of the mutation on stress resilience. We found that jao2 alleles and a triple jao mutant line displayed a strongly enhanced survival rate under severe drought stress. This response was suppressed by jar1 mutation and seemed to antagonize with the abscisic acid pathway.

RESULTS

Complex developmental JAO2 expression patterns determine foliar defense repression

We previously showed that among the 4-member AtJAO sub-clade, JAO2, JAO3 and JAO4 expression was readily induced in leaves reacting to Botrytis inoculation (Smirnova et al., 2017).

To determine if additive effects on leaf pathogen defense could be detected in multiple jao mutants, we examined basal defense levels and fungal resistance in single jao2-1, jao3-1, jao4-2, in three combinations of double mutants, and in a triple jao2-1 jao3-1 jao4-2 (jaoT) mutant.

PDF1.2 is a sensitive marker to probe JA signaling in leaves, and its expression was specifically elevated in jao2-1, while in jao3-1 and jao4-2, its transcripts remained at low, WT levels (Figure S2a). Only double or triple mutant lines bearing the jao2-1 mutation displayed elevated PDF1.2 expression, with no additive effect of inactivating the other JAOs. Resistance to B. cinerea infection, monitored as necrotic lesion diameter, was strong and similar in all JAO2-deficient lines, strictly reflecting elevated PDF1.2 expression (Figure S2b). These results suggest that the sole inactivation of JAO2 accounts for de-repressed antimicrobial leaf defense and that no synergistic effects of other JAO mutations could be measured in this assay.

To investigate the pattern of JAO2 expression in plants, we developed a reporter line consisting in a JAO2-GUS translational fusion driven by its native promoter, which was introduced in the jao2-1 background (jao2-1::JAO2p-JAO2-GUS). The functionality of the JAO2-GUS fusion was tested by assessing defense levels by RT-qPCR. Expression of JAO2-GUS in jao2-1 reverted constitutive expression of ORA59 and its target PDF1.2 back to low, WT levels in two independent lines (Figure S3a). This was correlated with a loss of resistance to B. cinerea infection (Figure S3b), indicating functional complementation of the jao2-1 mutant. Line jao2-1::JAO2p-JAO2-GUS#3 (hereafter called GUS#3) was further used to study spatial distribution of JAO2 expression in plants. In 10-days old seedlings, histochemical GUS staining identified roots as the organ displaying strongest signal (Figure 1a1). Staining was homogeneous across main and secondary roots, but close-up observation showed exclusion from central cylinder and

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meristematic zone of main root. Moderate GUS signal was also visible in leaf vasculature. Plants were examined at later stages for expression in aerial parts. In 20-d old plants, GUS staining was apparent in younger leaves, whereas older leaves showed little or no signal (Figure 1a2). At 35 days (Figure 1a3), GUS staining extended over youngest leaves and was gradually limited to leaf margins as leaves aged (Figure 1a3). Fully-developed leaves were essentially devoid of signal. In flowers, JAO2-GUS stained mostly anther filaments and the abscission zone (Figure 1a4).

Finally, in agreement with JAO gene induction by biotic stress (Smirnova et al., 2017), JAO2-GUS signal was apparent in the periphery of B. cinerea necrotic lesions (Figure 1a5), but only sporadic signal was associated with the response to mechanical wounding (Figure 1a6). As root tissue exhibited stronger JAO2 expression than leaves at the vegetative stage (Figure 1b), the question arises as to whether expression of JAO2 in roots or in leaves accounts for repression of basal JA defenses in WT leaves (Smirnova et al., 2017). To address this question, we conducted reciprocal grafts between WT and jao2-1 backgrounds to dissociate these two sites of expression; after recovery, plants were cultivated for 3 weeks in soil, and basal defense was then assessed in leaves by monitoring transcripts for ORA59 and its target genes PDF1.2 and PATHOGENESIS-RELATED PROTEIN 4 (PR4). Defense markers were elevated only in combinations where JAO2 expression was disrupted in leaves, whereas abolition of JAO2 expression in roots did not turn on defense in leaves (Figure 1c). This result shows that JAO2 expression in WT leaves is solely responsible for repressing basal JA-dependent defense marker genes locally in leaves.

Given the age-dependent expression distribution revealed in GUS#3 line, we attempted to dissect the architecture of the JAO2 repression system at a single leaf resolution. We numbered the successive leaves according to Farmer et al., (2013), leaf 1 being the first leaf emerging after cotyledons and higher numbers designating younger leaves (Figure 2a). Leaves were collected from three individual plants from each WT, jao2-1 and GUS#3 genotype, by combining two successive leaves for each plant. Relative JAO2 and PDF1.2 transcript levels were determined in this material by RT-qPCR. JAO2 transcripts were relatively stable in older leaves, and their abundance dropped in younger leaves (Figure 2b). Consistently, JAO2-GUS transcripts in GUS#3 complemented line exhibited a decreasing gradient from older to younger leaves. Basal PDF1.2 expression was extremely low throughout WT and GUS#3 leaves (Figure 2b), but in jao2-1 leaves, high transcript accumulation was evidenced in oldest leaves (4-11, peaking in leaves 6-7), matching elevated JAO2 expression in corresponding WT leaves (Figure 2b). To further investigate an apparent discrepancy between higher JAO2 transcript levels in older leaves and higher JAO2-GUS protein signal in young leaves (Figure 1a), we complemented the jao2-1

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This article is protected by copyright. All rights reserved mutant with a 4x-myc-tagged version of JAO2 (jao2-1::JAO2p:JAO2-4xmyc). Western-blot analysis confirmed that JAO2-myc protein was preferentially detected in younger leaves, particularly 11 to 18 (Figure 2c). Collectively, these data illustrate the differential basal accumulation pattern of JAO2 transcript and protein in distinct sites in unstimulated Arabidopsis rosettes. To evaluate the spatial impact of jao2-1 mutation on JA metabolism, we determined JA profiles within similar leaf pairs of WT and jao2-1 plants. Despite of careful collection of the material with a freeze-sampling method (Heyer et al., 2018), absolute metabolite levels were variable between individual plants. As expected from a block in JA metabolism, JA levels were higher in jao2-1 than in WT leaves (statistically different in leaves 8-9), with no age-dependent effect (Figure 2d). JA-Ile could only be detected in one out of three jao2-1 plants (limit of quantification, LOQ, was < 2 pmol g -1 fresh weight), and not in WT plants, preventing it's quantification. In contrast, the catabolites 12OH-JA and 12OH-JA-Ile were found preferentially accumulated in younger leaves (16 to 21). These derivatives appeared slightly more abundant in jao2-1 compared to WT, but due to high interplant variability, the difference was below statistical significance in most leaf ages (except for 12OH-JA in leaves 14-15). This trend extends earlier findings on basal JAs levels in a whole rosette analysis (Smirnova et al., 2017). The higher abundance of 12OH-JA in jao2-1 is counterintuitive and probably reflects the indirect formation of this derivative through enhanced expression of the JA-Ile oxidase and amido-hydrolase catabolic pathways as reported previously (Smirnova et al., 2017).

Global analysis identifies transcriptomic and metabolic changes in JAO2-deficient leaves

To gain insight into the global spectrum of transcriptional changes triggered by JAO2 ablation before and after stress, we performed comparative transcriptome analysis by RNA-seq on leaves (pooled leaves 8-13) of WT and jao2-1 plants, before and after B. cinerea inoculation. Fungusinoculated leaves were collected at 48 h, before differences in surface of necrotic areas become prominent between the two genotypes (Smirnova et al., 2017). Differentially expressed genes (DEGs) were determined with regards to genotype and infection status. Principal component analysis revealed that response to infection accounted for 97% variance whereas genotypedifferences were responsible for only 1% variance in non-stressed leaves (Figure 3a). When differentially expressed genes (DEGs) were computed, considering a significant threshold fold change (FC) of 2 and FDR < 0.05, the comparison of the two infected groups highlighted only 21 DEGs (16 up and 5 down, Figure 3C, lower panel), despite of fungal infection deregulating 5514 and 5237 genes in WT and jao2-1 backgrounds respectively (Table S1). Two upregulated genes relevant to defense are MYROSINASE-BINDING PROTEIN 1 and PDF1.3 defensin. In contrast,

