Ph D Manuscript |

Anani Amegan

Catherine Leblanc

Hugues Renault

Mathieu Rousseau-Gueutin

Mélanie Lagarrigue-

Joël Boustie

Sylvie Baudino

Marie-Hélène Balesdent

Charles-Éric Durel

Pascal N Et Venceslas

Ph D Manuscript

| Anani

Amegan Missinou

Antoine Gravot
email: antoine.gravot@univ-rennes1.fr

Julie Ferreira

Thomas Delhaye

David Abdel

Maria J Manzanares

avec qui j'ai partagé mes études et notamment en

et Sandrine LAGARRIGUE) pour l'honneur qu'ils m'ont fait en acceptant de siéger dans le jury

Liste des figures

Figure 17: The "triangle of U" diagram (Nagaharu U, 1935) shows the genetic relationships between six genus species of Brassica.

Foreword

Plants synthesize a vast diversity of low molecular weight compounds (<2000 Da), which exhibit a tremendous structural diversity and are highly specific to a taxon, a cell type, or a developmental stage. These compounds generally termed «secondary metabolites» (SM), have long been widely used in medicine, cosmetics, and agriculture, like spices, perfumes, flavors, fragrances, drugs, insecticides, and herbicides (Traka and Mithen, 2009;Dinkova-Kostova and Kostov, 2012;[START_REF] Zachariah | Spices: secondary metabolites and medicinal properties[END_REF][START_REF] Faccio | Plant complexity and cosmetic innovation[END_REF]. They also include pigments or volatile compounds accumulated in flower petals to attract pollinators or respond to abiotic stress, bitter or toxic chemicals accumulated or triggered by herbivore injuries that serve as antifeedants, and compounds released by roots into the rhizosphere to modulate soil microorganisms. These metabolites are now considered «specialized» due to their predominant role in plant physiology and ecology [START_REF] Bentley | Secondary metabolite biosynthesis: the first century[END_REF][START_REF] Wink | Evolution of secondary metabolites from an ecological and molecular phylogenetic perspective[END_REF][START_REF] Wink | Introduction: Biochemistry, Physiology and Ecological Functions of Secondary Metabolites[END_REF][START_REF] Spinelli | Emission and Function of Volatile Organic Compounds in Response to Abiotic Stress[END_REF][START_REF] Tissier | Specialized Plant Metabolites: Diversity and Biosynthesis[END_REF], thus reconciling functional specialization and phylogenetic specificity. Consequently, they have commonly been considered the principal actors of ecological interaction processes that shape the species diversity, their coexistence, and trophic networks [START_REF] Weng | The evolutionary paths towards complexity: A metabolic perspective[END_REF][START_REF] Corwin | Quantitative resistance: More than just perception of a pathogen[END_REF][START_REF] Vleminckx | Divergent secondary metabolites and habitat filtering both contribute to tree species coexistence in the peruvian amazon[END_REF]Katz et al., 2021;Uckele et al., 2021).

The study of specialized metabolites is crucial in agriculture because of their ecological role. However, our understanding of the plant's specialized metabolome is yet insufficient. Indeed, a considerable part of the enzymes involved in specialized metabolism remains to be discovered or characterized [START_REF] Milo | Achieving diversity in the face of constraints: lessons from metabolism[END_REF]. The specific roles of most known specialized metabolites in physiological processes or responses to environmental stresses have not been conclusively established. The recent development of high-throughput, spatial, or genetical metabolomics has opened new perspectives to assess the phytochemical diversity in large panels of genotypes, investigate their regulation under stress conditions, and identify the genetic determinants controlling their biosynthesis. Considering the central role of specialized metabolism in biotic interactions, this knowledge can support plant breeding strategies (Yang et al., 2021).

In this project, oilseed rape (Brassica napus) was chosen as a study model to analyze the diversity of the specialized metabolism and its relationship with the plant's response to biotic stresses. Today, oilseed rape/canola is the worldwide second most-produced oilseed, behind soybeans [START_REF] Mittaine | The globalization of international oilseeds trade[END_REF], after being an auxiliary crop for food and industrial purposes in the last half-century. In France, its total cultivated area is 1.17 million hectares (Agreste: Grande cultures -n°2022-15 de Février 2022). The significant oilseed rape cultivation extension brought setbacks, such as a negative fingerprint on the environment, and the emergence of harmful pathogens and pests (i.e., blackleg, clubroot, broomrape, insects, etc.), endangering and compromising oilseed rape production. However, although taxonomic closeness with Arabidopsis thaliana, the diversity, regulation, and genetic determinism of the specialized metabolism in Brassica napus is poorly understood. This lack of effort limits scientific understanding of key determinants of biochemical and agroecological processes affecting the tolerance to biotic constraints in this crop. This was the main challenge we set ourselves during this thesis work.

This manuscript is built according to an "articles-based theses" format. It is structured around four chapters which first one will be devoted to the bibliographic introduction.

Introduction

For more than two centuries, scientific research around metabolism has shaped the perception of biologists across time, leading them to distinguish metabolites into three major classes based on approximations of their functions: primary metabolites, secondary/specialized metabolites (SM), and regulating metabolites like hormones or vitamins [START_REF] Wink | Introduction: Biochemistry, Physiology and Ecological Functions of Secondary Metabolites[END_REF]. Moreover, the terms "goal-directed metabolites" or "chemical defensive means" were suggested by the pioneers of chemical ecology (Anton Kerner von Marilaun, Léo Errera, and Ernst Stahl). In particular, Stahl uses these terms to designate, among other things, "the chemical defenses that plants produce to protect themselves" [START_REF] Hartmann | From waste products to ecochemicals: Fifty years research of plant secondary metabolism[END_REF][START_REF] Hartmann | The lost origin of chemical ecology in the late 19th century[END_REF]. However, for a long time, this idea was firmly rejected by phytochemists and plant physiologists, who considered these compounds as "metabolic wastes" or "detoxification products". It was only at the end of the XX th century-beginning of the XXI st that the functional studies focused on the role of the plant-specialized metabolism in the communication with other plant and nonplant species started (such as allelopathy and legume-rhizobia interactions, defense against pathogens, herbivores, and beneficial interactions with insects). Results obtained over the last two decades clearly highlight the function of specialized metabolites as mediators between plants and the environment (Weng et al. 2021).

Among the pressing questions arising from the field of specialized metabolism and chemical ecology are the assession of their structural and biosynthetic diversity, their adaptive significance, and the identification of the genetic determinants controlling their content. The structural investigation of the compounds involved in both abiotic and biotic interactions has allowed the inventory, for example, of 57,000 metabolites entries in the KNApSAcK database [START_REF] Afendi | KNApSAcK family databases: Integrated metabolite-plant species databases for multifaceted plant research[END_REF]. The expected number of metabolites in the plant kingdom is 200,000 to one million [START_REF] Dixon | Phytochemistry meets genome analysis, and beyond[END_REF][START_REF] Rai | Integrated omics analysis of specialized metabolism in medicinal plants[END_REF]. However, despite the significant scientific efforts attested by abundant literature in this field, it is rare to conclusively identify more than two hundred metabolites in a single taxon while the contents are probably much higher.

Due to their sessile nature, plants modify their morphology, physiology, and metabolism to acclimatize and adapt to their dynamic environment. While some subclasses of SM appear widely present in the plant kingdom (e.g., terpenoids and phenolics, including flavonoids), others appear restricted to some taxonomic groups (e.g., glucosinolates, cyanogenic glycosides, and alkaloids), indicating both ancestral and recent metabolic pathways. Recent advances in whole-genome sequencing suggest that all land plants have duplicated genomes, the fate of which several factors, including environmental stress, dictate enzymatic gene copies. Some biosynthetic similarities (enzymes, chemical structure, and chemical function) may appear independently in distant taxa, raising huge evolutionary questions about plantspecialized metabolism.

In this chapter, by focusing on specific examples, I will briefly review the metabolism so-called specialized of plants, focusing on the metabolism of the polyploid species under study (Section I.A.) before introducing the thesis objectives (Section I.B.).

I.A. The specialized metabolism in vascular plants

Firstly, is reported the progress in understanding the roles of metabolites, especially those considered specialized, in-plant/environment interactions (section I.A.1).

Secondly, is provided a global overview of the structural and functional diversity of the

I.A.1. The paradigm of the multifunctionality of specialized plant metabolism

For the following, numbers in bold after each metabolite name correspond to the number of the illustration of the structures of compounds 01 to 06 shown in Figure 1. These numbering will be used and incremented throughout this chapter.

Historically, the distinction between primary and secondary (or specialized)

metabolites was based on their functions: Primary metabolites are crucial to the immediate growth and development of plants when natural (secondary or specialized)

products are required to interact with the biotic and abiotic factors of environment [START_REF] Hartmann | From waste products to ecochemicals: Fifty years research of plant secondary metabolism[END_REF]. Besides, phytohormones or vitamins regulate the growth, development, and reproductive processes [START_REF] Van Overbeek | Plant hormones and regulators[END_REF][START_REF] Davies | The Plant Hormones: Their Nature, Occurrence, and Functions[END_REF].

However, more recently, some evidence that compounds that have been classically assigned as primary or secondary metabolites can also play roles in plant cell signaling, thus suggesting that the rough distinction into three distinct classes of compounds might be obsolete. This has led to consider the "multifunctionality" of the metabolism, thus marking a new historical landmark in the functions of plant Ph D. manuscript | Anani Amegan MISSINOU P a g e 17 metabolism [START_REF] Návarová | Pipecolic acid, an endogenous mediator of defense Ph D. manuscript | Anani Amegan MISSINOU P a g e 230 amplification and priming, is a critical regulator of inducible plant immunity[END_REF][START_REF] Erb | Plant Secondary Metabolites as Defenses, Regulators, and Primary Metabolites: The Blurred Functional Trichotomy[END_REF][START_REF] Durán-Medina | Specialized metabolism and development: An unexpected friendship[END_REF]Li et al., 2021). Some nitrogen-containing organic acid compounds encompassed primary or specialized roles, even phytohormones, e.g., L-proline (01), pipecolic acid (02), and heteroauxin (03) (Figure 1). Thus, pipecolic acid (02), an alkaloid analog to proteinogenic amino acid L-proline (01)), is a cyclic nonproteinogenic amino acid derived from L-lysine catabolism, whereas heteroauxin (03) derived from L-tryptophan is a phytohormone alkaloid. Similarly, diterpenes (C20) often encompassed the three functional categories (primary, secondary, and hormones). For instance, kaurenoic acid (04), abietic acid (05), and gibberellin A12 (GA12) (06) are diterpenoid carboxylic acids (Figure 1). (03), ent-kaurenoic acid (04), abietic acid (05), and gibberellin A12 (06). Proline (01) and kaurenoic acid (04) are admitted as primary metabolites, while they are structural neighbors of the specialized metabolites: pipecolic acid (02) and abietic acid (05). Gibberellins A12 (06) and heterauxin (03) are phytohormones (adapted from [START_REF] Croteau | Natural Products (Secondary Metabolites)[END_REF].

Ph D. manuscript | Anani Amegan MISSINOU P a g e 18

These three compounds (04, 05, 06) exhibit close structures and derive from geranylgeranyl pyrophosphate. Abietic acid (05) has been described as a significant component of the secreted resin and a defense phytochemical against insect and pathogen attacks found in Fabaceae, Pinaceae, and other conifer species [START_REF] Funk | Diterpenoid Resin Acid Biosynthesis in Conifers: Characterization of Two Cytochrome P450-Dependent Monooxygenases and an Aldehyde Dehydrogenase Involved in Abietic Acid Biosynthesis[END_REF]. Ent-kaurenoic acid (04) is also oxidized into the phytohormone GA12

(06) by an NADPH-dependent, membrane-bound CYP701A (ent-kaurene oxidase) [START_REF] Helliwell | The CYP88A cytochrome P450, ent-kaurenoic acid oxidase, catalyzes three steps of the gibberellin biosynthesis pathway[END_REF]. These structural overlaps of metabolite types (primary, specialized, and phytohormone) illustrate the blurred boundaries when applying a functional classification. Moreover, current research suggests that this functional separation is becoming obsolete such as the works characterizing for instance the accumulation of the proteinogenic aminoacid proline (01) in the context of incompatible interaction Arabidopsis thaliana-bacteria [START_REF] Fabro | Proline accumulation and AtP5CS2 gene activation are induced by plant-pathogen incompatible interactions in Arabidopsis[END_REF] and those detailing the contribution of hormone signalization (heteroauxin (03), JA, ethylene) to the plant defense against the attacks of pathogens and herbivores [START_REF] So | A Plant miRNA Contributes to Antibacterial Resistance by Repressing Auxin Signaling[END_REF][START_REF] Chen | Pseudomonas syringae type III effector AvrRpt2 alters Arabidopsis thaliana auxin physiology[END_REF][START_REF] Wang | Salicylic Acid Inhibits Pathogen Growth in Plants through Repression of the Auxin Signaling Pathway[END_REF][START_REF] Grant | Hormone (Dis)harmony Moulds Plant Health and Disease[END_REF]. Similarly, GC/MS-based profiling of mutants of A. thaliana revealed how pipecolic acid (Pip) (02) orchestrates systemic immunity [START_REF] Návarová | Pipecolic acid, an endogenous mediator of defense Ph D. manuscript | Anani Amegan MISSINOU P a g e 230 amplification and priming, is a critical regulator of inducible plant immunity[END_REF] (Figure 2). Pip is essential to establishing the local and systemic immune response (SAR 1 ) to pathogens. Indeed, the accumulation and the signaling contribution of Pip in the distal part of the infected leaf site of A. thaliana by Pseudomonas syringae have been pointed out. These few examples represent some breakthroughs in our understanding of the interconnection between specialized metabolites and hormones in plant defense and primary metabolites. Besides, several 1 SAR is an integral immune-activating pathway of plants, also called systemic immune response of plants, triggered by localized infection by pathogens from primary (local) tissues to uninfected secondary (distal) tissues.

Ph D. manuscript | Anani Amegan MISSINOU P a g e 19

reviews have highlighted a more direct contribution of primary metabolism in plant defense responses against bioaggressors [START_REF] Drew | Effect of primary metabolites on secondary metabolism[END_REF][START_REF] Bolton | Primary metabolism and plant defense-fuel for the fire[END_REF][START_REF] Morkunas | The role of sugar signaling in plant defense responses against fungal pathogens[END_REF][START_REF] Rojas | Regulation of primary plant metabolism during plantpathogen interactions and its contribution to plant defense[END_REF]. andALD1). PAD4: phytoalexins-deficient4, ISC1: isochorismate synthase1, ALD1: AGD2-like defense response protein [START_REF] Návarová | Pipecolic acid, an endogenous mediator of defense Ph D. manuscript | Anani Amegan MISSINOU P a g e 230 amplification and priming, is a critical regulator of inducible plant immunity[END_REF].

Recently, [START_REF] Erb | Plant Secondary Metabolites as Defenses, Regulators, and Primary Metabolites: The Blurred Functional Trichotomy[END_REF] demonstrated that all the metabolites (primary, specialized, and hormone) would be endowed with functional versatility (growth, development, defense, and regulation processes), which breaks the functional trichotomy paradigm. This functional versatility suggests that SMs interact with other classes of compounds (Figure 3). This new concept stimulates scientific thought and provides some working hypotheses for future research on the ecological roles of specialized metabolites. The questions that arise now are, for example: how do the metabolites that perform regulatory functions work? Do they act by binding to protein receptors? or by altering specific non-receptor proteins? or through general autotoxicity/reactivity? [START_REF] Erb | Plant Secondary Metabolites as Defenses, Regulators, and Primary Metabolites: The Blurred Functional Trichotomy[END_REF]. Other authors also pointed out the functional overlap between primary/specialized metabolites and hormones, thus supporting functional multiplicity, which is becoming a norm rather than an exception [START_REF] Durán-Medina | Specialized metabolism and development: An unexpected friendship[END_REF]Li et al., 2021). The structural patterns of SMs can be divided into major classes: alkaloids, cyanogenic glycosides, glucosinolates, tannins, coumarins, quinones, phenylpropanoids, flavonoids, polyketides, terpenoids, and benzoxazinoids. These categories of compounds typically display strong biological activities that largely contribute to the structuration of plants used by humans for food and non-food applications. The biosynthesis of terpenoids, alkaloids, phenolics, quinones, and polyketides occurs in the whole plant kingdom. Terpenoids, alkaloids, and phenolics regroup the highest number of already described molecules with ≥25,000 structures for terpenoids, ≥21,000 structures for alkaloids, and ≥10,000 structures for phenolic compounds [START_REF] Wink | Introduction: Biochemistry, Physiology and Ecological Functions of Secondary Metabolites[END_REF][START_REF] Christianson | Structural and Chemical Biology of Terpenoid Cyclases[END_REF].

Ph D. manuscript | Anani Amegan MISSINOU P a g e 22 43), (epi)progoitrin (44) are displayed. Adapted from [START_REF] Hartmann | From waste products to ecochemicals: Fifty years research of plant secondary metabolism[END_REF][START_REF] Wang | The Structure and Function of Major Plant Metabolite Modifications[END_REF].

Ph D. manuscript | Anani Amegan MISSINOU P a g e 23

Terpenoids (TPNs), so-called terpenes or isoprenoids, are ubiquitous in the plant's kingdom. However, some of the TPN subgroups (mono-(C10), sesqui-(C15), di-(C20), tri-(C30), and tetraterpenoids (C40)) have been widely used for chemotaxonomic studies due to the restriction of specific molecules to specific taxons.

For example, in Lamiaceae 2 , glycosylated monoterpenes (C10) (called iridoids), such as 5,9-epi-penstemoside (07) (Figure 4), are specific to certain plant species. This allows subdividing the Lamiaceae family (3500 species) into two sub-families: the Nepetoideae members (that are potent producers of essential oils and are lacking iridoids), and the Lamioideae, which are weak producers of essential oil but have a high content of 5,9-epi-penstemoside (7) [START_REF] Delazar | Iridoid Glycosides from Eremostachys baissunensis[END_REF]) (Figure 4).

Most sesquiterpenes and diterpenes have antimicrobial activity, e.g., 2-ketoepimanool (08), capsidiol (09), and lubimin (10) in tobacco Nicotiana spp [START_REF] Cohen | A preformed chemical inhibitor of tobacco powdery mildew on leaves of Nicotiana glutinosa[END_REF][START_REF] Threlfall | Co-ordinated inhibition of squalene synthetase and induction of enzymes of sesquiterpenoid phytoalexin biosynthesis in cultures of Nicotiana tabacum[END_REF][START_REF] Ahmed | Evaluation of induction of systemic resistance in pepper plants (Capsicum annuum) to Phytophthora capsici using Trichoderma harzianum and its relation with capsidiol accumulation[END_REF], oryzalide A (11) in rice [START_REF] Kono | Antibacterial diterpenes and their fatty acid conjugates from rice leaves[END_REF], artemisinin [START_REF] Pfalz | The Gene controlling the indole glucosinolate modifier1 quantitative trait locus alters indole glucosinolate structures and aphid resistance in Arabidopsis[END_REF] in Artemisia annua [START_REF] Klayman | Qinghaosu (artemisinin): An antimalarial drug from China[END_REF][START_REF] Li | A golden phoenix arising from the herbal nest -A review and reflection on the study of antimalarial drug Qinghaosu[END_REF], kauralexin B2 (13) in maize, and β-caryophyllene (14) in A. thaliana [START_REF] Schmelz | Identity, regulation, and activity of inducible diterpenoid phytoalexins in maize[END_REF][START_REF] Poloni | Red card for pathogens: Phytoalexins in sorghum and maize[END_REF]. Triterpenoids (C30) include several classes of compounds, many of which have potent deterrent and antifeedant effects on herbivores and insects (e.g., phytosterols, saponins, sapogenins, and pentacyclic triterpenes) [START_REF] Kuzina | Identification of defense compounds in Barbarea vulgaris against the herbivore Phyllotreta nemorum by an ecometabolomic approach[END_REF][START_REF] González-Coloma | Triterpene-based plant defenses[END_REF][START_REF] Thimmappa | Triterpene biosynthesis in plants[END_REF]. Finally, tetraterpenoids (C40) are carotenoids that determine the red color of flower petals, and polyterpenoids that are non-polar tackifiers, such as rubber.

2 Lamiaceae family, formerly the mint family, with 230/7000 genera/species, is one of the most investigated families of angiosperms [START_REF] Zhao | An updated tribal classification of Lamiaceae based on plastome phylogenomics[END_REF]. 4). Cinnamic acid derivatives (with acyl groups) are crucial as metabolic crossroads for building phenolic compounds. Among flavonoids, some have no chemical modification (e.g., 3-deoxyanthocyanidin, 20), while others can be acylated by one or more glycosylations (Figure 4). The glycosylation of flavonoids is favored in 3-OH (e.g., kaempferol-3-O-glucose, 21) and 7-OH groups of the flavone aglycone skeleton (Figure 4).

Some plant SMs contain one or more nitrogen atoms in their carbon skeletons. The most important classes are alkaloids, cyanogenic glycosides, benzoxazinoids, and glucosinolates (sulfur-containing compounds) (Figure 4). Globally, the nitrogen atom is derived from the amine function of primary amino acids.

Alkaloids are nitrogenous compounds with basic properties, most often harboring a heterocyclic ring system (Figure 4), and they are reported in more than 150 plant families [START_REF] Yamane | Chemical defence and toxins of plants[END_REF]. These compounds are synthesized from the decarboxylation of amino acids or transamination followed by structural modifications and are classed according to the amino acid (often nucleic acids) precursor and/or 3 Phenolic acids: e.g., (hydro)benzoic, salicyclic, caffeic, coumaric, ferulic, sinapic, syringic, m/p-cinnamic, coumaric gallic, protocatechuic, gentisic, vanillic acids and etc. 4 Flavonoids skeleton consists of rings A, B, and C of the C6-C3-C6 skeleton of flavone, on which variable substitutions (ketone, hydroxy, O-methyl) allow their classification into main classes: flavonols, flavone, isoflavone, flavan-3-ol, flavanone, anthocyanidin. 5 Lignans are a large group of low molecular weight polyphenols that are precursors to phytoestrogens.

Ph D. manuscript | Anani Amegan MISSINOU P a g e 25 according to their chemical skeleton (e.g., the indole skeleton of tryptophan in camalexin (26), spirobrassinin (27), and 6-GlcO-ICOOGlc 7 (28)). As a result, some alkaloids with similar skeletons, or even the same precursors, can come from different biosynthetic pathways (e.g., the two phytoalexins camalexin (26) and 6-GlcO-ICOOGlc (28)) or may present contrasting biological activities (e.g., the hormone IAA (03) and the phytoalexin 6-GlcO-ICOOGlc (28)) [START_REF] Böttcher | The Biosynthetic Pathway of Indole-3-Carbaldehyde and Indole-3-Carboxylic Acid Derivatives in Arabidopsis[END_REF]. Thus, based on their underlying heterocyclic nucleus and biosynthetic precursor, alkaloids can be grouped into pyrrole, pyridine, piperidine, purine, pyrimidine, imidazole, and indole, among others 8 (Ponikvar-Svet et al., 2021).

Benzoxazinoids (BXZ) are tryptophan-derived specialized metabolites of the

Poaceae family, including wheat, rye, maize, and some dicots. They are often methylated and glycosylated which monoglycosylated benzoxazinoids being the most frequent. Some unusual di-, tri-, tetra-hexoxylated, and acetyl-hexosylated derivatives have recently been reported [START_REF] De Bruijn | Mass Spectrometric Characterization of Benzoxazinoid Glycosides from Rhizopus-Elicited Wheat (Triticum aestivum) Seedlings[END_REF][START_REF] Pihlava | Determination of benzoxazinoids in wheat and rye beers by HPLC-DAD and UPLC-QTOF MS[END_REF].

These SMs are effective in plant defense against pathogens [START_REF] Villagrasa | Benzoxazinoid allelochemicals in wheat: Distribution among foliage, roots, and seeds[END_REF][START_REF] Macías | Rediscovering the bioactivity and ecological role of 1,4-benzoxazinones[END_REF][START_REF] Tanwir | Comparison of the levels of bioactive benzoxazinoids in different wheat and rye fractions and the transformation of these compounds in homemade foods[END_REF]. Non-glycosylated benzoxazinoids are toxic, and plants or insects detoxify them using various mechanisms such as hydroxylation and O-or N-glycosylation [START_REF] De Bruijn | Structure and biosynthesis of benzoxazinoids: Plant defence metabolites with potential as antimicrobial scaffolds[END_REF]. These inactive conjugated forms stored in vacuoles and commonly termed phytoanticipins are enzymatically released when needed to respond to a microbial attack or other environmental stimuli [START_REF] Cambier | Non-injured maize contains several 1,4-benzoxazin-3-one related compounds but only as glucoconjugates[END_REF][START_REF] Niemeyer | Hydroxamic acids derived from 2-hydroxy-2h-1,4-benzoxazin-3(4h)-one: Key defense chemicals of cereals[END_REF]. They can be divided into three structural classes: (A) benzoxazolinone glycosides, for example, 1,3-benzoxazol-2-one (BOA-glucose, 33), 7 6-GlcO-ICOOGlc stand for b-D-glucosyl 6-hydroxyindole-3-carboxylate 6-O-b-D-glucoside. 8 Other heterocycle of alkaloids: pyrroline, pyrrolidine, piperideine, pyrrolizidine, triazine, tropane, (benyl)(iso)quinoline. benzoxazin-3-one (HMBOA-glucose, 37) (Figure 4).

Ph

Cyanogenic glycosides (CNglcs) are nitrogen-compounds belonging to cyanogenic compounds 9 composed of cyanide aglycone (from amino acids) attached to a sugar moiety (mostly β-D-monoglucose), which sometimes gets modified to a second monosaccharide, a sugar ester (e.g., Amygdalin (40)) [START_REF] Francisco | Cyanogenic glycosides in plants[END_REF] (Figure 4). [START_REF] Yamane | Chemical defence and toxins of plants[END_REF].

Cyanogenic glycosides are phytoanticipins activated into toxic HCN derivatives. The enzymes (O-β-glycoside) catalyze the production of HCNs in different cellular compartments from which the substrates are present [START_REF] Poulton | Tissue level compartmentation of (R)-amygdalin and amygdalin hydrolase prevents largescale cyanogenesis in undamaged Prunus seeds[END_REF]. For

example, in Sorghum bicolor, the enzyme responsible for the hydrolysis of dhurrin (41)

is present in the mesophyll cells. At the same time, its substrate is stored in the vacuole of the leaf epidermal cells [START_REF] Nielsen | Dhurrin metabolism in the developing grain of Sorghum bicolor (L.) Moench investigated by metabolite profiling and novel clustering analyses of time-resolved transcriptomic data[END_REF]. The HCNs derivatives released in plant cells are detoxified by mitochondrial β-cyanoalanine synthase and rhodanese (i.e., sulfurtransferase) [START_REF] Machingura | The β-cyanoalanine synthase pathway: beyond cyanide detoxification[END_REF]. 9 Cyanogenic compounds encompass, cyanogenic lipids (from Sapindaceae) cyanohydrin, cyanogenic glycosides Ph D. manuscript | Anani Amegan MISSINOU P a g e 27

Glucosinolates (GLSs) are nitrogen-sulfur-containing compounds consisting of a β-D-glucopyranose moiety linked to sulfated oxime via the isothiocyanate group and variable aglycone. GLSs can be phenylalkyl, indolic, aliphatic linear, or branched/linear derivatives of amino acid precursors such as phenylalanine, tryptophan, methionine, or branched-chain amino acids, respectively (Fahey et al., 2001;[START_REF] Blažević | Glucosinolate structural diversity, identification, chemical synthesis and metabolism in plants[END_REF]Missinou et al., 2022). GLSs are found mainly in the order of Brassicales, whose evolution and radiation began 103 million years ago [START_REF] Cardinal-Mcteague | Biogeography and diversification of Brassicales: A 103 million year tale[END_REF] (Figure 4). GLSs are hydrolyzed by β-thioglucosidases, also known as myrosinases.

Like benzoxazinoids, myrosinase, and glucosinolates are stored in separate subcellular compartments and come together only under conditions of tissue injury (e.g., cell disruption due to biting or chewing by herbivores), and the resulting products (nitriles, epithionitrile, thiocyanates, isothiocyanates, oxazolidinethiones) are bioactive against generalist herbivores.

The contribution of these antimicrobial compounds to plant immunity will be described in section I.A.5.

I.A.2.2. Metabolic origin of plant specialized metabolites

All SM categories are derived from the primary metabolism through a series of key are the first committed enzymes in the pathway that diverts the central flux of carbon from the primary metabolism (i.e., phenylalanine et tyrosine) to initiate the synthesis of various phenolics compounds (Figure 5). These series of enzymes, at the interface between primary and specialized metabolism, are conserved in the plant kingdom.

The resulting products of these reactions become the fundamental precursors and biochemical scaffolds of the whole phytochemical diversity by entering into more specific biosynthetic pathways involving taxon-specific enzymes from SM-related large multigenic families. These notably include terpene synthases, polyketide synthases for the biosynthesis of the diversity of SM 'molecular scaffolds', and for example,

I.A.2.3. Biosynthetic diversity of plant-specialized metabolites

The metabolic grid concept 10 is based on a theory proposed in the 1990s, stating that the enzymes catalyzing a series of transformations are not substrate-specific [START_REF] Bu | Comparative and Functional Aspects of the Isoprene Pathway in Fungi[END_REF]. Today, this enzymatic property referred to as enzyme-substrate promiscuity (discussed in section I. A.3.1.3.), displayed by some secondary metabolism enzymes, is one of the drivers providing varied chemical structures from a conserved limited number of primary precursors.

Figure 6: Diverse routes of metabolite precursors in the conceptual metabolic grid schema [START_REF] Tissier | Specialized Plant Metabolites: Diversity and Biosynthesis[END_REF].

The different routes that metabolic precursors can take are illustrated in Figure 6. In this schema, six enzymes (numbered E1 to E6) could theoretically be involved in the biosynthesis of 27 different products from a single precursor depending on their relative expression level (Figure 6). The relative amounts of each metabolite in the grid will 10 Bu'Lock has largely contributed to the development of the metabolic grid concept in relation to the biosynthesis of aromatic polyketides in Penicillium urtice [START_REF] Bu | Comparative and Functional Aspects of the Isoprene Pathway in Fungi[END_REF].

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depend on the relative level of expression of the different enzymes, the availability of these enzymes in the various tissues or cellular compartments, and the subsequent modification or transport of the metabolites. Additionally, enzyme isoforms can coexist with slightly different affinities for molecules within a set of related metabolites [START_REF] Tissier | Specialized Plant Metabolites: Diversity and Biosynthesis[END_REF].

This model makes it possible to speculate on uncharacterized metabolic pathways or even produce a distinct set of compounds with specific biological functions by metabolic engineering. This flexible pathway architecture has allowed the characterization of the biosynthetic pathways of the Leguminosae quinolizidine alkaloids (e.g., anagyrine, 32) [START_REF] Nowacki | Use of the metabolic grid to explain the metabolism of quinolizidine alkaloids in Leguminosae[END_REF], isoflavones [START_REF] Barz | Biosynthesis and Metabolism of Isoflavones and Pterocarpan Phytoalexins in Chickpea, Soybean and Phytopathogenic Fungi[END_REF][START_REF] Barz | Constitutive and elicitation induced metabolism of isoflavones and pterocarpans in chickpea (Cicer arietinum) cell suspension cultures[END_REF], and phenolic glycosides from phenylpropanoid and benzenoid precursors [START_REF] Babst | Biosynthesis of phenolic glycosides from phenylpropanoid and benzenoid precursors in populus[END_REF].

I.A.3. Factors involved in the evolutionary diversification of plant specialized metabolites

The evolutionary diversification of plant SM relies, on one hand, on a series of genomic processes involved in the diversification of SM biosynthetic enzymes and, on the other hand, on the driving selection exerted by biotic and abiotic environmental pressures.

I.A.3.1. Genomic processes involved in the diversification of SM-related biosynthetic enzymes

The genomes of terrestrial land plants are estimated to contain between 15 and 28% of genes coding for biosynthetic enzymes involved in the biosynthesis of specialized metabolites [START_REF] Schläpfer | Genome-Wide Prediction of Metabolic Enzymes, Pathways, and Gene Clusters in Plants[END_REF][START_REF] Moore | Robust predictions of specialized metabolism genes through machine learning[END_REF]. Many mechanisms, including the compounds or reactions produced are identical but obtained by distinct evolutionary enzymes [START_REF] Pichersky | Convergent evolution in plant specialized metabolism[END_REF].

Concerning the first class, a surprising co-occurrence of cyanogenic glycosides and glucosinolates has been reported in Carica papaya (Caricaceae, Brassicales) [START_REF] Williams | An unusual combination in papaya (Carica papaya): The good (glucosinolates) and the bad (cyanogenic glycosides)[END_REF] and of indolic-CNglc and indolic-GLS in A. thaliana [START_REF] Rajniak | A new cyanogenic metabolite in Arabidopsis required for inducible pathogen defense[END_REF]. This co-occurrence of cyanogenic glycosides and glucosinolates for critical . [START_REF] Li | Convergent evolution of a metabolic switch between aphid and caterpillar resistance in cereals[END_REF].