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This article is protected by copyright. All rights reserved leaves from non-infected plants exhibited 412 DEGs, with 337-up and 75-down regulated in jao2-1 vs WT (Figure 3b, Figure 3c upper panel and Table S1). This result supports our earlier finding that JAO2 suppression mostly impacts basal defense marker expression (Smirnova et al., 2017), rather than the amplitude reached after fungal challenge. Among the 337 upregulated DEGs in jao2-1, 62,6% overlap with genes deregulated after a treatment of WT plants with MeJA (Hickman et al., 2017). Gene ontology (GO) analysis of the 337 DEGs identified as expected a strong enrichment in JA-and defense-related processes (Figure 3d). Genes in the JA metabolic and signaling pathway were moderately upregulated relative to WT (Figure 3e), JAZ7 standing out as the most differential repressor gene. Upon more specific inspection, the most upregulated subset of genes belonged to the anti-microbial branch of JA signaling, controlled by ORA59 transcription factor, and targeting several defensin (PDF), thionin (THI) genes and other antimicrobial effector cascades (Figure 3e). Consistently, ethylene (ET) biosynthetic genes and ER-responding factors (ERFs) were also found among DEGs (Table S1). Likewise, distinct pathways governing defense against insects were enhanced, including VSP1, or L-ornithine N5acetyltransferase (NATA1), directing the synthesis of the Brassicacea-specific defense compound N  -acetylornithine [START_REF] Adio | Biosynthesis and defensive function of Nδacetylornithine, a jasmonate-induced Arabidopsis metabolite[END_REF]. A significant number of genes with demonstrated or potential roles in glucosinolate biosynthesis or modification was found upregulated in jao2-1 leaves (Figure 3e, full dataset available in Table S1). Genes encoding the classical myrosinases TGG1/2 were not differential, but MYROSINASE BINDING PROTEIN 1 and 2 or INDOLE GLUCOSINOLATE O-METHYLTRANSFERASE (IGMT) 1 and 4 were so, along with genes encoding components of endoplasmic reticulum (ER) body, a wound-and JA-inducible ER subdomain in Brassicacae (Yamada et al., 2011). These genes include the transcription factor NAI1, its target BETA-GLUCOSIDASE 18 (BGLU18) and several jacalin-related lectins (Figure 3e). ER bodies have recently been associated with glucosinolate breakdown and defense against herbivory [START_REF] Nakano | PYK10 myrosinase reveals a functional coordination between endoplasmic reticulum bodies and glucosinolates in Arabidopsis thaliana[END_REF][START_REF] Nakazaki | Leaf Endoplasmic Reticulum Bodies Identified in Arabidopsis Rosette Leaves Are Involved in Defense against Herbivory[END_REF]. Finally, three genes involved in the regulation and biosynthesis of anthocyanin pigments [START_REF] Nakabayashi | Enhancement of oxidative and drought tolerance in Arabidopsis by overaccumulation of antioxidant flavonoids[END_REF], namely PAP1/MYB75, DHFR and UGT79B1 were found upregulated, consistent with higher anthocyanin content in jao2 (Smirnova et al., 2017). These transcriptome results are in full agreement with previous targeted expression analysis (Smirnova et al., 2017) and identify at the whole genome scale the subset of JA-responsive genes whose basal levels are under JAO2 metabolic regulation in leaves. Furthermore, they establish that elevated fungal and insect tolerance phenotypes in JAO2-deficient mutants [START_REF] Caarls | Arabidopsis JASMONATE-INDUCED OXYGENASES down-regulate plant immunity by hydroxylation and inactivation of the hormone jasmonic acid[END_REF]Smirnova et al., 2017) likely result from a modified pre-existing state rather than from stronger induction of defense traits upon challenge.

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To explore metabolic changes associated with transcriptional reprogramming in jao2-1, we submitted resting leaves of WT and jao2-1 plants to untargeted metabolomic analysis. Methanolsoluble compounds were extracted from rosettes and separated by liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS). 1166 and 217 compounds were detected in positive (ESI+) and negative (ESI-) ionization modes respectively. Upon principal component analysis, the two genotypes (each analyzed in 8 replicates) clearly separated into two groups, showing the global impact of jao2-1 on leaf metabolism (Figure S4a). A threshold of 1.5 fold change (with p-value 0.01) was applied, yielding 105-lower and 64-higher accumulated compounds in jao2-1 in ESI+, and 20-lower and 11-higher in ESI-(Table S2). Putative identification was achieved by interrogating several databases as indicated in Methods. Most less-abundant compounds in jao2-1 were modestly affected (1.5<FC<2) and were essentially non-identified, with the exception of a few phenylpropanoid derivatives including sinapic acid and derivatives. We then focused the analysis mainly on compounds that were more largely enriched in jao2-1 (Figure S4b and Table S2). Among those, 19 tentatively identified compounds in ESI+ and 4 in ESI-were significantly more abundant in jao2-1 leaves (Figure 4a), several of them were previously described for their defensive properties. Besides Arabidopsides B and A [START_REF] Kourtchenko | Oxo-phytodienoic acid-containing galactolipids in Arabidopsis: jasmonate signaling dependence[END_REF], a class of esterified oxylipins, this set was particularly enriched in indole compounds. In particular were found isomers of the major indole glucosinolate 1/4methoxyglucobrassicin and several isothiocyanate or nitrile derivatives, as well as a variety of breakdown products such as ascorbigen, arvelexin, rapalexin (Figure 4a, Table S2), most of these latter compounds having documented functions as phytoalexins [START_REF] Pedras | Interaction of cruciferous phytoanticipins with plant fungal pathogens: indole glucosinolates are not metabolized but the corresponding desulfoderivatives and nitriles are[END_REF][START_REF] Pedras | The cruciferous phytoalexins rapalexin A, brussalexin A and erucalexin: chemistry and metabolism in Leptosphaeria maculans[END_REF]. These metabolic data are in accordance with the higher abundance of transcripts encoding glucosinolate biosynthetic, modification or breakdown activities (Figure 3e). In marked contrast, accumulation of camalexin, a major indole phytoalexin in Arabidopsis whose biosynthesis is partly regulated by JA (Zhang et al., 2017), was not found differential, nor were its biosynthetic transcripts. Among putatively identified metabolites, the top ranking differential compounds in the extracts were different forms of phenolamides, or hydroxycinnamic acid amides (HCAAs), a conserved class of plant specialized compounds endowed with antimicrobial properties (Roumani et al., 2020). Isomers of N1-trans-feruloylagmatine (FerAgm) and cis-p-coumaroyl-agmatine (CoumAgm) were up to 40.71 and 12.57 fold more abundant respectively in mutant relative to WT leaves, consistent with the upregulation of AGMATINE COUMAROYLTRANSFERASE (ACT, At5g61160, Log 2 FC 2.189) and DETOXIFICATION 18 (DTX18, At3g23550, Log 2 FC 3.489) in jao2-1 (Figure 3e and Table S1).

ACT and DTX18 activities are essential for HCA agmatine amide biosynthesis and secretion in the apoplast respectively (Dobritzsch et al., 2016;[START_REF] Muroi | Accumulation of hydroxycinnamic acid amides induced by pathogen infection and identification of agmatine coumaroyltransferase in Arabidopsis thaliana[END_REF]. Of note, both genes are

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under the control of the ORA59 transcription factor [START_REF] Li | Jasmonic acid/ethylene signaling coordinates hydroxycinnamic acid amides biosynthesis through ORA59 transcription factor[END_REF] that is also upregulated in jao2-1 (Figure 3e). As act ko lines are unable to synthesize FerAgm and CoumAgm [START_REF] Muroi | Accumulation of hydroxycinnamic acid amides induced by pathogen infection and identification of agmatine coumaroyltransferase in Arabidopsis thaliana[END_REF], we addressed genetically the contribution of these compounds to the jao2-1 enhanced resistance to fungal infection in a double jao2-1 act mutant. The two compounds were searched for independently via targeted LC-MS/MS in the different genotypes, and their quantification confirmed that FerAgm and CoumAgm were about 49 and 10 fold more accumulated in jao2-1 than in WT leaves respectively, and were undetectable in act (Figure 4b). In response to B. cinerea inoculation, both compounds increased in abundance to comparable levels in jao2-1 and WT as expected from the strong induction of ACT (Log 2 FC 11.28 WT; 9.55 jao2-1) and DTX expression by B. cinerea (Log 2 FC 11.67 WT; 8.62 jao2-1) (Table S1). No FerAgm or CoumAgm signal was detected in jao2-1 act, before or after inoculation. The act mutant displayed larger than WT fungal lesions (Figure 4c), illustrating the contribution of HCA-agmatine amides to defense against necrotrophs in WT background, in agreement with data obtained previously with Alternaria brassicicola infection [START_REF] Muroi | Accumulation of hydroxycinnamic acid amides induced by pathogen infection and identification of agmatine coumaroyltransferase in Arabidopsis thaliana[END_REF]. Strikingly, the strong antifungal resistance characteristic of jao2-1 was fully maintained in jao2-1 act line (Figure 4c), indicating that agmatine HCAAs are dispensable for the jao2-1 enhanced resistance phenotype to Botrytis.

JAO2 deficiency upregulates an array of transcription factors related to drought adaptation and confers enhanced drought survival

To broaden the knowledge of transcriptional deregulation in jao2-1, we extracted the list of transcription factors (TF) from the general DEG list. About 41 TFs were found upregulated and 5

TFs mildly downregulated (Table S3). Among up-TFs, the most represented families were ERFand MYB-type TFs, that represented nearly 50 % of the total (Figure 5A). Several of these factors are known to control antimicrobial or herbivore defense, or more generally plant immunity, such as ORA59, or several other ERFs, but remarkably, none of the MYC2/3/4 trio members that control many JA responses [START_REF] Aerts | Multiple levels of crosstalk in hormone networks regulating plant defense[END_REF] was picked as differentially expressed. A significant number of TFs in the list (Table S3) have possible links with abiotic stress responses, including to drought or salt stimuli. Among those TFs, some are particularly relevant to drought tolerance (Figure 5b): ANAC55 regulates some drought responses such as proline biosynthesis and is a hub TF in abiotic and biotic JA stress responses (Fu et al., 2018;Hickman et al., 2017;Tran et al., 2004), MYB47 was found among dehydration memory genes (Ding et al., 2014), TZF5 interacts with ABA, drought and stress regulators [START_REF] Bogamuwa | Plant Tandem CCCH Zinc Finger Proteins Interact with ABA, Drought, and Stress Response Regulators in Processing-Bodies and Stress Granules[END_REF], DREB-A5 is drought-induced (Urano et al., 2017), RD26 mediates cross-talk between drought and brassinosteroid signaling pathways (Ye et al., 2017) and RAV2 modulates drought responses

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This article is protected by copyright. All rights reserved independent of ABA (Fu et al., 2014). These findings are consistent with JA signaling being recruited for tolerance to various abiotic stresses, in interaction with other hormonal pathways [START_REF] Ali | Jasmonic Acid Signaling Pathway in Response to Abiotic Stresses in Plants[END_REF]Kazan, 2015;Raza et al., 2020;Riemann et al., 2015). In addition, a droughtresponsive network was reported recently where histone deacetylase 6 triggers an acetatedependent stimulation of the JA pathway and ameliorates subsequent drought stress survival [START_REF] Kim | Acetate-mediated novel survival strategy against drought in plants[END_REF].

We therefore investigated the impact of the JAO pathway under severe water deprivation conditions, by using jao2 single alleles, and the jaoT mutant to explore potential additive effects.

Plants were cultivated for 17 days under optimal conditions until young rosette stage, before withholding watering for 14 days. Plants were then re-watered for 4 days before being scored visually as green, intermediate or dead (Figure 5c). Green plants have recovered from dehydration with almost no symptoms, although they were growth-retarded compared to wellwatered controls. The intermediate class represents plants with a stunted stature, leaf wilting and apparent anthocyanin accumulation, but that were still able to flower. This class represented the smallest group and showed little variation among genotypes (Figure 5d). Under the conditions used, about 50-55% of the WT population survived the stress. In contrast, jao2-1 and jao2-2 displayed significantly enhanced survival of about 70% and 88%, and a death rate of 18% and 9% respectively (Figure 5d). Almost all jaoT plants survived the severe drought episode. These data show that, similar to their better performance upon biotic stress [START_REF] Caarls | Arabidopsis JASMONATE-INDUCED OXYGENASES down-regulate plant immunity by hydroxylation and inactivation of the hormone jasmonic acid[END_REF]Smirnova et al., 2017), JAO2-deficient plants withstand better severe water deprivation, and suggest additional effects by other jao mutations are revealed in this assay. To further establish if this phenotype was dependent on JA-Ile hormone signaling, double jao2-1 jar1 and jao2-2 jar1 plants were assayed simultaneously and were found, particularly in the case of jao2-2 jar1, to recover a survival rate similar to WT. This confirms that jao2-mediated drought tolerance requires JAR1-dependent JA-Ile formation and likely JA-Ile responses.

JAO2-deficiency drought survival negatively correlates with ABA responses

Abscisic acid (ABA) is a major hormone mediating rapid adaptation to drought (Vishwakarma et al., 2017), and several of the TFs upregulated in jao2-1 have previously been connected to ABA (Figure 5b, Table S1 andS3). To perform expression studies and hormone profiling, we collected leaf material at 3 stages of the kinetic drought experiment: at well-watered stage 1 (S1), collected on the next day after last watering; at stage 2 (S2), day 9 after last watering, plants exhibited reduced growth but little damage; at stage 3 (S3), after 14 days without watering, plants were

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wilted and showed strong damage (Figure 6a). NCED3 and RD29A, two markers for ABA biosynthesis (Iuchi et al., 2001), and response [START_REF] Msanne | Characterization of abiotic stressresponsive Arabidopsis thaliana RD29A and RD29B genes and evaluation of transgenes[END_REF], respectively, were induced by drought as expected, particularly at S3 (Figure 6b). Surprisingly, both genes had their lowest transcript levels in jaoT, and this trend was supported by ABA measurements whose levels increased steadily upon hydric stress, but to lesser extent in jao2-2 and jaoT mutants (Figure 6c).

A possible antagonistic relationship between JA and ABA pathways is also suggested by the observation that in lines bearing the jar1 mutation interrupting JA-Ile formation, resting ABA levels were higher than in WT at the S1 watered stage. To determine how JA signaling was affected by JAO deficiency under drought, expression of the JAZ9 marker was monitored. No increase in JAZ9 transcripts was revealed in WT, but marker expression was higher than WT in both jao2 alleles at S1, confirming RNAseq data (Figure 3e and Figure 6d). Moreover, JAZ9 expression further increased at S2 and S3 (with additive effects in jaoT), and reverted to near-WT levels in jao2 jar1 lines. This indicates that JAO2 deficiency primes higher JA signaling under drought stress, further enhanced by jao3-1 and/or jao4-2 mutations. Next, we performed quantitative jasmonate profiling to determine how JA metabolism underlies this response (Figure 6e). The hormone precursor JA was detected at all stages, and increased accumulation was seen at S3 in WT, confirming drought stimulation of the JA pathway. Significantly enhanced JA levels were detected in jaoT line at all 3 stages. JA-Ile, the receptor-activating jasmonate, was not detected in WT neither in JAR1-deficient lines, but was increasingly accumulated in jaoT and in jao2-1. JA-Ile levels were below LOQ in numerous samples, except jaoT (and jao2-1 S3 for two replicates), rendering difficult accurate measurements of such low amounts. The more stable and abundant catabolite 12COOH-JA-Ile was overaccumulated in jaoT at all times and in jao2-1 at S3 (Figure 6e), and was suppressed in all jar1 lines, identifying this compound (with JA) as a better tractable marker of enhanced jasmonate metabolism in jao mutants. These hormone profiling and expression data in different genetic backgrounds confirm that enhanced drought survival in jao mutants is positively correlated with higher JA-Ile metabolism/signaling and negatively with ABA abundance and response.

At a physiological level, we further found that stomatal opening did not vary from WT in jao2 lines under watered conditions (Figure 7a). We also measured stomatal evapotranspiration in excised rosettes, along with the ost1 mutant, in which ABA-dependent stomatal closure is impaired due to disruption of the SnRK2.6 kinase [START_REF] Belin | Identification of features regulating OST1 kinase activity and OST1 function in guard cells[END_REF]. When submitted to a whole-rosette water loss assay, jaoT behaved like WT, and jao2 single alleles displayed discernably higher water loss rates, but far from non-responding ost1 (Figure 7b). These results are consistent with decreased ABA accumulation and transcriptional responses (Figure 7b andc) in JAO2-deficient plants and

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This article is protected by copyright. All rights reserved indicate that higher survival rates in jao2 lines are not mainly due to a better capacity to retain water.

Finally, we examined in the drought survival experiment the kinetic expression of the droughtrelated TFs revealed by jao2-1 non-stressed transcriptome (Figure 5b). TF genes including DREB-A5, RD26, TZF5, RAV2, DREB26 showed various expression patterns (Figure S5) in response to drought but their genotype fluctuations, if any, did generally not follow survival capacity (Figure 5d) of the different genotypes. In contrast, ANAC55, and more so MYB47 and PAP1 displayed expression patterns that positively correlate with survival rate (Figure 7c). These genes show enhanced expression in jao mutants that is reversed close to WT when JA signaling is impaired by jar1 mutation, illustrating their JA-Ile-dependent regulation upon drought. However, MYB47 stands out from the analysis because its expression levels were jao2-enhanced at all stages and stricly correlated with the distinct survival performance of the different genotypes (Figure 5D). MYB47 may thus be considered as a robust molecular marker of a jao2-triggered drought tolerance pathway.

DISCUSSION

The JAO/JOX biochemical pathway has been elucidated recently and defines a new metabolic fate of JA [START_REF] Caarls | Arabidopsis JASMONATE-INDUCED OXYGENASES down-regulate plant immunity by hydroxylation and inactivation of the hormone jasmonic acid[END_REF]Smirnova et al., 2017). JA hydroxylase activity is encoded by 4 paralogous JAO/JOX genes in Arabidopsis, of which 3 are inducible by JA and biotic stress; however, understanding the precise function of their stress induction awaits further investigation.