Other examples include the couples of anthocyanins/betacyanins that play essential roles in pollination [START_REF] Brockington | Complex pigment evolution in the Caryophyllales[END_REF] and indolic-GLSs/benzoxazinoids in insect defense (Figure 8) [START_REF] Li | Convergent evolution of a metabolic switch between aphid and caterpillar resistance in cereals[END_REF]. This is also observed in Brassica pathogens such as Leptosphaeria maculans, which produce sulfur metabolites like its host, making blur/confound attributions in metabolomics studies. Similarly, cyanogenic glycosides (CNglcs) and glucosinolates (GLSs) are both activated by plant enzymes in response to tissue damage, producing cyanide and thiocyanates derivatives that target hostplant protection against insect feeding [START_REF] Morrissey | Fungal Resistance to Plant Antibiotics as a Mechanism of Pathogenesis[END_REF]. A chemical convergence between plants and insects is associated with plants producing phenyl-CNglc and benzyl-GLS [START_REF] Beran | Chemical convergence between plants and insects: Ph D. manuscript | Anani Amegan MISSINOU P a g e 222 biosynthetic origins and functions of common secondary metabolites[END_REF].

An example of the second type of convergence evolution is the case of caffeine (29), whose biosynthetic pathways (nearly 12 potential pathways) have evolved independently in many quite distant species, such as the lineage of coffee (Coffea arabica (Gentianales), tea (Camellia sinensis, Ericales), Citrus spp, cacao (Theobroma cacao, Malvaceae) and Guarana (Paullinia cupana) [START_REF] Huang | Convergent evolution of caffeine in plants by co-option of exapted ancestral enzymes[END_REF].

I.A.3.1.3. Enzyme promiscuity

The promiscuity of an enzyme is the ability to catalyze unexpected reactions, so-called promiscuous reactions distinct from predictable (primary) reactions; this promiscuity is due to nucleotide mutations impacting one or fewer amino acids. Two main promiscuities can be distinguished for enzyme specificities: substrate promiscuity and product promiscuity. The ability of an enzyme to catalyze different products from a single substrate refers to the enzyme-product promiscuity, such as aureusidin synthase of snapdragon (Antirrhinum majus), which provides unequivocal oxidation of polyphenol, giving the yellow color [START_REF] Kusumi | Aureusidin synthase: a polyphenol oxidase homolog responsible for flower coloration[END_REF] or even the oxidative rearrangement of (+)-sesamin by sesaminol synthase (CYP91C) in sesame seeds (Sesamum indicum) [START_REF] Murata | Oxidative rearrangement of (+)-sesamin by CYP92B14 co-generates twin dietary lignans in sesame[END_REF]. By contrast, enzyme-substrate promiscuity is an ability of an enzyme to use multiple substrates with relaxed or broad substrate specificity, which is valuable for environmental adaptation. For example, groups: hydroxyl and sulfhydryl, so including broad aromatic and aliphatic thiols substrates, [START_REF] Zhao | A SABATH Methyltransferase from the moss Physcomitrella patens catalyzes S-methylation of thiols and has a role in detoxification[END_REF][START_REF] Leong | Promiscuity, impersonation and accommodation: evolution of plant specialized metabolism[END_REF]. Similarly, the enzymes coded by paralogs flavonoid-3′-hydroxylase and flavonoid-3,5-hydroxylase have broad substrate specificity subject to hydroxylation of the B-ring of hydroxylated flavanones, dihydroflavonols, flavonols, and flavones determining red cyanidin-/blue delphinidinbased anthocyanins flower of various plant species [START_REF] Castellarin | Colour variation in red grapevines (Vitis vinifera L.): Genomic organisation, expression of flavonoid 3′hydroxylase, flavonoid 3′,5′-hydroxylase genes and related metabolite profiling of red cyanidin-/blue delphinidin-based anthocyanins in berry skin[END_REF][START_REF] Tanaka | Flower colour and cytochromes P450[END_REF]. Furthermore, the substrate and donor of flavonoid-

I.A.3.2. Environmental drivers of plant SM diversification over geologic timescale

Establishing the environmental factors that participated in the diversification of specialized metabolites is fundamental to understanding how these metabolic body innovations (e.g., leaves, trichomes, roots), associated with the biosynthesis of terpenes, phenolics, and alkaloids as antiherbivore defense [START_REF] Labandeira | Middle Devonian liverwort herbivory and antiherbivore defence[END_REF][START_REF] Delgoda | Evolutionary Perspectives on the Role of Plant Secondary Metabolites[END_REF]. The seeds appear in the early Mesozoic with the expression of tannins that protect them from biotic and abiotic stresses (Figure 10).

The appearance of fruits is more recent in the middle of the Cenozoic era (~40 million years), following the production of volatile compounds necessary for the attraction of pollinators [START_REF] Delgoda | Evolutionary Perspectives on the Role of Plant Secondary Metabolites[END_REF].

I.A.4. Factors involved in the regulation of plant-specialized metabolite biosynthesis

Specialized metabolites typically accumulate in concentrations ranging from nmol to tens of μmol.g -1 DW, and usually are restricted to the cellular production site. loop-helix) 60 conserved amino acid residues and consist of bipartite to the basic region and helix-loophelix region. The members of the bZIP TF family comprise a conserved leucine zipper and a positively charged DNA binding site. Divided into four groups, 1R-, R2R3-, 3R-, and 4RMYB, the MyB TF R2/R3 family of MYB TF significantly regulates plant-specialized metabolite pathways. NAC TF family has five subdomains (A-E), with A necessary for dimerization, B and E responsible for functional diversity, and C and D highly conserved and accountable for DNA binding [START_REF] Meraj | Transcriptional Factors Regulate Plant Stress Responses Through Mediating Secondary Metabolism[END_REF][START_REF] Jan | Plant secondary metabolite biosynthesis and transcriptional regulation in response to biotic and abiotic stress conditions[END_REF].

Sometimes

AP2/ERF TFs family members bind to the jasmonate-and elicitor-responsive element (JERE) in the promoter site of genes involved in the biosynthesis of terpenoid indole alkaloids, steroidal glycoalkaloids, nicotine, saponins, taxol, and resveratrol following biotic stress [START_REF] Van Der Fits | ORCA3, a Jasmonate-Responsive Transcriptional Regulator of Plant Primary and Secondary Metabolism[END_REF][START_REF] Meraj | Transcriptional Factors Regulate Plant Stress Responses Through Mediating Secondary Metabolism[END_REF][START_REF] Jan | Plant secondary metabolite biosynthesis and transcriptional regulation in response to biotic and abiotic stress conditions[END_REF] (Figure 10). WRKY TFs regulate the expression of the genes involved in the biosynthetic pathway responsible for hydroxycinnamic acid amides (HCAAs), alkaloids, terpenoids, terpenes, benzylisoquinoline, and alkaloid production [START_REF] Meraj | Transcriptional Factors Regulate Plant Stress Responses Through Mediating Secondary Metabolism[END_REF][START_REF] Jan | Plant secondary metabolite biosynthesis and transcriptional regulation in response to biotic and abiotic stress conditions[END_REF]. bHLH TFs are associated with anthocyanin, alkaloids, glucosinolates, diterpenoid phytoalexins, and saponins biosynthesis [START_REF] Meraj | Transcriptional Factors Regulate Plant Stress Responses Through Mediating Secondary Metabolism[END_REF][START_REF] Jan | Plant secondary metabolite biosynthesis and transcriptional regulation in response to biotic and abiotic stress conditions[END_REF]. bZIP TFs are involved in stress responses to ROS, osmotic, nutrient, drug, and pathogens stresses by regulating anthocyanin, tanshinone, artemisinin, terpenoid phytoalexins production [START_REF] Meraj | Transcriptional Factors Regulate Plant Stress Responses Through Mediating Secondary Metabolism[END_REF][START_REF] Jan | Plant secondary metabolite biosynthesis and transcriptional regulation in response to biotic and abiotic stress conditions[END_REF].

MYB TFs regulate genes involved in the biosynthesis of flavonoids, HCAAs, and proanthocyanins in response to attacks by fungi and herbivores [START_REF] Meraj | Transcriptional Factors Regulate Plant Stress Responses Through Mediating Secondary Metabolism[END_REF][START_REF] Jan | Plant secondary metabolite biosynthesis and transcriptional regulation in response to biotic and abiotic stress conditions[END_REF] (Figure 12). Finally, the biotic and abiotic stress-responsive NAC TFs are involved in the biosynthetic pathway of flavonoid, putrescine, and camalexin [START_REF] Meraj | Transcriptional Factors Regulate Plant Stress Responses Through Mediating Secondary Metabolism[END_REF][START_REF] Jan | Plant secondary metabolite biosynthesis and transcriptional regulation in response to biotic and abiotic stress conditions[END_REF].

Ph D. manuscript | Anani Amegan MISSINOU P a g e 41 [START_REF] Borevitz | Activation tagging identifies a conserved MYB regulator of phenylpropanoid biosynthesis[END_REF].

I.A.4.2. Ontogenic factors

Some chemical traits may vary or even be specific to some plant developmental stages: seeds, seedlings, and juvenile or mature reproductive individuals. Plant ontogeny can influence the composition and content of specialized metabolites in the whole organism and/or in specific organs (leaves, roots, stems, glands, laticifers, trichomes,…). The content of SM declines during ontogeny in the case of cyanogenic glycosides [START_REF] Neilson | Phenylalanine derived cyanogenic diglucosides from Eucalyptus camphora and their abundances in relation to ontogeny and tissue type[END_REF][START_REF] Ochoa-Lopez | Ontogenetic changes in the targets of natural selection in three plant defenses[END_REF], glucosinolates [START_REF] Pereira | Influence of temperature and ontogeny on the levels of glucosinolates in broccoli (Brassica oleracea var. italica) sprouts and their effect on the induction of mammalian phase 2 enzymes[END_REF][START_REF] Palaniswamy | Ontogenic variations of ascorbic acid and phenethyl isothiocyanate concentrations in watercress (Nasturtium officinale R.Br.) leaves[END_REF][START_REF] Schreiner | Ontogenetic changes of 2-propenyl and 3-Lndolylmethyl glucosinolates in Brassica carinata leaves as affected by water supply[END_REF][START_REF] Hanschen | Isothiocyanates, Nitriles, and Epithionitriles from Glucosinolates Are Affected Ph D. manuscript | Anani Amegan MISSINOU P a g e 226 by Genotype and Developmental Stage in Brassica oleracea Varieties[END_REF], sesquiterpenes, and triketones [START_REF] Goodger | Differential metabolic specialization of foliar oil glands in Eucalyptus brevistylis Brooker (Myrtaceae)[END_REF], alkaloids [START_REF] Liu | Variations in the secondary metabolite camptothecin in relation to tissue age and season in Camptotheca acuminata[END_REF][START_REF] Karinho-Betancourt | Phylogenetic correlations among chemical and physical plant defenses change with ontogeny[END_REF]. Ontogeny can also affect in opposite ways the content of several plant defense metabolites; for instance, phenolics decrease, and terpenoids increase throughout ontogeny [START_REF] Goodger | Contrasting ontogenetic trajectories for phenolic and terpenoid defences in Eucalyptus froggattii[END_REF]. These studies highlighted the role of ontogeny as a source of variation of the SM composition and content, contributing thus to the adaptive value of the plant to its environment.

Otherwise, some compounds may exhibit different ontogenic patterns due to the existence of opposite ontogenic trajectories, as shown in figure 13. This suggests a "Janus-faced" ontogeny impact on specialized metabolism, which prompts careful extrapolation of metabolic observations from the juvenile stage to the reproductive stage of plants.

I.A.5. Plant Immunity: Qualitative and quantitative resistance

Depending upon the nature of plant-pathogen interactions (non-host 11 and host 12 relationship), plants generally have three main defense mechanisms: non-host resistance (which will not be discussed), qualitative resistance, and quantitative resistance (Figure 14a). 11 Non-host relationship is characterized by an incompatibility interaction between all cultivars of the species and all biotypes of the pathogen agent. 12 Host relationship is described by a compatible or incompatible interaction conditioned by cultivar or biotype.

Ph D. manuscript | Anani Amegan MISSINOU P a g e 43

I.A.5.1. Qualitative resistance

Qualitative resistance prevents symptom appearance by rapidly stopping the progression and multiplication of pathogens in the host plant tissues. This type of resistance is mainly controlled by major genes 13 (R genes) (Figure 14b). Of the 314 R genes cloned so far, more than half code for proteins belonging to the NLR (191 genes), Receptor-like protein (RLP), and receptor-like kinase (RLK) (60 genes) families (Kourelis and van der Hoorn, 2018) (Figure 14c,e). NLRs are cytosolic proteins involved in the direct or indirect perception of certain effectors ("avirulence proteins") delivered by microbes into plant cells. RLP/RLK are transmembrane proteins with an extracellular domain capable of detecting specific effectors or PAMPs 14 secreted by microorganisms in the apoplast (Figure 14d). This suggests that qualitative resistance is essentially based on the perception of "non-self"

and "self-modification by non-self ", which allows resistant plants to quickly initiate effective defense responses to stop the progression of the pathogen [START_REF] Dangl | Plant pathogens and integrated defence responses to infection[END_REF][START_REF] Cui | Effector-triggered immunity: From pathogen perception to robust defense[END_REF]. Ultimately, activation of R genes leads to two types of responses: resistance-related (RR) metabolites (RRMs) and proteins (RRPs). The R genes regulate the amount of specialized metabolites (e.g., phenylpropanoids, flavonoids, and some alkaloids) biosynthesized, either by metabolic-type regulators (hormones) or by activating protein-type regulators (transcription factors). These strengthen the cell walls or directly suppress the pathogen depending on their antimicrobial properties [START_REF] Kushalappa | Plant Innate Immune Response: Qualitative and Quantitative Resistance[END_REF].

However, this resistance response is generally effective against only a limited number of strains (so-called specific resistance). The breakdown of qualitative resistance is usually very rapid after their deployment due to the evolution of the pathogen populations and the inability of a deployed resistant variety (resistant to a specific strain) to recognize the effectors of other strains. This type of resistance has been the most used in plant breeding for the development of resistant varieties during the last century.

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I.A.5.2. Quantitative resistance

Faced with the breakdown of qualitative resistance in several major crops, the breeding process today aims to build varieties with more durable resistance. Indeed, other plant pathosystems display diverse phenotypes or resistance continuously ranging from partially resistant individuals to partially susceptible ones. Genetic analyses of this type of resistance in segregating populations show a continuous distribution of phenotypes and a polygenic control of this trait (Figure 15). This often corresponds to a more complex genetic architecture involving different genetic factors of resistance (Quantitative Trait Loci-QTLs) each with a small effect on the phenotype. [START_REF] Corwin | Quantitative resistance: More than just perception of a pathogen[END_REF]. (c) the small effect of 'non-self' perception by receptors and multiplicity initiating quantitative resistance through a network implied many co-regulated genes [START_REF] Roux | Resistance to phytopathogens e tutti quanti: Placing plant quantitative disease resistance on the map[END_REF]. (d) Qualitative resistances are determined by genes coding for enzymes of the metabolism of organic chemical defenses (phytoalexins, antimicrobial peptides/proteins), hormonal signaling, and oxidative stress.

Quantitative resistance (QR) is often effective against a large number of pathogen strains ("broad spectrum" resistance) [START_REF] Nelson | Navigating complexity to breed disease-resistant crops[END_REF] and appears to be significantly more durable than resistance controlled by major resistance genes. It has been shown that the combination of quantitative and qualitative resistance could increase the durability of major resistance genes (Delourme et al., 2014;Pilet-Nayel et al., 2017). Genes underlying the resistance QTLs are diverse in functions, ranging from non-self recognition (NLR or RLK) [START_REF] Diener | Resistance to Fusarium oxysporum 1, a dominant Arabidopsis disease-resistance gene, is not race specific[END_REF][START_REF] Huard-Chauveau | An Atypical Kinase under Balancing Selection Confers Broad-Spectrum Disease Resistance in Arabidopsis[END_REF][START_REF] Hurni | The maize disease resistance gene Htn1 against northern corn leaf blight encodes a wallassociated receptor-like kinase[END_REF][START_REF] Debieu | Quantitative disease resistance to the bacterial pathogen Xanthomonas campestris involves an Arabidopsis immune receptor pair and a gene of unknown function[END_REF], signaling-associated protein families, to primary metabolism and very frequently to specialized metabolism. This suggests a non-negligible contribution of specialized metabolism to the quantitative resistance response. For instance, overexpression of biosynthetic genes of GLSs, BnMAM1, BnCYP83A1, and BnUGT74B1 enhanced the resistance of B. napus to Sclerotinia sclerotiorum [START_REF] Zhang | Overexpression of three glucosinolate biosynthesis genes in Brassica napus identifies enhanced resistance to Sclerotinia sclerotiorum and Botrytis cinerea[END_REF][START_REF] Wu | Comparative transcriptomic analysis uncovers the complex genetic network for resistance to Sclerotinia sclerotiorum in Brassica napus[END_REF]. Functional categories of chemical defenses used in a process underlying quantitative resistance are discussed in the following subsection.

I.A.6. Contribution of specialized metabolism to plant immunity

Plants synthesize and store many specialized defense metabolites to protect themselves from foreign bioaggressors. cadmium, and lead in vacuoles or trichomes, and these elements contribute to chemical defense against pests. This strategy, so-called elemental defenses or inorganic chemical defenses, allows plants to eliminate these harmful/toxic elements from the cellular machinery and to release them only upon cell death or injury, mainly caused by herbivores [START_REF] Poschenrieder | Can metals defend plants against biotic stress?[END_REF][START_REF] Boyd | Plant defense using toxic inorganic ions: Conceptual models of the defensive enhancement and joint effects hypotheses[END_REF][START_REF] Cooke | Tradeoffs between foliar silicon and carbon-based defences: Evidence from vegetation communities of contrasting soil types[END_REF].

Organic chemical defenses include constitutive polymers (callose, lignin, suberin, etc.), defense proteins (e.g., ricin), fatty acid derivatives, nonprotein amino acids, and antimicrobial metabolites (phytoanticipins) essentially.

Phytoanticipins 15 , including saponins, are an essential source of constitutive antimicrobials, setting chemical barriers against pathogens. They are biosynthesized in healthy plants, accumulated in dead cells, excreted into the external environment (e.g., rhizosphere), or stored in vacuoles in an inactive form even before the pathogen attack [START_REF] Vanetten | Two Classes of Plant Antibiotics: Phytoalexins versus "Phytoanticipins[END_REF][START_REF] Osbourn | Preformed antimicrobial compounds and plant defense against fungal attack[END_REF]. Phytoanticipins encompass phenolics, nitrogen-containing compounds (alkaloids, glucosinolates, benzoxazinoids, cyanogenic glycosides, polyketides, pyrrolizidine alkaloids), or benzylisoquinolin [START_REF] Pedras | Plant chemical defenses: Are all constitutive antimicrobial metabolites phytoanticipins?[END_REF]. They also show insecticidal, piscicidal, molluscicidal, allelopathic action, and anti-nutritional effects. Phytoanticipins have soap-like properties (wetting agent with surface-active properties) on the sterols constituting the microbial membrane, which induces pore formation and even cell lysis. The most striking example is avenacin A1 (a glycosylated triterpenoid), which is localized in the 15 The term of Phytoanticipins coined by John W. Mansfield at a symposium on "Phytoalexin Hypothesis and Beyond" held in Dannenfels, Germany, to honor the 50-year anniversary of the phytoalexin concept and define as « are low molecular weight, antimicrobial compounds that are present in plants before the challenge by microorganisms or are produced after infection solely from preexisting constituents » [START_REF] Vanetten | Two Classes of Plant Antibiotics: Phytoalexins versus "Phytoanticipins[END_REF].

Ph D. manuscript | Anani Amegan MISSINOU P a g e 48 epidermal cells of Gramineae roots (Figure 16A) [START_REF] Osbourn | Preformed antimicrobial compounds and plant defense against fungal attack[END_REF][START_REF] Morrissey | Fungal Resistance to Plant Antibiotics as a Mechanism of Pathogenesis[END_REF] and the α-tomatine (a steroidal glycoalkaloid) of Solanaceae species [START_REF] Roddick | Subcellular localization of steroidal glycoalkaloids in vegetative organs of Lycopersicon esculentum and Solanum tuberosum[END_REF][START_REF] Keukens | Molecular basis of glycoalkaloid induced membrane disruption[END_REF]. Similarly, tannins of the terpenoid class, 2ketoepimanool (08) of Nicotiana spp (Solanaceae), oryzalide A (11) of rice, and artemisinin (12) of A. annua, have been identified as constitutive antimicrobial compounds in leaves where their content increases after fungal infection [START_REF] Cohen | A preformed chemical inhibitor of tobacco powdery mildew on leaves of Nicotiana glutinosa[END_REF][START_REF] Kono | Antibacterial diterpenes and their fatty acid conjugates from rice leaves[END_REF][START_REF] Bora | The genus Artemisia: A comprehensive review[END_REF]. release toxic HCN, which inhibits the activity of the cytochrome c oxidase and metalloenzymes of herbivores/pathogens [START_REF] Gleadow | Cyanogenic glycosides: Synthesis, physiology, and phenotypic plasticity[END_REF].

I.A.6.2. Induced chemical defenses

In response to the plethora of biotic stress factors, plants have developed an innate immune system that detects and/or represses bioagressors. Plant immunity depends on perception, signal transduction, and the defense response [START_REF] Spoel | How do plants achieve immunity? Defence without specialized immune cells[END_REF].

The induced chemical defense is triggered once the physical defenses have been breached. This starts with the detection of non-self by surface-anchored recognition receptors (PRR 17 ). These receptors are highly conserved across the plant kingdom and perceive damage/herbivore/microbe/pathogen-associated molecular patterns (DAMPs/HAMPs/MAMPs/PAMPs), then triggering the innate immune response, DAMPs-triggered immunity (DTI), HAMPs-triggered immunity (HTI), (MAMP)-triggered immunity (MTI), and pattern-triggered immunity (PTI) [START_REF] Spoel | How do plants achieve immunity? Defence without specialized immune cells[END_REF][START_REF] Zipfel | Plant pattern-recognition receptors[END_REF]. However, some pathogens can introduce or release effector proteins in the host cell to inhibit or degrade host immune factors. In turn, plants rely on versatile symplastic sentinels, namely nucleotide-binding site and leucine-rich repeat receptors (NBS-LRR, also termed NLR), to identify specific pathogen-derived effector proteins and trigger effector-triggered immunity (ETI). These receptors activate signal transduction networks, including phytohormone-dependent defense signaling (salicylic, jasmonic, gibberellic, indole acetic acid derivatives, and ethylene). These hormones regulate plant defense responses through highly interconnected signaling networks [START_REF] Glazebrook | Contrasting mechanisms of defense against biotrophic and necrotrophic pathogens[END_REF].

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This detection system provides broad-spectrum surveillance of various pathogens and contributes to the evolution of disease resistance specificity across the plant kingdom.

Nevertheless, triggered innate immune signaling pathways differ among species.

Research on the integration of growth and defense and their involvement in the induction of antimicrobial defense compounds is currently intense [START_REF] Chen | N-hydroxy-pipecolic acid is a mobile metabolite that induces systemic disease resistance in Arabidopsis[END_REF]Hartmann et al., 2018;Hartmann and Zeier, 2018;[START_REF] Hartmann | N-hydroxypipecolic acid and salicylic acid: a metabolic duo for systemic acquired resistance[END_REF][START_REF] Yildiz | The mobile SAR signal N-hydroxypipecolic acid induces NPR1-dependent transcriptional reprogramming and immune priming[END_REF] because these compounds regulate the expression of genes involved in the biosynthetic pathways of antimicrobial molecules often limited to one species [START_REF] Ahuja | Phytoalexins in defense against pathogens[END_REF]. This synthesis concerns: antimicrobial polymers (callose and lignin [START_REF] Pei | Molecular evidence for the involvement of cotton GhGLP2, in enhanced resistance to Verticillium and Fusarium Wilts and oxidative stress[END_REF]), antimicrobial proteins 18 Ace-AMP1 of onion Allium cepa L. [START_REF] Cammue | A potent antimicrobial protein from onion seeds showing sequence homology to plant lipid transfer proteins[END_REF], antimicrobial peptides 19 [START_REF] Campos | The role of antimicrobial peptides in plant immunity[END_REF], and induced antimicrobial metabolites (phytoalexins) [START_REF] Pedras | Plant chemical defenses: Are all constitutive antimicrobial metabolites phytoanticipins?[END_REF].

Phytoalexins are antimicrobial compounds produced by plants in response to biotic and abiotic stresses [START_REF] Vanetten | Two Classes of Plant Antibiotics: Phytoalexins versus "Phytoanticipins[END_REF]. For instance, 3-deoxyanthocyanidin (20, [START_REF] Llorach | HPLC-DAD-MS/MS ESI Characterization of unusual highly glycosylated acylated flavonoids from cauliflower (Brassica oleracea L. var. botrytis) agroindustrial byproducts[END_REF] of Brassica crops, all cyanides released from cyanogenic glycosides and deglycosylated benzoxazinoids (e.g., 33 to 40) (Figure 4) are classic phytoalexins associated with fungus infection. 18 Plant antimicrobial proteins: e.g., PR: pathogenesis-related 19 Plant antimicrobial peptide contains 10 and 60 amino acids thionins, defensins, hevein-like peptides, knottin-type peptides, αhairpinin family, lipid transfer proteins, snakins [START_REF] Campos | The role of antimicrobial peptides in plant immunity[END_REF]. 18). This allopolyploid species ('AACC', 2n = 4X = 38) is the result of interspecific crosses whose estimate dates back to about 0.075 Ma (Chalhoub et al., 2014), between a diploid turnip (Brassica rapa, 'AA', 2n=2x=20) and a diploid cabbage (Brassica oleracea, 'CC', 2n=2x=18) (Nagaharu U, 1935) (Figure 17). Three subspecies are recognized in B.

napus: subsp. oleifera (oilseed rape or rape), subsp. rapifera (rutabaga or swede), and subsp. pabularia (leaf rape). Two triplication events and two genome duplication events occurred during the evolution of Brassicas. The oldest triplication event allowed the separation between monocots and dicots, and the most recent caused the hexaploid ancestor of Brassicas (Figure 18). Phylogenetic approaches have well-defined the evolutionary relationships between most of these genomes. The diploid progenitors, each derived by ancestral hexaploidy from a common origin, diverged from the A. thaliana pattern 17-20 Mya ago [START_REF] Waminal | Repeat Evolution in Brassica rapa (AA), B. oleracea (CC), and B. napus (AACC) Genomes[END_REF]. that portions of the A and C subgenomes come from European B. napus (An et al., 2019;[START_REF] Song | Eight high-quality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus[END_REF]. B. napus ecotypes are widely distributed in Europe, Asia, Australia, and North America [START_REF] Zou | Genome-wide selection footprints and deleterious variations in young Asian[END_REF], with winter and spring cultigroups.

I.A.7.2. Economic importance and breeding of B. napus

Oilseed rape is the second most widely grown oilseed crop in the world, behind soybeans [START_REF] Mittaine | The globalization of international oilseeds trade[END_REF], whose nutritional intake is based on oil (44% of seed weight) and proteins (23% of seed weight) [START_REF] Balalić | Variabilty of oil and protein content in rapeseed cultivars affected by seeding date[END_REF], with a world contribution extending to around 13-16% of vegetable oil (Wang et al., 2018). In Western Europe and Asia, mainly winter oilseed rape accessions are grown, while spring oilseed rape accessions are primarily grown in Canada, Australia, and northern Europe. Winter and spring oilseed rape have been the subject of specific breeding to improve their production, resistance to pathogens, and seed quality. By decreasing their GLS and erucic acid contents in the seeds, winter and spring B. napus accessions with low GLS content in the seeds have emerged (Pellan- [START_REF] Pellan-Delourme | Cytoplasmic male sterility in rapeseed (Brassica napus L.): female fertility of restored rapeseed with "Ogura" and cybrids cytoplasms[END_REF][START_REF] Denis | Expression of engineered nuclear male sterility in Brassica napus: Genetics, morphology, cytology, and sensitivity to temperature[END_REF][START_REF] Delourme | Identification of RAPD markers linked to a fertility restorer gene for the Ogura radish cytoplasmic male sterility of rapeseed (Brassica napus L.)[END_REF][START_REF] Nesi | Genetic and molecular approaches to improve nutritional value of Brassica napus L. seed[END_REF].

First, "0" cultivars (the "Primor" cultivar) with low levels of unhealthy erucic acid (a monounsaturated fatty acid) in the oil were obtained [START_REF] Morice | Avant-propos : la sélection du colza sans acide érucique[END_REF]. Then, the level of GLS was reduced in the meal of these cultivars, giving rise to "00" cultivars. This double innovation allowed the production of high-quality edible vegetable oil and meal proteins [START_REF] Pinochet | Progrès génétique en colza et perspectives[END_REF], which spread throughout Europe. Then, high-yielding fertile hybrid cultivars were produced and are currently grown in most regions dedicated to oilseed rape cultivation in France [START_REF] Pinochet | Progrès génétique en colza et perspectives[END_REF]. Today, Ph D. manuscript | Anani Amegan MISSINOU P a g e 54 oilseed rape/ canola 20 after having been an auxiliary crop for food and industrial purposes for the last half-century, the total cultivated area in France is 1.4 million hectares, yielding more than 5.4 million tons (figure 19) [START_REF] Charbonnier | Rapeseed: how to value varieties with higher nitrogen use efficiency in France[END_REF].

I.A.7.3. Brassica Genomic Resources

In 2018, at the beginning of my research work, the first B. napus genome (NCBI taxonomic identifier: txid3708) was already assembled from the variety "Darmor-bzh" that possesses a dwarf gene compared to its parent, 'Darmor' (Chalhoub et al., 2014).

This accession exhibits phenotypic resistance to Leptosphaeria maculans, the causative agent of stem canker (or Phoma), whose cycle and impact on Brassica crops will be discussed in the following subsections. Today, there are nine other genomes assembled from other B. napus accessions [START_REF] Song | Eight high-quality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus[END_REF]. Genomes of good quality are also available for the progenitors, with two B. oleracea genomes (Parkin et 20 Canola is an annual winter or spring oil crop in the Brassicaceae family, created by plant breeding in Canada in the 1970s.

Ph D. manuscript | Anani Amegan MISSINOU P a g e 55 al., 2014;[START_REF] Belser | Chromosome-scale assemblies of plant genomes using nanopore long reads and optical maps[END_REF]Lv et al., 2020) and one B. rapa genome [START_REF] Wang | The genome of the mesopolyploid crop species Brassica rapa[END_REF][START_REF] Belser | Chromosome-scale assemblies of plant genomes using nanopore long reads and optical maps[END_REF].

The 'Darmor-bzh' genome has undergone updates [START_REF] Bayer | Assembly and comparison of two closely related Brassica napus genomes[END_REF][START_REF] Lee | Chromosome-Scale Assembly of Winter Oilseed Rape Brassica napus[END_REF], the most recent of which (Rousseau-Gueutin et al 2020) brings new data and offers, among other things, better assembly and annotation of genes shifting from 89% to 97%. The improved quality of this genomic resource is a key point for every functional genomic approach (Rousseau-Gueutin et al., 2020).

I.A.7.4. Brassica napus -Leptosphaeria maculans interaction

The significant oilseed rape cultivation extension brought setbacks, such as a negative fingerprint on the environment, the emergence of harmful pathogens, and pests endangering oilseed rape cultivation [START_REF] Carré | Rapeseed market, worldwide and in Europe[END_REF] Oilseed rape production in many countries is affected by the pathogenic fungus L.

maculans (commonly known as phoma), which causes crown stem cankers, known as blackleg disease or phoma (Fitt et al., 2006;Dukhnytskyi, 2019). The disease results in production losses of 90%, equivalent to approximately $7.3 million, leading to severe damage to the oilseed rape oil industry (Sprague et al., 2006a;[START_REF] Van De Wouw | Evolution of linked avirulence effectors in Leptosphaeria maculans is affected by genomic environment and exposure to resistance genes in host plants[END_REF]. Phoma also affects other Brassica crops (oilseed rape, canola, mustard, turnip, cabbage) worldwide. This fungus is a hemibiotrophic 21 pathogen with a complex life cycle, alternating saprophytic and long parasitic phases. Its life cycle is closely linked to its host plant, oilseed rape (Rouxel and Balesdent, 2005;Bousset et al., 2018).

Conservation and primary infection: infection starts in summer; the strains of L.

maculans, having infected plants the previous season, ensure their long-term survival by saprophytism on the stem residues (stage 1: summer, Figure 21). These strains of L. maculans are of the obligate heterothallic 22 type, and their sexual reproduction forms pseudothecia containing ascospores after sporulation 23 . The ascospores contained in the pseudothecia 24 serve as inoculum for primary infection, and their maturation requires a temperature varying between 15°C and 20°C [START_REF] Naseri | Maturation of pseudothecia and discharge of ascospores of Leptosphaeria maculans on oilseed rape stubble[END_REF]. This coincides with the young plant stage of the developmental cycle. Mature ascospores are ejected from the pseudothecia during rainfall events or even dew.

Ph D. manuscript | Anani Amegan MISSINOU P a g e 58 After the precipitation decreases, it is disseminated over several meters or even a few hundred meters [START_REF] Marcroft | Crop isolation, not extended rotation length, reduces blackleg (Leptosphaeria maculans) severity of canola (Brassica napus) in south-eastern Australia[END_REF][START_REF] Lô-Pelzer | Relationship between severity of blackleg Leptosphaeria maculans L biglobosa species[END_REF]. Ascospores initiate primary infection by plant penetration through leaf wounds or stomata, causing the formation of leaf lesions or leaf spots. The effectiveness of this contamination requires leaves moistened by rain or dew, an optimum temperature (15-20°C), and darkness (step 2: mid-autumn, Figure 21). From then on, L. maculans colonizes the tissues without expression of visible symptoms and grow exclusively in the apoplast for a few days before becoming necrotrophic over a short period [START_REF] Gout | Lost in the middle of nowhere: The AvrLm1 avirulence gene of the Dothideomycete Leptosphaeria maculans[END_REF]. This change ). (West et al., 2001). The disease epidemics are favored by mild and wet autumns and high temperatures in the spring [START_REF] Evans | Range and severity of a plant disease increased by global warming[END_REF].