JAO2 is the dominant JAO gene expressed in non-stressed leaves and, in contrast to JAO3 and JAO4, its genetic suppression elevates expression of selected biotic stress defense markers and enhances antifungal resistance (Smirnova et al., 2017). We show here that a triple jaoT mutant exhibits similar PDF1.2 expression and Botrytis resistance than a single jao2-1 or double jao2-1 jao3-1 or jao2-1 jao4-2 alleles, indicating that JAO3 and JAO4 do not contribute to regulate basal antimicrobial defense and resistance in leaves. When visualized in a complemented GUS reporter line, JAO2 displayed developmentally-regulated expression in roots, leaves and floral organs, all being sites of JA-regulated responses (Wasternack and Hause, 2013). In the present study, we investigated the organization of the signaling attenuation function exerted by JAO2 in leaves and the broader consequences of its genetic disruption. In young seedlings, GUS staining and transcripts were strongest in roots, raising the possibility of a long-distance regulatory function of root JAO2 over aerial organs. However, removal of root expression by grafting did not

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turn on defenses in WT leaves, indicating that constitutive upregulation of leaf defense occurs only in JAO2-deficient leaves. Role of JAO2 in roots remains thus unknown. At later stages in whole rosettes, both JAO2-GUS histological staining and a myc-tagged version of JAO2 generated predominant signal in young leaves. This protein distribution is somehow at odds with higher detection of JAO2 transcripts in older leaves, both in WT and in complemented lines.

Consistent with JAO2 protein pattern, examination of JAs profiles illustrated that JA metabolism is more active in young leaves and is slightly enhanced by JAO2 mutation due to stronger expression of several JA-Ile catabolic enzymes (Smirnova et al., 2017). In contrast, the expression intensity of PDF1.2 marker in jao2-1 was found to match better the transcript profile of JAO2 in WT leaves. Overall, the analysis at single leaf scale revealed the opposite gradients of PDF1.2 expression and of JAO2 protein accumulation, calling for additional levels of regulation leading to whole-leaf JA signaling attenuation.

JAO2-deficiency upregulates specific biotic stress defense pathways

We next undertook global investigation of the spectrum of transcriptional and metabolic changes triggered in jao2-1 mutant rosette leaves. RNA-seq analysis extended to the whole-genome scale the initial picture revealed by targeted JA marker analysis (Smirnova et al., 2017). Remarkably, transcriptomes of B. cinerea-infected WT and jao2-1 leaves are nearly identical, suggesting that the level of induced defense reached at 3 days is similar in both backgrounds, and cannot account for their strong difference in antifungal resistance. In contrast, the jao2 resistance phenotype correlated with the deregulation of a small set of about 400 genes -mostly upregulated in jao2-1 -in leaves before they encounter stress. JAO2 suppression therefore preactivates some leaf JA responses, rather than priming a stronger induction upon microbial challenge. This gene set was highly enriched for JA-related GO terms, but remarkably, the 337 upregulated genes in jao2-1 leaves only represent a small subset of the > 3000 DEGs previously identified in MJ-treated leaves (Hickman et al., 2017), indicating that JAO2-deficiency specifically turns on limited JA targets. Possibly, this spectrum may be restrained by cell type specificity, below-threshold JA signaling or peculiar interactions with other hormonal pathways. The ORA59/ERF module governing antimicrobial defense through cross-talk with ethylene (Pieterse et al., 2012;Wasternack and Hause, 2013) signaling was found under strong repressive JAO2 control in WT, with a number of ET biosynthetic and ERF homologs found among DEGs. In jao2-1, ORA59/ERF targets comprise genes encoding various classes of antimicrobial proteins with significantly elevated basal expression. Upon metabolic profiling, agmatine-type phenolamides, a class of potent antifungal compounds (Dobritzsch et al., 2016;[START_REF] Muroi | Accumulation of hydroxycinnamic acid amides induced by pathogen infection and identification of agmatine coumaroyltransferase in Arabidopsis thaliana[END_REF] were identified

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This article is protected by copyright. All rights reserved as the most overaccumulated coupounds in jao2-1, owing to the ORA59-dependent activation of their biosynthetic and secretion pathway components [START_REF] Li | Jasmonic acid/ethylene signaling coordinates hydroxycinnamic acid amides biosynthesis through ORA59 transcription factor[END_REF]. Their genetic suppression in a jao2-1 act double mutant unexpectedly did not alleviate the strong Botrytis resistance phenotype, pointing to the probable prevalence of other toxic compounds in jao2. The most compelling evidence emerged from the coordinated overexpression of indole glucosinolate biosynthesis, modification or breakdown machinery, comforted by non-targeted metabolome analysis. Several compounds putatively identified as indole glucosinolates and some nitrile, or isothiocyanate derivatives were found more abundant in jao2 and are known to be toxic to Botrytis [START_REF] Buxdorf | The effects of glucosinolates and their breakdown products on necrotrophic fungi[END_REF]. The combined transcriptome and metabolome data converge to the conclusion that JAO2 suppression elevates basal indole glucosinolate biosynthesis and their partial breakdown, and ER bodies are predicted cellular sites for such metabolism. Another example is illustrated by the upregulation of the N-acetyltransferase producing N  -acetylornithine, a potential insect-deterrent metabolite [START_REF] Adio | Biosynthesis and defensive function of Nδacetylornithine, a jasmonate-induced Arabidopsis metabolite[END_REF]. This metabolic shift, along with other unidentified phytochemicals, is likely at the basis of the strong defensive capacities in JAO2deficient plants, and their superior resistance to fungi and insects [START_REF] Caarls | Arabidopsis JASMONATE-INDUCED OXYGENASES down-regulate plant immunity by hydroxylation and inactivation of the hormone jasmonic acid[END_REF]Smirnova et al., 2017). It is well possible that low JAO2-expressing plants are more tolerant to a wider range of pests.

JAO-deficiency incrementally ameliorates drought stress survival without recruiting stronger ABA responses

We demonstrate in this study that the spectrum of targets affected in jao2 extends beyond biotic stress responses, based on a broader set of upregulated TFs, with potential or demonstrated roles in abiotic stress tolerance, particularly in response to hydric stress. We established that jao2 alleles survived much better severe drought conditions, and this trend was even more pronounced in the jaoT mutant. Such additive effects suggest that JAO3 and/or JAO4 may also contribute to water stress management, but their site of action is currently unknown. Because drought tolerance relies on physiological reponses both above-and below-ground, it could be foreseen that the remarkable resilience of jaoT results from more than one JA-dependent mechanism, due to multiple JAO deficiency. Unexpectedly, possible independence of this response of abscisic acid, the canonical hormonal pathway triggering hydric stress tolerance in plants was inferred from the negative correlation between increased drought survival and lower stress-induced ABA levels, and ABA-responsive gene markers. Despite of BGLU18, one of the top-ranking DEGs in jao2, has been previously involved in ABA release from ABA-glucose ester pools under drought stress (Han et al., 2020), our results show that jao2 mutations were Accepted Article associated with lower ABA levels. Additionally, jao2 alleles were found to display slightly higher stomatal evapotranspiration than WT, indicating that survival of these mutants does not rely on better ABA-dependent water retention. Similarly, neither the osmoprotectant proline nor its biosynthetic gene P5CS1 were found differential in jao2 (Figure S5). In contrast, JA accumulation and JA-Ile metabolism increased incrementally in jao2 and jaoT leaves relative to WT, before and after stress, which indicates elevated JA-Ile metabolic flux and signaling. Of note, the steadystate levels of bioactive JA-Ile remain low in leaves upon drought and are not a robust marker on their own to trace JA signaling, that was better probed by its catabolite 12COOH-JA-Ile, or by JAZ9 expression analysis. In addition, genetically suppressing JA-Ile formation in jao2 jar1 double mutants fully reversed survival (and ABA abundance) to WT levels, demonstrating JA-Ile dependency of the enhanced drought survival phenotype. These findings indicate that elevated basal JA-Ile signaling upon jao2-deficiency directs a distinct drought-survival pathway. Some of these characteristics are reminiscent of a recently reported, conserved drought survival strategy where stress-induced acetate triggers JA signaling and much ameliorated tolerance without recruiting typical ABA responses [START_REF] Kim | Acetate-mediated novel survival strategy against drought in plants[END_REF][START_REF] Ogawa | Acetic-acid-induced jasmonate signaling in root enhances drought avoidance in rice[END_REF]. In contrast to increased Botrytis resistance that seemed to rely mainly on elevated basal defenses in jao2, jao2-triggered drought tolerance is additionally characterized by primed responses under stressed conditions.

Elucidating the precise mechanism and adaptative responses that underly the jao2-triggered phenotype will require further investigations as to novel JA targets and their impact on withstanding harsh water limitation. By mining the set of TFs upregulated in jao2-1 even before plants are enduring stress, we retrieved several genes such as ANAC55, or fairly uncharacterized ERFs, RAV2 or RD26 that have been previously reported for their regulation by abiotic stress (Tran et al., 2004); however in our assay, their kinetic expression profiles poorly correlated with drought tolerance. By analyzing numerous genetic backgounds with various survival degrees, we ended-up with two TFs of special interest due their tight expression link with survival rate : higher PAP1 expression is known to drive higher anthocyanin accumulation whose antioxidant properties can mitigate drought-induced damage [START_REF] Nakabayashi | Enhancement of oxidative and drought tolerance in Arabidopsis by overaccumulation of antioxidant flavonoids[END_REF]. On the other hand, we identified MYB47 of unknown function, and whose expression profile reflects quantitatively the drought tolerance phenotype strength. MYB47 is so far reportedly required for Arabidopsis seed longevity (Renard et al., 2020), or indirectly associated with dehydration memory (Ding et al., 2014) and constitutes a promising candidate for mediating survival responses that are yet to be characterized.

CONCLUSIONS

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We have deepened in this work our understanding of a recently established regulatory paradigm in the biochemical JA pathway (Heitz et al., 2019). By oxidizing trace levels of JA in unstressed leaves, JAO2 contributes to attenuate JA-Ile formation and signaling, maintaining a number of defense/adaptation responses at minimal levels. Our findings examplify the importance of basal JA management and its impact on JA-Ile signaling, and demonstrate that significant signaling can occur with JA-Ile levels below detection threshold. It is possible that other JAO isoforms exert similar attenuation functions in distinct stress-, development-, or organ-specific situations to ensure proper regulation of JA responses in their timing and distribution. The ecological importance of JA hydroxylation in modulating the growth/defense balance under competition cues was recently demonstrated. Under high density settings, the sulfotransferase ST2a derives JAOgenerated jasmonate precursor pools to prioritize growth for shade avoidance over defense responses (Fernandez-Milmanda et al., 2020). Here we showed by using global approaches that conversely, when JAO2 is suppressed, a wide yet selective spectrum of JA metabolic targets are de-repressed in leaves and confer multiple stress adaptation traits that are compatible with growth maintenance. Some accumulated compounds that were identified such as glucosinolates are genus specific; it is conceivable that alleviating basal defense attenuation mechanisms in other plant families may release activation of genus specific defense effectors and provide tolerance benefits. Finally, we set the basis to study an unknown JA-dependent drought survival strategy. Monitoring or engineering the JAO/JOX pathway offers a new possibility to optimize the deployment of JA responses for reinforced crop adaptation to defavorable growth conditions.

EXPERIMENTAL PROCEDURES

Plant growth and treatments

Plant culture conditions

Arabidopsis thaliana genotypes used were in the Col-0 ecotype and were grown under a 16 h light/8 h dark photoperiod in a growth chamber for hydric stress assay and grafting experiment, and under a 12 h light/12 h dark photoperiod in a growth chamber for other experiments. The individual T-DNA insertion lines were obtained from the Nottingham Arabidopsis Stock Center (NASC): jao2-1 (SALK_206337C), jao2-2 (GK_870C04), jao3-1 (SAIL_861E01), jao4-2 (SAIL_268_B05), jar1-1 (SALK_034543), act-1 (SALK_097380) and ost1-3 (SALK_008068). The

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This article is protected by copyright. All rights reserved multiple mutant lines jao2-1 jao3-1, jao2-1 jao4-2, jao3-1 jao4-2, jao2-1 jao3-1 jao4-2 (jaoT), jao2-1 jar1, jao2-2 jar1 and jao2-1 act were obtained by crossing the single mutants and PCRgenotyping the progeny.

Individual leaf analysis

Rosette leaves were numbered from oldest to youngest based on characteristics described by Farmer et al., (2013); i.e. size, shape and trichome density, and the development of the leaves in a spiral with an angle of 137° between successive leaves. For each biological replicate for gene expression studies, 3 plants were grouped by alternately collecting leaves of increasing or decreasing age. Cut leaves were immediately frozen in liquid nitrogen and stored at -80°C.

Grafting experiment

Grafting experiment is based on the protocol of Turnbull et al., (2002). Ethanol-sterilized seeds were germinated on a vertical dish of 0.9 % MS-agar pH 5.7, supplemented with 0.05 % MES and 1 % sucrose, in a Versatile environmental test chamber (Sanyo, MLR-351H model) with 16 h light/8 h dark photoperiod. Grafting was performed under sterile conditions on five-day-old seedlings. Seedlings were placed on a wet nitrocellulose filter. One of the two cotyledons of the scion was cut and hypocotyl was sectioned to one-third of height, root portion was removed.

Cotyledons of rootstock was cut and hypocotyls was sectioned one-third of height, leaf part was removed. The moisture content of the filter was adjusted to slide the rootstock to the scion at the grafting point. Grafts were placed back in a culture chamber. After five days, any adventitious root developed from the grafting point was removed under sterile conditions. Successful transplants were transferred to soil culture under 16 h light/8 h dark photoperiod.

Botrytis cinerea resistance assay and mechanical wounding

B. cinerea inoculation and resistance scoring were as described in [START_REF] Aubert | CYP94-mediated jasmonoylisoleucine hormone oxidation shapes jasmonate profiles and attenuates defence responses to Botrytis cinerea infection[END_REF]. For mechanical wounding experiments for GUS staining, 4 or 5 fully expanded leaves were wounded two times across mid-vein with a hemostat.

Drought stress assessment

Hydric stress survival assay Hydric stress assay was adapted from [START_REF] Kim | Acetate-mediated novel survival strategy against drought in plants[END_REF] protocol. Four Arabidopsis seedlings of

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This article is protected by copyright. All rights reserved the selected genotypes were cultivated per pot under 16 h light/8 h dark photoperiod onto a soil mixture (50% sieved soil, 25% perlite and 25% vermiculite) previously equalized between 40 g  0.5 of soil mixture. Each replicate is composed of 65 plants per genotype. Each seedling was watered with 1 mL of water every other day until stress began. Watering was suspended for 14 days at young rosette stage (17-day-old). Plants were collected at three stages: S1 (wellwatered), S2 (reduced growth but little damage) and S3 (wilted leaves and severe damage) at 1, 9 and 14 days after watering was stopped, respectively. Four whole rosettes per replicate were pooled, immediately frozen in liquid nitrogen and stored at -80°C. A separate set of about 50 plants per genotype per replicate was re-watered on day 14, for 4 days, before determining the survival rate.

Stomatal aperture

Leaf 8 from four week-old Arabidopsis leaves were collected and abaxial side was glued on microscope slide using double-side tape. A small amount of water was deposited on the leave and green part was scraped with a scalpel. After flushing and adding a cover slide, stomatal aperture was observed on an optic Zeiss observer Z1 microscope. Preparation and observation of slides was conducted between 10:am and 4:pm, during stomatal opening period (Kang et al., 2007).

Water loss assay

Six week-old Arabidopsis plants were excised at hypocotyl level with a scalpel and the cut hypocotyl was sealed with grease. Individual excised plants were installed upside down on a scale (with a holder to facilitate ventilation) and fresh weight was recorded every 2 min for 1 h.

Percentage water loss was calculated using the formula: % water loss = ((FW t0 -FW t0 )/(FW t0 -DW))x100 where FW is fresh weight and DW is dry weight. Experimentation was conducted during stomatal opening period, between 10:am and 4:pm (Kang et al., 2007).

RT-qPCR gene expression assays

Total RNA was extracted from plant leaves with TRI reagent (Molecular Research Center). One microgram of RNA was reverse transcribed using SuperScript IV reverse transcription system (Thermo Fisher Scientific). Real-time PCR was performed on 10 ng of cDNA as described in Berr et al., (2010) using a LightCycler 480 II instrument (Roche Applied Science). The housekeeping

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This article is protected by copyright. All rights reserved genes EXP (At4g26410) and TIP41 (At4g34270) were used as references genes for all quantitative PCR analysis. Gene-specific primer sequences used for qPCR are listed in Table S1.

Construction of plasmid and transgenic plants

Transgenic plants expressing β-glucuronidase (GUS) or 4xmyc under the control of the pJAO2 promoters were generated. Promoter region 3.1 kb upstream of JAO2 translation initiation sites and JAO2 sequence gene were PCR amplified from Arabidopsis (Col-0) with specific primers (Table S4) and were cloned in pDONR-Zeo (Thermo Fisher Scientific) or pDONR221 (Invitrogen) respectively by homologous Gateway recombination. The resulting plasmids were used to transfer JAO2 promoter into the expression vectors pGWB633 containing C-ter GUS sequence or pGWB616 containing C-ter 4xmyc sequence by recombination. The resulting pGWB633 with pJAO2:JAO2-GUS and pGWB616 with pJAO2:JAO2-4xmyc constructs were transfered into A. tumefaciens strain GV3101 then to Arabidopsis jao2-1 mutant by floral dip [START_REF] Bent | Arabidopsis thaliana floral dip transformation method[END_REF]. Twenty transformant lines harboring pJAO2:JAO2-GUS were analyzed for mRNA expression of the transgene. Among these, two jao2-1 pJAO2:JAO2-GUS lines (#3 and #10) were propagated to obtain homozygous T3 lines. Twenty lines harboring pJAO2:JAO2-4xmyc were similarly selected on the basis of JAO2-4xmyc protein accumulation.