Ph D. manuscript | Anani Amegan MISSINOU P a g e 60
After the cultivation period and stem lodging, the sexual reproduction phase sets in, and the cycle can begin again. The amount of pathogen in the spring is a determining factor in the inoculum level the following fall.

Several methods are used to control phoma in Brassica crops (prophylactic, chemical, biological, genetic) [START_REF] Aubertot | Improved resistance management for durable disease control: A case study of phoma stem canker of oilseed rape (Brassica napus)[END_REF]. Genetic control by improving host resistance traits is the most economical and ecological method.

I.A.7.4.2. Genetic basis of B. napus resistance to L. maculans infection

There are two types of resistance to L. maculans in oilseed rape occurring at different ontogenetic stages of oilseed rape. The qualitative resistance has a monogenic determinism (major gene R), which confers total resistance to a specific strain of the pathogen, which is a total resistance of seedlings expressed from the cotyledon stage onwards (figure 21). The second type is quantitative resistance, governed by several minor genes; it has a polygenic determinism and confers active partial resistance on a wide range of strains of L. maculans (in other words, "broad-spectrum resistance"). It is mainly expressed at the stem stage of infection in adult plants (Figure 22). [START_REF] Delourme | Major gene and polygenic resistance to Leptosphaeria maculans in oilseed rape (Brassica napus)[END_REF][START_REF] Huang | Quantitative resistance to symptomless growth of Leptosphaeria maculans (phoma stem canker) in Brassica napus (oilseed rape)[END_REF][START_REF] Levrel | Differential growth of Leptosphaeria maculans in the stem of susceptible and partially resistant oilseed rape (Brassica napus L.) genotypes[END_REF].

Ph D. manuscript | Anani Amegan MISSINOU P a g e 61 Rlm2/LepR3 (allelic variants) and Rlm9 code for a receptor-like protein (LRR-RLP) and a wall-associated kinase-like protein (WAKL), respectively. LepR3 and Rlm2 mediate specific resistance to L. maculans isolates harboring the avirulence proteins AvrLm1, AvrLm2, and Rlm9 to those harboring AvrLm5-9, respectively [START_REF] Larkan | The Brassica napus blackleg resistance gene LepR3 encodes a receptor-like protein[END_REF][START_REF] Larkan | A supervised fingerprint-based strategy to connect natural product mass spectrometry fragmentation data to their biosynthetic gene clusters[END_REF][START_REF] Larkan | A supervised fingerprint-based strategy to connect natural product mass spectrometry fragmentation data to their biosynthetic gene clusters[END_REF]. While R genes cause complete resistance, some R genes lose their effectiveness after deployment in the field. Indeed, many cultivars recorded as being resistant show shreds of evidence of specific resistance breakdown in response to rapidly changing populations of L. maculans. These include

Ph D. manuscript | Anani Amegan MISSINOU P a g e 62
Rlm1, Rlm3, Rlm6, Rlm7, LepR1, and LepR3 genes [START_REF] Brun | A field method for evaluating the potential durability of new resistance sources: Application to the Leptosphaeria maculans-Brassica napus pathosystem[END_REF][START_REF] Rouxel | A 10-year survey of populations of Leptosphaeria maculans in France indicates a rapid adaptation towards the Rlm1 resistance gene of oilseed rape[END_REF]Sprague et al., 2006a;Sprague et al., 2006b;[START_REF] Brun | Quantitative resistance increases the durability of qualitative resistance to Leptosphaeria maculans in Brassica napus[END_REF][START_REF] Winter | Race spectra of Leptosphaeria maculans, the causal agent of blackleg disease of oilseed rape, in different geographic regions in northern Germany[END_REF][START_REF] Zhang | Breakdown of Rlm3 resistance in the Brassica napus-Leptosphaeria maculans pathosystem in western Canada[END_REF][START_REF] Van De Wouw | Independent breakdown events of the Brassica napus Rlm7 resistance gene including via the off-target impact of a dual-specificity avirulence interaction[END_REF].

Faced with this problem, it is crucial to adopt a new approach for sustainable management of oilseed rape cultivation against phoma disease and resistance breakdown. Chemical control is difficult to implement and has a high environmental footprint. Interestingly, quantitative resistance mediated by multiple genetic factors was shown to increase the potential for the durability of major resistance genes [START_REF] Brun | Quantitative resistance increases the durability of qualitative resistance to Leptosphaeria maculans in Brassica napus[END_REF]Delourme et al. 2014). Breeding cultivars with quantitative resistance or with combined qualitative and quantitative resistance can thus effectively contribute to stem canker control in oilseed rape. Quantitative resistance of B. napus to L. maculans is highly polygenic and controlled by many QTL (Pilet et al. 1998;2001;Fopa Fomeju et al. 2014;Jestin et al. 2015;Raman et al. 2018;[START_REF] Faccio | Plant complexity and cosmetic innovation[END_REF]Kumar et al. 2018;Fikere et al. 2020;[START_REF] Meraj | Transcriptional Factors Regulate Plant Stress Responses Through Mediating Secondary Metabolism[END_REF]Vollrath et al. 2021). However, little is known about quantitative resistance. Stem infection processes and histological changes were studied in wintertype B. napus by Hammond and Lewis (1987) and Li et al. (2007). Hammond and Lewis (1987) observed a sequence of host reactions, including lignification, cambium formation, and callose deposition at the perimeter of the lesion in the stems, with variation in the timing, the spatial distribution, and the intensity of lignification according to cultivars and isolates. Li et al. (2007) showed the variability in location, timing, and histochemistry of stem responses between compatible and incompatible interactions.

Post-penetration defense reactions such as lignification, suberization, and additional cambium formation occurred in resistant cultivars but four to five days earlier in cultivars with monogenic resistance than quantitative resistance, resulting in hypersensitive reaction in incompatible interactions and limitation of the necrosis in cultivars with quantitative resistance. Significant advances were made in deciphering the pathogen's life cycle and especially in identifying effectors that correspond to small secreted proteins [START_REF] Sánchez-Vallet | The genome biology of effector gene evolution in filamentous plant pathogens[END_REF]. Eight waves of genes specifically expressed during the interaction with the plant were discriminated, all being enriched in genes encoding effectors [START_REF] Gay | Large-scale transcriptomics to dissect 2 years of the life of a fungal phytopathogen interacting with its host plant[END_REF]. Of these, L. maculans expresses several genes encoding late effectors during the systemic colonization of rapeseed and are thought to interfere with plant defenses in the stem [START_REF] Gervais | Different waves of effector genes with contrasted genomic location are expressed by Leptosphaeria maculans during cotyledon and stem colonization of oilseed rape[END_REF]. The identification of these plant defenses would help in understanding the mechanisms underlying quantitative resistance and its further use in plant breeding.

I.A.7.4.3. Biochemical bases of constitutive and inducible chemical defenses of Brassicas

The ambition here is not to (re)conceptualize "the evolution of metabolic pathways in Brassicaceae". Above all, with the proven risk of being partial, given the difficulty of not being able to list exhaustively the articles on the subject of shared or specific specialized metabolic pathways between Arabidopsis and Brassica, the interest will be focused on those involved in the plant-pathogen interactions.

Given that, the diverse origin of these compounds was discussed in the section dealing with structural diversity (I. A.2.1). In what follows, I will briefly present the biosynthetic pathways of the most characterized GLSs: aliphatic glucosinolates derived from methionine and indole GLSs derived from tryptophan.

Ph D. manuscript | Anani Amegan MISSINOU P a g e 64

The biosynthetic pathway of aliphatic GLSs derived from methionine is initiated by BCAT4 26 , which operates an elongation of the methionine-C3 chain into a C3 precursor at the crossroads of the biosynthetic blocks of C3-, to C10-derived from methionine, by the activity of MAM1 27 , IPMI, IPMDH1. These hammers of each contingent are used for the biosynthesis of methylsulfanyl-GLS derivatives by concerted actions of several enzymes, including CYP79F1/F2, CYP83A1, GSTF11/U20, GGP1, SUR1, UGT74C1, SOT17/18. GS-OX supports methylsulfanyl-GLSs derivatives for methylsulfinyl-GLSs derivative biosynthesis (figure 22). By the action of AOP2 and AOP3 enzymes, alkenyl-GLSs, and hydroxyalkyl-GLSs. The alkenyl-GLSs are then taken up by GLS-OH to give hydroxyalkenyl-GLSs, including the famous (epi)progoitrin. Only C3-to C5-GLSs derived from methionine are conserved between Arabidopsis and Brassica (Figure 23). products repels herbivorous insects, birds, nematodes, and fungi. However, the enzymes downstream of glucobrassicin and IAN synthesis are primarily taxon-specific, so many of them remain partially understood in B. napus. A number of these metabolites are thought to be absent in Brassica species. For example, raphanusamic acid, an inducible insecticide in Arabidopsis, results from the activity of atypical myrosinase in intact cells of infected plants [START_REF] Bednarek | A Glucosinolate Metabolism Pathway in Living Plant Cells Mediates Broad-Spectrum Antifungal Defense[END_REF]. More than 40

Brassica-specific indole phytoalexins have been reported, and for some of them, the biosynthetic pathways are poorly characterized (Pedras and Yaya, 2010).

On the indole core of 3IMG, CYP81F4, and CYP81F1-3 form hydroxylated derivatives of glucobrassicin (1-hydroxylucobrassicin and 4-hydroxylucobrassicin), which receive methyl groups to produce neoglucobrassicin and 4-methoxylucobrassicin by the action of IGMT5 and IGMT1-4 (Fig. 24). Assuming an absence of mutual exclusion of the enzymes at the origin of these isomeric forms, there may be that dimethoxyglucobrassicin as reported in Barbarea vulgaris [START_REF] Blažević | Glucosinolate structural diversity, identification, chemical synthesis and metabolism in plants[END_REF], or dihydroxyglucobrassicin (never registered), or even chimeric forms such as hydroxymethoxy-glucobrassicin, can exist in oilseed rape (figure 24, box 2).

Ph D. manuscript | Anani Amegan MISSINOU P a g e 67 (3) The synthesis of 3-carboxylic acid Indole (I3CA) and its derivatives from IAN as described by Erich Glawischnig's team [START_REF] Böttcher | The Biosynthetic Pathway of Indole-3-Carbaldehyde and Indole-3-Carboxylic Acid Derivatives in Arabidopsis[END_REF]. (4) In Arabidopsis, the biosynthetic pathway (absent in the Brassica genus) results in the synthesis of what has long been considered the only phytoalexin in Arabidopsis: camalexin [START_REF] Iven | Transcriptional Activation and Production of Tryptophan-Derived Secondary Metabolites in Arabidopsis Roots Contributes to the Defense against the Fungal Vascular Pathogen Verticillium longisporum[END_REF]. ( 5) In parallel with camalexin, IAN is the precursor of a procession of phytoalexins derived from indole 3carboxynitrile, whose pathway was characterized recently in Arabidopsis, appears to be absent from the Brassica genus [START_REF] Rajniak | A new cyanogenic metabolite in Arabidopsis required for inducible pathogen defence[END_REF]. ( 6) Also, in Arabidopsis, I3MG and its methoxylated derivative 4M-I3MG can be converted by atypical myrosinase into intact cells of infected plants, leading to the synthesis of raphanusamic acid [START_REF] Bednarek | A Glucosinolate Metabolism Pathway in Living Plant Cells Mediates Broad-Spectrum Antifungal Defense[END_REF][START_REF] Clay | Glucosinolate Metabolites Required for an Arabidopsis Innate Immune Response[END_REF]. The biosynthetic pathways of GLSs derived from phenylalanine, tyrosine, and linear and branched amino acids are even less described in all species of Brassicales, and these compounds are rarely reported in the genera Arabidopsis and Brassica, except for gluconasturtiin (Agerbirk et al., 2015;Liu et al., 2019).

Concerning phenolics, the biosynthetic pathways are poorly described, and most of the studies are based on corroborations with Arabidopsis. However, there is quite a dazzling literature on polyglycosylated and polyacylated forms of Brassica phenolic compounds (Nielsen et al., 1998;Llorach et al., 2003;Ferreres et al., 2005;Harbaum et al., 2007;Francisco et al., 2009;Olsen et al., 2009;Schmidt et al., 2010;Velasco et al., 2011;Farag et al., 2013;[START_REF] Shao | Analysis of flavonoids and hydroxycinnamic acid derivatives in rapeseeds (Brassica napus L. var. napus) by HPLC-PDA-ESI(-)-MSn/HRMS[END_REF]. The characterization of these pathways highlights the enzymes involved in plant-pathogen interactions. The genetic determinism of a large part of these phytoanticipins is unknown.

I.B. Presentation of the Ph.D.

I carried out my thesis 28 (4) to better characterize the phytochemical diversity of oilseed rape and its modulation in the presence of environmental stress.

I.B.1 Objectives of the Ph.D. and research questions

The complex SM repertoire of B. napus and its genomic components, despite the close phylogenetic proximity with the species Arabidopsis thaliana, exhibits a range of specificities. This leads to still incomplete knowledge of this repertoire, its diversity, and its regulation, which impairs ambitious functional genomics works on Brassica defense chemistry. Hence, the characterization of the specialized metabolism diversity in Brassica crops is of dual importance: first, from a fundamental perspective, this represents a direct or indirect bridge between genotypes and phenotypes of these crops; second, from a breeding perspective, it is a first step to identify candidate metabolites/genes and to elucidate the relevant metabolic pathways in ecological interactions.

The objective of my thesis was to characterize the specialized metabolism of B. napus

in

I.B.2. Thesis outlines

The second chapter highlights our work characterizing the phytochemical diversity of B. napus and its genetic determinants using metabolomics and quantitative genetics The first article is associated with so-called additional information documents, presenting the details of the experimental data. These documents, which can be consulted on the publisher's websites, have not been included in this thesis. The link is specified at the beginning of the article. As for the additional information, documents of the other manuscripts are presented in the appendix of each study.

In addition to these results, I participated in MetaPhor project, another project of the team. I work with Regine Delourme (Researcher within the team) on transcriptomic and metabolomic modulation of oilseed rape during L. maculans infection. My contribution to validating the metabolomic variation presaged by the variation in gene expression associated with the metabolism of aliphatic and indole glucosinolates (Delourme et al., in preparation).

The fourth chapter leveraged a general discussion to summarize the significance of the results and identifies the boundaries of our research to offer directions for future works. (spring-type oilseed rape), rutabaga, fourrager, qui avaient le statut "+ /+", "0/+", "+/0" et "0/0" pour l'acide érucique et les GLSs dans les graines afin de maximiser la diversité phytochimique potentielle (combinant ainsi les génotypes de printemps, hiver, fourrager et rutabaga). L'ambition ici était : (i) d'aller au-delà des affirmations empiriques de l'absence/présence de certains composés rarement décrits chez le colza, (ii) de mettre les données en perspective avec des génotypes représentatifs de la diversité des deux espèces progénitrices, (iii) de fournir une étape importante de l'architecture génétique de composés rarement rapportés chez Brassica, (iv) d'étudier les conséquences de la sélection du colza pour la teneur en GLSs dans les graines, 29 Le genre Brassica est issu du dernier événement de triplication des génomes chez les plantes. résultats obtenus dans plusieurs études précédentes sur les glucosinolates (Kliebenstein et al., 2001b;Kliebenstein et al., 2001a;[START_REF] Rowe | Biochemical networks and epistasis shape the Arabidopsis thaliana metabolome[END_REF]Kittipol et al., 2019;Liu et al., 2020) et les composés phénoliques [START_REF] Routaboul | Metabolite profiling and quantitative genetics of natural variation for flavonoids in Arabidopsis[END_REF]Francisco et al., 2016;[START_REF] Ishihara | Natural variation in flavonol accumulation in Arabidopsis is determined by the flavonol glucosyltransferase BGLU6[END_REF][START_REF] Tohge | Characterization of a recently evolved flavonol-phenylacyltransferase gene provides signatures of natural light selection in Brassicaceae[END_REF].

Le

■ INTRODUCTION

Brassicaceae synthesize a large diversity of glucosinolates (GLSs) and phenolic compounds as bioactive so-called secondary compounds or specialized metabolites. Their profile signatures are often distinctive of subtaxonomic groups 1 and are involved in both the diverse food and feed usages 2,3 and chemical ecology. 4,5 For instance, contrasted GLS profiles among 96 ecotypes of Arabidopsis thaliana were associated with phytophagous insect resistance. 6 The ability to biosynthesize certain acylated flavonoids is a major determinant of UV tolerance among ecotypes of A. thaliana. 7 Such large-scale studies on the biological importance of intraspecific chemical variations have been mostly investigated in wild Brassicaceae species 8-10 and reported by other authors 11-13 including wild Brassica oleracea. 14,15 Available data are however still scarce for cultivated Brassica species. 16-18 Brassica napus is a cultivated plant species of major agronomical importance, encompassing various forms of human and animal feed: oilseed rape (spp. oleifera), swede (ssp. rapifera), and fodder rapeseed. This allopolyploid species arose from a postneolithic interspecific hybridization between B. rapa and B. oleracea, 19,20 which occurred spontaneously. Since 1970, first modification of low erucic acid and low GSLs for animal feeding, modern oilseed rape cultivars have been selected to lower the amount of GLS in seeds (<30 μmol g -1 DW) from Bronowski accession. 21 This selection had some side-effect impact on the general lowering of a series of GLS in leaves of modern cultivars, 22 although the extent of this phenomenon may have been mitigated by the counter selection exerted by herbivory pressure during breeding processes. 23 The phytochemical composition in vegetative organs of B. napus, B. oleracea, or B. rapa has been well documented 24-30 and put in line with its possible implications in human health and animal nutrition 2,3 as well as in ecological interactions. 31-35 Remarkable chemical features in leaves of Brassica species are a series of multihexosylated and multiacylated kaempferol, quercetin, and isorhamnetin derivatives, hexosylated or quinic-acid conjugated phenylpropanoids, 24,26,27,30,36-41 and glucosinolates. GSL diversity in the genus is mainly derived from tryptophan and chain elongated homologues of methionine and phenylalanine, but the major part of leaf glucosinolates of Brassica napus belong to the methionine-derived aliphatic subfamily. 26,29,37 By contrast, roots typically accumulate much lower levels of phenolic compounds, 42 and a broader diversity of glucosinolate structures, including abundant levels of the phenylalanine-derived phenylalkyl-GLS gluconasturtiin 29 and tryptophanderived indolic-GLS. 43 A surge of phytochemistry research has explored the structural diversity of glucosinolates and/or phenolics in different organs and environmental conditions yet often across a limited number of accessions of Brassica. 24-26,29,30,37,43-47 More recently, main glucosinolates have been reported in large panels of B. napus accessions. 22,48 There is still, however, a need for more exhaustive characterization of GLS and phenolic profiles within leaves and roots of B. napus as well as the main patterns of accumulation of these compounds across the available varietal diversity.

Hence, the objective of the present work was to get an extensive overview of the diversity of chemical profiles of glucosinolates and phenolic compounds in roots and leaves of a large panel of Brassica accessions. For this, MS/MS annotation of the largest possible range of glucosinolates and phenolic compounds was performed using HPLC-HRMS in selected sets of root and leaf samples reflecting the varietal diversity. From this, the quantitative analysis of 36 glucosinolates and 32 phenolic compounds (in leaves and roots) was performed (UPLC-UV-MS) on a large panel of 304 Brassica accessions. The resulting data set was then analyzed (i) to investigate the chemical diversity among B. napus accessions, (ii) to assess the range of accumulation for each compound, and (iii) to search for the existence of chemotypes. We have searched, in particular, for chemicals showing notable differences between B. napus accessions and the accessions of both parental species B. rapa and B. oleracea. Altogether, the results of this work provides a valuable resource representative of the Brassica chemical diversity for potential use in chemical ecology and breeding.

■ MATERIALS AND METHODS

Chemicals. HPLC-grade acetonitrile, methanol, and formic acid were from Carlo Erba. Authentic glucosinolate standards (Supporting Table S2) were acquired from PHYTOPLAN Diehm & and Neuberger GmbH. Authentic phenolic standards were provided by Sigma-Aldrich. The Marvin suite was used for drawing and displaying chemical structures and substructures with Marvin version 21.14 ChemAxon (https://www.chemaxon.com).

Plant Growth Conditions and Experimental Design. A total of 281 accessions of Brassica napus (261 ssp oleifera, 10 ssp rapifera, and 10 fodder) were analyzed in this project. The set of spp oleifera encompassed 130 accessions of winter oilseed rape (WOSR), 120 spring oilseed rape (SOSR), and 11 elite WOSR hybrid accessions. WOSR and SOSR included both ancient and "00" accessions. In addition, phytochemical analyses were performed in two small genetic core collections reflecting the genetic diversity of B. rapa (12 accessions) and B. oleracea (11 accessions), thus leading to a whole panel of 304 Brassica accessions. All seed stocks were produced, at the same site, in two batches during the last 2 years before the experiment. Seeds were germinated in a glasshouse in pots, using a mixture of soil and sand (ratio 2:1). Plants were cultivated in a phytotron (photoperiod 16 h light/8 h dark, 20/18 °C) and were fertilized twice with a half-strength Hoagland solution. Additional watering with tap water was automatically brought under the control of soil moisture sensors to maintain soil hygrometry at about 70%. The experiment consisted of three independent biological replicates, performed at 6-week intervals. The 304 accessions were studied in each biological replicate: 8 plants from each accession were cultivated in two spatially randomized blocks of 4 plants. Four weeks after sowing, root and leaf tissues of the 8 plants were removed and pooled per tissue. Roots were rapidly washed with tap water, then immediately frozen in liquid nitrogen, then stored at -80 °C before lyophilization. Dried samples were ground using a TissueLyser (Qiagen, Hiden Germany). The resulting powders were stored in the dark and protected from humidity up to the extraction.

Four weeks was chosen because the root biomass at this stage is sufficient for metabolic analyses and the relatively short experiment time allows performing three independent replicates in 1 year. Morever, many biotic interactions can typically be studied at this stage (clubroot, phoma, insect susceptibility,...).

Metabolites Extraction Procedure. Samples (30 mg) of freezedried powders were extracted with 1 mL of methanol/formic acid (99/1, v/v). The tubes were vortexed and then sonicated in a water bath at 25 °C for 10 min. After centrifugation at 7000 rpm for 10 min, the supernatants were collected and filtered using a 0.22 μm PTFE membrane. Extracts were stored at 4 °C and analyzed by LC-MS less than 24 h after extraction. This extraction procedure was conducted on each sample for quantitative analyses. In addition, extraction was performed on pools from several roots or leaf powder samples from different accessions (five randomly chosen accessions for each of the following groups: B. napus winter, spring, fodder, swede, B. oleracea, and B. rapa). These two bulks were thereafter used for HPLC-Orbitrap LTQ-XL analysis and annotation of GLS and phenolics (see below).

HPLC-Orbitrap LTQ-XL Analyses for the Annotation of GLS and Phenolics. The following chromatographic conditions were designed to maximize the simultaneous separation of both glucosinolates and phenolics but also to separate isobaric compounds which presented identical fragmentation and therefore an equivocal isomerization. HPLC analysis was performed using an Xselect column (CSH C18, 2.5 μm 2.1 mm × 150 mm; Waters Corp) maintained at 30 °C using Agilent 1200 series LC system. The mobile phase consisted of solvent A (water with 0.1% formic acid, v/v) and solvent B (acetonitrile with 0.1% formic acid, v/v). The elution gradient was 0-3 min (2-9% of B), 3-12 min (9-17% of B), 12-13 min (17-20% of B), 13-24 min (20-32% of B), 24-29 min (32-90% of B), 29-30 min (90-2% of B), and held for column equilibration for the next analysis. The flow rate of the mobile phase was 0.4 mL min -1 , and the injection volume was 2.0 μL. Mass spectrometry was performed using the LTQ-Orbitrap XL equipped with an ESI source operating in negative mode. Experimental settings were optimized, and the following parameters were applied: 3.0 kV, electrospray ionization spray voltage; 20 V, capillary voltage; 55 arbitrary units, sheath gas flow; 9 a.u., auxiliary gas pressure; capillary temperature, 350 °C; sweep gas flow rate, 0.0,; vaporizer and drying-gas temperature, 350 °C. The MS1 spectra were acquired as a profile in full scan mode and used for recording an accurate mass ranging from 250 to 1500 m/z, with 500 ms of scan time (with a resolution of 30 000 at m/z 200). The MS/MS scanning mode was set as a datadependent ms2 scan (dd-ms2). The high energy collision dissociation was 30 eV, and the cone voltage was at 35 V. The available spectral and chromatographic information were used for an extensive annotation of GLS and phenolic compounds using the software Xcalibur Qual Browser 2.2 SP1.48 (Thermo Fisher Scientific, see details in the Results and Discussion).

UPLC-UV-TQD for the Quantification of GLS and Phenolics. The quantification of 68 metabolites (including 36 glucosinolates and 32 phenolic compounds) was performed in the 1820 samples. Samples were extracted, and 2 μL was injected in a UPLC ACQUITY system equipped with a column Acquity UPLC CSH C18, 1.7 μm (2.1 mm × 150 mm; Waters Corporation), coupled to a photodiode array detection and a triple quadrupole detector (TQD, Waters Corporation). The mobile phase consisted of a mixture of solvent A (water with 0.1% formic acid, v/v) and solvent B (acetonitrile with 0.1% formic acid, v/v) at a flow rate of 0.45 mL min -1 . The gradient program was as follow with 0.45 mL min -1 flow rate: initially, 2-9% B from 0 to 3 min, 9-17% B from 3 to 12 min, 17-20% B from 12 to 13 min, 20-32% from 13 to 24 min, 32-90% from 24 to 29 min for washing the column, 90-2% B from 29 to 30 min, and held for column equilibration for the next analysis. The sample holder was kept at 4 °C during the analysis and the column temperature was 30 °C. The ESI source of the TQD was set in the negative mode to perform glucosinolate detection with conditions as follows: the Table 1. Identification of Glucosinolates a a Numeration of GLS (ID) follows subcategories (G01-G13, Met-derived aliphatic-GLSs; G14-G17, Phe/Tyr-derived phenylalkyl-GLSs; G18-G23, tryptophan-derived indolic-GLSs; and G24-G36, branched and linear alkyl-GLSs). Additional details are given in Supporting Table S1. [M] capillary voltage was maintained at 2.9 kV, source and desolvation temperatures were set at 150 and 400 °C, respectively. Pure analytical standards of glucosinolates were used to prepare the calibration standard stock methanol solution, stored at -25 °C. This stock solution was diluted as needed each day for making a 5-point calibration curve. This external calibration gives a linear regression for each glucosinolate and was checked before the quantification of the samples. Total data acquisition was controlled using Masslynx (version 4.1) software and preprocessing with the Quanlynx program (Waters Corporation). Each of the 32 GLS analyzed was quantified using the calibration curve of the authentic GLS standard with the closest chemical structure (details in Supporting Table S2). In parallel to GLS analysis, the phenolic compounds were measured through UV absorbance at 330 nm and quantified using external calibration with the following commercially available flavonols and hydroxycinnamic acids (HCA) (kaempferol glucose, quercetin glucose, isorhamnetin glucose, sinapic acid, coumaric acid, and chlorogenic acid). From all UV-chromatograms, peak deconvolution was preprocessed using Empower (version 2). The quantification of each 36 phenolic compounds was based on the authentic standard with the most closely related aglycone structure. To avoid an overestimated quantification of multiacylated molecules, a theoretical UV-response coefficient was Table 1. continued stands for the neutral structure. GLSs annotated with two asterisks (**) were tentatively identified only from daughter anions and accurate parent mass; those with one asterisk (*) were further validated with certified reference plant materials; and those remaining without an asterisk were confirmed with authentic reference compounds.

Figure 1. Structures of glucosinolates found in Brassica napus. Numeration of GLSs follows subcategories G01-G13, Met-derived aliphatic-GLSs; G14-G17, Phe/Tyr-derived phenylalkyl-GLSs; G18-G23, tryptophan-derived indolic-GLSs; and G24-G36, branched and linear alkyl-GLSs. Alkyl-GLSs derived from unknown amino acids are not represented due to their unknown structure and multiple possibilities of branched isomers. Only m/z for molecular anions are represented. Please see Table 1 and Supporting Results 1. calculated for each compound by adding the UV-responses of authentic standards corresponding to flavonol and acyl building moieties of each molecule (i.e., kaem-O-Disin-O-dihex was calibrated using the addition of response coefficients of kaem-O-glucose and twice those of sinapic acid) (Supporting Table S2). This approach was validated using a calibration curve of the acylated kaempferol derivative tiliroside (from Sigma).

Multivariate Analyses. Analyses were performed using software R and interface RStudio (R Core Team, 2021). Variables with unquantified values representing more than 5% of the data set were removed from the following analyses. Normalized data sets were mean-centered using the least-squares method and a linear model including biological replicates using the "emmeans" R package. 49 Mean-centered values of each compound were visualized on boxplots and comparisons between species were evaluated using Tukey's tests. Multivariate statistical analyses were performed to describe metabolic profile diversity. PCAs were made with "gridextra" and "ade4" R packages, 50 heatmaps were performed with the "pheatmap" R package, and hierarchical clustering were achieved using the "NbClust" R package. 51 All visualization plots were realized using the "ggplot2" R package. 52 ■ RESULTS AND DISCUSSION Identification of 36 Glucosinolates in Brassica Leaves and Roots. GLS annotation was based on the corpus of analytical information about all GLS previously reported in Brassicaceae species, 53-55 including high-resolution mass spectrometry (HRMS) and mass fragmentation patterns. 56-58 In Table 1 are listed 36 ion features (most of which were observed in both root and leaf extracts) that matched (<10 ppm) with theoretical m/z from published GLS data and with the spectral signature expected from compounds containing one or two nitrogen atoms and two or three sulfur atoms (Supporting Table S1). The GLS structure of those compounds was then corroborated (Table 1) with typical GLS-related diagnostic ions (at m/z 195, 227, 241, 259, 275, and 291). 56-59 Neutral losses [START_REF] Brachi | Coselected Genes determine adaptive variation in herbivore resistance throughout the native range of Arabidopsis thaliana[END_REF]162,178,196,242,and 223 Da), which correspond to sulfur-trioxide, anhydroglucose, gluconolactone, thioglucose, sulfur trioxide + anhydroglucose, hydrogen-cyanide + thioglucose, respectively, gave further indications on the fragmentation and structure of R-groups (Table 1). The main results from these annotations are detailed below, and extensive explanations for each 36 individual GLS are given in Supporting Results S1. Eleven of these compounds were confirmed by the retention time of authentic standards. An additional series of GLSs were further validated by identical retention time with compounds from reference plant materials and were indicated with one asterisk (*) (Supporting Results S3). For the rest of GLSs (with two asterisks), the proposed annotation was based on daughter anions and accurate parent mass (Table 1, see also Supporting Results S1).

Thirteen aliphatic methionine-derived GLS were found (from peak G01** to peak G13**, 3-methysulfanylpropyl-GLS**, 3-methysulfinylpropyl-GLS, 2-propenyl-GLS, 4-methysulfanylbutyl-GLS, 4-ethylsulfinylbutyl-GLS, 3-butenyl-GLS, (R)-2-hydroxy-3-butenyl-GLS, (S)-2-hydroxy-3-butenyl-GLS**, 5-methysulfanylpentyl-GLS**, 5-methylsulfinylpentyl-GLS, 4-pentenyl-GLS, hydroxy-pentenyl-GLS**, and 6-methysulfanylhexyl-GLS** (Figure 1). This series of glucosinolates has been widely reported in Brassicaceae and was especially expected in leaves and roots of Brassica species.

Five phenylalanine/tyrosine-derived phenylalkyl-GLSs (peak G14-G18**) were identified (Figure 1). Peak G14 (m/z 422.056 [M -H] -) was identified as gluconasturtiin, and confirmed with an authentic reference compound. The peaks G15*-G18** were four isobaric anions of m/z 438.053 [M -H] -, putatively corresponding to four hydroxyl-derivatives of phenylalkyl-GLSs. Peak G15* was annotated as parahydroxyphenethyl-GLS* (= p-hydroxygluconasturtiin* = homosinalbin*) and confirmed using an extract of Arabis soyeri, a documented source for this compound 60 (Supporting Results S3). For peak G16*, the chromatographic elution pattern of root and seed extracts of Barbarea vulgaris P-type 62 (classic source of epiglucobarbarin*) allowed the validation of this compound as (R)-2-hydroxy-2-phenethyl-GLS* (Table 1, Supporting Results S1 and Supporting Figure S3). Peak G17 was proposed as (S)-2-hydroxy-2-phenethyl-GLS and validated by the retention time of an authentic reference of Glucobarbarin and an extract from Barbarea vulgaris G-type (Table 1, Supporting Results S1 and Supporting Figure S3). The presence of this compound in B. napus has been already observed in at least one previous work on B. rapa and B. oleracea. 45 Peak G18** was proposed as meta-hydroxyphenethyl-GLS** (= m-hydroxygluconasturtiin**) (Figure 1, Table 1, Supporting Results S1). Although Wang and coworkers 61 recently suggested the presence of m-methoxybenzyl-GLS in B. napus, we did not find this compound in our samples compared to an extract of Aubrieta deltoidei, which is a classic source (Supporting Result S3). We can however not fully rule out the hypothesis proposed by Blazevic et al., that G18** in B. napus could be an isoGLS, i.e., an isobaric GLS derived from "exotic" hexoses. To our knowledge, this is the first time that these four hydroxyl derivatives of phenylalkyl-GLSs are described in Brassica species, although they have been previously reported in Arabis (tribe Arabideae) 60 and Barbarea (tribe Cardamineae) genus. 62 Five tryptophan-derived indolic-GLSs (peak G19-G23**) were recorded (Figure 1, Table 1, Supporting Results S1). The identification of peak G19 as 3-indolylmethyl-GLS (glucobrassicin, m/z 447.051 [M -H] -) was validated by an authentic standard. The peaks G20* and G21* were isobaric anions of m/z 477.062 [M -H] -and were putatively assigned as neoglucobrassicin* and 4-methoxyglucobrassicin* based on mass fragmentation profiles (Supporting Results S1). This was confirmed (Supporting Results S3) by the comparison with a root extract of Barbaria vulgaris P-type. 62 Both compounds have been abundantly reported in Brassica species. 63-67 Another pair of isobaric anions of m/z 463.047 [M -H] - was putatively annotated as 4-hydroxyglucobrassicin** (G22**) and 1-hydroxyglucobrassicin** (G23**), respectively (see details in Supporting Results S1). Those indolic-GLS have been commonly reported in Brassica species. 63,65 Thirteen branched and linear alkyl-GLSs (G24-G36) were annotated. It contained one alanine-derived alkyl-GLS (G24**), six BCAA-derived alkyl-GLSs (G25*-G29** and G31*), six alkyl-GLSs derived from unknown amino acids (G30**, G32**-G36**) (Table 1, details of the annotations are in Supporting Results S1).