Histochemical detection of GUS activity

Whole transgenic plants, or tissues obtained from jao2-1 pJAO2:JAO2-GUS lines, were collected in ice-cold 90 % acetone and then incubated for 15-20 min at ambient temperature. These tissues were washed briefly with washing buffer (50 mM sodium phosphate, pH 7.2) before infiltrating four successive times with staining solution (50 mM sodium phosphate, pH 7.2, 0.01 % Triton X-100, 10 mM EDTA, 1 mM potassium ferrocyanide, 1 mM potassium ferricyanide, and 0.4 mg/mL X-gluc (Euromedex) under vaccuum. Material was incubated at 37°C in the dark until blue coloration appeared. Plant material was cleared with serial ethanol washes (70 %-100 %).

Images of X-gluc-stained tissues were taken with either the DMC-LX 100 digital camera (Panasonic), the Stemi 305 stereo microscope (Zeiss) or the DMRB optical microscope (Leica Leitz).

Statistical analysis

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This article is protected by copyright. All rights reserved

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This article is protected by copyright. All rights reserved (a) Numbering of leaves of whole rosette according to Farmer et al., (2013). Leaf 1 is the first emerged leaf, and higher numbers designate younger leaves, following the growth spiral.

(b) JAO2 and PDF1.2 relative transcript levels in leave age-series in WT, jao2-1 and jao2-1::pJAO2-JA2-GUS#3 lines. Two successively numbered leaves as defined in (a) were combined from individual plants for RNA extraction. JAO2 expression was normalized with respect to leaves 4-5 fixed to 1 for both genotypes. Relative gene expression was determined by real-time PCR using gene-specific primers and technically normalized using EXP and TIP41 reference genes.

Transcript quantification was performed on three (top panel) or two (bottom panel) independent Accepted Article biological replicates analyzed in triplicate. Histograms represent mean expression ± SEM with replicates depicted by dots.

(c) The tagged protein JAO2-4xmyc (47 kDa) deriving from the transgene was immunodetected in leaf extracts with an anti-myc antibody (top panel). An aspecific signal was detected at 25 kDa.

Lower panel shows Coomassie blue staining of Rubisco taken as a loading control. GO terms enrichement was determined using the online tool DAVID (https://david.ncifcrf.gov/). E, Transcriptional behavior of JA-responsive genes categorized as jasmonate pathway (biosynthesis, catabolism, repression), defense responses, glucosinolate pathway or specialized metabolism in jao2-1 relative to WT in non-infected leaves. Red color intensity is proportional to log2FC value. Full expression data can be found in Table S1. S3.

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Relative gene expression was determined from three biological replicates by real-time PCR using gene-specific primers and normalized using EXP and TIP41 reference genes.

(c) ABA accumulation profile during drought stress.

(e) Levels of three jasmonates during drought stress. Dotted line represents limit of quantification (LOQ) of JA-Ile at 2 pmol g FW -1 . No statistical analysis was applied on JA-Ile data as samples except jaoT have replicates below LOQ.

For hormone analysis the same plant material as for gene expression was used, methanol- (top, or after (bottom, jao2-1_Bc_vs_WT_Bc) Botrytis inoculation. Red dots represent significant DEG with -1 ≤ Log2FC ≤ 1 and adj p-value ≤ 0.05. (d) Gene ontology (GO) term enriched in DEGs overexpressed in the jao2-1_vs_WT comparison. GO terms enrichement was determined using the online tool DAVID (https://david.ncifcrf.gov/). (e) Transcriptional behavior of JA-responsive genes categorized as jasmonate pathway (biosynthesis, catabolism, repression), defense responses, glucosinolate pathway or specialized metabolism in jao2-1 relative to WT in non-infected leaves. Red color intensity is proportional to log2FC value. Full expression data can be found in Supplemental Table 1.

  Pieterse, C.M., Van der Does, D., Zamioudis, C., Leon-Reyes, A. & Van Wees, S.C. (2012) Hormonal modulation of plant immunity. Annu Rev Cell Dev Biol, 28, 489-521. Poudel, A.N., Holtsclaw, R.E., Kimberlin, A., Sen, S., Zeng, S., Joshi, T., Lei, Z., Sumner, L.W., Singh, K., Matsuura, H. & Koo, A.J. (2019) 12-Hydroxy-Jasmonoyl-l-Isoleucine Is an Active Jasmonate That Signals through CORONATINE INSENSITIVE 1 and Contributes to the Wound Response in Arabidopsis. Plant Cell Physiol, 60, 2152-2166. Raza, A., Charagh, S., Zahid, Z., Mubarik, M.S., Javed, R., Siddiqui, M.H. & Hasanuzzaman, M. (2020) Jasmonic acid: a key frontier in conferring abiotic stress tolerance in plants. Plant Cell Rep, Renard, J., Niñoles, R., Martínez-Almonacid, I., Gayubas, B., Mateos-Fernández, R., Bissoli, G., Bueso, E., Serrano, R. & Gadea, J. (2020) Identification of novel seed longevity genes related to oxidative stress and seed coat by genome-wide association studies and reverse genetics. Plant Cell Environ, 43, 2523-2539. Riemann, M., Dhakarey, R., Hazman, M., Miro, B., Kohli, A. & Nick, P. (2015) Exploring Jasmonates in the Hormonal Network of Drought and Salinity Responses. Front Plant Sci, 6, 1077. Roumani, M., Besseau, S., Gagneul, D., Robin, C. & Larbat, R. (2020) Phenolamides in plants: An update on their function, regulation, and origin of their biosynthetic enzymes. J Exp Bot, Schaller, A. & Stintzi, A. (2009) Enzymes in jasmonate biosynthesis -structure, function, regulation. Phytochemistry, 70, 1532-1538. Smirnova, E., Marquis, V., Poirier, L., Aubert, Y., Zumsteg, J., Menard, R., Miesch, L. & Heitz, T. (2017) Jasmonic Acid Oxidase 2 Hydroxylates Jasmonic Acid and Represses Basal Defense and Resistance Responses against Botrytis cinerea Infection. Mol Plant, 10, 1159-1173. Staswick, P.E. & Tiryaki, I. (2004) The oxylipin signal jasmonic acid is activated by an enzyme that conjugates it to isoleucine in Arabidopsis. Plant Cell, 16, 2117-2127. Stitz, M., Baldwin, I.T. & Gaquerel, E. (2011) Diverting the flux of the JA pathway in Nicotiana attenuata compromises the plant's defense metabolism and fitness in nature and glasshouse. PLoS One, 6, e25925. Tang, J., Yang, D., Wu, J., Chen, S. & Wang, L. (2020) Silencing JA hydroxylases in Nicotiana attenuata enhances jasmonic acid-isoleucine-mediated defenses against Spodoptera litura. , J. (2007) JAZ repressor proteins are targets of the SCF(COI1) complex during jasmonate signalling. Nature, 448, 661-665.

  , K. & Yamaguchi-Shinozaki, K. (2004) Isolation and functional analysis of Arabidopsis stress-inducible NAC transcription factors that bind to a drought-responsive cis-element in the early responsive to dehydration stress 1 promoter. Plant Cell, 16, 2481-2498. Turnbull, C.G., Booker, J.P. & Leyser, H.M. (2002) Micrografting techniques for testing longdistance signalling in Arabidopsis. Plant J, 32, 255-262. Urano, K., Maruyama, K., Jikumaru, Y., Kamiya, Y., Yamaguchi-Shinozaki, K. & Shinozaki, K. (2017) Analysis of plant hormone profiles in response to moderate dehydration stress. Plant J, 90, 17-36. Vishwakarma, K., Upadhyay, N., Kumar, N., Yadav, G., Singh, J., Mishra, R.K., Kumar, V., Verma, R., Upadhyay, R.G., Pandey, M. & Sharma, S. (2017) Abscisic Acid Signaling and Abiotic Stress Tolerance in Plants: A Review on Current Knowledge and Future Prospects. Front Plant Sci, 8, 161. Wasternack, C. & Hause, B. (2013) Jasmonates: biosynthesis, perception, signal transduction and action in plant stress response, growth and development. An update to the 2007 review in Annals of Botany. Ann Bot, 111, 1021-1058. Wasternack, C. & Song, S. (2017) Jasmonates: biosynthesis, metabolism, and signaling by proteins activating and repressing transcription. J Exp Bot, 68, 1303-1321. Wasternack, C. & Strnad, M. (2018) Jasmonates: News on Occurrence, Biosynthesis, Metabolism and Action of an Ancient Group of Signaling Compounds. Int J Mol Sci, , T. (2013) The amidohydrolases IAR3 and ILL6 contribute to jasmonoyl-isoleucine hormone turnover and generate 12-hydroxyjasmonic acid upon wounding in Arabidopsis leaves. J Biol Chem, 288, 31701-31714. Yamada, K., Hara-Nishimura, I. & Nishimura, M. (2011) Unique defense strategy by the endoplasmic reticulum body in plants. Plant Cell Physiol, 52, 2039-2049. Hormone crosstalk in wound stress response: wound-inducible amidohydrolases can simultaneously regulate jasmonate and auxin homeostasis in Arabidopsis thaliana. J Exp Bot, 67, 2107-2120.