G24** was annotated as n-propyl-GLS** (Table 1, details of the annotations are in Supporting Results S1), unprecedentedly reported in any plant. 68 This GLS might be derived from alanine with two chain elongations or possibly methionine derived in a complex way.

Peak G25* was putatively identified as isopropyl-GLS* (glucoputranjivin*), a valine derivative, and this annotation was validated by comparison with a Cardamine diphylla seed extract as reference material. 69 Peaks G26** and G27* were Journal of Agricultural and Food Chemistry putatively identified as 2-methylpropyl-GLS** (glucoconringianin** = isobutyl-GLS**) and 1-methylpropyl-GLS* (glucocochlearin*), respectively (Table 1, Supporting Results S1). 2-Methylpropyl-GLS** was previously convincingly characterized in other Brassicales based on spectroscopic data (NMR and MS). 54,55,70,71 Peak G27* was confirmed by comparison with a leaf extract from Cochlearia off icinalis, the species where it was initially characterized. 72 This compound was also detected in leaves of B. rapa 16 and B. napus. 73 Peaks G28** and G29** were annotated as 2-hydroxy-2-methyl-propyl-GLS** (glucoconringiin**) and 1-ethyl-2-hydroxyethyl-GLS** (glucosisautricin**), previously reported in B. juncea. 46 Peak G31* was annotated as 3-methylpentyl-GLS* by comparison with an extract from Cardamine pratensis. 74 Peak G30** was tentatively annotated as pentyl-GLSisomer** (ramification unknown). Peaks G32** and G33** were putatively annotated as hexyl-GLS** isomers (ramification unknown) and peaks G34**-G36** as heptyl-GLS** (ramification unknown). Interestingly, a series of 3-methylbutyl-GLS, 4-methylpentyl-GLS, n-pentyl-GLS, n-hexyl-GLS, [M] stands for the neutral structure. phenolics annotated with two asterisks (**) were tentatively identified only from daughter anions and accurate parent mass, and the phenolics remaining without an asterisk were confirmed with authentic reference compounds. Additional details are given in Supporting Table S1.

and n-heptyl-GLS has already been detected in B. rapa based on the detection of their isothiocyanate derivatives. 75 Based on these annotations, a UPLC-PDA-TQD method was developed for the quantification of individual GLS, using an optimized gradient of 30 min enabling the simultaneous resolution of phenolic compounds (see the Materials and Methods).

Thorough Annotation of 32 Compounds as Main Phenolics in Leaf Extracts. UPLC-based UV-chromato-grams from leaves displayed well-resolved peaks in leaves (Figure 2). UV-spectra, MS, and MS/MS spectra underlying each of those peaks were combined with high-resolution data from HPLC-ESI LTQ-Orbitrap, thus leading to the identification of 32 well-resolved phenolics (Figure 2) which were numbered following their categorization into different phenolic subclasses. The occurrence of these compounds in Brassica species and their fragmentation patterns were often confirmed by the literature. UV-based quantification was not possible for Table 3. Identification of Nonacylated Hexosylated Flavonols a a [M] stands for the neutral structure. Phenolics annotated with two asterisks (**) were tentatively identified only from daughter anions and accurate parent mass, and Phenolics remaining without an asterisk were confirmed with authentic reference compounds. Additional details are given in Supporting Table S1. [M] stands for the neutral structure. Phenolics annotated with two asterisks (**) were tentatively identified only from daughter anions and accurate parent mass, and Phenolics remaining without an asterisk were confirmed with authentic reference compounds. Additional details are given in Supporting Table S1. a few UV peaks for which m/z spectra revealed multiple chromatographically unresolved phenolic compounds. The numbered peaks including acyl-quinic acids, hydroxycinnamic acid hexoside esters, and hexosylated and acylated flavonols are summarized in Tables 2-4 and Figure 3. The main flavonoids present in this Brassica panel were O-hexosides of kaempferol, quercetin, and isorhamnetin, which were consistent with previous works. 26,36,44,76,77 These studies have also reported many Brassica phenolic compounds and their fragmentation pattern, including multihexosylated and acylated. The hexosylation was characterized by the multiple neutral loss of m/z 162 (loss of anhydrohexose). Phenolic compounds yielded characteristic neutral losses of acyl groups, the loss of m/z 162, 146, 192, 194, 206, and 204 were assigned to caffeoyl, coumaroyl, feruloyl, hydroxyferuloyl, ferulic acid, sinapoyl, and sinapic acid groups (Tables 234and Supporting Results S2). In a similar way to GLS, we also frequently observed dehydration of phenolic compounds in fragmentation patterns. For each analyte, fragmentation propensities were deduced from the daughter ion's profiles and applied for structural identification using previously reported patterns of phenolic fragmentations. 26,36,44,76,77 Three propensities of phenolics fragmentation were deduced from (1) the possible occurrence of deacetylated and/or dehexosylated moieties of acylated and/or hexosylated phenolics frequently associated with dehydration, (2) possible dehydration of phenolics due to the hydroxyl group, (3) then demethylation followed by a decarboxylation or vice versa. The main results from these annotations are detailed below, in Tables 234, and extensive explanations for all 32 phenolic compounds are given in Supporting Results S2.

Phenylpropanoids. Thirteen phenylpropanoids belonging to acyl-quinic acids (peaks PL01 and PL02**) and hydroxycinnamic acid hexoside esters (peaks PL03 to PL13) were annotated (Table 2, Supporting Results S2). Among these compounds, we found some isomers chromatographically resolved (i.e., duo peaks, PL07**-PL08**, and trio peaks, PL09**-PL10**-PL11**). Succinctly, PL01 was authentified by the standard 5-caffeoylquinic acid (5-CQA) and PL02**, as feruloyl-O-quinic acid** (Table 2). The presence of these two acyl-quinic acids is consistent with earlier research in Brassica species. 38,47,78 Peak PL03** and peak PL06** were identified as feruloyl-O-hex** and diferuloyl-O-dihex** (dimers of feruloyl-O-hex), respectively (Table 2), already reported in Brassica. 38,47 Peak PL04** and peak PL05** were designated as sin-O-hex** and sin-O-dihex**, respectively. Unlike PL05**, PL04** was reported in B. rapa 37 and described as being among the most abundant hydroxycinnamic acids of B. oleracea and B. napus leaves. 26 Disinapoyl-O-dihex** and trisinapoyl-O-dihex** were assigned to peak PL07** and PL08**, respectively, which have been previously reported in cabbage and turnip. 26,37,38,47,78 Peaks PL09**, PL10**, and PL11** were nominated as feruloyl-O-sinapoyl-O-dihex**. Although this structure has been identified earlier in cabbage and oilseed rape, 24-26,38,47 heretofore no structural isomers have been reported. Peak PL12** was characterized as trisin-O-dihex**, consistent with a previous study on Brassica. 24,26,37,38,47,78 Peak PL13** was earmarked as feruloyl-di-O-sin-O-dihex** and already recognized in Brassica species. 24,26,37,38,47,78 Flavonols. We detected five nonacylated hexosylated flavonols (Table 3, Supporting Results S2). Peak PL14** was identified as kaem-O-dihex**, as previously detected in B. rapa. 40 Peak PL16** and PL17** were proposed as kaem-Otrihex isomers I** and II**, respectively, consistent with previous reports on B. oleracea var. botrytis and var. sabellica. 27,36,40 Peak PL28** was annotated as quer-Otrihex**, already described in some Brassica species. 26,27,36,40 PL32** was tentatively proposed as isor-O-trihex** described in Brassica species. 78,79 Fourteen flavonols (peak PL15, PL19-PL27, and PL29-PL31) were detected, and almost all were monocharged except peaks PL26** and PL27** (Table 3 and Supporting Results S2). The peaks PL29** and PL31** were acylated hexosylated quercetin derivatives and the remaining were exclusively kaempferol derivatives. Briefly, peaks PL15**, PL22**, and PL24** were provisionally assigned as kaem-Ofer-O-dihex**, kaem-O-fer-O-trihex**, and kaem-O-fer-Otetrahex**, respectively, as described by previous studies in B. napus 25,30 and B. oleracea and B. rapa. 24,27,36-38,40,41,47 Peaks PL19** and PL21** exhibited aglycon ions of kaempferol (285 [Y0] -and 284 [Y0 -H] -) and hydroxyferuloyl moieties, allowing their provisional identification as kaem-O-hydroxyferuloyl-O-dihex** and kaem-O-hydroxyferuloyl-O-trihex**, respectively, which was in line with the reported literature of Brassica crops. 24,27,30,36,38,47 Peak PL18** was tentatively defined as kaem-O-caf-O-dihex** comparably with anterior studies. 26,27,30,37,47 Peaks PL20**, PL23**, and PL25** were annotated as kaem-O-sin-O-dihex**, kaem-O-sin-O-trihex**, and kaem-O-sin-O-tetrahex**, as supported by previous Brassica works. 25-27,30,36-38,41,47 Although PL26** was to our knowledge never reported in Brassicaceae, PL27** was previously detected in leaves of B. oleracea curly kale. 24 The remaining peaks PL29**, PL30**, and PL31** were characterized as quer-O-caf-O-trihex**, quer-O-hydroxyferuloyl-trihex**, and quer-O-Disin-O-tetrahex**, all of which have been previously described in Brassica species. 24,26,36,37,47 Phytochemical Diversity and Concentration Ranges in 304 Brassica Accessions. Quantitative profiling of the above detailed 36 GLS and 32 phenolics was performed on a set of 1820 root and leaf samples from 304 accessions (3 biological replicates). The whole data set is given in Supporting Tables S3, S4, and S5 for root GLS, leaf GLS, and leaf phenolics, respectively. Supporting Tables S3a,S4a, and S5a show data of the three replicates. Supporting Tables S3b,S4b, and S5b give mean values, min, max, and percentiles 5% and 95% for each accession. Supporting Tables S3c,S4c, and S5c allow, for any metabolic compound, to screen for genotypes harboring among the 5% lowest or highest mean values. These tables also allow rapid visualization of the peculiar metabolic features of any given genotype. This constitutes a unique and easily accessible phytochemical atlas for Brassica scientists. In the following parts, the most striking features are presented.

Glucosinolates. Figure 4 and Table 5 give key quantitative results and propose a global overview of phytochemical profiles among accessions of the three species. B. napus contained on average 2.5 and 26 μmol g -1 DW of glucosinolates in leaves and roots, respectively. Total GLS in leaves were mainly composed of Met-derived aliphatic-GLS (on average 74%), as seen in Figure 4 and as detailed in Table 5. This mean value encompasses striking interaccession variations. This diversity partly reflected the presence in the panel of both ancient and recent accessions which have been selected for a low aliphatic GLS content in seeds. Root GLS content also displayed interaccession variations, from 5.7 to 49.4 μmol g -1 DW, but included a larger proportion of Phe-derived (∼47% on average), besides Met-derived aliphatics (37% on average). In both roots and leaves, several accessions displayed strikingly consistent accumulations of branched and linear alkyl-GLSs, with few exceptions (detailed below).

Met-derived aliphatic GLS exhibited quasi exclusively 4 and 5-carbon chains. Relative proportions between those C4-and C5-aliphatic GLS displayed great variations among accessions, with C4-aliphatic GLS representing between 22% and 98% of total Met-derived aliphatic GLS (Table 5). As expected, Metderived aliphatic glucosinolates with 3-carbon radical chains (C3-aliphatics) were found very low in accessions of both B. S2,S3, and S4. The percentile 5 and percentile 95 of metabolic trait in each per species are given per species in Supporting Tables S2d,S3d, and S4d.

napus and B. rapa but ranged from 0.3 up to 89% in accessions of B. oleracea (Table 5). The R-chain length of Met-derived aliphatic glucosinolates influences their biological activities, as exemplified by the consequences of allelic variations at the GS-ELONG locus on plant-insect interactions in Arabidopsis 80,81 and wild Brassica oleracea. 5 Thus, the diversity of C4 to C5aliphatic GLS ratio in B. napus accessions from our panel may have some interesting consequences on resistance to insects that would deserve further explorations. Beyond chain elongation, the level of maturation of the R-chain of Metderived is also relevant to the biological activity. 80,81 From this perspective, GLS profiles were qualitatively distinct in roots (mainly alkenyl-, hydroxyalkenyl-, and methylsulfinyl-GLS) and leaves (mostly methylsulfinyl-, methylthio-, and hydroxyalkenyl-GLS). Most remarkable was the large interaccession range of ratios between those GLS subcategories (Table 5). For example, in leaves, the proportion of alkenyl-GLS toward total Met-derived aliphatic-GLS varied between 0.5% (accession no. 271-WIL) to 80% (accession no. 001-ADR).

Consistently with the literature, gluconasturtiin was by far the most abundant phenylalkyl-GLS in roots and leaves (92.1% and 99.8% of total phenylalkyl-GLS, respectively). Interestingly, a series of hydroxylated derivatives including glucobarbarin were observed and reached up to 10% of total phenylalkyl-GLSs (in leaves of no. 152-C34). Such a concentration can be seen as elevated considering that only a few studies have reported glucobarbarin in Brassica crops, 46 and this compound was even used as an internal standard in some Brassica studies. 82 Glucobrassicin was the most abundant indolic-GLS in leaves. However, in roots, a wide range of contents of its methoxy-derivatives 1-methoxyglucobrassicin (from 7 to 63% of total indolic-GLS) and 4-methoxyglucobrassicin (from 7 to 63% of total indolic-GLS) was observed. The primary role of the latter as a precursor of various phytoalexins 83 suggests that this range of variations might be worthy of further investigation in the context of response to pathogen attacks.

Although the biosynthesis of BCAA-derived alkyl-GLSs is based, from an evolutionary point of view, on an ancient biosynthetic pathway among Brassicaceae species, 53 those compounds are only occasionally reported in Brassica species. Our work highlighted the occurrence in B. napus of understudied isomers from propyl to heptyl-GLSs, accounting from 0% up to 41% of total GLS in leaves. Isomeric butyl-GLSs (particularly glucochlearin**, G27**), although accumulated mostly in a small subset of accessions, were found up to 0.9 μmol g -1 DW (in leaves of no. 088-Oase) and up to 2 μmol g -1 DW (in roots of no. 147-C25). Noteworthy, seven swede accessions were in the top percentile 95% for the highest butyl-GLSs concentration in roots, with above 0.5 μmol g -1 DW. To temperate this statement, those values have to be compared to higher BCAA-derived alkyl-GLSs contents found in some wild accessions of Brassicaceae with for instance up to 29 μmol g -1 DW isopropyl-GLS in Cardamine diphylla. 84 Nevertheless, as branched-chained and linear alkyl-GLSs have been pinpointed for their volatility and possible role in plant-insect interactions, 85 their observed content variations among B. napus accessions may be worthy of interest for breeding purposes.

Phenolic Compounds. Using our methodology, we did not detect quantifiable phenolic compounds in root extracts, which was consistent with previously reported low levels of phenolic compounds in Brassica roots. 30 By contrast, the total molar concentration of phenolics was on average at 15 μmol g -1 DW in leaves, a magnitude which was consistent with Neugart et al. 86 and which was 6-fold higher compared to glucosinolates. Phenylpropanoids and flavonol derivatives accounted for about 1 / 3 and 2 / 3 (respectively) of total leaf phenolics detected by UV 330 nm in our analyses in B. napus and B. rapa, and about 1 / 2 in B. oleracea (Table 5). Equivalent ratios were previously reported for B. rapa. 87 Globally, total concentrations of flavonoid derivatives were higher in the panel of B. napus and B. oleracea compared to B. rapa. Accessions of B. napus with the highest concentrations of flavonol derivatives (percentile 95% > 13.5 μmol g -1 DW) belonged to the spring type, while most of the accessions with the highest concentrations of phenylpropanoids (percentile 5% >7.5 μmol g -1 DW) belonged to the winter type (Supporting Table S5c). Overall, 80.5% of flavonols in B. napus were derived from the aglycone kaempferol (68% of flavonols being trihexosylated kaempferol derivatives). This proportion varied from 63% (accession no. 150-C30) to 97% (accession no. 234-TOK). The data set also highlighted noticeable interaccession variations for quercetin (from 2% in no. 234-TOK to 28% in no. 171-GEN) and isorhamnetin derivatives (from 0% in no. 148-C28 to 20% in no. 138-BSC). These relatively low concentrations of isorhamnetin derivatives in leaves are consistent with previous works in Brassica, which reports larger accumulations in inflorescences and seeds. 30 In B. rapa, they contribute to the visual attractiveness of flowers to insect pollinators. 88 On average, 2 / 3 of flavonols harbored one acylation in B. napus (with variations from 48% in no. 119-SWG to 83% in no. 164-DRK), and only 4% of flavonols harbored two acylations (with the highest values in swede accessions, i.e., 12% in the swede variety no. 264-BRH). In line with ref 7, accession-dependent variations in the concentrations of these high UV-absorbing multiacylated compounds may play a role in the tolerance of oilseed rape to abiotic constraints.

In B. napus accessions, leaf phenylpropanoids were composed mainly of (87%) hydroxycinnamic acid hexosylated esters and more precisely of monoacyl-(25-70%) and diacylderived (27-66%) compounds. The prominence of Disin-Odihex** (PL07**) and feruloyl-O-sin-O-dihex** (PL10**) was consistent with previous reports in kale. 86 Remarkably in B. napus, the highest accumulations for those compounds were found in winter accessions. Triacyl-derived compounds were found at globally low concentrations in B. napus leaves, although they reached up to 12% of total phenylpropanoids in some accessions (no. 088-OAS). In line with Francisco et al., 6 accession-dependent variations in the concentrations of those high UV-absorbing multiacylated compounds may play a role in the tolerance of oilseed rape to abiotic constraints. High levels of hexosylation are a key signature of Brassica phytochemistry. 89 Indeed, our data set revealed that 48% to 98% of flavonols in B. napus are trihexosylated derivatives, the highest levels being typically gained in spring accessions. Tetrahexoside and penta-hexoside kaempferol derivatives were also found to reach up to 12 and 20% (respectively), and the largest accumulation of the two latter categories was typically found in swede accessions. In our data set, all hexosylation residues were hexosides, which was consistent with previous reports on Brassica species 4 and significantly differed from the presence of flavonol rhamnoside derivatives in many other Brassicaceae species. 4,90 Finally, the present data set allowed the identification of varietal accession contrasts for phenolics Journal of Agricultural and Food Chemistry with established ecological functions. This is illustrated by a range between 0.4 μmol g -1 DW (in the swede accession no. 268-LOR) and 3.2 μmol g -1 DW (in the SOSR accession no. 177-GUZ) of kaem-O-sin-O-trihex** (PL23**), a flavonol which has been reported to play a role in resistance toward cabbage seedpod weevil. 9192 Chemotypes Pointed out through Multivariate Analyses. Unsupervised multivariate analyses were conducted to identify the prevalence of accession clusters and the most relevant variables describing the phytochemical specificity (Figure 5 for root glucosinolates, Figure 6 for leaf phenolics). Although the diversity of phytochemical patterns was relatively modest, as illustrated by short branches among accession clusters in roots and leaves (Figure 5A, Figure 6A), this approach nevertheless highlighted phytochemically defined clusters of B. napus accessions and highlighted their respective In summary, this work provides enriching information about the chemical diversity in B. napus. The number of compounds (36 GLS and 32 phenolics) and the number of accessions analyzed (304) represent one of the largest set described in a single study until now. 22,93 Kaempferol-O-sin-O-pentahex** (PL26**) is reported here for the first time in Brassicaceae. To our knowledge, this is also the first report in Brassica species of four isomers of hydroxyphenylethyl-GLS (G15*, G16*, G17, G18**) and branched chain or linear alkyl-GLS (G25*, G26*, G28**, G30**, G31*, G32**-G36**) in B. napus. The large range of glucocochlearin (G27*) concentrations (from zero up to 26% of leaf GLS) over the diversity of B. napus accessions was unexpected, suggesting possible ecological consequences to be explored. The content of phenolics in B. napus also greatly varied among genotypes, offering a basis for further works in chemical ecology and breeding. This metabolic data set will be exploited in our future work to investigate the genetic architecture of metabolic traits, and identify underlying genes involved in the control of these metabolic variations, and explore their roles in biotic interactions.

■ ASSOCIATED CONTENT

* sı Supporting Information

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jafc.1c08118. Supporting Results S1, detailed explanations for the annotation of GLS in this study; Supporting Results S2, detailed explanations for the annotation of phenolics in this study; Supporting Results S3, chromatograms of isobaric ions from rare GLSs observed in Brassica extracts and chromatograms from reference plant materials; and Supporting Results S4, box plots comparing the diversity of leaf content for every phenolics and GLS among the accessions for the three species B. napus, B. rapa, and B. oleracea (PDF)

Supporting Table S1, detailed HRMS and MS/MS data, elution times, and proposed annotation of 36 glucosinolates and 32 phenolic compounds detected in the panel of 304 Brassica accessions (XLSX) Supporting Table S2, external standards used for quantification (XLSX) Supporting Table S3, leaf GLS content in a panel of 304 Brassica accessions; Supporting Table S3a, leaf GLS content in each biological replicate (nmol g -1 DW); Supporting Table S3b, mean leaf GLS content, min, max, percentile 5, and percentile 95; Supporting Table S3c, selection of accessions belonging to percentile 5 and percentile 95 for each GLS (XLSX) Supporting Table S4, root GLS content in a panel of 304 Brassica accessions; Supporting Table S4a, root GLS content in each biological replicate (nmol g -1 DW); Supporting Table S4b, mean root GLS content, min, max, percentile 5, and percentile 95; Supporting Table S4c, selection of accessions belonging to percentile 5 and percentile 95 for each GLS (XLSX) Supporting Table S5, leaf phenolic content in a panel of 304 Brassica accessions; Supporting Table S5a, leaf phenolic content in each biological replicate (nmol g -1 DW); Supporting Table S5b, mean leaf phenolic content, min, max, percentile 5, and percentile 95; Supporting Table S5c, selection of accessions belonging to percentile 5 and percentile 95 for each phenolic compound (XLSX)

GWAS reveals genetic networks involved in the control of phenolics and glucosinolates, and specifies the metabolic consequences of breeding history in Brassica napus cultigroups

Julie Ferreira de Carvalho #,a , Anani Amegan Missinou # First authors and * corresponding author, Antoine.Gravot@univ-rennes1.fr

Introduction

Specialized metabolites play major roles in the interactions between plants and their abiotic and biotic environment. This notably includes resistance to phytophagous insects, tolerance to UV, or the assembling of rhizosphere microbial communities [START_REF] Abedini | Metabolic interactions in beneficial microbe recruitment by plants[END_REF]. A better understanding of the genetic determinants influencing the diversity of these metabolic compositions among crop varieties is therefore key to define breeding strategies and design varieties adapted to fluctuating environments, as required to face climate change and to promote agroecological systems.

Brassica napus is a crop of major importance, as it is one of the few oilseed species in European cropping systems. Its cultivation is nowadays threatened by abiotic and biotic stresses. These notably include an increasing challenge with insects such as cabbage-stem weevil or flea beetle, but also several microbial pathogens and the parasitic plant broomrape. Therefore, the exploitation of the diversity of specialized Ph D. manuscript | Anani Amegan MISSINOU P a g e 104 metabolites is a real challenge for this species. Like in all Brassica crops, its specialized metabolite repertoire primarily encompasses glucosinolates (GLS) and phenolic compounds (PHL), including phenylpropanoids and flavonoids. Previous studies on oilseed rape have stated the relevance and complex ecological functions played by GLSs in resistance or stimulation of oilseed rape toward generalist and specialist phytophagous insects (Mithen, 1992;Giamoustaris and Mithen, 1995) as well as their involvement in improving plant resistance to fungi [START_REF] Zhang | Overexpression of three glucosinolate biosynthesis genes in Brassica napus identifies enhanced resistance to Sclerotinia sclerotiorum and Botrytis cinerea[END_REF][START_REF] Wu | Comparative transcriptomic analysis uncovers the complex genetic network for resistance to Sclerotinia sclerotiorum in Brassica napus[END_REF].

Phenolic compounds can be also involved in a wide range of functions, such as developmental processes, symbioses, and responses to pathogen attacks [START_REF] Bhattacharya | The roles of plant phenolics in defence and communication during Agrobacterium and Rhizobium infection[END_REF][START_REF] Mandal | Phenolic acids act as signaling molecules in plant-microbe symbioses Phenolic acids act as signaling molecules in plantmicrobe symbioses[END_REF]. Metabolite profiles in B. napus depend on genetic factors, but also on plant developmental stages, plant organs [START_REF] Obermeier | Genetic analysis of phenylpropanoid metabolites associated with resistance against Verticillium longisporum in Brassica napus[END_REF]Francisco et al., 2016), and environmental conditions. The quantitative genetic control of GLSs has been well documented for seed GLS content (e.g. Wang et al., 2018). A small series of QTLs regulating total seed GLS content, located on chromosomes A09, C02, C07, and C09, may correspond to different copies of MYB28 as suggested by [START_REF] Li | Genome-wide association study dissects the genetic architecture of seed weight and seed quality in rapeseed (Brassica napus L.)[END_REF]. More recently, advances have been made to investigate GLS in other organs, leaves, and roots, and their genetic architecture (Kittipol et al., 2019), highlighting A02, A03, A09, C02, and C09 regions. These regions were also found associated with total Met-derived aliphatic-GLSs (Kittipol et al., 2019). Concerning phenolics, few genetic studies, within general unannotated PHL molecules, were undertaken in Brassica sp. so far [START_REF] Obermeier | Genetic analysis of phenylpropanoid metabolites associated with resistance against Verticillium longisporum in Brassica napus[END_REF]Francisco et al., 2016). Interestingly, the focus of attention in phenolic compounds has been the molecular regulation of sinapine (=sinapoylcholine), an anti-nutritional compound accumulated in B. napus seeds [START_REF] Milkowski | Molecular regulation of sinapate ester metabolism in Brassica napus: Expression of genes, properties of the encoded proteins and correlation of enzyme activities with metabolite accumulation[END_REF][START_REF] Baumert | Formation of a complex pattern of sinapate esters in Brassica napus seeds, catalyzed by enzymes of a serine carboxypeptidaselike acyltransferase family?[END_REF]. Brassica napus specie was formed approximately 7500 years ago by hybridization between B. rapa and B. oleracea followed by spontaneous whole genome doubling (Chalhoub et al., 2014). Since then, diverse vegetable and oilseed crops were selected and grown worldwide. Diversification led to two main subspecies whose origin was estimated ca 3,000 years ago [START_REF] Hu | Exploring the gene pool of Brassica napus by genomics-based approaches[END_REF]. One includes swede forms (ssp rapifera) while the other one, ssp oleifera, comprises fodder, winter oilseed rape (WOSR), and spring oilseed rape (SOSR) forms (An et al., 2019). During the 1970s, to compel with animal feed purposes, total glucosinolate content has been drastically reduced in the seeds of modern oilseed rape varieties by the introgression of alleles from the Polish cultivar 'Bronowski' [START_REF] Kondra | Inheritance of the major glucosinolates of rapeseed (Brassica napus) Meal[END_REF][START_REF] Rosa | Glucosinolates in Crop Plants[END_REF]. This rapid reduction resulted both in an erosion of genetic diversity within the oilseed rape genetic pool [START_REF] Bus | Patterns of molecular variation in a species-wide germplasm set of Brassica napus[END_REF] and in a concomitant decrease of some glucosinolates (GLSs) in other organs such as leaves and roots (Kittipol et al., 2019;Liu et al., 2019;Liu et al., 2020). The potential impact of this seed GLS reduction on phenolics (PHL) and GLSs in leaves and roots in WOSR and SOSR has been however until now only insufficiently investigated. We also previously identified two major chemotypes in a large panel of B. napus accessions, a distinction that was partly explained by the balance between the relative contents of flavonols and phenylpropanoids (Missinou et al., 2022), suggesting that other factors than GLS reduction have shaped the genetic and metabolomic diversity in B. napus. All these elements are leading to a need to improve the knowledge of the genetic diversity of these specialized metabolites in a large panel of oilseed rape and their genetic control to better exploit the B. napus germplasm for breeding.

Ph D. manuscript | Anani Amegan MISSINOU P a g e 106

In our previous work we have reported the identification and annotation of GLSs and phenolics in a large diversity panel (Missinou et al., 2022) allowing us to document the metabolic diversity in 270 accessions of B. napus representing the different cultigroups grown worldwide and representing the history of selection (genotypes presenting low and high seed GLS content). To decipher the genetic bases of metabolic diversity of GLS and phenolics in oilseed rape metabolism, we performed a metabolic genomewide association study (mGWAS). The present work provides an overview of the genetic control of these two principal families of phytochemicals in roots and leaves of oilseed rape and addresses the question of the impact of breeding for low seed GLS content on the allelic diversity at the genetic factors controlling these specialized metabolites. We also explored the impact of breeding for low seed GLS content by comparing the allele frequencies between "low-GLS" and "high-GLS" genotypes both for winter and spring types. Finally, we discussed the results in light of this genetic architecture and diversity in the different B. napus cultigroups, which provide avenues to design metabotypes of these specialized metabolites according to breeding needs.

Resultats and Discussion

Glucosinolates and Phenolic compounds identified in B. napus

The phytochemical dataset from (Missinou et al., 2022) was investigated to address the phytochemical contrasts between B. napus cultigroups and investigate the genetic architecture of GLS and PHL specialized metabolites. Table 1 details the biochemical nomenclature adopted for this dataset by Missinou et al. 2022. GLS molecules may be divided into four main types: Met-derived aliphatic-GLSs (G1 to G13), Phe/Tyr-derived phenylalkyl-GLSs (G14 to G18), Trp-derived indolic-GLSs (G19 to G23) and Branched Ph D. manuscript | Anani Amegan MISSINOU P a g e 107 and linear alkyl-GLSs (G24 to G36) (Missinou et al. 2022). Quantitative profiles of those four biochemical categories in leaves and roots of B. napus accessions are represented according to the six identified crop types (Figure 1). Met-derived aliphatic GLSs are ranked according to the length (C3 to C6), then the decoration (sulfanyl-, sulfinyl-, alkenyl-, hydroxyalkenyl-) of their lateral chain, and the decoration. Branched and linear alkyl-GLSs are ranked according to the length (C3 to C7) of their lateral chain. Phenylpropanoids are ranked according to the number of acyl and hexose groups. Flavonols are ranked according to the nature of their aglycone (K=Kaempferol, Q=Quercetin, I=Isorhamnetin) and the number of acyl and hexose decorations.