Figure 1 .

 1 FIGURE LEGENDS

Figure 2 .

 2 Figure 2. JAO2 expression and metabolic impact at individual leaf resolution.

  (d) Jasmonates content (JA, 12OH-JA and 12OH-JA-Ile) in successive paired leaves in WT and jao2-1 lines determined by LC-MS/MS. FW : fresh weight. Histograms represent mean accumulation ± SEM of three biological replicates.

Figure 3 .

 3 Figure 3. Comparative transcriptome analysis of WT and jao2-1 leaves. (a) Principal component analysis (PCA) of transcriptomes of WT and jao2-1 Arabidopsis leaves before (WT and jao2-1) and 48 h after Botrytis cinerea inoculation (WT_Bc and jao2-1_Bc). Three independent biological replicates (indicated by numbers) were analyzed for each genotype. (b) Number of differentially expressed genes (DEGs) in the jao2-1_vs_WT comparison with -1 ≤ Log 2 FC ≤ 1 and adj p-value ≤ 0.05. (c) MA-plot of DEG before (top, jao2-1_vs_WT) or after (bottom, jao2-1_Bc_vs_WT_Bc) Botrytis inoculation. Red dots represent significant DEG with -1 ≤ Log 2 FC ≤ 1 and adj p-value ≤ 0.05. (d) Gene ontology (GO) term enriched in DEGs overexpressed in the jao2-1_vs_WT comparison.

Figure 4 .

 4 Figure 4. Analysis of jao2-1 leaf metabolome and contribution of phenolamides to fungal resistance (a) List of putatively identified compounds significatively overaccumulated (top panel, positive ionization, ESI+) in jao2-1 compared to WT. Lower panel, negative ionization (ESI-) also shows lower accumulated compounds of interest. Ranking is in decreasing fold change (FC). Structural classes are indicated by colored backgrounds. Putative identification was performed by interrogating databases as indicated in Methods section. Eight biological replicates were analyzed per genotype. Full data set is available in Supplemental Table 2. (b) Upper panel: phenolamide synthesis by agmatine coumaroyl transferase (ACT). CoA: Coenzyme A. Lower panels: feruloyl-agmatine and p-coumaroyl-agmatine accumulation in WT, jao2-1, act and jao2-1 act lines. Leaves were collected at 0 and 3 days post-inoculation (dpi) with Accepted Article

Figure 5 .

 5 Figure 5. Transcription factor genes overexpressed in jao2-1 and impact of JAO deficiency on drought stress survival. (a) Distribution into structural families of 41 transcription factors overexpressed in non-infected jao2-1 leaves. Full list is available in TableS3.

  (b) Top-ranking jao2-1-uregulated transcription factor genes with potential link with drought stress responses. (c) Illustration of phenotypic classes of plants after severe drought survival assay. Plants were cultivated for 17 days before watering was stopped for two weeks and representative plants of each class were photographed four days after re-watering. (d) Survival score of WT, jao2-1, jao2-2, jaoT, jar1, jao2-1 jar1 and jao2-2 jar1 lines after water deprivation assay. Histograms represent mean percentage survival score of three biological replicates with 50 plants each per genotype. Sectors labeled with different letters indicate a significant difference in category size between genotypes of same state as determined by oneway ANOVA with Tukey posthoc test, P < 0.05.

Figure 6 .

 6 Figure 6. ABA and JA pathway marker gene expression and hormone profiling during severe drought stress. (a) Representative plants at three stages of drought stress assay. Stage S1 is well-watered, photographed the next day after last watering; at stage S2 plants displayed reduced growth but little damage after 9 days of stress; and at stage S3, after 14 days, most plants show wilted leaves and strong damage. Expression analysis of genes involved in ABA biosynthesis (NCED3) and response (RD29A) (b) or in JA response (d). Plant material (four whole rosettes for each biological replicate) was harvested at stages S1, S2 and S3 and submitted to RNA extraction and RT-qPCR analysis.

  soluble compounds were extracted and analyzed by LC-MS/MS. Histograms in (b), (c) and (d) represent mean ± SEM of three biological replicates (depicted by dots). Columns labeled with different letters indicate a significant difference between genotypes at each stage independently as determined by one-way ANOVA with Tukey posthoc test, P < 0.05.

Figure 7 .Figure 1 .Figure 2 .

 712 Figure 7. Evaluation of the impact of jao mutations on stomatal opening, evapotranspiration and expression of JA-responsive transcription factors. (a) Representative pictures of three states of stomatal opening : open, partially open and closed. Epidermal peels were sampled on each genotype as indicated in Methods and the proportion of each category was determined on leave number 8, selected according to Farmer et al., (2013), from 4-week-old plants. Histograms represent mean percentage aperture rate of three biological replicates with around 160 stomata inspected by genotype. (b) Transpirational water loss in rosettes at indicated times after detachement from hypocotyl. Values are means ± SEM of three samples per genotype. ost1 is a mutant line deficient for the SnRK2.6 kinase required for ABA-dependent stomatal closure. Different letters indicate a significant difference between genotypes as determined by one-way ANOVA with Tukey posthoc test, P < 0.05.(c) Expression analysis of transcription factor genes ANAC55, MYB47 and PAP1/MYB75 upon drought survival assay. The biological material and methodology is the same as in Figure6b.Accepted Article

Figure 3 .

 3 Figure 3. Comparative transcriptome analysis of WT and jao2-1 leaves (a) Principal component analysis (PCA) of transcriptomes of WT and jao2-1 Arabidopsis leaves before (WT and jao2-1) and 48 h after Botrytis cinerea inoculation (WT_Bc and jao2-1_Bc). Three independent biological replicates (indicated by numbers) were analyzed for each genotype. (b) Number of differentially expressed genes (DEGs) in the jao2-1_vs_WT comparison with -1 ≤ Log 2 FC ≤ 1 and adj p-value ≤ 0.05. (c) MA-plot of DEG before (top, jao2-1_vs_WT) or after (bottom, jao2-1_Bc_vs_WT_Bc) Botrytis inoculation.Red dots represent significant DEG with -1 ≤ Log2FC ≤ 1 and adj p-value ≤ 0.05. (d) Gene ontology (GO) term enriched in DEGs overexpressed in the jao2-1_vs_WT comparison. GO terms enrichement was determined using the online tool DAVID (https://david.ncifcrf.gov/). (e) Transcriptional behavior of JA-responsive genes categorized as jasmonate pathway (biosynthesis, catabolism, repression), defense responses, glucosinolate pathway or specialized metabolism in jao2-1 relative to WT in non-infected leaves. Red color intensity is proportional to log2FC value. Full expression data can be found in Supplemental Table1.

Figure 4 .

 4 Figure 4. Analysis of jao2-1 leaf metabolome and contribution of phenolamides to fungal resistance (a) List of putatively identified compounds significatively overaccumulated (top panel, positive ionization, ESI+) in jao2-1 compared to WT. Lower panel, negative ionization (ESI-) also shows lower accumulated compounds of interest. Ranking is in decreasing fold change (FC). Structural classes are indicated by colored backgrounds. Putative identification was performed by interrogating databases as indicated in Methods section. Eight biological replicates were analyzed per genotype. Full data set is available in Supplemental Table 2. (b) Upper panel: phenolamide synthesis by agmatine coumaroyl transferase (ACT). CoA: Coenzyme A. Lower panels: feruloyl-agmatine and p-coumaroyl-agmatine accumulation in WT, jao2-1, act and jao2-1 act lines. Leaves were collected at 0 and 3 days post-inoculation (dpi) with Botrytis cinerea. Phenolamides were extracted and quantified by LC-MS/MS. Histograms represent mean accumulation ± SEM of three biological replicates (depicted by dots). Columns labeled with different letters indicate a significant difference between genotypes as determined by one-way ANOVA with Tukey posthoc test, P < 0.05. (c) Disease resistance assessment of WT, jao2-1, act and jao2-1 act lines. Two sites per leaf were inoculated across the main vein. Representative leaves of each genotype were detached and photographed at 3 dpi (top panel). Box plot represents the mean lesion diameters ± SEM of about 80 lesions from 10 to 15 plants per genotype (bottom panel). Columns labeled with different letters indicate a significant difference as determined by one-way ANOVA with Tukey post-hoc test, P < 0.01.

Figure 5 .

 5 Figure 5. Transcription factor genes overexpressed in jao2-1 and impact of JAO2 on drought stress survival (a) Distribution into structural families of 41 transcription factors overexpressed in non-infected jao2-1 leaves. Full list is available in Supplemental Table 3. (b) Top-ranking jao2-1-uregulated transcription factor genes with potential link with drought stress responses. (c) Illustration of phenotypic classes of plants after severe drought survival assay. Plants were cultivated for 17 days before watering was stopped for two weeks and representative plants of each class were photographed four days after re-watering. (d) Survival scores of WT, jao2-1, jao2-2, jaoT, jar1, jao2-1 jar1 and jao2-2 jar1 lines after water deprivation assay. Histograms represent mean percentage survival score of three biological replicates with 50 plants each per genotype. Sectors labeled with different letters indicate a significant difference in category size between genotypes of same state as determined by one-way ANOVA with Tukey posthoc test, P < 0.05.