In leaves, Met-derived aliphatic-GLSs are the most represented GLS molecules, and their global content exhibits a wide quantitative variability among accessions. In roots, overall GLS content was higher compared to leaves (by approximately 8 to 10-fold),

G01 3mSp 3-methylsulfanylpropyl-GLS Glucoiberverin PL01 CQA Caffeoylquinic acid G02 3mSOp 3-methylsulfinylpropyl-GLS Glucoiberin PL02 FQA Feruloylquinic acid G03 2Prop 2-propenyl-GLS Sinigrin PL03 Fer-Hx Feruloyl-O-hexoside G04 4mSb 4-methylsulfanylbutyl-GLS Glucoerucin PL04 Sin-Hx Sinapoyl-O-hexoside G05 4mSOb 4-methylsulfinylbutyl-GLS Glucoraphanin PL05 Sin-diHx Sinapoyl-O-dihexose G06 3Ben 3-butenyl-GLS Gluconapin PL06 diFer-diHx Diferuloyl-O-dihexoside G07 (R)-2h3Ben (R)-2-hydroxy-3-butenyl-GLS Progoitrin PL07 diSin-diHx, i1 Disinapoyl-O-dihexoside, isomer I G08 (S)-2h3Ben (S)-2-hydroxy-3-butenyl-GLS Epiprogoitrin PL08 diSin-diHx, i2 Disinapoyl-O-dihexoside, isomer II G09 5mSp 5-methylsulfanylpentyl-GLS Glucoberteroin PL09 Fer-Sin-diHx, i1 Feruloyl-O-sinapoyl-O-dihexoside, isomer I G10 5mSOp 5-methylsulfinylpentyl-GLS Glucoalyssin PL10 Fer-Sin-diHx, i2 Feruloyl-O-sinapoyl-O-dihexoside, isomer II G11 4Pen 4-pentenyl-GLS Glucobrassicanapin PL11 Fer-Sin-diHx, i3 Feruloyl-O-sinapoyl-O-dihexoside, isomer III G12 2h4Pen hydroxy-pentenyl-GLS Gluconapoleiferin PL12 triSin-diHx Trisinapoyl-O-dihexoside G13 6mSh 6-methylsulfanylhexyl-GLS Glucoesquerellin PL13 Fer-diSin-diHx Feruloyl-O-disinapoyl-O-dihexoside G14 2PE 2-phenylethyl-GLS Gluconasturtiin PL14 K-diHx Kaempferol-O-dihexoside G15 p-4hPE p-hydroxyphenylethyl-GLS p-hydroxygluconasturtiin PL15 K-F-diHx Kaempferol-O-feruloyl-O-dihexoside G16 (R)-2hPE (R)-2-hydroxy-2-phenetyl-GLS Epiglucobarbarin PL16 K-triHx, i1
Kaempferol-O-trihexoside, isomer I G17 (S)-2hPE

(S)-2-hydroxy-2-phenetyl-GLS Glucobarbarin PL17 K-triHx, i2 Kaempferol-O-trihexoside, isomer II G18 m-3hPE m-hydroxyphenylethyl-GLS m-hydroxygluconasturtiin PL18 K-C-diHx Kaempferol-O-caffeoyl-O-dihexoside G19 3IM 3-indolylmethyl-GLS Glucobrassicin PL19 K-hF-diHx Kaempferol-O-hydroxyferuloyl-O-dihexoside G20 1M-3IM 1-methoxyindol-3-ylmethyl-GLS Neoglucobrassicin PL20 K-S-diHx Kaempferol-O-sinapoyl-O-dihexoside G21 4M-3IM 4-methoxyindol-3-ylmethyl-GLS 4-Methoxylucobrassicin PL21 K-hF-triHx Kaempferol-O-hydroxyferuloyl-O-trihexoside G22 4h-3IM 4-hydroxyindol-3-ylmethyl-GLS 4-Hydroxylucobrassicin PL22 K-F-triHx Kaempferol-O-feruloyl-O-trihexoside G23 1h-3IM 1-hydroxyindol-3-ylmethyl-GLS 1-Hydroxylucobrassicin PL23 K-S-triHx Kaempferol-O-sinapoyl-O-trihexoside G24 nPr n-propyl-GLS - PL24 K-F-tetraHx Kaempferol-O-feruloyl-tetrahexoside G25 iPr 1-methylethyl-GLS Glucoputranjivin PL25 K-S-tetraHx Kaempferol-O-sinapoyl-O-tetrahexose G26 2mPr 2-methylpropyl-GLS Glucoconringianin PL26 K-S-pentaHx Kaempferol-O-sinapoyl-O-pentahexoside G27 1mPr 1-methylpropyl-GLS Glucocochlearin PL27 K-diSin-pentaHx Kaempferol-O-disinapoyl-O-pentahexoside G28 2h2mPr 2-hydroxy-2-methylpropyl-GLS Glucoconringiin PL28 Q-triHx Quercetin-O-trihexoside G29 1Et2hEt 1-ethyl-2-hydroxyethyl-GLS Glucosisautricin PL29 Q-C-triHx Quercetin-O-caffeoyl-O-trihexoside G30 Pent i pentyl-GLS-isomer - PL30 Q-hF-triHx Quercetin-O-hydroxyferuloyl-O-trihexoside G31 3mPent 3-methylpentyl-GLS - PL31 Q-diSin-tetraHx Quercetin-O-disinapoyl-O-tretrahexose G32 Hex i1 hexyl-GLS iso. I - PL32 I-triHx Isorhamnetin-O-trihexoside G33 Hex i2
hexyl-GLS iso. II -

G34 Hept i1

heptyl-GLS iso. I -

G35 Hept i2

heptyl-GLS iso. II -

G36 Hept i3

heptyl-GLS iso. III - with a main proportion of Met-derived aliphatic-GLSs and Phenylalkyl-GLS (= 'aromatics') (Figure 1B). In leaves, WOSR '0' accessions displayed about two-fold lower mean GLS contents compared to WOSR '+' accessions, while SOSR '0' displayed about four-fold lower mean GLS contents compared to '+' types (Figure 1A, Supplementary Table S1), suggesting that breeding of '0' varieties had a stronger impact on the content of Met-derived aliphatic-GLS in SOSR than in WOSR varieties.

Branched

In roots also, a similar stronger depressive impact of '0' breeding was observed in SOSR varieties on Met-derived aliphatic-GLS, compared to WOSR varieties (Figure 1B and Supplementary Table S1). This phenomenon had however few consequences on the total root GLS content, due to a higher proportion of the other GLS categories.

Met-derived aliphatic-GLS content in swede and fodder types, although represented by fewer individuals, was in the same range as modern oilseed '0' varieties in both leaves and roots.

Met-derived aliphatic GLSs G1 to G13 compounds were found positively correlated between leaves and roots as well as with global GLS content in seeds (Figure S1). In addition, most aromatic phenylethyl-GLSs (G14-G18) were also positively correlated with branched and linear alkyl-GLSs (G30-G37) in leaves but not in roots. On the other hand, in roots, Met-derived aliphatic-GLSs (G1 to G13) were positively correlated, for the most part, with branched and linear alkyl-GLSs (G30-G37) (Figure S2). PHL molecules did not seem strongly correlated with either GLS in seeds, leaves nor roots (Figure S3). Within phenolics, the highest positive correlations are found between phenylpropanoid (PPN) diHexosides and to a lesser extent between Quercetin derivatives (Figure S4).

Multivariate analyses to identify discriminating molecules between B. napus crop types

For both GLS roots and leaves, Principal Component Analysis revealed weak clustering between crop types. To identify more precisely molecules discriminating the different B. napus types, we performed Linear Discriminant Analyses revealing specific molecules distinctive of each type (Figure 2). As expected, several Met-derived aliphatic-GLS (G7=progoitrin, G8=epiprogoitrin, G10=glucoalyssin, and G11= glucobrassicanapin) were preferentially accumulated in leaves of WOSR and SOSR '+' compared to '0' types. Higher leaf concentrations of branched and linear C6/C7 alkyl-GLSs were characteristics of WOSR varieties (Figure 2A). C3/C4 alkyl-GLS were typically accumulated at higher concentrations in the roots of swede varieties (Figure 2B). Finally, PHL in leaves also discriminates swedes from the other B. napus types (Figure 2C) and WOSR from SOSR varieties. Swede accessions are characterized by high amounts of PL5 (Sin-diHex) and PL24 (Kaempferol-Feruloyl-tetraHex). PL21 (Kamepferol-hydroxyFeruloyl-triHex) characterizes SOSR while a series of Hydroxycinnamic Acid Glucosyl Esters (HAGE) were found distinctive of WOSR (Figure 2C). in seeds. Branched/linear alkyl GLSs forms discriminates the subsp. rapifera (rutabaga) compared to the subsp. oleifera in leaves (B), with a propensity to compensate the aliphatic Met-derived GLSs in leaves of accessions with '0' status (A). HAGEs and an acylated kaempferol derivative with tetrahexosylated discriminate WORS from SORS and the acylated kaempferol highly hexosylated discriminates between the subsp. rapifera (rutabaga) and the subsp. oleifera (C).

GWA analysis to decipher the genetic control of GLS and PHL content in leaves and roots

Heritabilities were quite high on average (equal to 0.65, 0.81, and 0.75 for Leaf GLS, root GLs, and root PHL, respectively) with some variation between traits and organs (Table S2). Using 28,383 genome-wide SNPs with a mixed linear model, we dissected the genetic basis of the phenotypic variation present in 36 GLS and 32 PHL molecules, as well as for additional descriptive variables (sums of some sub-categories and total GLS/PHL content). Among the 270 B. napus accessions, a total of 203 individual QTLs corresponding to 104 genomic regions (hereafter referred to as mQTLs) were significantly associated with one or more phenotypic variables at a threshold of -log10 equal to 5.296. Numerous mQTL, 63 and 41, respectively, were found on both subgenomes A and C. 62, 90, and 51 QTLs were detected for leaf GLS, root GLS, and root PHL, respectively, which correspond to 31, 33, and 54 mQTLs in the B. napus genome (Table S3a,b,c).

Only a few mQTL were found for most of the compounds, and each of these mQTL displayed R 2 in a range between 3.1 and 37.5%. A network analysis of the multiple links between mQTL and GLSs and PHLs was drawn using the Cytoscape software, allowing a global overview of the genetic architecture of root and leaf phytochemistry in B. napus (Figure 3). the association between specialized metabolites and QTLs, with the thickness of the link proportional to the correlation. Distinct genomic architecture underlies independent control of SMs, especially different subcategories of PHLs (phenylpropanoids, non-acylated hexosylated flavonols, and acylated and hexosylated flavonols) and GLSs (aliphatic-GLSs, phenylalkyl-GLSs, indolic-GLSs, branched and linear alkyl-GLSs). QTLs historically associated with the content of Met-derived aliphatic-GLSs in the seeds are highlighted in red diamonds. Interestingly, a single connection between the foliar phenolic and glucosinolate subnetwork. This analysis did not identify any master mQTL that would have controlled a large part of the specialized metabolites. Instead, the Figure 3 highlights that the genetic architecture of constitutive phytochemicals in B. napus consists in small networks of mQTL which independently control the different subcategories of GLSs and phenolics.

No link except for one QTL was observed between GLS and PHL leaf networks, which is in accordance with the absence of correlation between GLS and PHL compound content in the leaves.

Four mQTL controlling total seed GLS content (indicated by red diamonds in the Figure 3) were also strongly involved in the control of a series of Met-derived aliphatic GLSs in both leaves and roots but did not display any genetic link with other categories of GLSs or phenolics. A complementary GWAS analysis conducted with a sub-panel of 00 accessions also identified an additional QTL on the chromosome A03 in the region previously reported by (Liu et al. 2020). Two abundant aliphatic-GLSs 4methylsufinylbutyl (G5=glucoraphanin) and 3-butenyl-GLS (G6=gluconapin) were controlled by mQTLs that were not found involved in the control of seed total GLSs, highlighting that the genetic control of leaf and root Met-derived GLSs does not fully overlap with the QTL involved in total seed GLS content.

As reported in the previous work of (Missinou et al., 2022), short-chain Met-aliphatic-GLSs (G1=glucoiberverin, G2=glucoiberin, and G3=sinigrin) are accumulated at Ph D. manuscript | Anani Amegan MISSINOU P a g e 115 relatively low concentrations in leaves and roots of B. napus (contrasting with high abundance in some accessions of B. oleracea). In the present work, however, the genetic analysis identified a series of QTL involved in the control of their variations among the B. napus accessions. These mQTL network involved in the control of C3aliphatic-GLSs was found independent from the above evoked mQTL networks involved in the control of C4-and C5-Met-derived aliphatic-GLSs. This independent genetic control on C3-aliphatic GLSs might have some biological significance in plantbiotic interactions, keeping in mind the strong affinity to sinigrin of gustatory receptors the Brassicaceae specialist Pieris rapae (Yang et al., 2021).

Branched and linear alkyl GLSs compose only a few percent of the total content of GLSs in most B. napus varieties (Missinou et al. 2022 32 ) but have occasionally been found to accumulate up to 1 µmol.g -1 DW in leaves or 2.4 µmol.g -1 DW in roots of some varieties. Figure 3 and Supplementary Table 1 show that different mQTL networks were found to distinctly control subgroups of those alkyl GLSs in both leaves and roots, apparently in the function of the length and decoration of their lateral chain. Similarly, distinct mQTL were found to control the series of rarely reported hydroxylated derivatives of phenylethyl-GLSs in roots (Supplementary Table 1), depending on if the hydroxylation was positioned on the ethyl (G16 and G17), or the position para-/meta of the phenyl (G15 and G18).

The genetic control of phenolics in leaves was also organized in several genetic subnetworks associated with the control of different biochemical flavonol and phenylpropanoid sub-categories. For flavonols, three genetic networks were involved Ph D. manuscript | Anani Amegan MISSINOU P a g e 116 in the control of flavonol diHexose, two networks were involved in the control of flavonol triHexose, and one QTL was involved in the control of PL24 = Kaempferol-tetraHexose.

For hydroxycinnamic acid glycosyl esters (HAGE), different QTL were involved in the control of Acyl-monoHexosides, Acyl-diHexosides, Diacyl-diHexosides, and Diacyl-triHexosides. Finally, the two close compounds feruloyl-quinic acid and coumaroylquinic acid were controlled each by two distinct mQTL. Few mQTL were found connected to different biochemical subcategories. For one of them, mQTL A08_2.4, the allele variation had opposite effects on two of the most abundant leaf phenolics PL16 (Kaempferol-triHexose, i1) and PL04 (Sinapoyl-Hexose), whose relative proportions consistently contributed to the distinction of two main chemotypes in unsupervised analyses of Brassica accessions reported by Missinou et al. (2022).

GWAS was also conducted to analyze the proportions of metabolite subcategories. S4. This approach allowed identifying the QTL C01_7.3 which was found involved in the control of the length of the lateral chain of Met-derived aliphatic GLS, the two alleles exerting opposite effects on the % of C4-aliphatic GLSs, and the % of C5-aliphatic GLSs (compared to total aliphatic GLSs). These diverging effects of the allelic variation at this QTL were found in both roots and leaves. In line with these results, two QTLs were also found in the control of the % of C3-aliphatic GLSs in leaves, and six QTLs were involved in the control of the % of C6-aliphatic GLSs in roots.

Results are indicated in Table

Consistently with its above-evoked opposite effects on PL16 and PL4, the allele variation at the A08_2.4 was found to also exert opposite effects on the relative proportions of phenylpropanoid and flavonol derivatives (expressed as % of total Ph D. manuscript | Anani Amegan MISSINOU P a g e 117 phenolics). A08_2.4 thus seems to play a significant role in the higher proportion of HAGE in the leaves of winter varieties that have been highlighted by PLS-DA analyses (Figure 4). Finally, GWA analysis identified a series of QTLs involved in the control of the proportion of the three flavonol aglycones kaempferol, quercetin, and isorhamnetin.

Noteworthy, the allele variation on the mQTL A10_10.0 exerted opposite effects on the proportions of Kaempferol and Quercetin derivatives (over the total concentration of flavonoids), and the allele variation on the mQTL C3_7.8 exerted opposite effects on the proportions of quercetin and isorhamnetin derivatives. These results might suggest that those two QTLs could play specific roles in the regulation of the final biosynthetic steps of those three aglycones.

Allele frequencies

To further explore the possible impact of low seed-GLS breeding on the genomic control of B. napus phytochemistry, allele frequencies in each oilseed rape cultigroup Ph D. manuscript | Anani Amegan MISSINOU P a g e 118 (WOSR+, WOSR0, SOSR+, and SOSR0) were mapped on the edges of the mQTL network (Figures 5 and6). As expected, the history of selection led to the fixation of alleles controlling lowglucosinolate at the four main mQTL involved in the control of C4/C5 Met-derived aliphatic GLSs, in both leaves and roots, and in both WOSR and SOSR accessions. SOSR 0 accessions were found to display a strong diminution, compared to SOSR+, of the proportion of low-concentration alleles at the QTL A03_1.4, which is involved in Ph D. manuscript | Anani Amegan MISSINOU P a g e 120 the control of root gluconasturtiin concentration (G14). This phenomenon was not observed in WOSR accessions and is consistent with the significant reduction of gluconasturtiin in the roots of SOSR0 accessions compared to other cultigroups (Figure 7). Beyond this, the breeding of modern low seed-GLSs varieties appeared to have little impact on allele frequencies at almost every other mQTL sub-networks. Interestingly, the QTL A09_10.3 involved in the control of PL24 (Kampferol-Feruloyl-tetraHex) displayed almost exclusively the 'high-concentration allele' in SOSR accessions, but the 'low-concentration allele' in WOSR. This contrast was consistent with the globally higher concentrations observed in the SOSR accessions compared to WOSR accessions (Figure 8). Most mQTL displayed a medium range of allele frequencies, suggesting interesting perspectives for the breeding of varieties with targeted phytochemical profiles. fodder varieties, and 10 accessions of B. napus ssp. rapifera (i.e rutabaga/swede). In addition, WOSR and SOSR types were divided into low GLS in seeds (or '0') and high GLS (or '+') types. This information was deduced from pedigree information and validated with quantification of total GLS in seeds by Near-infrared Spectroscopy. Our dataset includes 63 '+' and 67 '0' WOSR as well as 74 '+' and 46 '0' SOSR (Supplementary Table 1). Details of growing conditions and sampling were previously Ph D. manuscript | Anani Amegan MISSINOU P a g e 122 described in Missinou et al. (202X). Briefly, plants were cultivated in a phytotron with fertilized Hoagland solution. Three independent biological replicates were performed at 1.5-month intervals. Each replicate is a pool of eight plants grown in spatially randomized blocks. Root and leaf tissues of these plants were harvested, rapidly washed with tap water, frozen in liquid nitrogen, and stored at -80°C until lyophilization and further extraction procedure.

Glucosinolate and Phenolic compounds' quantification

A complete description of the extraction protocols, annotation methodology, and descriptive analyses was presented in Missinou et al. (2022). Briefly, glucosinolate extraction was performed using methanol/formic acid on freeze-dried powder samples.

After centrifugation, the supernatant was collected and filtered to be further analyzed by mass spectrometry. Correct annotation of both glucosinolate and phenolic compounds was realized with HPLC-Orbitrap LTQ-XL analyses and software Xcalibur Qual Browser 2.2 SP1. 48 (Thermo Fisher Scientific). Precise quantification of all 68 metabolites (including 36 glucosinolates and 32 phenolic compounds) was performed on UPLC-UV-TQD. Total data acquisition was controlled using Masslynx™ (version 4.1) software and preprocessing with the Quanlynx™ program (Waters Corporation).

Seed glucosinolate content quantification

All the accessions were grown under small cages for seed glucosinolate content quantification under the same environmental conditions per oilseed rape type. Spring accessions were grown in spring 2017 and winter accessions in the 2017-2018 season. Total seed glucosinolate content was assessed through Near-Infrared Reflectance (NIR). Acquisition of NIR spectra was performed using an FT-NIR Ph D. manuscript | Anani Amegan MISSINOU P a g e 123 spectrometer (MPA, Bruker Optik GmbH, Germany). The range used for scanning was between 12 500 and 4 000 cm -1 with a step of 8 cm -1 . Intact seeds (∼5 g) were placed in a standard ring cup and scanned. Each spectrum was the mean of 64 scans per sample. The results were predicted from an in-house calibration established for total glucosinolate content. The results were given as in μmol of total glucosinolates per seed at 9% humidity.

Genotyping

The whole panel was genotyped using the Brassica 60K Illumina Infinium array (Clarke et al. 2016). A total of 30,817 SNPs were scored and validated using a threshold of 5% for the minor allele frequency (MAF) and 30% for the missing values. The missing genotyping data were inferred using Beagle v3 software (Browning and Browning, 2009). All SNPs were physically anchored by BLASTing context sequences on the Brassica napus reference genome Darmor-bzh V10 (Rousseau-Gueutin et al., 2020).

Only uniquely mapped context SNPs were included in the analysis.

Statistical analyses

Various multivariate analyses were performed to describe the phenotypic datasets.

Principal component analysis (PCA) was achieved on the data using the R package FactoMineR [START_REF] Lê | FactoMineR: An R package for multivariate analysis[END_REF] while the PLS-DA (Discriminant Analysis) was performed using the package MASS [START_REF] Venables | Modern Applied Statistics with S[END_REF]. Spearman correlation coefficients (α=0.05) were calculated between metabolic compounds with the package corrplot (Wei T). Broad-sense heritability (h²) was calculated for each metabolic molecule as h²=σg²/(σg²+σe²) where σg² is the genetic variance, σe² is the residual error variance. The estimates of σg² and σe² were obtained from mixed linear models Ph D. manuscript | Anani Amegan MISSINOU P a g e 124 fitted using the lmer function in lme4 package [START_REF] Bates | Fitting linear mixed-effects models using lme4[END_REF] in R environment in R program (R Core Team, 2020).

Genome-Wide Association analyses

Adjusted quantitative values using the least-squares method were further processed through GWA analyses. These genetic analyses were conducted using the FastLMM algorithm (Lippert et al., 2011) with a kinship calculated using the Van Raden algorithm [START_REF] Van Raden | Efficient Methods to Compute Genomic Predictions[END_REF] for each chromosome as described by Rincent and coworkers (2014). In addition to the kinship, the three main axes of the PCoA explaining respectively 13.0, 9.1, and 6.0% of the variance were also added in the FastLMM analysis added as covariables. To run these different steps the R script developed by Negro and co-authors (2019) was adapted. The significance threshold was set based on the Bonferroni threshold of 5% calculated on a corrected SNP population as proposed by the simple M method developed by [START_REF] Spinelli | Emission and Function of Volatile Organic Compounds in Response to Abiotic Stress[END_REF] (Gao et al., 2008;[START_REF] Spinelli | Emission and Function of Volatile Organic Compounds in Response to Abiotic Stress[END_REF]. This method is based on the composite linkage disequilibrium (CLD) correlation between SNPs. The CLD was used to calculate the effective number of independent tests (M eff). Here, Meff was calculated and fixed to 5,544 SNPs. The threshold -log10(p) was thus defined at 5.296 for the B. napus panel.

Linkage disequilibrium approach to identify QTLs

From significant SNPs, QTL regions were defined as hereafter. First, for each significant SNP, Plink software was used to calculate the local LD decay (ré=0.25) at the chromosome scale. Physical intervals were deduced from LD borders around every significant SNP at each QTL, with a LD decay of 0.2. Then, a custom script (available on github/jferreira) was developed to define the confidence interval for each QTL. It Ph D. manuscript | Anani Amegan MISSINOU P a g e 125 merged overlapping physical intervals for a single trait, which defined mQTL with its confidence interval. mQTL were named according to the physical position of the peak SNP.

Network analyses

A first visualization approach using MapChart (Voorrips, 2002 J of Heredity) was performed to identify co-localizing QTLs. Overlapping mQTLs for different metabolites and organs were renamed similarly to identify genomic regions controlling multiple metabolites. So, for each mQTL, all associated metabolites and the maximum R 2 were retrieved to be further included in a network analysis using the software Cytoscape 3.9.0 (Shannon et al. 2003). In this network, nodes represent QTL (source) or traits (target), and edges represent statistically significant links between loci and phenotypic traits. Edge widths were used to represent R 2 , which is, the percentage of phenotypic variance explained by each QTL for a given metabolite. In addition, the frequency of the allele contributing to an increase of the metabolite was calculated within each subset of the panel i.e. within WOSR+, WOSR0, SOSR+ and SOSR0.

%Flavonol-diHex / Flavonols % Flavonol-monoacyl / Flavonols 65. 1 50 -82.7 64.4 51.3 -78.9 64.4 52.1 -75.8 67.5 47.5 -81.8 % Flavonol-diacyl / Flavonols

Introduction

A key challenge in plant chemical ecology is to extend the current knowledge of specialized metabolite (SM) diversity and identify genomic factors controlling their biosynthesis. This should increase our understanding of the roles played by these SMs in plant growth and development [START_REF] Nakabayashi | Integrated metabolomics for abiotic stress responses in plants[END_REF][START_REF] Chattha | Coumarin-Based Heteroaromatics as Plant Growth Regulators[END_REF], biotic interactions [START_REF] Gresshoff | Post-genomic insights into plant nodulation symbioses[END_REF]Shroff et al., 2008;[START_REF] Erktan | Frontiers in root ecology: recent advances and future challenges[END_REF], and abiotic challenges [START_REF] Stringlis | MYB72-dependent coumarin exudation shapes root microbiome assembly to promote plant health[END_REF][START_REF] Huang | A specialized metabolic network selectively modulates Arabidopsis root microbiota[END_REF]. Besides typical chemical approaches for isolation and identification, the research on SM genomics in plants has benefited from collaborations between phytochemists, geneticists, physiologists, and Ph D. manuscript | Anani Amegan MISSINOU P a g e 143 molecular biologists. For instance, in Brassicaceae, integrative studies were able to highlight the main genes controlling glucosinolate (Kroymann et al., 2003;[START_REF] Kim | Identification and Quantitative Determination of Glucosinolates in Brassica napus cv[END_REF]Kittipol et al., 2019;Liu et al., 2020), phenylpropanoids (Francisco et al., 2016), and flavonoids (Lee et al., 2014) contents. Such studies, aiming to identify associations between genetic variants and chemical traits using large genetic diversity are so-called metabolic genome-wide association studies (mGWAS).

Brassica napus is an allopolyploid species derived from the post-neolithic interspecific hybridization between B. rapa and B. oleracea and includes oilseed rape, swede, and fodder crops (Nagaharu U, 1935;Chalhoub et al. 2014). This species is economically important for seed oil and protein meal production across different continents, including coumarins was shown to act as an allelopathic plant growth regulator [START_REF] Chattha | Coumarin-Based Heteroaromatics as Plant Growth Regulators[END_REF] or as an iron uptake stimulator from substrates with low iron availability [START_REF] Schmid | Feruloyl-CoA 6′-Hydroxylase1-dependent coumarins mediate iron acquisition from alkaline substrates in Arabidopsis[END_REF]. Coumarins may shape root microbiota assembly to promote plant health [START_REF] Stringlis | MYB72-dependent coumarin exudation shapes root microbiome assembly to promote plant health[END_REF], or be involved in biotic and abiotic stress responses [START_REF] Nakabayashi | Integrated metabolomics for abiotic stress responses in plants[END_REF].

Brassica species typically accumulate very large amounts of flavonols and phenylpropanoids in leaves, but the few available studies on the root compartment reported only very low concentrations of phenolics (Fernandes et al., 2007). In previous work, we documented large-scale metabolic profiling of glucosinolates and phenolic compounds in the roots and leaves of a genetic panel of 304 accessions of B. napus, B. rapa, and B oleracea (Missinou et al., 2022). This work confirmed that flavonol and phenylpropanoid derivatives are accumulated at very low concentrations (under quantification ranges) in Brassica roots. Also, unpublished chromatographic results obtained during these investigations highlighted a series of atypical UV-absorbing root compounds. For most of those compounds, mass spectra did not match with any available phenolics from public databases. Two of those unknown compounds (m/z 320.099 and m/z 368.099) have been previously reported in our studies (Wagner et al. 2019) to be genetically related to clubroot resistance in B. napus. Thus, because of the potential roles that this series of unknown compounds may potentially play in biotic interactions, we focused our efforts in the present work on the investigation of the chemical and genetic characteristics of this series of unknown aromatic structures.

We first investigated the concentrations of these compounds in the roots of the abovementioned genetic panel of 304 Brassica accessions, using a UV-detection semiquantification approach. We then used a mGWAS approach to investigate the genomic regions involved in the control of their concentrations in roots. Three of these compounds were further purified and their chemical structures were investigated by a combination of Q-Exactive Orbitrap High-Resolution Mass Spectrometry (HRMS) and NMR (1D and 2D).

Materials and Methods

Plant material and sampling

Seeds from 304 Brassica accessions (281 B. napus, 12 B. rapa, and 11 B. oleracea) were germinated, cultivated, sampled, and stocked as described in Missinou et al.

2022. The subset of spp. oleifera from B. napus was constituted by 130 accessions of winter oilseed rape (WOSR) and 120 spring oilseed rape (SOSR). Eight plants from each accession were cultivated in two spatially randomized blocks of 4 plants according to cultivation conditions described in Missinou et al. 2022. Three independent biological replicates were performed at 6-week intervals. Four-week-old plants per accession were harvested, and roots were rapidly washed with tap water, immediately frozen in liquid nitrogen, then stored at -80°C before lyophilization. The lyophilized materials were powdered, homogenized, and stored in the dark until further phytochemical analysis.

Chemicals

HPLC-grade acetonitrile, methanol, and formic acid were from Carlo Erba. Authentic phenolic standards were provided by Sigma-Aldrich. For NMR experiments, deuterated solvents (MeOD-d3, MeOD-d4, and CD3OD) were obtained from Eurisotop (France).

Ph D. manuscript | Anani Amegan MISSINOU P a g e 146

Metabolite extraction procedure

Thirty milligrams (mg) aliquots of freeze-dried powders were extracted with 1mL of methanol/formic acid (99/1, v/v). The suspensions were vortexed and then sonicated in a water bath at 25°C for 10 min. After centrifugation at 7000 rpm for 10 min, the supernatants were collected and filtered using a 0.22 μm PTFE membrane. Extracts were stored at 4°C and analyzed by LC-MS less than 24h after extraction. This extraction procedure was conducted on each sample for quantitative analyses. In addition, for "bulk" analysis, similar extractions were performed on pools from several root powders sampled from different accessions (five randomly chosen accessions for each of the following groups: B. napus WOSR, SOSR, fodder, swede, B. oleracea, and B. rapa). After that, these powder bulks were used for HPLC-Orbitrap LTQ-XL highresolution mass spectrometry analysis. As some compounds were accumulated more specifically in specific genotypes, additional powder bulks were also prepared by combining typical accessions to gain more intense signals and allow better chemical fragmentation.

Chromatography, semi-quantitative profiling

Sample extracts were processed through UPLC-UV-TQD as previously described (Missinou et al. 2022). UV-absorbing compounds content was simultaneously measured at λ330mn, and peak deconvolution of UV-chromatograms was preprocessed using Empower (version 2). Alphanumeric IDs were assigned to the UVabsorbing compounds as numbered peaks noted from R01 to R18 (according to the chromatographic elution order). These numbers were followed by an underscore and by the monoisotopic m/z, except for three peaks R12, R14, and R17 harboring multiple m/z possibly corresponding to multiple coeluted compounds. Those three compounds were then annotated as MNA for "Mass Not Available". The measure was based on determining arbitrary area units under the absorbance curve at λ330 nm using the baseline method and fitting with 1/x weighting.

MS/MS fragmentation

The experiments of MS2 fragmentation from "bulk" extracts were executed on LTQ-Orbitrap-LTQ-XL mass spectrometer as previously described (Missinou et al. 2022).

Succinctly, mass spectrometry experiments were performed using the LTQ-Orbitrap XL (Thermo Fisher Scientific) equipped with an ESI source operating in negative mode.

The MS1 spectra were acquired as a profile in full scan mode and used for recording accurate mass ranging from 250-1500 m/z, with 500 ms of scan time (with a resolution of 30.000 at m/z 200). The MS/MS scanning mode was set as a data-dependent ms2 scan (dd-ms2). The high energy collision dissociation was 30eV, and the cone voltage at 35V. Several diagnostic neutral losses were searched to get initial structural information and define the family of each compound.

Multivariate statistical analysis

Analyses were performed using the software R and the interface RStudio (R Core Team, 2021). Variables with undetermined values representing more than 5% of the dataset were removed from the following analyses. Normalized datasets were meancentered using the least-squares method and a linear model including biological replicates using the "emmeans" R package [START_REF] Lenth | Emmeans: estimated marginal means, aka least-squares means [R package emmeans version 1.7.0[END_REF]. Mean-centered values of each compound were visualized on boxplots, and comparisons between species were evaluated using Tukey's tests. Multivariate statistical analyses were performed to describe phytochemical profile diversity. PCA models were made with "gridextra"

and "ade4" R packages (Dray and Dufour, 2007). Heatmaps were performed with "complexheatmaps" R package, converting the data to z-scores (centered samples divided by standard deviation) [START_REF] Gu | Complex heatmaps reveal patterns and correlations in multidimensional genomic data[END_REF]. PLS-DA models were performed using the mixOmics R package [START_REF] Rohart | mixOmics: an R package for 'omics feature selection and multiple data integration[END_REF]. All visualization plots were realized using the "ggplot2" R package (Wickham, 2016).

Metabolic genome-wide association analysis

Adjusted quantitative values using the least-squares method were further processed through GWA analyses for the B. napus diversity panel. These genetic analyses were conducted using the FastLMM algorithm (Lippert et al., 2011) with a kinship calculated using the Van Raden algorithm [START_REF] Vanraden | Efficient Methods to Compute Genomic Predictions[END_REF] for each chromosome as described by Rincent and coworkers (2014). In addition to the kinship, the three main axes of the PCoA explaining respectively 13.0, 9.1, and 6.0% of the variance were also added in the FastLMM analysis added as covariables. To run these different steps the R script developed by Negro and coauthors (2019) was adapted. The significance threshold was set based on the Bonferroni threshold of 5% calculated on a corrected SNP population as proposed by the simple M method developed by (Gao et al., 2008). This method is based on the composite linkage disequilibrium (CLD) correlation between SNPs. The CLD was used to calculate the effective number of independent tests (M eff). Here, Meff was calculated and fixed to 5,544 SNPs. The threshold -log10(p) was thus defined at 5.296 for the B. napus panel. Then, significative SNPs were fused to Ph D. manuscript | Anani Amegan MISSINOU P a g e 149 identify mQTLs as long as their confidence intervals (using LD decay, r 2 =0.25) overlapped.

Identification of candidate genes

First, the location (start and end) of genes in the B. napus genome v05 (Chalhoub et al., 2014) was searched into the genetic intervals of the mQTLs using a homemade R script. Then, the functional annotations of oilseed rape genes inferred from Arabidopsis were retrieved from Brassica genome v05 (Chalhoub et al., 2014) to identify the candidate genes for the mQTLs detected. Attention has been given to genes encoding for transcription factors, major enzyme families known to be involved in specialized metabolism, and their presumed cousins in primary metabolism, considering chemical functions and structural information of purified compounds.

Metabolite purification

Reversed-phase SPE fractionation procedure

The purification of specific compounds implied the production of large amounts of root material with a selection of the genotypes harboring the highest concentrations (details in the support table S1). Plants were cultivated as described above. For each selected genotype qualified as super-accumulators, 60 g freeze-dried roots were extracted with 400 mL of methanol/formic acid (99/1, v /v). These extracts were concentrated to dryness using a rotary evaporator (40°C, 150 rpm), then re-dissolved in 5 mL of a methanol/water (50/50, v/v) mixture, and sonicated for 2 min. This extract was loaded column for each run. Fractions of 1.75 mL were collected each 30 sec. Fractions corresponding to UV-absorbing peaks were thereafter analyzed by UPLC-UV-TQD-MS to get additional spectrometric information on the compounds of interest. Fractions obtained from iterated (about 20) injections were pooled, then concentrated by a rotary evaporator to dryness, and were re-dissolved in 5 mL 50% MeOH in water and centrifuged at 7000 rpm for 10 min. Aliquots of 250 µL were then re-loaded on the same HPLC system, using another gradient. This elution gradient was adapted around the eluting % solvent B for each targeted compound and optionally maintained under isocratic conditions. The products collected were concentrated to dryness under nitrogen flux.

Structural analysis of purified molecules

Q-Exactive Orbitrap MS/MS experiments

The three purified compounds were investigated by HRMS2 and HRMS3 by infusion on a Q-Exactive Orbitrap. For each compound, some basic rules of mass spectrometry (C, H, N, O, S) were applied to identify fragmentation patterns (neutral losses, degree of unsaturation, and formula of small neutral fragments) and the empirical molecular formula could be designed [START_REF] Bright | Mass spectral interpretation using the 'rule of "13[END_REF][START_REF] Pellegrin | Molecular formulas of organic compounds the nitrogen rule and degree of unsaturation[END_REF]. These constraints allowed us to remove more than 95% of false candidate formulas for compounds.

NMR experiments

NMR spectra were recorded in MeOD-d3, MeOD-d4, and DMSO-d6 at 300 K on a Bruker Avance III 500 spectrometer equipped with a BBFO+ probe and a Bruker

Avance NEO 500 MHz spectrometer with CryoProbe, both driven by the TopSpin NMR software (v3.6.1). The solvent was used as an internal standard to determine chemical stebpgp1s sequence was performed. The DOSY spectra were processed with the bayesian algorithm with 32 points in diffusion dimension. NMR data processing and plotting were performed using MestreNova software (v14.2. 3) [START_REF] Willcott | MestRe Nova[END_REF].

Combining NMR and MS allowed a simultaneous assignment and structural elucidation.

Results

LC-MS/MS fragmentation of eighteen unidentified UV-absorbing compounds extracted from Brassica roots

The complete analysis of the 304 accessions revealed a newly described series of UVabsorbing compounds (at λ330 nm). Eighteen peaks that were well resolved among a series of chromatographic injections were selected for further analyses (Figure 1). In Table 1 are compiled their retention times (after either HPLC or UHPLC separation, see material and methods), accurate parent masses (<10 ppm), and daughter anions.

The fragmentation patterns (daughter anions and neutral losses) and parent anions of these compounds did not share any feature with any of the phenolic compounds that had been identified in the leaf samples in Missinou et al. (2022) that also suggest the structural proximity between R04 and R09 (Table 1). Although the parent masses of those two compounds may suggest sinapoyl-glucose, both of those two compounds harbored different chromatographic elution times compared to the compound PL04 which was annotated as sinapoyl-glucose in Missinou et al. 2022. This could suggest the accumulation of different stereoisomers in roots and leaves for this family of compounds.

We searched the mass features in the databases (COCONUT, KNAPSAcK, KEGG, BioCyc, Natural Products, PubChem, PlantCyc) and found that accurate masses of UR01_M315 and UR08_681 agreed with dihydroxybenzoylhexose and dihexosyl derivative of pinoresinol. For every other peak, to the best of our efforts, none of the other mass features matched with any compound from public databases. After fragmentation, neutral losses of 18 Da, 46 Da, 68 Da, and 136 Da, shared by R02_M431, R04_M385, R07_M551, R10_M565, R11_M523, R15_M380, and R16_M493 features, suggested that they may have quite close structures (Table 1). (46 Da), respectively (Table 1). These fragmentation patterns suggest the structural isomerization of a single structure. 1). The remaining features that displayed specific fragments suggest a structural singularity (Table 1).

Targeted metabolite profiling of UV-absorbing at λ330 nm in Brassica roots highlights wide intraspecific quantitative variations

Based on the integration of UVλ330 peaks, relative quantification of the eighteen eluted compounds was acquired from the methanolic root extracts of the 304 Brassica accessions.

Ph D. manuscript | Anani Amegan MISSINOU P a g e 156

Table 1: Mass fragmentation (m/z) patterns of unknown root compounds absorbing at λ330nm in the panel of 304 accessions of Brassica. The IDs from R01_M315 to R18_M368 represent the metabolites numbered according to the order of elution. RT min HPLC and RT min UPLC determine retention time for qualitative and semi-quantitative analysis.

[M] stands for the neutral structure relative intensity of the fragment to the base peak is shown in parentheses. "Exp" strands for experimental mass (m/z [M-H] -) and MS2 (daughter anions) were acquired on HPLC-Orbitrap LTQ-XL. MNA: for "Mass Not Available"). 6) 317( 5) 249( 3) 177(100 12.41 7.14 434.207 416(10) 390( 10) 388( 15) 366( 20) 18.29 11.22 565.191 547(9) 497( 3) 429( 3) 339(100)[M-H-226] -, 327 [START_REF] Li | Characterization of glucosinolates in 80 broccoli genotypes and different organs using UHPLC-triple-TOF-MS method[END_REF][M-H-238] -, 357 [START_REF] Harbaum | Identification of flavonoids and hydroxycinnamic acids in pak choi varieties (Brassica campestris L. ssp. chinensis var. communis) by HPLC-ESI-MSn and NMR and their quantification by HPLC-DAD[END_REF][M-H-208] -, 518 [START_REF] Lee | Rapid screening method for intact glucosinolates in chinese medicinal herbs by using liquid chromatography coupled with electrospray ionization ion trap mass spectrometry in negative ion mode[END_REF][M-H-47] -, 498 [START_REF] Bradburne | Glucosinolate genetics and the attraction of the aphid parasitoid Diaeretiella rapae to Brassica[END_REF][M-H-67] - R11_M523 18. 71 12.72 523.144 505(3) 477( 15) 455( 11) 387( 3) 5) 312( 12) 244( 2) 22.49 15.71 493.115 475(5) 447( 18) 425( 53) 357( 14 In the absence of any authentic standard, no calibration could be applied. Thus, relative root contents were expressed in an arbitrary unit of UV absorbance at λ330nm per dry weight (AUλ330.g -1 DW). As the molecular extinction coefficients can vary greatly according to the nature of the structures concerned, the semi-quantitative comparisons proposed below only consider the variations observed between accessions for the same compound and not the variations compared between compounds. The supporting Table S1 provides an overview of metabolite contents detected in the whole Brassica panel. Sheet 1b, 1c, and 1d summarizes the means, percent, and 5th to 95th percentile values, including minimum, and maximum values of contents of each compound in all accessions (Supporting Table S1, coming soon in the published article).

M-H-H 2 O M-H-CO 2 M-H-? M-H-? M-H-CO

)[M-H-208] -, 162(7)[M-H-223] -, 207(1)[M-H-178] - R05_M434
391(100)[M-H-43] -, 392(48)[M-H-42] -, 175(30)[M-H-259] -, 406 (12)
343(100)[M-H-180] -, 456(7)[M-H-67] -, 434(2)[M-H-89] -, 494(2)[M-H-29] -, 433 (2)
176(100)[M-H-204] -, 333(4)[M-H-47] -, 243(3)[M-H-137] -, 320(3)[M-H-60] -, 311(2)[M-H-69] - R16_M493
The oleracera ssp. capitata (687 AUλ330.g -1 DW) (Table 2, supporting Tables S1b andS1c, coming soon in the published article).

Quantitative differences were also observed at the level of subgroups (WOSR and SOSR) and subspecies (Table 2, supporting Tables S1b andS1c S1, coming soon in the published article). AU: absorbance unit, and DW: dry weight.

Chemotypes pointed out through multivariate analyses

Figure 2 presents the heatmap built with the UVλ330-absorbance values of the 18 root compounds highlighted in the Brassica panel. In Supporting specific patterns, as well as cultivar-common patterns ("hot points" and "cold points"

represented by regions of high-dark red-or low-dark blue-respectively), were observed (Figure 2A). Moreover, the heatmap highlighted three chemotypes and revealed moderate intra-specific variability in Brassica (Figure 2A). of compounds in all accessions revealed that pairs of putative isomers (R03_M434/R05_M434 and R04_M385/R09_M385) were clustered separately (see "cluster b" and "cluster c" in Figure 2C). At the same time, R13_M320 and R18_M368

were strongly correlated and grouped in the same cluster (see cluster a in Figure 2C). The three first components were kept, which would be enough to explain a moderate proportion of the variance of data, according to supporting Figure S1. The first three PCs explained about 37.1% of the total variance, with about 15.4%, 12.3%, and 9.4% of the total variation explained by the first, second, and third principal components, respectively (Supporting Figure S1, coming soon in the published article).

Thus, these PCA biplots displayed scattered distributions of accessions, with the highest contribution of three compounds (R03_M434, R13_M320, and R18_M368) (Figure 3A). It is noteworthy that the variation of R03_M434 was not correlated with those of R13_M320 and R18_M368. The remaining compounds mainly contribute to the other PCA components that explained a small proportion of the variance.

Nevertheless, PCA biplots allowed us to distinguish between spring and winter cultivar accessions of B. napus with slight overlapping (Figure 3A). Some of the 18 compounds exhibited positively correlated pairwise relationships (highlighted by background color)

and tended to have similar loadings: R13_M320 with R18_M368, R17_MNA with R4_385, and R1_315 with R14_MNA. biplot of PC1 and PC2 highlights the significant loadings exhibited by essential compounds in the PLS-DA model (on the left of Figure 3B). Although some overlap persisted, this approach allowed a better separation of winter and spring accessions of B. napus.

mGWAS identified genomic regions (mQTLs) associated with novel chemical traits in the roots of Brassica

The root contents (based on UVλ330-absorbance levels) of the 18 compounds were used as phenotypic variables for quantitative trait locus (QTL) analysis. All metabolic features showed a continuous frequency distribution (Supporting Figure S2, coming soon in the published article). Features R01_M315, R12_MNA, and R17_MNA

showed slight variations and a normal distribution. In contrast, the remaining compounds were distributed along with skewed density distributions. Therefore, QTL analysis was performed using single-nucleotide variant (SNP) markers (JF de

Carvalho & Missinou, et al, in preparation).

mGWAS thus highlighted several variants associated with UVλ330-absorbing compound content traits. In total, 208 significant SNPs were detected above the Gao threshold set to log10 pval = 5.296 (Figure S3). Seventeen UVλ330-absorbing compound content mQTLs were associated with the 11 metabolite features R01_M315, R02_M431, R03_M434, R05_M434, R07_M551, R08_M681, R11_M523, R12_MNA, R13_M320, R16_M493, and R18_M368 (Table 3). These mQTLs were distributed on ten chromosomes A01, A03, A04, A06, A07, A09, C01, C03, C07, and C05 representing 18 distinct genomic regions on the genetic map (Table 3, Supporting Figure S3, Supporting Table S2a, coming soon in the published article)). The explained phenotypic variation of the detected QTLs ranged from 10% (mQA06_37. [START_REF] Schulz | Natural variation among Arabidopsis accessions in the regulation of flavonoid metabolism and stress gene expression by combined UV radiation and cold[END_REF]mQC07_37.3,mQA04_4.7,and mQC05_32.6) to 31% (mQC03_22.2).

The content of five compounds was associated with more than one mQTL, i.e., three mQTLs for R03_M434 and R07_M551, two mQTLs for R16_M493 and R18_M368, and four mQTLs for R13_M320 (Table 3, Supporting Table S3a, Supporting Figure S3, coming soon in the published article). In two genomic regions, at least two mQTLs colocalized on chromosome A04 (R13_M320 and R18_M368) and chromosome A09 (R08_M681 and R16_M493) (Supporting patterns (Table 1), correlated level profiles, and best discriminant loadings of the spring accessions between the panel (PLS-DA, Figure 3. B). two leaf phenolic compounds, as previously shown 33 . Additional details are given in Supporting Table S3c, coming soon in the published article.

The network representation of the genetic architecture controlling the root concentration of 11 compounds (Figure 4), highlighted that most compounds were independently controlled by distinct and relatively small QTL networks. Only one of those QTLs, C07_37.3 (marker Bn.C07.p31107417) controlling the compound 33 Cf. chapitre II, article 2

Ph D. manuscript | Anani Amegan MISSINOU P a g e 166 R12_MNA was located in the same genomic regions that one QTL that has been previously identified as associated with the control of two flavonol trihexosides (PL32=Isorhamnetin trihexoside and PL17=Kaempferol trihexoside) (Chapter II, article

2). The two structurally related and co-regulated compounds R13_320 and R18_368

were found to share one QTL A04_9.36, and two additional QTL were specifically associated with the control of R13_320 and one QTL to the control of R18_368. Similar patterns of shared mQTL were also observed for two additional couples of metabolites, the QTL C07_52.2 controlling the two isomers R03_M434 and R05_M434, and the QTL A09_15.9 controlling both R08_M681 and R16_M493.

Analysis of potential candidate genes

Overall, 2444 genes were identified in the confidence interval of the 17 mQTL involved in the quantitative variation of the 11 compounds. About 87.7% of these genes have functional annotations inferred from Arabidopsis thaliana. In the confidence interval of each mQTL, at least one candidate gene was identified (Figure 5). (Chalhoub et al., 2014).

In the mQA09_15.9 (R08_M681 and R16_M493) confidence interval, 169 genes (with 140 annotated genes) were identified. Several genes were involved in the metabolism of sulfur-containing amino acids, carbohydrates, and phenylpropanoids. Of these, an ortholog of A. thaliana acyltransferase (BnaA09g23800D and BnaA09g23800D), BnaA09g23510D, BnaA09g23800D, BnaA09g24120D, BnaA09g23290D, BnaA09g24120D), and glutaredoxin (BnaA09g24210D) were found. For the very close QTL mQTLA04_9.9 and mQTLA04_9.36 (controlling R13_M320 and R18_M368), very few genes were identified. This list included MYB family transcription factors (BnaA04g10750D and BnaA04g10750D).

hexosyltransferase (BnaA09g23290D,
134 ( 102) 40 [START_REF] Gols | Seasonal and herbivore-induced dynamics of foliar glucosinolates in wild cabbage (Brassica oleracea)[END_REF] 169 ( 140) 151 ( 115) 67 [START_REF] Francisco | Simultaneous identification of glucosinolates and phenolic compounds in a representative collection of vegetable Brassica Rapa[END_REF] 16 ( 9) 45 ( 26)

1 (0)
16 ( 13) 500 ( 491) 899 ( 878 to a pteridine-like poly-nitrogenated aromatic heterocycle (C6H3N4O2), for which the exact position of the four nitrogen atoms is still unresolved (Figure 7 and Figure 9). R18_M368 (C17H15N5O5): This compound has been analyzed in DMSO-d6 solvent at a temperature of 300K. The fragment has been fully characterized in 1 H and 13 C for all the signals, by HSQC / HMBC / COSY / NOESY spectra. The connection to the polynitrogen aromatic cycles has been identified through the NH of the amino acid fragment. The structure of this compound was thus partially solved (figure 7) as an amino acid-like with a chain R = -CH2-CH2-Ph, connected to a pteridine-like polynitrogenated aromatic heterocycle (C6H3N4O2) for which the exact position of the four nitrogen atoms is still unresolved (Figure 8 and Figure 9).

Discussion

The Brassica root repertoire of specialized metabolites is largely dominated by glucosinolates. However, we need to further investigate the still unexplored root chemical diversity that could also play important roles in plant interactions with its soil environment. This work was originally focused on the search for root-specific phenolic compounds. However, the difficulties that we encountered for the annotation of UVλ330chromatographic profiles from Brassica root extracts, reflecting the absence of consistent mass-spectrum data in public databases, suggested that these compounds could be worthy of additional investigations.

UVλ330-based semi-quantitative data highlighted large ranges of concentrations for every 18 compounds among the accessions of B. napus. Multivariate approaches on these unknown compounds clearly distinguish between chemotypes for SOSR and WOSR accessions. It also highlighted, among others, the large contribution of R13_M320 and R18_M368 accumulation to the SOSR chemotype, thus bringing an interesting complementary view on the root phytochemical diversity of oilseed rape (following our previous work on glucosinolates and phenolicsf, Missinou et al., 2022 34 ). This also opens new perspectives about the possible biological roles of those compounds and the possible agronomic significance of their variations between oilseed rape cultigroups.

Eleven compounds were controlled by independent mQTL networks, which means that the chemotypical contrasts resulted from combinations of allele variations at multiple mQTL. The absence of colocalization with mQTL previously identified in this panel of Ph D. manuscript | Anani Amegan MISSINOU P a g e 173 accessions, suggests that the phytochemical profiles defined by these eleven compounds are controlled by evolutionary or breeding processes which are independent of those involved in the control of glucosinolates and phenolics (Missinou et al., 2022).

Experimental data support that the poly-nitrogenated aromatic heterocycle (C6H3N4O2) from R13_M320 and R18_M368 is based on a pteridine-like structure, although the exact position of nitrogen atoms on the bicyclic structure was not fully resolved by the NMR approaches used in the present work (figure 9). To the best of our knowledge however, pteridine basic structure would be the only proposition that has been reported in natural products, and biosynthetic pathways of pteridine-based compounds are reported in plants including flavin and folic acid (M. [START_REF] Pahor | Pterin chemistry and its relationship to the molybdenum cofactor[END_REF]. The occurrence in the roots of B. napus of two amino-acid conjugates of this basic structure is reminiscent of the aminoacid conjugation of a series of plant signaling compounds like jasmonic acid, indole-3-acetic acid, or salicylic acid, by GH3 enzymes belonging to a firefly luciferase-like superfamily.

Bioinformatic molecular network approaches use the similarities between MS/MS fragmentation patterns to screen for sub-groups of compounds that share common chemical sub-structures in large metabolomic datasets. In the present work, the lack of high-resolution MS2 fragments impaired the use of classical bioinformatic approaches (such as GNPS). However, the fact that pairs of compounds displayed both common MS2 fragmentation patterns and common mQTL not only suggested that they could display similar chemical structures, but also suggested that they could share common biosynthetic or regulation pathways. One QTL on chromosome A04 Ph D. manuscript | Anani Amegan MISSINOU P a g e 174 controlled both R13_M320 and R18_M368, i.e. two pteridine-like polynitrogenated aromatic heterocycles conjugated to leucine (m/z 320.099 [M-H] -) and homophenylalanine (368.099 [M-H] -). This suggests that this QTL might be involved in the biosynthesis of the core pteridine-like moiety. Each of these two molecules was also controlled by additional distinct QTLs, that might be involved in the conjugation with each amino acid. Additional work is now required not only to finalize the full annotation of the pteridine-like structure, which will require enhanced amounts of purified compounds. The confidence intervals of the mQTL encompass a reasonably small number of candidate genes, thus encouraging further work toward the validation of their possible regulatory roles in the biosynthesis of these compounds. This will include 1/ a complementary analysis of the gene content in the mQTL confidence intervals in genome sequences from other B. napus accessions 2/ the analysis of available root transcriptomes to identify the subset of expressed genes, 3/ an analysis of the possible presence of metabolic gene clusters, and 4/ the use of Cas9 strategies for the validation of hypotheses.

The work of Wagner et al. 2019 (based on a linkage genetic analysis on a progeny derived from a 'Darmor-bzh' x 'Yudal' cross), had previously reported that one major mQTL on chromosome C09 is involved in the control of the constitutive root content of R13_M320/R18_M368 and the resistance to the isolate eH of P. brassicae. We however did not detect this mQTL in the present work, which might suggest that the underlying allele variation might be rare in the whole genetic panel, thus impairing the detection of this QTL by the GWAS approach in the present work.

Conclusion

We provided new insights into root metabolism and identified new compounds and the key genomic regions underlying the variations of their concentrations in roots. The structural draft of two of these root chemical traits suggests that these compounds belong to a poorly studied subfamily of pteridine-like molecules, which brings an added value to the catalog of phytochemical diversity of Brassica in the springboard for a better understanding of root chemical ecology. The next challenge will be to characterize the candidate genes through cloning or transgene validation to interpret these associations in a physiological and genomic context. Therefore, metabolic GWAS-based dissection of genetic bases underlying the diversity of UV-absorbing compounds content combined with mass spectrometry and nuclear magnetic resonance is complementary to uncovering genes that regulate their accumulation in plants and offers discoveries and perspectives into the research of specialized plant metabolism.

Table 1: Unknown root compounds absorbing at λ330nm in the panel of 304 accessions of Brassica. [M] stands for the neutralized structure and (*) stands for the very percentage of relative intensity.

Table 2: Descriptive statistics (mean, percent, minimum, maximum) of unknown Brassica root compounds absorbing at λ330nm. Details for each accession and compound are given in Supporting Table S1). AU: UV-absorbing compounds content unit, and DW: dry weight.

List of Figures

Introduction

The production of oilseed rape in numerous countries is affected by the fungal pathogen Leptosphaeria maculans (commonly named phoma), which causes blackleg disease also known as stem canker or phoma stem canker (Fitt et al., 2006;Dukhnytskyi, 2019). The phoma-infected oilseed rape displays necrotic lesions at the stem, provoking symptoms of water and mineral impairment, reducing growth, and leading to plant mortality [START_REF] Mcgee | Black leg (Leptosphaeria maculans (Desm.) Ces. et de Not.) of rapeseed in Victoria: Crop losses and factors which affect disease severity[END_REF][START_REF] Howlett | Leptosphaeria maculans, the causal agent of blackleg disease of Brassicas[END_REF]. A high incidence of disease results in production losses and severe damage to the rapeseed oil industry [START_REF] Wang | Yield losses in canola in response to blackleg disease[END_REF]. L. maculans is a hemibiotroph whose complex life cycle includes alternating phases of saprophytism on stem residues, a short phase of the asymptomatic biotrophic stage during which it colonizes the apoplast, subsequently switching to a necrotrophic lifestyle in leaf lesions after ascopores landing on plant leaves, a long asymptomatic endophytic stage in plant tissue, and finally the second phase of symptomatic necrotrophy at the base of the stem, which affects the central tissues and kills the plant (West et al., 2001;Rouxel and Balesdent, 2005;Bousset et al., 2018).

Genetic factors involved in quantitative resistance to Blackleg mainly exert their effects at the stem stage of infection leading to the dampening of the extent of necrosis caused by L. maculans in partially resistant accessions (Delourme et al., 2014;Pilet-Nayel et al., 2017). One hypothesis is that specific metabolites accumulate at the site of infection and act directly on the pathogen to limit its centripetal progression within tissues, particularly in resistant genotypes.

Since its introduction by [START_REF] Caprioli | Molecular Imaging of Biological Samples: Localization of Peptides and Proteins Using MALDI-TOF MS[END_REF], mass spectrometry imaging technology has allowed the molecular mapping of diverse tissue cross-sections, allowing visualization of molecular details in their tissue context [START_REF] Qin | Recent advances in matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) for in situ analysis of endogenous molecules in plants[END_REF]. This technology is based on the irradiation of very thin tissue with a sub-micron laser spot, previously covered with an optimal matrix solution that allows the desorption and provides a suitable environment for the ionization of the molecules [START_REF] Dong | Sample Preparation for Mass Spectrometry Imaging of Plant Tissues: A Review[END_REF].

At thousands of different spatial locations, MALDI-MSI records each sampled position (pixel), mass spectrum, and intensity of each feature (mass-to-charge ratio), which represents the abundance of local analytes (metabolites, lipids, peptides, and proteins). MALDI-MSI provides multivariate two-spatial dimensional bioimages containing mass signals per pixel at the end of data collection. Although widely used in proteomics, MALDI-MSI for screenings of plant micromolecules is not very common, especially in the field of biotic interactions. Some works have shown that MSI is useful in the study of symbiosis [START_REF] Ye | MALDI mass spectrometry-assisted molecular imaging of metabolites during nitrogen fixation in the Medicago truncatula -Sinorhizobium meliloti symbiosis[END_REF], endophytism [START_REF] Kusari | Endophytes Are Hidden Producers of Maytansine in Putterlickia Roots[END_REF][START_REF] Wang | Hexacyclopeptides secreted by an endophytic fungus Fusarium solani N06 act as crosstalk molecules in Narcissus tazetta[END_REF], herbivory [START_REF] Shroff | Quantification of plant surface metabolites by matrix-assisted laser desorption-ionization mass spectrometry imaging: glucosinolates on Arabidopsis thaliana leaves[END_REF]Shroff et al., 2008), and plant-pathogen interactions [START_REF] Klein | Investigation of the chemical interface in the soybean-aphid and rice-bacteria interactions using maldi-mass spectrometry imaging[END_REF][START_REF] Santos | Phytochemistry Quantification and localization of hesperidin and rutin in Citrus sinensis grafted on C. limonia after Xylella fastidiosa infection by HPLC-UV and MALDI imaging mass spectrometry[END_REF][START_REF] Seneviratne | Non-host disease resistance response in pea (Pisum sativum) pods: Biochemical function of DRR206 and phytoalexin pathway localization[END_REF][START_REF] Barbosa | Imaging Mass Spectrometry of Endogenous Polypeptides and Secondary Metabolites from Galls Induced by Root-Knot Nematodes in Tomato Roots[END_REF][START_REF] Bhandari | Histology-guided high-resolution AP-SMALDI mass spectrometry imaging of wheat-Fusarium graminearum interaction at the root-shoot junction[END_REF][START_REF] St | MALDI-MSI method for the detection of large biomolecules in plant leaf tissue[END_REF].

Since little is known about plant cellular responses and partial resistance mechanisms at the stem stage of infection, we focused the present work on this stem stage, using the phytopathological test developed by [START_REF] Levrel | Differential growth of Leptosphaeria maculans in the stem of susceptible and partially resistant oilseed rape (Brassica napus L.) genotypes[END_REF]. In the first approach, we followed the regulation of GLSs in infected stems, using the UPLC-UV-TQD method described in chapter 2 (Missinou et al., 2022). Then, we developed a spatial metabolomics approach to investigate the hypothesis that the tissular spatialization of

Materials and Method

Plant growth

Two accessions of B. napus ssp. oleifera (winter oilseed rape (WOSR)), the partially resistant 'Darmor' and the moderately susceptible 'Bristol' were cultivated as described in Missinou et al., 2022 and analyzed in three biological replicates, each with eight plants per accession. Seeds were germinated in a climate-controlled greenhouse in pots using a mixture of soil and sand (ratio 2:1). Plants were grown in a growth chamber under a daily cycle of 16h/8h in light/dark at 20°C and 18°C, respectively. They were fertilized twice with a half-dosed Hoagland solution.

Inoculum preparation and petiole inoculations

Inoculum consisted of a suspension at 10 7 conidia per mL. Spore concentrations were standardized to 10 7 spores per mL after counting aliquots with a Malassez cell under a magnifying lens, aliquoted, and stored at -20°C until the plant inoculation experiment.

To reduce a long asymptomatic period, plantlets at the 3-leaves stage were inoculated with 10µL of the spore suspension at 10 7 spores/mL of JN2 isolate of L. maculans on Ph D. manuscript | Anani Amegan MISSINOU P a g e 192 cut petioles [START_REF] Ermel | Caractériser l'agressivité des souches de Leptosphaeria maculans par un test sur pétiole en conditions contrôlées[END_REF]. Plants treated with distilled water instead of spore suspension were used as controls. Both groups of plants (control and inoculated) were maintained under controlled conditions and covered with opaque plastic to create a 100% relative humidity atmosphere for 48 h, in the dark for the first 24 h. In the absence of light, increased humidity is favorable to spore germination.

Metabolomic analysis 2.4.1. Targeted metabolomic profiling

All steps of targeted metabolomic profiling, including extraction, chromatographic conditions (gradient, column, parameters), and quantification, were performed as previously described (Missinou et al., 2022).

Untargeted metabolomic profiling procedures: Sampling, GLSs extraction, and quantification

Fourteen days after inoculation, stems were sampled by a cross-section 1-5 mm around the necrotic area, wrapped in aluminum foil, and immediately immersed in liquid nitrogen. The samples were stored at -80 °C until they were lyophilized to dryness. The dried tissues were disintegrated by shaking for 60 s with a frequency of 30 Hz using the TissueLyser with grinding jars (10 ml) and stainless-steel grinding balls (Qiagen, Hilden, Germany). GLSs were quantified using the chromatographic procedures detailed in Missinou et al. 2022

Preparation of stem cross-sections

At fourteen days post-incubation (14 dpi), the infected stems (including the necrotic cavity and the proximal area) were sampled and directly embedded in a carboxymethylcellulose (homogenized CMC solution at 2.5% prepared at 60°C) using Peel-A-Way embedding molds under dry ice. To preserve tissue shape and protect biological components from degradation, these procedures were executed in 30-60 seconds. The samples were kept at -80 °C until sectioning. The frozen tissue block was removed and was cross-sectioned in a cryostat microtome (Leica Microsystems GmbH, Wetzlar, Germany) with the microtome chamber chilled at -22°C and the specimen holder at -12°C. Cross-sections 20-μm thick were thaw mounted onto ITOcoated microscopic slides (Bruker Daltonik GmbH) adapted for MALDI mass spectrometry. Samples were sprayed before mass spectrometry analysis with a matrix of DHB or 9AA for the mass-spectrometry analyses with positive and negative modes, respectively, dissolved at 50 mg/mL in 5:5 (v/v) MeOH/1% TFA in water.

High-resolution MALDI FT-ICR mass spectrometry imaging measurement

The analytes of the stems diffuse onto the matrix droplets, and MALDI mass spectrometry technology analyzes them every 50 µm, ionizes them, and measures the mass-to-charge ratio (m/z), generating one spectrum per spot, optical images of the stem, and a feature distribution map. MALDI-MSI was performed using Solarix XR™ 7

Tesla FT-ICR (Bruker Daltonics, Bremen, Germany) mass spectrometer. The spatial resolution was set to 50 µm, and laser shots per spectrum were used. The mass spectra were acquired in the positive ion mode with an m/z range of 100 up to 1400. The ions images were visualized using SCiLS Lab software 2016 (v4.01.8781, SCiLS Lab GmbH, Bremen, Germany), containing some customizable algorithms in the analysis pipeline. Unsupervised multivariate analysis was performed to generate a spectral similarity map. The clusters of similar spectra were coded by the same color using the bisecting K-means method, spectra differences were measured by correlation distance, and cluster centers were randomly initialized. Probabilistic Latent Semantic Analysis (pLSA) was used to assign tissular components to mass spectra [START_REF] Hofmann | Probabilistic latent semantic indexing[END_REF][START_REF] Hanselmann | Concise representation of mass spectrometry images by probabilistic latent semantic analysis[END_REF]. Discriminative m/z values in different regions were obtained by ROC (receiver operating characteristics) analysis.

It is a supervised univariate that identifies features (m/z values) that most strongly differentiate two predefined groups by the measure of the area under the curve (AUC) of 0.75 36 . All data processing was performed using weak denoising, root means square normalization methods, three ppm as minimal interval width, and maximal value on interval was chosen as interval processing mode.

Results and Discussion

Regulation of GLS content in oilseed rape stems infected by L. maculans

The analysis of necrosis symptoms revealed a greater progression of centripetal necrosis in the susceptible accession 'Bristol' compared to partially resistant accession 36 An AUC of 0.75 represents a probability (75% chance) that the model correctly separates them into two different classes.

Ph D. manuscript | Anani Amegan MISSINOU P a g e 195 'Darmor' (as illustrated in Figure 1A). A detailed analysis of the partial resistance of 'Darmor' and the near isogenic dwarf line 'Darmor-bzh' is reported in [START_REF] Levrel | Differential growth of Leptosphaeria maculans in the stem of susceptible and partially resistant oilseed rape (Brassica napus L.) genotypes[END_REF], revealing that the level of partial resistance was similar in 'Darmor' and its dwarf nearisogenic line 'Darmor-bzh' (harboring short stems). This suggested that the observed phenotypic contrasts between 'Bristol' and 'Darmor', recorded by the length of necrosis, depend on intrinsic defense factors and not on plant developmental aspects.

Next, to examine plant metabolite patterns regulated by L. maculans, metabolites were extracted from the inoculated and non-inoculated stems of three accessions at 14-and 28-days post-inoculation (three or two biological replicates, each replicate was made from pooled samples from 6 individual plants). Based on the analytic procedure described in Missinou et al., 2022, thirty-six metabolites, including thirteen Met-derived aliphatic-GLSs, five Trp-derived indolic-GLSs, five aromatic-GLSs, and thirteen branched and linear alkyl-GLSs, were quantitatively profiled using liquid chromatography-mass spectrometry (UPLC).

The most remarkable metabolic consequence of fungal infection was a large increase of the concentration of Trp-derived indolic-GLSs, at the two kinetic times, in both partially resistant genotypes 'Darmor' and 'Darmor-bzh' and the susceptible genotype 'Bristol' (Figure 1B). Additional regulations of individual GLSs were also observed, notably an induction of G32 (hexyl-GLS, isomer 1), a branched alkyl-GLS. This induction was weak, with only few nmol.g -1 DW in infected stems, but this response was sharply contrasted compared to the undetectable concentrations in non-inoculated stems. G32=hexyl-GLS (one of the branched alkyl-GLSs) was not detected in the stems of non-inoculated plants. Robin et al., (2017) previously reported an increase in aliphatic glucosinolates and indolic glucosinolates 15 days after L. maculans infection correlated with the simultaneous changes in levels of expression of GLS biosynthetic genes in the leaves of resistant and susceptible lines of cabbage. Similar regulations have been proposed to be associated with the response to white mold induced by Sclerotinia sclerotiorum fungus with a simultaneous increase in the levels of glucoiberverin (aliphatic-GLS) and glucobrassicin (indolic-GLS) [START_REF] Abuyusuf | Altered glucosinolate profiles and expression of glucosinolate biosynthesis genes in ringspot-resistant and susceptible cabbage lines[END_REF]. In the present work, however, the observed fungal-triggered induction of indolic-GLS content in stems was observed at similar magnitudes in susceptible and partially resistant accessions. Thus, if those responses might play a role in the general defense against the fungus, they do not seem to explain the partial resistance.