Figure 6 .

 6 Figure 6. ABA and JA pathway marker gene expression and hormone profiling during severe drought stress.(a) Representative plants at three stages of drought stress assay. Stage S1 is well-watered, photographed the next day after last watering; at stage S2 plants displayed reduced growth but little damage after 9 days of stress; and at stage S3, after 14 days, most plants show wilted leaves and strong damage. Expression analysis of genes involved in ABA biosynthesis (NCED3) and response (RD29A) (b) or in JA response (JAZ9) (d). Plant material (four whole rosettes for each biological replicate) was harvested at stages S1, S2 and S3 and submitted to RNA extraction and RT-qPCR analysis. Relative gene expression was determined from three biological replicates by real-time PCR using gene-specific primers and normalized using EXP and TIP41 reference genes. (c) ABA accumulation profile during drought stress. (e) Levels of three jasmonates during drought stress. Dotted line represents limit of quantification (LOQ) of JA-Ile (2 pmol g FW -1 ). No statistical analysis was applied on JA-Ile data as samples except jaoT have replicates below LOQ. For hormone analysis the same plant material as for gene expression was used, methanol-soluble compounds were extracted and analyzed by LC-MS/MS. Histograms in (b), (c), (d) and (e) represent mean ± SEM of three biological replicates (depicted by dots). Columns labeled with different letters indicate a significant difference between genotypes at each stage independently as determined by one-way ANOVA with Tukey posthoc test, P < 0.05 (c) and (e) or P < 0.01 (b) and (d)).

Figure 7 .

 7 Figure 7. Evaluation of the impact of jao mutations on stomatal opening, evapotranspiration and expression of JA-responsive transcription factors. (a) Representative pictures of three states of stomatal opening : open, partially open and closed. Epidermal peels were sampled on each genotype as indicated in Methods and the proportion of each category was determined on leave number 8, selected according to Farmer et al., (2013), from 4-week-old plants. Histograms represent mean percentage aperture rate of three biological replicates with around 160 stomata inspected by genotype. (b) Transpirational water loss in rosettes at indicated times after detachement from hypocotyl. Values are means ± SEM of three samples per genotype. ost1 is a mutant line deficient for the SnRK2.6 kinase required for ABA-dependent stomatal closure. Different letters indicate a significant difference between genotypes as determined by one-way ANOVA with Tukey posthoc test, P < 0.05. (c) Expression analysis of transcription factor genes ANAC55, MYB47 and PAP1/MYB75 upon drought survival assay. The biological material and methodology is the same as in Figure 6b.

GO description p value

				Category	Gene	log2FC	Adj p value
					LOX2	2.0504	3.82E-45
					AOS	1.0334	5.94E-09
				Biosynthesis	AOC1	2.5335	3.55E-24
					AOC2	2.1934	1.53E-38
					JAO3	1.6229	1.64E-03
			JA pathway	Catabolism	ILL6	2.0753	8.95E-13
					JAZ1	1.0204	3.76E-04
					JAZ5	1.5251	6.03E-05
				Repression	JAZ6	1.8819	1.01E-19
					JAZ7	3.7981	1.40E-21
					JAZ9	1.6041	9.31E-23
					ORA59	7.5535	1.68E-07
					PDF1.2	6.7972	2.58E-101
					PDF1.3	6.7105	9.73E-68
			Responses	Anti-microbial proteins	THI2.1 ACT	9.1781 2.189	3.73E-10 1.54E-03
	Response to jasmonic acid	< 0.0001			PR3	1.141	7.84E-03
	Response to wounding	< 0.0001			PR4	4.5459	5.48E-89
	Ethylene-activated signaling pathway	< 0.0001		Anti-herbivore proteins	VSP1	3.0098	9.07E-03
	Response to chitin	< 0.0001		Biosynthesis	CYP81F2	1.7287	1.03E-02
	Response to salicylic acid	< 0.0001			IGMT1	2.9537	2.03E-05
	Defense response to fungus	< 0.0001			IGMT4	1.335	6.93E-14
	Defense response	< 0.0001		Modification/breakdown	MBP1	6.355	2.10E-203
	Response to ethylene	0.0002			MBP2	4.675	5.86E-19
	Vasculature development	0.0008			BGLU18	4.845	5.97E-76
	Negative regulation of nucleic acid-templated transcription	0.0009	Glucosinolate		NAI1	2.071	3.08E-05
	Jasmonic acid mediated signaling pathway	0.0019			Jacalin-related 5	3.003	4.17E-106
	Response to salt stress	0.0023		ER body components	JAL23	2.486	4.36E-06
	Transcription, DNA-templated	0.0031			JAL34	1.692	7.55E-07
	Positive regulation of transcription. DNA-templated	0.0037			JAL35	2.312	5.53E-07
	Regulation of transcription, DNA-templated	0.0050		N d -acetylornithine	PBP1/JAL30 NATA1	1.483 3.956	1.87E-08 4.69E-40
	Regulation of jasmonic acid mediated signaling pathway	0.0056			MYB75	1.37	3.49E-08
	Ethylene biosynthetic process	0.0072	Metabolism	Anthocyanins	DHFR	4.429	2.97E-08
	Response to auxin	0.0093			UGT79B1	2.462	1.51E-02

Family Name Log2FC Adj p value Physiological response

	NAC	ANAC55	3.128	2.60E-03	Stomatal reopening, proline synthesis
	MYB	MYB47	2.596	3,97E-29	Upregulated by salt, drought and JA
	ERF	DREB-A5	2.454	1,83E-05	drought and stress response
	C3H	TZF5	2.403	3,23E-04	ABA, drought and stress response
	MYB	PAP1	1.37	3,49E-08	Anthocyanin biosynthesis
	ERF	DREB26	1.547	3.94931E-13 Abiotic stress response
	NAC	RD26	1.289	2,12E-10	Induced by dessication, activates ABA responses, BR interaction
	RAV	RAV2	1.125	3,91E-22	Negative regulation of drought and salt responses
				de

ACKNOWLEDGEMENTS

We are grateful to the IBMP gardener team for support in production of the numerous plants used in the study and to the Nottingham Arabidopsis Stock Center (NASC) for providing mutant seed stocks. We thank Simon Ndecky for critical reading of the manuscript. The work was supported by basic funding of CNRS and in part by grant ANR-12-BSV8-005 (JASMONOX) from the Agence Nationale de la Recherche to ES. VM was successively recipient of a predoctoral fellowship from the Université de Strasbourg and the Ministère de l'Enseignement Supérieur et de la Recherche and of a temporary teaching assistant position (ATER) from Université de Strasbourg.

Accepted Article

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Accepted Article

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DATA AVAILABILITY STATEMENT

The raw RNA-seq data were submitted to the NCBI Gene Expression Omnibus repository, under accession GSE178717. The material generated in this study can be obtained upon request to the corresponding author.

Accepted Article

This article is protected by copyright. All rights reserved non-targeted metabolomic analysis and data processing; JZ provided support for targeted metabolomic analysis. TH, VM and ES analyzed data. TH wrote the manuscript with input from all authors.

All statistical analysis was performed using InfoStat 2015d (http:// www.infostat.com.ar).

Comparisons of sample means were performed by one-way analysis of variance (P < 0.05 or P < 0.01) and Tukey's post-hoc multiple comparisons tests (P < 0.05 or P < 0.01), and significant differences of means were determined.

Protein extraction and immunoblot analysis

Leaves samples from jao2-1 pJAO2:JAO2-4xmyc lines were collected in 2 mL tubes containing glass beads and immediately frozen in liquid nitrogen. Before extraction, samples were supplemented with 150 to 300 µL of denaturation buffer (62.5 mM Tris pH 6.8, 4 M urea, 3 % SDS, 10 % glycerol, 0,1 % bromophenol blue, and 100 mM DTT) preheated to 95°C. Samples were homogenized in Precellys tissue homogenizer (Bertin Technologies, France) and cleared homogenates were recovered and stored at -20°C. Protein content in samples was quantified with an amidoblack assay. Proteins were separated by a standard SDS-PAGE procedure and JAO2-4xmyc protein was immunodetected with horseradish peroxidase luminescence using a Fusion Fx instrument (Vilber Lourmat). Equal loading of samples was evaluated by Coomassie staining of membranes.

Global (RNA-seq) transcriptome analysis, hormone/targeted metabolite analysis and nontargeted metabolomic analysis: described in Methods S1.

CONFLICT OF INTEREST

The authors declare that they have no competing interests. Table S1. RNA-seq analysis.

Table S2. Non-targeted metabolomic analysis of jao2-1 vs WT leaf extracts. Table S3. Transcription factor genes up-or down-regulated in jao2-1_vs_WT.

Accepted Article

This article is protected by copyright. All rights reserved Table S4. Primers used in the study.