The induction of indolic-GLS is consistent with transcriptomic data that were investigated in a previous project (Leptolife, coordinated by Thierry Rouxel, BIOGER, INRAE-AgroParisTech), using the same series of biological samples. These data are not presented here but this work highlighted the induction of genes involved in Trpderived indolic-GLSs as one of the key elements of the plant responses to the fungal infection in stems.

The transcriptomic work conducted in the project LEPTOLIFE also highlighted the induction of genes identified by (Klein and Sattely, 2017), as involved in the biosynthesis of a series of indolic phytoalexins derived from indolic-GLSs. Thus, it can be hypothesized that the induction of indolic-GLSs observed in our chromatographic analyses might serve in furnishing the metabolic precursors for the biosynthesis of multiple phytoalexins involved in the defense response. To further explore this hypothesis, a complementary untargeted LC-HRMS approach was started during my Ph.D. to elucidate the impact of fungal infection on a large spectrum of indolic-derived specialized compounds, including those reported by Pedras (Pedras et Yaya, 2010) and additional putative other sulfur-containing phytoalexins (Figure 2). However, due to a long series of technical misadventures, a high-quality metabolomic raw dataset from this work has been acquired only recently. A detailed analysis of this dataset Ph D. manuscript | Anani Amegan MISSINOU P a g e 198 cannot be presented here. Soon, the combination of these untargeted metabolomic and transcriptomic datasets will enable the analysis of metabolite/gene co-regulations, thus offering interesting opportunities for the investigation of the still unknown metabolic pathways involved in the biosynthesis of phytoalexins and branched and linear alkyl-GLSs in Brassica. The spatial metabolomic approach was performed on inoculated and non-inoculated stem samples at 14 dpi. The MALDI-FT-ICR-MSI analysis of stem cross-sections at the spatial resolution of 50 µM led to the acquisition of more than 20.000 mass-spectra Ph D. manuscript | Anani Amegan MISSINOU P a g e 199 per sample with the positive mode with the DHB matrix (23.448,22.421,'Darmor' control,'Bristol' inoculated and Bristol control,respectively). Benefiting from the strong resolving power (140.000) of the FT-ICR-MSI, each mass spectrum from this dataset contained a huge amount of mass signals. A series of supervised and unsupervised statistical analyses of this MALDI-FT-ICR MSI dataset were performed using the SCiLS (Figure 3).

First, the spatial segmentation (unsupervised multivariate analysis) generated a spectral similarity map (Figure 3. A), allowing the comparison of the global metabolic responses to phoma in susceptible and resistant genotypes. This highlighted that 1/ metabolic spectra from non-inoculated stems were strongly different from those of inoculated samples, for both plant genotypes, and 2/ different metabolic responses were observed depending on spatial sub-zones in the infected stems.

Then, a pLSA analysis of the dataset allowed us to distinguish 5 groups (components 1 to 5) of metabolomic features, each of those five components being associated with different patterns of regulations (Figure 3. B). First, components 1 and 2 both regroup metabolomic features that were induced by the infection. Then, components 3 and 4 gather the metabolomic features that were measured in the non-inoculated but depleted by the disease. Finally, metabolomic features that are constitutively accumulated in stem tissues, and displaying weak regulations by the infection, are represented by component 5.

Finally, an analysis of the Receiver Operating Characteristic (ROC) identified 384 metabolomic features (m/z) that most strongly differentiated the infected group and the control group. 197 m/z were found at higher levels in the infected samples compared to the controls. 187 m/z were found at lower levels in the infected samples compared to the control group. These selected metabolomic features were then analyzed by the METASPACE plate-form [START_REF] Palmer | FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry[END_REF] dedicated to the automated annotation of imaging mass-spectrometry data, using a false discovery rate (FDR) below 10%. This analysis was based on the SWISSLIPID, LIPIDMAP, ChEBI public databases, and on our in-house Brassica-focused chemical database, generated from the scientific literature. Based on the excellent mass resolution (error close to 3 ppm, or 0.001 m/z), and taking account of possible adducts, this approach allowed the putative annotation for 18 m/z among the 197 chemical features induced by the infection (with multiple possible stereoisomers for each) and 18 m/z were putatively annotated from the 187 m/z features that were depleted by the infection. In the example given in Figure 2. C, the metabolomic feature m/z 471.089, which was induced by the fungus, can be proposed as a sodium adduct of Kaempferol hexose. The metabolic response was common to the two genotypes (R: resistant, S: susceptible) 14 days after infection with the JN2 strain of L. maculans. The arrows represent the point of infection/inoculation. Spatial segmentation reveals areas of interest in the stem that respond to infection. pLSA reveals a pattern of metabolic responses to infection and depletion of metabolites) clearly distinguishable from constitutive metabolism. (C) Analysis of the ROC curve identified the metabolic features (m/z) that differentiated the infected group from the control using an AUC (area under the curve) threshold of 0.75.

Genotype-specific metabolic responses to L. maculans

To determine the differences between metabolic responses of susceptible and resistant genotypes to L. maculans infection, ROC analyses of the metabolic features induced or depleted by the infection were performed separately for 'Darmor' and 'Bristol'. The four feature lists obtained were compared to each other. Most of the depleted chemical traits were common to 'Darmor' and 'Bristol'. Many induced metabolic features were also common to the two genotypes (31 accumulated features in 'Bristol' are included in the 224 accumulated features in 'Darmor'). However, some accumulated metabolic features were specific to each genotype (Figure 4).

Conclusion and perspectives

MALDI-MSI technology has given us access to hundreds of biomolecules, allowing us to better understand the metabolic responses to blackleg disease. We offer a view of the commonalities and differences in metabolic responses of the genotypes.

At the beginning of this project, many methodological aspects had to be solved, including the preparation of samples and post-analytic data treatment. For this reason, the initial project included only one biological replicate. Based on the results described Ph D. manuscript | Anani Amegan MISSINOU P a g e 204 above, we decided to engage the whole experiment with three biological replicates.

The resulting samples have been recently analyzed in both positive and negative modes. The analysis of this new dataset is still in progress, but a few aspects of the results can be given here:

First, the use of the negative mode allowed to locate of a series of glucosinolates, namely gluconapin, glucobrassicanapin, (epi)progoitrin, gluconasturtiin, glucoalyssin (aliphatic GLS derived from methionine), glucobrassicin (indolic GLS derived from tryptophan) (Figure 5). Interestingly, the spatial metabolomics approach highlighted that these GLSs were mostly accumulated in the vascular parts of the stem (Figure 6).

Finally, contrasting with our previous metabolomic works for which every independent biological replicate was made from pooled samples from 6 to 8 individual plants, in the present work our biological replicates consist of three unique individual plants. Then, we will have to cope with inevitable biological variations between these three samples, and then it will soon be necessary to work on the definition of adequate statistical analyses to cope with this possible problem.

Brassica napus, une "corne d'abondance" de métabolites spécialisés anciens et nouveaux

Mi-2021, la littérature sur les GLSs répertoriait 139 glucosinolates chez les Brassicales (dont 90 structures caractérisées de façon concluantes et 49 structures partiellement caractérisées) [START_REF] Blažević | Glucosinolate structural diversity, identification, chemical synthesis and metabolism in plants[END_REF][START_REF] Montaut | Investigation of the glucosinolates in Hesperis matronalis L. and Hesperis laciniata All.: Unveiling 4′-O-β-D-apiofuranosylglucomatronalin[END_REF][START_REF] Trabelcy | Investigation of glucosinolates in the desert plant Ochradenus baccatus (Brassicales: Resedaceae). Unveiling glucoochradenin, a new arabinosylated glucosinolate[END_REF]. Rares sont les études qui rapportent plus de 20 GLSs chez une même espèce. Chez B.

napus, pendant longtemps, les études se sont concentrées sur les GLSs contenus dans les graines qui sont en majorité des aliphatiques dérivés de la méthionine.

Cependant, l'article 1 du chapitre 2 de ce document révèle 36 GLSs dont certains ont été rarement rapportés chez B. napus (Missinou et al., 2022). Ceux-ci représentent environ le quart de l'ensemble des GLSs répertoriés dans les synthèses bibliographiques les plus récentes [START_REF] Blažević | Glucosinolate structural diversity, identification, chemical synthesis and metabolism in plants[END_REF][START_REF] Montaut | Investigation of the glucosinolates in Hesperis matronalis L. and Hesperis laciniata All.: Unveiling 4′-O-β-D-apiofuranosylglucomatronalin[END_REF][START_REF] Trabelcy | Investigation of glucosinolates in the desert plant Ochradenus baccatus (Brassicales: Resedaceae). Unveiling glucoochradenin, a new arabinosylated glucosinolate[END_REF]. Certaines des structures GLSs que nous avons observées chez le colza GLSs) de structures inconnues (Missinou et al., 2022).

IV.A.1. Les GLSs de Brassica issues de voies de biosynthèses anciennes

D'un point de vue évolutif, les voies les plus anciennes de biosynthèse des GLS correspondent à celles mises en place chez les espèces basales dans la phylogénie des Brassicales. Il s'agit des familles telles que les Akaniaceae, Tropaelaceae, Moringaceae, Caricaceae, Setchellanthaceae, et Limnanthaceae [START_REF] Edger | Brassicales phylogeny inferred from 72 plastid genes: A reanalysis of the phylogenetic localization of two paleopolyploid events and origin of novel chemical defenses[END_REF].

Par exemple, les formes branchées de GLS, telles que la 1-methyethyl-GLS (glucopurtanjivine), la 2-methylpropyl-GLS (glucoconringianine) et la 1-methylpropyl-

IV.A.2. Les GLSs issues des voies de biosynthèses plus récentes

La diversité des GLSs décrite dans notre travail contient un certain nombre de GLSs (Taveira et al., 2009), un isomère de dihydroxyphenylalkyl-GLS potentiellement équivalent à l'un des deux isomères signalés chez Barbarea vulgaris (Agerbirk et al., 2015), et un dérivé dihydroxylés de l'indol-3-ylméthyl-GLS (dihydroxyglucobrassicine), qui cependant n'a jamais été reporté dans aucune espèce (Missinou, communication personnelle des données non publiés). En outre, nous détectons à un très faible niveau, des masses équivalentes à des dérivés dihydroxybenzyl-GLS, le cinnamoyl-eptyl-GLS et le sinapoylhydroxyglucobrassicine déjà signalés chez le chou [START_REF] Capriotti | Chromatographic column evaluation for the untargeted profiling of glucosinolates in cauliflower by means of ultra-high performance liquid chromatography coupled to high resolution mass spectrometry[END_REF], dans les racines et feuilles de notre panel. Avec l'avènement des méthodes de traitement des données métabolomiques non ciblées, il est possible d'extraire, pour un grand nombre de molécules, les premiers jalons à l'annotation. Il existe plusieurs outils dont les plus célèbres sont XCMS [START_REF] Mo | XCMS2: Processing Tandem Mass Spectrometry Data for Metabolite Identification and Structural Characterization[END_REF], MS-DIAL [START_REF] Tsugawa | MS-DIAL 4: accelerating lipidomics using an MS/MS, CCS, and retention time atlas[END_REF], mzMine2 [START_REF] Pluskal | MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data[END_REF]. A l'heure actuelle, ces outils contiennent des étapes de traitement des données pour les réseaux moléculaires basés sur les fonctionnalités (FBMN) [START_REF] Nothias | Feature-Based Molecular Networking in the GNPS Analysis Environment[END_REF] et des réseaux d'identité ionique (IIN). IIN analyse les corrélations de formes de pic LC-MS et corrèle différents ions, y compris les isopotologues, les adduits, les multimères et la fragmentation dans la source [START_REF] Schmid | Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment[END_REF] et fournissent des sorties à GNPS (Products Social Molecular Networking : http://gnps.ucsd.edu) [START_REF] Wang | Sharing and community curation of mass spectrometry data with GNPS[END_REF]. Le serveur GNPS permet de réaliser la déréplication des variables (correspondances

IV.B.4. Validation fonctionnelle des gènes candidats

Le développement du système CRISPR-Cas9 pour l'édition du génome dans les cellules de plantes, a révolutionné le domaine de la recherche en génomique fonctionnelle, permettant une validation relativement rapide des gènes candidats suspects de rôle dans la biosynthèse de métabolites spécialisées [START_REF] Qian | Novel rice mutants overexpressing the brassinosteroid catabolic gene CYP734A4[END_REF][START_REF] Fan | Evolution of a plant gene cluster in solanaceae and emergence of metabolic diversity[END_REF]. Il serait aussi intéressant de réaliser des mutations par

IV.B.5. Investiguer les clusters de gènes biosynthétiques (BGCs) et leur évolution chez les Brassicas

La découverte de métabolites spécialisées connait une révolution avec l'avènement dédiés aux outils informatiques permettant de prédire les BGCs de façon automatique dans des ressources génomiques de plantes. Il existe plusieurs outils bioinformatiques, dont PhytoClust [START_REF] Töpfer | The PhytoClust tool for metabolic gene clusters discovery in plant genomes[END_REF], PlantClusterFinder [START_REF] Schläpfer | Genome-Wide Prediction of Metabolic Enzymes, Pathways, and Gene Clusters in Plants[END_REF]. Lors de ma thèse, j'ai exploré cette piste dans le but de déterminé les BGCs de B. napus. Nous avons prédit 104 BGCs dans le génome de B. napus (v10) à l'aide de l'outil plantiSMASH [START_REF] Kautsar | PlantiSMASH: Automated identification, annotation and expression analysis of plant biosynthetic gene clusters[END_REF][START_REF] Kautsar | Genomic Identification and Analysis of Specialized Metabolite Biosynthetic Gene Clusters in Plants Using PlantiSMASH[END_REF]. L'architecture génétique ainsi mise en évidence suggère un controle indépendant des souscatégories de GLSs, PHLs et des nouveaux composés racinaires. Ces travaux fournissent une ressource utile pour l'écologie chimique et la sélection des Brassicas. En utilisant la même méthode de profilage ciblé, nous avons montré une induction des GLSs indoliques 14 jours après inoculation de la tige de B. napus par L. maculans. L'imagerie par spectrométrie de masse de la section transversale de tige de colza infectée a permis de révéler une spatialisation des réponses métaboliques suite à l'infection par L. maculans. Title: Specialized metabolism in Brassica napus: Characterization of phytochemical diversity, genetic determinants, and its regulation by a pathogen infection.

Keywords: oilseed rape, specialized metabolites, diversity, mGWAS, pathogen, metabolomic Specialized metabolism plays an essential role in plant-environment interactions. Its characterization in cultivated plants represents a significant scientific challenge. During my thesis, I worked on the characterization of the specialized metabolism and its genetic determinants in Brassica napus (oilseed rape), and I studied its regulation in response to infection by Leptosphaeria maculans (causal agent of phoma). I contributed to developing a targeted metabolic profiling method and identified 36 foliar/root glucosinolates (GLSs), 32 foliar phenolic compounds (PHLs), and 18 previously undocumented root compounds. The quantification of these SMs in 304 Brassica accessions revealed important phytochemical contrasts within the panel. GWA analysis of these phytochemical variations identified 104 loci (QTLs). The genetic architecture thus highlighted an independent control of the subcategories of GLSs, PHLs, and new root compounds. This work provides a useful resource for Brassica chemical ecology and breeding. Using the same targeted profiling method, we showed induction of indole GLSs 14 days after inoculation of the B. napus stems with L. maculans. Mass spectrometric imaging of the cross-section of infected rapeseed stem revealed the spatialization of metabolic responses to L. maculans infection.

1 . 8 IV 1 .

 181 Introduction du chapitre III ............................................................................................................. 1. Introduction ................................................................................................................................ 2. Materials and Method ................................................................................................................ 2.1. Chemicals ............................................................................................................................. 2.2. Plant growth ........................................................................................................................ 2.3. Inoculum preparation and petiole inoculations .................................................................. 2.4. Metabolomic analysis .......................................................................................................... 2.4.1. Targeted metabolomic profiling ................................................................................................. 2.4.2. Untargeted metabolomic profiling procedures : Sampling, GLSs extraction, and quantification .............................................................................................................................................................. 2.4.3. Mass spectrometry imaging (MSI) by MALDI (Matrix-Assisted Laser Desorption-Ionisation) procedures ............................................................................................................................................ 2.4.3.1. Preparation of stem cross-sections ....................................................................................... 2.4.3.2. High-resolution MALDI FT-ICR mass spectrometry imaging measurement .......................... 3. Results and Discussion ................................................................................................................ 3.1. Regulation of GLS content in oilseed rape stems infected by L. maculans ......................... 3.2. Mass spectrometry imaging reveals the spatial distribution of metabolic responses in stems of B. napus after L. maculans infection ...................................................................................... 3.2.1. Metabolic responses to L. maculans infection in the two genotypes of B. napus 'Darmor' and 'Bristol' .................................................................................................................................................. 3.2.2. Genotype-specific metabolic responses to L. maculans ............................................................. 4. Conclusion and perspectives ....................................................................................................... References ...................................................................................................................................... Les GLSs de Brassica issues de voies de biosynthèses anciennes .................................... IV.A.2. Les GLSs issues des voies de biosynthèses plus récentes ................................................. IV.A.3. Redondance structurelle dans la biodiversité GLSs ......................................................... Ph D. manuscript | Anani Amegan MISSINOU P a g e Étendre l'inventaire des métabolites spécialisés chez B. napus ..................................... 214 IV.B.2. Profilage métabolomique non ciblé de B. napus et annotation des métabolites à l'aide de réseaux moléculaires .................................................................................................................. 216 IV.B.3. Affiner la puissance de détection de gènes candidats .................................................... 217 IV.B.4. Validation fonctionnelle des gènes candidats ................................................................. 218 IV.B.5. Investiguer les clusters de gènes biosynthétiques (BGCs) et leur évolution chez les Brassicas ...................................................................................................................................

Figure 1 :

 1 Figure 1: Similarities between the chemical structures of phytohormones and primary and specialized metabolites.

Figure 2 :

 2 Figure 2: Proposed model for the role of Pipecolic acid (Pip (02)) during activation of local resistance, systemic acquired resistance, and defense priming in Arabidopsis thaliana.

Figure 3 :

 3 Figure 3: A New paradigm of the functional versatility/polyvalence of the plant metabolites.

Figure 4 :

 4 Figure 4: Core structural diversity of specialized metabolites derived from the central metabolism in the plant kingdom.

Figure 5 :

 5 Figure 5: Simplified biosynthesis route showing the unexhaustive origin of most plantspecialized metabolites from (a) Calvin cycle and (b) glycolysis.

Figure 6 :Figure 7 :

 67 Figure 6: Diverse routes of metabolite precursors in the conceptual metabolic grid schema Figure 7: Potential fates of duplicated genes.

Figure 8 :Figure 9 :

 89 Figure 8: Independently evolved O-methylation of benzoxazinoids and glucosinolates regulates defense and resistanceFigure 9: Substrate and donor promiscuity of Sb3GT1 from Scutellaria baicalensis.

Figure 10 :Figure 11 :

 1011 Figure 10: Origin and expression of specialized metabolites during green plant phylogeny lineage evolution Figure 11: Conserved structures and domains of transcription factors regulate plant stress responses through mediating specialized metabolism.

Figure 12 :

 12 Figure 12: Overexpression of the MYB transcription factor gene PAP1 leads to enhanced phenylpropanoid production in Arabidopsis thaliana (left) and Nicotiana tabacum cv xanthi (right).

Figure 13 :Figure 14 :

 1314 Figure 13: Prediction of ontogenetic trajectories of some plant defenses Figure 14: Qualitative resistances and cellular actors underlying the characterized R genes.

Figure 15 :Figure 16 :

 1516 Figure 15: Quantitative resistances and cellular actors underlying the characterized resistance QTLs Figure 16: Localization of antifungal compounds in plants. (A) UV light autofluorescence of the saponin avenacin A1.

Figure 18 :

 18 Figure 18: Genomic origin of oilseed rape

Figure 19 :

 19 Figure 19: A) Global distribution of oilseed rape production measured in tons in 2017 and B) Evolution of rapeseed production measured in tons from 1961 to 2017.

Figure 20 :

 20 Figure 20: Presence of important diseases on oilseed rape worldwide (A) and in Europe (B).

Figure 21 :

 21 Figure 21: The pathogenic life cycle of Leptosphaeria maculans in winter oilseed rape in Europe.

Figure 22 :

 22 Figure 22: Genetic resistance associated with the pathogenic life cycle of Leptosphaeria maculans.

Figure 23 :

 23 Figure 23: Representation of the main biosynthetic pathways of methionine-derived glucosinolates in Brassica species and Arabidopsis.

Figure 24 :

 24 Figure 24: Biosynthesis pathways of auxins, phytoanticipins, and tryptophan-derived phytoalexins characterized (at least in part) in Arabidopsis and some Brassica species.

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 16 SM in plants, including metabolic pathways and specific examples of enzymes that govern the structural diversity of metabolites universally distributed in land plants or restricted to some taxa (section I.A.2). Factors shaping the SM of plants are discussed in section I.A.3 before presenting some approaches used to investigate the specialized metabolism (section I.A.4). Next, will be demonstrated how SM contribute to plants' immune systems in response to bioaggressors (section I.A.5). The biochemical and genetic basis of specialized metabolites in Brassica napus are finally presented in section I.A.6.

Figure 1 :

 1 Figure1: Similarities between the chemical structures of phytohormones and primary and specialized metabolites. L-proline (01), pipecolic acid (02), heteroauxin (IAA: indole-3-acetic acid) (03), ent-kaurenoic acid (04), abietic acid (05), and gibberellin A12 (06). Proline (01) and kaurenoic acid (04) are admitted as primary metabolites, while they are structural neighbors of the specialized metabolites: pipecolic acid (02) and abietic acid (05). Gibberellins A12 (06) and heterauxin (03) are phytohormones (adapted from[START_REF] Croteau | Natural Products (Secondary Metabolites)[END_REF].

Figure 2 :

 2 Figure 2: Proposed model for the role of Pipecolic acid (Pip (02)) during activation of local resistance, systemic acquired resistance, and defense priming in Arabidopsis thaliana. 1°, pathogen-inoculated leaf; 2°, distal leaf. Leaf infection by P. syringae induces Pip production through lysine catabolism. (1) Pip activates the amplification and defense priming and effectively synthesizes the phytoalexin camalexin. (2) Pip activates the feedback amplification cycle facilitating the SAR response in the distal leaves, involving the increased Pip biosynthesis, defense hormones salicylic acid (S.A.), and overexpression of defense enzymes (PAD4, ISC1, and ALD1). PAD4: phytoalexins-deficient4, ISC1: isochorismate synthase1, ALD1: AGD2-like defense response protein[START_REF] Návarová | Pipecolic acid, an endogenous mediator of defense Ph D. manuscript | Anani Amegan MISSINOU P a g e 230 amplification and priming, is a critical regulator of inducible plant immunity[END_REF].

Figure 3 : 21 I

 321 Figure 3: A New paradigm of the functional versatility/polyvalence of the plant metabolites. The overlapping zones illustrate the inter-regulation of phytohormone, primary, and specialized metabolites. (Erb and Kliebenstein, 2020).

Figure 4 :

 4 Figure 4: Core structural diversity of specialized metabolites derived from the central metabolism in the plant kingdom. Photosynthesis (center), central metabolism (2nd circumscribed layer), tailored enzymes-catalyzed modifications (3rd circumscribed layer), specialized metabolites (4th circumscribed layer). Structure of terpenoids: 5,9-epi-penstemoside (07), 2-ketoepimanool (08), capsidiol (09), lubimin (10), oryzalide A (11), artemisinin (12), kauralexin B2 (13), β-caryophyllene (14); phenolic acids: gallic acid (15), sinapoyl-O-glucose (16); stilbenoids: trans-resveratrol; coumarins: (17), scopolin (18), isopimpinellin (19); flavonoids: 3-deoxyanthocyanidin (20), kaempferol-3-O-glucose (21); lignans: pinoresinol-glucose (22), lariciresinol (23); tannins: gallotanin (24); alkaloids: nicotine (25), camalexin (26), spirobrassinin (27), 6-GlcO-ICOOGlc (28), caffeine (29), lumazine (30), gramine (31), anagyrine (32), benzoxazinoids: BOA-glucose (33), DIBOA-glucose (34), DIMBOA-glucose (35), HDMBOA-glucose (36), HMBOA-glucose (37), cyanogenic glycosides: lotaustralin (38), linamarin (39), amydalin (40), dhurrin (41), glucosinolates: neoglucobrassicin (42), (epi)glucobarbarin (43), (epi)progoitrin (44) are displayed. Adapted from[START_REF] Hartmann | From waste products to ecochemicals: Fifty years research of plant secondary metabolism[END_REF][START_REF] Wang | The Structure and Function of Major Plant Metabolite Modifications[END_REF].

  D. manuscript | Anani Amegan MISSINOU P a g e 26 (B) hydroxamic acids glycoside, for example, 2,4-dihydroxy-1,4-benzoxazin-3-one (DIBOA-glucose, 34) and 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOAglucose, 35); and (C) lactams glycosides, for example, 2-hydroxy-7-methoxy-1,4-

  enzymes. Geranyl diphosphate synthase (GPPS), geranylgeranyl diphosphate synthase (GGPPS), farnesyl pyrophosphate synthase (FPPS), and chalcone synthase (CHS) are essentially ubiquitous enzymes in higher plants. The active forms of GGPPS, FPPS PAL/TAL, and CHS are the first committed enzyme in phenylpropanoids and flavonoid biosynthesis (Figures 5.A and 5.B). Phenylalanine ammonia-lyase (PAL), tyrosine ammonia-lyase (TAL), and chalcone synthase (CHS) Ph D. manuscript | Anani Amegan MISSINOU P a g e 28

  involved in the subsequent 'decoration' or 'tailoring' of SMs which further contribute to their structural and functional diversification (Anarat-Cappillino and Sattely, 2014) Ph D. manuscript | Anani Amegan MISSINOU P a g e 29

Figure 5 :

 5 Figure 5: Simplified biosynthesis route showing the unexhaustive origin of most plantspecialized metabolites from (A) Calvin cycle and (B) glycolysis. Some specialized metabolites classes are derived from several amino acid precursors, such as glucosinolate subclasses. PEP: phosphoenolpyruvate, Phe: phenylalanine, Tyr: tyrosine, Trp: tryptophan, TDC: tryptophan decarboxylase, PAL: phenylalanine ammonia-lyase, TAL: tyrosine ammonia-lyase, CHS: chalcone synthase, STS: strictosidine synthases, DMAPP: dimethylallyl diphosphate, IPP: isopentenyl diphosphate, GPPS: geranyl diphosphate synthase, GGPPS: geranylgeranyl diphosphate synthase, FPPS: farnesyl pyrophosphate synthase. The mevalonate-independent pathway for isoprenoid biosynthesis is not represented. The figure was adapted from Tissier et al., 2015.

Figure 7 :

 7 Figure 7: Potential fates of duplicated genes. (a) One paralog becomes a non-functional pseudogene by acquiring deleterious mutations, while the other retains the ancestral functions. (b) Both genes acquire deleterious mutations in cis-regulatory and protein-coding modules, thus sub-functionalizing the ancestral gene function. (c) One paralog acquires a novel advantageous mutation (orange) that can lead to evolutionary innovation in plant form, whereas the other paralog retains the ancestral functions[START_REF] Preston | Evo-Devo: Regulatory and Protein-Coding Evolution in Plant Diversification[END_REF].

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 34 enzymes such as CYP82C2 (indolic-CNglc) and CYP79B2/3 (of indolic-GLSs) can be traced back to ancestral plant forms.

Figure 8 :

 8 Figure 8: Independently evolved O-methylation of benzoxazinoids and glucosinolates regulates defense and resistance[START_REF] Li | Convergent evolution of a metabolic switch between aphid and caterpillar resistance in cereals[END_REF].

3 -

 3 O-glycosyltransferase from Scutellaria baicalensis (Sb3GT1) could accept five types of sugars like glucose, galactose, N-acetylglucosamine, rhamnose, xylose, arabinose brought by uridine 5′-diphosphate (UDP)-sugar as donors (Figure 9) (Wang-Zilong et al., 2019).

Figure 9 :

 9 Figure 9: Substrate and donor promiscuity of Sb3GT1 from Scutellaria baicalensis. 1a-1e: type of substrate. Glc: glucose, Gal: galactose, GlcNAs: N-acetylglucosamine, Xyl: xylose, Ara: arabinose (Wang-Zilong et al., 2019).

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 37 pathways co-evolved with environmental variation. Indeed, the taxonomic distribution of major plant-specific metabolic pathways suggests a very early diversification of central biosynthetic blocks since the adaptation of plants to the terrestrial environment (Figure10). The biogeochemical-based models estimate that the land plants (e.g., charophytes) emerged in the middle of the Cambrian and early Ordovician eras (~512-443 million years ago).[START_REF] Weng | The evolutionary paths towards complexity: A metabolic perspective[END_REF] reported that the closest primitive plant form to Charophytes (green algae, Chlamydomonas reinhardtii) already had important enzyme families known to participate in specialized plant metabolism and primary metabolism. These enzymes potentially contributed to redox homeostasis and the emergence of natural antioxidants in the aquatic environment of the early Ordovician age era (~500 million years ago)[START_REF] Weng | The evolutionary paths towards complexity: A metabolic perspective[END_REF].

Figure 10 :

 10 Figure 10: Origin and expression of specialized metabolites during green plant phylogeny lineage evolution[START_REF] Delgoda | Evolutionary Perspectives on the Role of Plant Secondary Metabolites[END_REF].

39 I.A. 4 . 1 .

 3941 , they are stored in vacuoles under glycosylated forms, often in specialized secretory structures such as trichomes, laticifers, ducts, and canals. Two types of factors condition the metabolite content: intrinsic (genetic, ontogenic, and morphogenetic) and environmental or extrinsic factors (temperature, salinity, drought, UV, altitude, injuries, and nutrient deficiencies) Ph D. manuscript | Anani Amegan MISSINOU P a g e Transcription factors (TF)Transcription factors affect the biosynthesis of specialized metabolites by regulating gene expression. For example, MYC2 transcripts are accumulated in leaves of Nicotiana attenuate in response to herbivore attack (Manduca sexta); this TF regulates the expression of nicotine and phenolamides, jasmonates, and some JA-/NaCOI1dependent metabolites (e.g., 17-hydroxy-geranyl-linalool diterpene glycosides)[START_REF] Woldemariam | NaMYC2 transcription factor regulates a subset of plant defense responses in Nicotiana attenuata[END_REF]. Many other studies report the regulation of many biosynthetic pathways such as alkaloids, terpenoids, glucosinolates, and saponins by TFs belonging to AP2/ERF, WRKY, bHLH, bZIP, and NAC FTs families (Figure11) in different plant species such as A. thaliana, Artemisia annua, Vitis vinifera, Salvia sclarea, Withania somnifera, Scutellaria baicalensis, Camellia sinensis, Medicago truncatula, etc.[START_REF] Jan | Plant secondary metabolite biosynthesis and transcriptional regulation in response to biotic and abiotic stress conditions[END_REF].

Figure 11 :

 11 Figure 11: Conserved structures and domains of transcription factors regulate plant stress responses through mediating specialized metabolism. The AP2/ERF TF family (APETALA2 (AP2)/Ethylene Responsive Element Binding Factor (EREB)) has a domain of 60 amino acids involved in DNA binding and structurally contains three β-sheets before the α-helix motif. WRKY TF family transcription factor includes a 60-amino-acid well-conserved in the WRKY domain composed of a conserved WRKYGQK motif (N-terminal) and a zinc-finger motif at the C-terminal. bHLH TF (basic helix-

Figure 12 :

 12 Figure 12: Overexpression of the MYB transcription factor gene PAP1 leads to enhanced phenylpropanoid production in Arabidopsis thaliana (left) and Nicotiana tabacum cv xanthi (right). Flowers on 12-week-old plants control transformants (A and C) and transformants overexpressing Pap1 (D and B)[START_REF] Borevitz | Activation tagging identifies a conserved MYB regulator of phenylpropanoid biosynthesis[END_REF].

Figure 13 :

 13 Figure 13: Prediction of ontogenetic trajectories of some plant defenses (Ochoa-Lopez et al., 2019).

Figure 14 :

 14 Figure 14: Qualitative resistances and cellular actors underlying the characterized R genes. (a) Mendelian ratio phenotypes of total resistance contrast sharply with susceptible plants and (b) monogenic determinism (Corwin and Kliebenstein, 2017), (c) perception of 'non-self' by receptors (NBS-LRR), and rapid initiation of the qualitative resistance response through a network implying a small number of co-regulated genes (Roux et al., 2014), (d) Qualitative resistance is essentially determined by genes of the RLK family, NBS-LRR, and transcription factors, (e) 191 R genes code for NLR or NLR-ID (Integrated Decoy) proteins, involved in the direct recognition or direct influence of intracellular

Figure 15 :

 15 Figure 15: Quantitative resistances and cellular actors underlying the characterized resistance QTLs. (a) continuous distribution of the resistance trait of individuals ranging from partially resistant to partially susceptible (b) polygenic determinism involving several minor QTLs contributing to the final phenotype. The red line indicates the significance threshold chosen for the genetic analysis[START_REF] Corwin | Quantitative resistance: More than just perception of a pathogen[END_REF]. (c) the small effect of 'non-self' perception by receptors and multiplicity initiating quantitative resistance through a network implied many co-regulated genes[START_REF] Roux | Resistance to phytopathogens e tutti quanti: Placing plant quantitative disease resistance on the map[END_REF]. (d) Qualitative resistances are determined by genes coding for enzymes of the metabolism of organic chemical defenses (phytoalexins, antimicrobial peptides/proteins), hormonal signaling, and oxidative stress.

Figure 16 :

 16 Figure 16: Localization of antifungal compounds in plants. (A) UV light autofluorescence of the saponin avenacin A1. This compound is localized in the epidermal cell layer of oat roots. (B) A resistant sorghum line responding to an attack by Colletotrichum graminicola, showing the formation and mobilization of vesicles containing pigmented 3-deoxyanthocyanidin phytoalexins toward the site of attempted penetration by an appressorium (visualized by light microscopy)[START_REF] Morrissey | Fungal Resistance to Plant Antibiotics as a Mechanism of Pathogenesis[END_REF].

Figure 4 ,

 4 Figure 4, Figure16B) of sorghum, lubimin (10) of potato, kauralexin B2 (13) of maize,

Figure 17 :

 17 Figure 17: The "triangle of U" diagram(Nagaharu U, 1935) shows the genetic relationships between six genus species of Brassica. Different colors represent the chromosomes of each of the A, B, and C genomes.

Figure 18 :

 18 Figure 18: Genomic origin of oilseed rape. Different authors provide different estimates of divergence time and WGD/WGT time. WGD: whole-genome duplications (polyploidization), WGT: whole-genome triplication. Mya: millions of years ago (Waminal et al., 2016).

Figure 19 :

 19 Figure 19: A) Global distribution of oilseed rape production measured in tons in 2017 and B) Evolution of rapeseed production measured in tons from 1961 to 2017. The color gradient illustrates the growing regions from the FAO database). (https://ourworldindata.org/grapher/rapeseedproduction).

Figure 20 :

 20 Figure 20: Presence of important diseases on oilseed rape worldwide (A) and in Europe (B). The top 10 diseases worldwide are shown in bold. *In China, only Leptosphaeria biglobosa has been reported (absence of L. maculans) according to Zheng et al., 2020.

Figure 21 :

 21 Figure 21: The pathogenic life cycle of Leptosphaeria maculans in winter oilseed rape in Europe. (1) saprophytism on stem residues (long-term survival); (2) sexual reproduction/construction of primary inoculum; (3 to 4) a short phase of asymptomatic necrotrophy on the leaves of the plants after the establishment of the first infections; (5) a long phase of endophyte (biotroph) with asymptomatic colonization in the tissues of the leaf tissues at the stem and the crown stem (late Autumn to late Winter); (6) second phase of symptomatic necrotrophy, formation of basal stem cankers (severe necrosis) and lodging phenomena.(Rouxel and Balesdent, 2005).

5 ,

 5 Figure 21).

Figure 22 :

 22 Figure 22: Genetic resistance associated with the pathogenic life cycle of Leptosphaeria maculans. (A) qualitative/total and monogenic resistance (B) partial and polygenic quantitative resistance (Adapted from Huang et al., 2014).

Figure 23 :

 23 Figure 23: Representation of the main biosynthetic pathways of methionine-derived glucosinolates in Brassica species and Arabidopsis. Allelic variability on MAM genes contributes to the diversity of side-chain lengths. Allelic variability in the genes encoding the enzymes AOP2, AOP3, GS-OH, and BZO1 contributes to the variety of side-chain chemical decorations. Esterified forms of benzoates (3BOP and 4BOB) have never been described in Brassica, despite copies of BZO1 in the B. napus genome. The C11-aliphatic compounds of Camelina are not shown.[START_REF] Gravot | Génomique fonctionnelle des processus métaboliques impliqués dans les résistances quantitatives[END_REF].

Figure 24 :

 24 Figure 24: Biosynthesis pathways of auxins, phytoanticipins, and tryptophan-derived phytoalexins characterized (at least in part) in Arabidopsis and some Brassica species. (1)The multiplicity of auxin biosynthesis pathways described from tryptophan. A recent consensus attributes a significant role of IAA synthesis to the TAA / YUCCA pathway under non-pathological conditions[START_REF] Won | Conversion of tryptophan to indole-3-acetic acid by TRYPTOPHAN AMINOTRANSFERASES OF ARABIDOPSIS and YUCCAs in Arabidopsis[END_REF][START_REF] Lehmann | Arabidopsis NITRILASE 1 Contributes to the Regulation of Root Growth and Development through Modulation of Auxin Biosynthesis in Seedlings[END_REF]. (2) Synthesis of indolic glucosinolates in all Brassicaceae: I3MG (glucobrassicin) and its methoxylated derivatives (1M-I3MG and 4M-I3MG) can be metabolized by the activity of myrosinases (TGGs) to give I3C (indole-3-carbinol or its methoxylated derivatives 1MI3C and 4MI3C). Based on allelic combinations on several loci, the presence of Epithiospecifier proteins (ESP / ESM1) conditions the metabolism of I3MG to IAN, which can be a source of biosynthesis for auxin (IAA) via the activity of nitrilases (NIT1-3)[START_REF] Pfalz | Methyl Transfer in Glucosinolate Biosynthesis Mediated by Indole Glucosinolate O-Methyltransferase 5[END_REF][START_REF] Lehmann | Arabidopsis NITRILASE 1 Contributes to the Regulation of Root Growth and Development through Modulation of Auxin Biosynthesis in Seedlings[END_REF] [START_REF] Lehmann | Arabidopsis NITRILASE 1 Contributes to the Regulation of Root Growth and Development through Modulation of Auxin Biosynthesis in Seedlings[END_REF]). (3) The synthesis of 3-carboxylic acid Indole (I3CA) and its derivatives from IAN as described by Erich Glawischnig's team[START_REF] Böttcher | The Biosynthetic Pathway of Indole-3-Carbaldehyde and Indole-3-Carboxylic Acid Derivatives in Arabidopsis[END_REF]. (4) In Arabidopsis, the biosynthetic pathway (absent in the Brassica genus) results in the synthesis of what has long been considered the only phytoalexin in Arabidopsis: camalexin[START_REF] Iven | Transcriptional Activation and Production of Tryptophan-Derived Secondary Metabolites in Arabidopsis Roots Contributes to the Defense against the Fungal Vascular Pathogen Verticillium longisporum[END_REF]. (5) In parallel with camalexin, IAN is the precursor of a procession of phytoalexins derived from indole 3carboxynitrile, whose pathway was characterized recently in Arabidopsis, appears to be absent from the Brassica genus[START_REF] Rajniak | A new cyanogenic metabolite in Arabidopsis required for inducible pathogen defence[END_REF]. (6) Also, in Arabidopsis, I3MG and its methoxylated derivative 4M-I3MG can be converted by atypical myrosinase into intact cells of infected plants, leading to the synthesis of raphanusamic acid[START_REF] Bednarek | A Glucosinolate Metabolism Pathway in Living Plant Cells Mediates Broad-Spectrum Antifungal Defense[END_REF][START_REF] Clay | Glucosinolate Metabolites Required for an Arabidopsis Innate Immune Response[END_REF]. (7) Of the nearly 40 indolic phytoalexins described in Brassica, significant steps have recently been characterized(Pedras and Yaya, 2010). Brassinin is synthesized from the I3MG-derived isothiocyanate via the action of atypical BABGa/b myrosinases (Brassinin Associated Beta Glucosidases) and can lead to the synthesis of spirobrassinin and its derivatives spirobrassinin in B. rapa, or 1-methoxybrassenin B in B. oleracea(Klein and Sattely, 2017). (Figure was adapted from Gravot, 2019).

( 7 )

 7 Figure 24: Biosynthesis pathways of auxins, phytoanticipins, and tryptophan-derived phytoalexins characterized (at least in part) in Arabidopsis and some Brassica species. (1)The multiplicity of auxin biosynthesis pathways described from tryptophan. A recent consensus attributes a significant role of IAA synthesis to the TAA / YUCCA pathway under non-pathological conditions[START_REF] Won | Conversion of tryptophan to indole-3-acetic acid by TRYPTOPHAN AMINOTRANSFERASES OF ARABIDOPSIS and YUCCAs in Arabidopsis[END_REF][START_REF] Lehmann | Arabidopsis NITRILASE 1 Contributes to the Regulation of Root Growth and Development through Modulation of Auxin Biosynthesis in Seedlings[END_REF]. (2) Synthesis of indolic glucosinolates in all Brassicaceae: I3MG (glucobrassicin) and its methoxylated derivatives (1M-I3MG and 4M-I3MG) can be metabolized by the activity of myrosinases (TGGs) to give I3C (indole-3-carbinol or its methoxylated derivatives 1MI3C and 4MI3C). Based on allelic combinations on several loci, the presence of Epithiospecifier proteins (ESP / ESM1) conditions the metabolism of I3MG to IAN, which can be a source of biosynthesis for auxin (IAA) via the activity of nitrilases (NIT1-3)[START_REF] Pfalz | Methyl Transfer in Glucosinolate Biosynthesis Mediated by Indole Glucosinolate O-Methyltransferase 5[END_REF][START_REF] Lehmann | Arabidopsis NITRILASE 1 Contributes to the Regulation of Root Growth and Development through Modulation of Auxin Biosynthesis in Seedlings[END_REF] [START_REF] Lehmann | Arabidopsis NITRILASE 1 Contributes to the Regulation of Root Growth and Development through Modulation of Auxin Biosynthesis in Seedlings[END_REF]). (3) The synthesis of 3-carboxylic acid Indole (I3CA) and its derivatives from IAN as described by Erich Glawischnig's team[START_REF] Böttcher | The Biosynthetic Pathway of Indole-3-Carbaldehyde and Indole-3-Carboxylic Acid Derivatives in Arabidopsis[END_REF]. (4) In Arabidopsis, the biosynthetic pathway (absent in the Brassica genus) results in the synthesis of what has long been considered the only phytoalexin in Arabidopsis: camalexin[START_REF] Iven | Transcriptional Activation and Production of Tryptophan-Derived Secondary Metabolites in Arabidopsis Roots Contributes to the Defense against the Fungal Vascular Pathogen Verticillium longisporum[END_REF]. (5) In parallel with camalexin, IAN is the precursor of a procession of phytoalexins derived from indole 3carboxynitrile, whose pathway was characterized recently in Arabidopsis, appears to be absent from the Brassica genus[START_REF] Rajniak | A new cyanogenic metabolite in Arabidopsis required for inducible pathogen defence[END_REF]. (6) Also, in Arabidopsis, I3MG and its methoxylated derivative 4M-I3MG can be converted by atypical myrosinase into intact cells of infected plants, leading to the synthesis of raphanusamic acid[START_REF] Bednarek | A Glucosinolate Metabolism Pathway in Living Plant Cells Mediates Broad-Spectrum Antifungal Defense[END_REF][START_REF] Clay | Glucosinolate Metabolites Required for an Arabidopsis Innate Immune Response[END_REF]. (7) Of the nearly 40 indolic phytoalexins described in Brassica, significant steps have recently been characterized(Pedras and Yaya, 2010). Brassinin is synthesized from the I3MG-derived isothiocyanate via the action of atypical BABGa/b myrosinases (Brassinin Associated Beta Glucosidases) and can lead to the synthesis of spirobrassinin and its derivatives spirobrassinin in B. rapa, or 1-methoxybrassenin B in B. oleracea(Klein and Sattely, 2017). (Figure was adapted from Gravot, 2019).

  at IGEPP (Institute of Genetics, Environment and Plant Protection, UMR INRAE/Institut Agro/Université Rennes 1) in the DEBI team (Diversity, Evolution, and genomics of BIotic interactions). This group, led by Pr. Antoine Gravot and Dr. Mathieu Rousseau-Gueutin, works on the genetics/genomics of biotic interactions in Brassica, including blackleg and clubroot. The objectives of the team are (1) to identify/diversify sources of resistance in the Brassica gene pool, (2) to unravel the genetic/evolutive mechanisms of quantitative resistance, (3) to understand the cellular/molecular processes involved in quantitative resistance in this species, and Ph D. manuscript | Anani Amegan MISSINOU P a g e 69

  relation to the pathogen resistance response. This work was subdivided into two parts: (1) a characterization of the phytochemical diversity in a panel of Brassica, and the genetic control of SMs constitutively biosynthesized in roots and leaves, and (2) a study on the regulation of SMs in response to fungal infection by L. maculans in the stems of B. napus.

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 70 approaches. We have developed a metabolic profiling method to simultaneously identify ninety-two oilseed rape compounds by liquid chromatography coupled in tandem with detection by high-resolution mass spectrometry (HPLC-Orbitrap LTQ-XL).Eighty-six compounds resolved by chromatography were selected and quantified by UPLC-UV-TQD. Of these compounds, 18 UV-absorbing root compounds were detected for the first time herein. The results have been described in depth, resulting in one published article and two manuscripts in preparation.The first, recently published in "Journal of Agricultural and Food Chemistry" (IF 5.279), describes the identification and quantification of 36 glucosinolates and 32 phenolic compounds in a large panel of B. napus and highlights valuable genetic resources for chemical ecology and breeding(Missinou et al., 2022). Furthermore, the second manuscript concerns genome-wide association studies that provide insights into the genetic basis of specialized metabolism and reveal seed glucosinolate content's breeding history in B. napus. Its submission is planned to "Plant Biotechnology Journal"(IF 9.803). Thirdly, we exploited the absorbance variation of 18 UV-absorbing compounds in the genetic investigation of novel root UV-absorbing and used NMR to initiate de novo structural elucidation of the most relevant metabolites. This article is planned to submit to the "Phytochemistry" journal (IF 4.072).The third chapterwas devoted to the characterization of metabolic responses of B. napus to the fungal Leptosphaeria maculans. This chapter investigated previously unknown phytoalexins involved in the defense response of B. napus to L. maculans infection by UPLC-Orbitrap-Q-Exactive and molecular network-based (GNPS) annotation. The fifth manuscript deals with the spatialization of the metabolic response Ph D. manuscript | Anani Amegan MISSINOU P a g e 71 to infection using mass spectrometry imaging approaches. Both submissions are planned in "Journal of Experimental Botany," IF 5.906).

  des phytoanticipines correspond souvent à l'adaptation évolutive des organismes confrontés à des changements environnementaux spécifiques. Du fait de leur emplacement apical 29 dans l'arbre phylogénétique des Brassicales, les espèces du genre Brassica constituent un modèle idoine pour l'identification et la caractérisation des gènes associés aux étapes biosynthétiques menant à de nouvelles structures de défense chimiques propres aux espèces de la famille des Brassicacées (Edger et al., 2018). L'objectif global de ce chapitre est de caractériser la diversité phytochimique du colza et de déterminer les déterminants génétique contrôlant leur teneur afin de contribuer à une meilleure connaissance du métabolisme des phytoanticipines. Nous avons incorporé B. napus et les espèces progénitrices (B. rapa et B. oleracea), y compris divers cultigroupes englobant les accessions WOSR (winter-type oilseed rape), SOSR

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 76 et (v) d'enrichir le catalogue de la diversité phytochimique des composés racinaires absorbant dans les UV et leurs déterminants génétiques. Le chapitre est structuré autour de trois articles complémentaires, un publié et deux en cours de finalisation. Le premier article, publié dans Journal of Agricultural and Food Chemistry (AA Missinou, J Ferreira de Carvalho, N Marnet, T Delhaye, OHamzaoui, D Abdel Sayed, Y Guitton, LLebreton, C Langrume, A Laperche, R Delourme, MJ Manzanares-Dauleux, A Bouchereau, A Gravot. 2022. Identification and Quantification of Glucosinolates and Phenolics in a Large Panel of Brassica napus Highlight Valuable Genetic Resources for Chemical Ecology and Breeding. J. Agric. Food Chem https://doi.org/10.1021/acs.jafc.1c08118), vise à décrire la diversité phytochimique des glucosinolates et des composés phénoliques dans un large éventail d'accessions de Brassica. Pour sa réalisation, j'ai collaboré avec des ingénieur(e)s chimistes, dont Nathalie Marnet de plateforme P2M2 (Corsaire, Biogenouest), Yann Guitton plateforme MELISA 30 (Corsaire, Biogenouest) et Thomas Delhaye de la plateforme de spectrométrie de masse et métabolomique de l'UMR 6164. Nous avons développé une méthode de profilage simultanée des glucosinolates et des composés phénoliques. Un atlas phytochimique de 36 glucosinolates (GLS) foliaires/racinaires et 32 composés phénoliques foliaires a été établi, dont certains sont rarement décrits chez les Brassica. La quantification de ces composés dans un panel de 304 accessions de Brassica a révélé de grandes variations qualitatives et quantitatives, notamment pour la glucocochlearine et les dérivés kaempferol tetra-et penta-hexosides. Deux principaux Ph D. manuscript | Anani Amegan MISSINOU P a g e 77 chémotypes se dégagent en fonction des proportions de sinapoyl-O-hexoside et de kaempferol-O-trihexoside. Eu égard à ces phénotypes variables, nous avons émis le postulat que des polymorphismes génétiques seraient responsables des variations qualitatives et quantitatives observées entre les accessions et cultivars, à l'instar des

Figure 2 .

 2 Figure 2. UPLC-UV chromatogram of a leaf extract (QC). Annotated phenolic compounds are numbered according to the different phenolic subcategories (see in the text, and Tables2, 3, and 4).

  Peaks PL26** and PL27** yielded double-charged parents which were annotated as kaem-O-sin-O-pentahex** and kaem-O-Disin-O-pentahex**.

Figure 3 .

 3 Figure 3. Common aglycone structures of phenolics found in Brassica species: (A) phenylpropanoids (B) and flavonols.

Figure 4 .

 4 Figure 4. Histograms of total glucosinolate concentrations in roots (A) and leaves (B) and phenolics in leaves (C) in the panel of 304 Brassica accessions. The x-axis represents all varieties ordered decreasingly according to total glucosinolates and phenolic compounds concentrations for each species. Each bar represents the mean concentration for one variety, from three independent biological replicates.

Figure 5 .

 5 Figure 5. Multivariate analyses of root glucosinolate profiles of the 304-accession panel of Brassica varieties. (A) Heatmap and clustering of accessions (Y-axis) with the 36 glucosinolates quantified in this work (X-axis). Data were mean-centered for each accession. (B) Total concentration (μmol g -1 DW) of root glucosinolates for each accession. (C) PCA analysis. Data were mean-centered for each compound. Representation of accessions on the score plot and variables on the loading plot as defined by the first three principal components. For visualization clarity, the G14 compound as the most abundant molecule in the root panel was not shown.

Figure 6 .

 6 Figure 6. Multivariate analyses of leaf phenolic profiles among the 304-accession panel of Brassica varieties. (A) Clustering of accessions (Y-axis) according to the concentration of 32 phenolics (X-axis). Data were mean-centered for each accession. (B) Total concentration (μmol g -1 DW) of leaf phenolics in each accession and (C) PCA analysis. Data were mean-centered for each compound. Representation of accessions on the score plot and variables on the loading plot as defined by the first three principal components (AQA, acyl-quinic acids; HAGE, hydroxycinnamic acid hexoside esters; Quer, quercetin; Isor, isorhamnetin).

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 105

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 109

Figure 1 .

 1 Figure 1. GLS content in leaves (A) and roots (B) of B. napus accessions from the different cultigroups. WOSR+ and WOSR 0: high-and low-GLS varieties of Winter Oilseed Rape, respectively. SOSR+ and SOSR 0: high-and low-GLS varieties of Spring Oilseed Rape.

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 111

Figure 2 .

 2 Figure 2. PLS-DA of phytochemical diversity among B. napus cultigroups. PLS-DA highlighted discriminating ions, (A) aliphatic-GLSs between '+' and '0' accessions in leaves, (B) aliphatic-GLSs between '+' and '0' accessions in roots, (C) phenolics between WOSR and SOSR accessions in leaves. The aliphatic Met-derived GLSs discriminate WORS+/SORS+ accessions compared to their counterpart with WORS00/SORS00 in leaves (A) and roots (B), illustrating the selection effect of these compounds

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 113

Figure 3 :

 3 Figure 3: Genetic Networks of QTL controlling GLSs and PHLs in leaves (A) and roots (B). mQTLs and metabolites (nodes) are shown as diamonds and circles, respectively, and links (edges) indicate

Figure 4 .

 4 Figure 4. Leaf concentrations of HAGE in the varieties from the four-oilseed rape cultigroups of B. napus.

Figure 5 .

 5 Figure 5. Mapping of allele frequencies on the genetic networks controlling PHL and GLS in leaves of the four-oilseed rape cultigroups of B. napus. Diamonds represent mQTL, circles represent the metabolites. % of the allele controlling high concentration is indicated on each arrow. Red arrows indicate that % of high-concentration alleles is above 90%. Blue arrows indicate that the % of high-concentration alleles is below 10%.

Figure 6 .

 6 Figure 6. Mapping of allele frequencies on the genetic networks controlling and GLS in roots of the four-oilseed rape cultigroups of B. napus. Diamonds represent mQTL, circles represent the metabolites. % of the allele controlling high concentration is indicated on each arrow. Red arrows indicate that % of high-concentration alleles is above 90%. Blue arrows indicate that the % of highconcentration alleles is below 10%.

Figure 7 .

 7 Figure 7. Root gluconasturtiin content in the four-oilseed rape cultigroups of B. napus

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 121

Figure 8 .

 8 Figure 8. Leaf Kaempferol-feruloyl-tetraHex content in varieties from the four-oilseed rape cultigroups of B. napus

  #,a, , Clément Orione c , Julie Ferreira de Carvalho a , Youcef Haddad a , Nathalie Marnet b , Philippe Jéhan c , Anne Laperche a , Régine Delourme a , Alain Bouchereau a , Maria J. Manzanares-Dauleux a , Antoine Gravot * ,a a Univ Rennes, Institut Agro, INRAE, IGEPP, 35653, Le Rheu, France b INRAE, BIA, 35653, Le Rheu, France c Univ Rennes, CRMPO, 35700 Rennes, France # First author and * corresponding author, Antoine.Gravot@univ-rennes1.frAbstractInfra-specific diversity of plant-specialized metabolic compounds is assumed to play major ecological roles but much remains to be more deeply explored in the root compartment as an interface for biotic and abiotic environments. In this work, we present a detailed quantitative profiling of 18 previously unreported root-specific UVabsorbing compounds among 281 accessions of Brassica napus. The resulting dataset allowed identifying three root chemotypes, and GWAS analysis allowed the identification of QTL involved in the control of 11 of those compounds. After purification, the structural elucidation of three of those compounds was obtained from spectroscopic data, including 1D, and 2D nuclear magnetic resonance, and highresolution mass spectrometry. This analysis revealed one sulfur-containing compound derived from ferulic acid (m/z 493.115 [M-H] -). It also revealed two pteridine-like polynitrogenated aromatic heterocycles conjugated to leucine (m/z 320.099 [M-H] -)

  temperate and subtropical regions in Europe, Canada, South Asia, China, and Australia(FAOSTAT, 2022). Despite its significance, there are still many uncharacterized SM possibly involved in plant production performance and product quality. Although roots play a determinant role in the growth and development of plants, little attention has been paid to root phytochemicals, especially those with aromatic structures. Based on the benzene-type nucleus, aromatic compounds can be divided into three groups: (1) alkyl, aryl-, and alicyclic-nitrogen-sulfur-substituted benzene derivatives, (2) di-and polyphenyl, and (3) polycyclic compounds formed from the fusion of two or more benzene ring systems[START_REF] Baxter | Polycyclic Aromatic Hydrocarbons and Azaaromatic Compounds[END_REF]. These compounds contain extended-electron π-systems and display almost as much light absorption in the UVA (315-400 nm) as in the UVB (280-315 nm) ranges and null absorption of visible radiation (400 to 800 nm). Phenolic and aromatic compounds are poorly described in the roots of Brassicaceae. For instance, coumarins are aromatics lactone-derived from the multi-branched phenylpropanoid pathway. The exudation of Ph D. manuscript | Anani Amegan MISSINOU P a g e 144

  on a series of vacuum solid-phase extraction systems (SPE columns, Chromabond, C18, 45 µm, 70 mL/10000 mg, 60 Å, Macherey-Nagel, Germany)(Krishnan and Ph D. manuscript | Anani Amegan MISSINOU P a g e 150[START_REF] Krishnan | Solid-phase extraction technique for the analysis of biological samples[END_REF] Zhuang et al. 1997) to pre-fractionate root methanolic extracts removing the contaminant and interfering substances. The SPE columns were preconditioned with two column volumes (CV) of methanol and equilibrated with two CVs of water. Subsequently, 1 mL of the concentrated aqueous phase was loaded onto every single column, and rapidly washed polar compounds were removed, including GLS. Cartridges were eluted with 2 CVs of pure methanol, which disrupted the interaction (non-polar and hydrophobic) of the remaining analytes adsorbed by the stationary phase. The eluted fraction was then concentrated by a rotary evaporator (40°C, 150 rpm) to dryness, re-dissolved in 5 mL of methanol/water(50/50, v/v) mixture, sonicated for 2 min, and centrifuged at 7000 rpm for 10 min before loading on the semi-preparative HPLC system.Semi-preparative HPLCHPLC chromatographic runs were performed using a Dionex Ultimate 3000 HPLC system, coupled to a UV/vis absorbance detector set at λ330 nm and piloted by the Chromeleon software and using a Macherey-Nagel semi-preparative HPLC column (Nucleodur, C18, 250 mm × 10 mm internal diameter, five μm, 110 Å) maintained at 36 °C. The mobile phase consisted of a mixture of solvent A (H2O with 0.1% formic acid, v/v) and solvent B (acetonitrile with 0.1% formic acid, v/v) at a flow rate of 3.5 mL/min. The gradient elution schedule was as follows: initially 2% B, 2-7% B from 0-3 min, 7-17% B from 3-12 min,17-20% B from 12-13 min, 20-32% B from 13-24 min, 32% B maintained from24-34 min, 32-90% B between 34-36 min, held at 90% B between 36-39 min, then 90-2% B from 39-40 min, and the remaining 11 minutes of the gradient allowed for re-equilibrating the column for the next run. 250 µL were injected into the Ph D. manuscript | Anani Amegan MISSINOU P a g e 151

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 152 shifts. Spectra were recorded employing standard Bruker pulse sequences except for the band-selective experiments. The 1D 1H, 13C-zgpg, and 13C-JMOD and the 2D 1H-1H COSY (correlated spectroscopy), 1H-13C HSQC (heteronuclear singlequantum correlation), 1H-13C HMBC (heteronuclear multiple bond correlation) experiments were performed, respectively with cosygpqf, hsqcetgpsisp2.2, hmbcctetgpl2nd. During the acquisition, all the 1H-13C 2D experiments were recorded with the NUS algorithm, with the NUS amount of 25% for the HSQC and 50% for the HMBC. Band-selective experiments were also performed, with shsqcetgpsisp2.2 & shmbcctetgpl2nd, on 50 ppm wide windows in f1 to increase the precision of the assignations for all the close signals. To separate the pure spectra of compounds within a mixture and check simple purity, diffusion-ordered spectroscopy (DOSY) with

Figure 1 :

 1 Figure 1: UPLC chromatogram showing UV absorbance at λ330nm of root extract (QC) from Brassica. R01-R18 represented root-specific UV-absorbing compounds (with their mass-to-charge ratio in negative mode) observed in pooled Brassica napus.

  or with any known Phe/Tyr-derived phenylalkyl-GLSs, or Trp-derived indolic-GLSs (which also display UV-absorbance at λ330 nm), except for R04_385 and R09_385. These two isobaric anions at m/z 385.113 (HPLC-RT 12.03 min and 16.84 min, respectively) displayed daughter anions at m/z 339 [M-H]-, 317 [M-H]-, and 249 [M-H]-, common neutral loss of 46 Da (C2H6O, ethanol) and C5H8 (68 Da, possibly pentadiene), and loss of 136 Da Ph D. manuscript | Anani Amegan MISSINOU P a g e 154

Furthermore, three pairs

  of features (R03_M434/R05_M434; R04_M385/R09_M385; R13_M320/ R18_M368) seem very close from a chemical point of view based on their fragmentation patterns. Features R03_M434 and R05_M434 yielded the deprotonated quasi-molecular ions at m/z 434.207 [M-H] -(HPLC-RT 11.43 min and 12.41 min, respectively). They both generated the daughter anions at 391 [M-H] -, 390 [M-H] -, 388 [M-H] -, 366 [M-H] -illustrating the putative losses of C2H5N (43 Da), CO2 (44 Da), C2H6O

Features

  R13_M320 and R18_M368 were relevant to compounds m/z 320.099 [M-H] - (at HPLC-RT 13.48 min) and m/z 368.099 [M-H] -(at HPLC-RT 17.45 min), that was previously identified in roots of B. napus as genetically related to a QTL conferring resistance to the root pathogen P. brassicae (Wagner et al., 2019). These compounds exhibited common fragments at m/z 233 [M-H] -and m/z 163 [M-H] -and putative similar neutral losses of 44 Da (CO2, carboxylic acid group) generating two main fragments at m/z 276 [M-H] -and m/z 324 [M-H] -, from R13 and R18 respectively. Ions 233 [M-H] - and 281 [M-H] -putatively resulted from the secondary fragmentation of in-source generated m/z fragments 276 [M-H] -and m/z 324 [M-H] -, respectively. They both suggested the loss of the 43 Da typical of amide function HOCN (Table

  [M-H-118] -, 268(<1)[M-H-117] -, 181(*)[M-H-204] -

  #087NSL accession of B. napus ssp. oleifera and #282R50 accession of B. rapa ssp. trilocularis showed high levels (1594 and 2090 AUλ330.g -1 DW, respectively) of R03_M434. The accessions #027CET of B. napus ssp oleifera and #302BAL of B. oleracea ssp. capitata exhibited huge amounts of R07_M551, which reached up to 1303 and 1562 AUλ330.g -1 DW on average, respectively. For R14_MNA, the top mean contents were pointed out in accessions #286TER of B. rapa ssp. rapa (5840 AUλ330.g - 1 DW), #074MAR of B. napus ssp. oleifera (892 AUλ330.g-1 DW), and #300VER of B.

Table 2 :

 2 , coming soon in the published article). Strikingly, seven compounds (R02_M431, R03_M434, R06_M479, R09_M385, R12_MNA, R14_MNA, and R16_M493) showed estimated contents that vary from tens to 100-fold in whole accessions of B. napus, B. rapa and B. oleracea. Ph D. manuscript | Anani Amegan MISSINOU P a g e 158 Descriptive statistics (mean, percent, minimum, maximum) related to the contents of 18 UVλ330-absorbing unidentified compounds in Brassica roots. Details for each accession and compound are given in Supporting Table

Figure 2 :

 2 Figure 2: Heatmap showing absorbance at λ330 nm based-quantitative differences among 304 accessions of Brassica for eighteen unidentified root compounds. (A) Each row and column represent one accession and one new compound detected in the study. Each point in the heatmap stands for the averaged data from three biological replicates (n = 3 of each accession). On the left, the long and short branches of the tree indicate complete similarity and maximum dissimilarity. The scale bar represents the normalized mean absorbance of features (from R01_M315 to R18_M368). Hierarchical clustering was performed using the z-score values of each accession. The color gradient highlights the relative compound contents across accessions. The Z-score transformation ranged from red for positive Z-score values to blue for negative values. (B) Annotations of accession groups per species and cultivars. (C) Boxplots display the variation level of absorbance (AUλ330.g -1 DW) of each

  Unsupervised and supervised analyses were performed with the mean content values measured on 250 accessions belonging to four cultigroups of B. napus (spring and winter). As a first step, principal component analysis (PCA) provided an overview of Ph D. manuscript | Anani Amegan MISSINOU P a g e 161variable levels (loadings) and accessions (scores) distribution but did not identify variables driving clear separation among cultivars (Figure3A).

Figure 3 :

 3 Figure 3: Multivariate analysis of unidentified root compounds in 250 B. napus accessions. (A) Biplot of the unsupervised clustering using PCA model based on UVλ330-absorbing root compounds in Brassica accessions. Each point represents the mean of the three biological replicates. The quality of compounds represented was estimated by cos2 values of variables and illustrated by the increased size of the circle. Compounds strongly contributing to the projection of PC1, PC2, and PC3 are highlighted

Further

  supervised component analysis based on partial least squares discriminant analysis (PLS-DA) regression was performed to better reveal the different chemical profiles corresponding to the four groups of B. napus accessions. The definition of latent components was based on the loading weights of regression coefficients. The Ph D. manuscript | Anani Amegan MISSINOU P a g e 163

Figure 4 :

 4 Figure 4: Network-dissected mQTL regions illustrating associations between phenolics, and root UV-absorbing compounds content traits. K-triHx = Kaempferol-triHexoside, I-triHx = Isorhamnetin-triHexoside. The genetic marker of QTL C07_37.3 was in the region of the mQTL C07_37.5 controlling

Figure 5 :

 5 Figure 5: Number of genes identified in each mQTL region. The numbers between the parentheses represent the number of annotated genes. The research of candidate genes was performed on the reference genome of B. napus accession 'Darmor-bzh' version 5(Chalhoub et al., 2014).

  novel root compounds in Brassica R13_M320 and R18_M368 correspond to the two metabolic features reported byWagner et al. 2019 putatively involved in the genetic resistance of B. napus to the clubroot isolate eH. In the present work, the confidence intervals of the mQTL controlling those two molecules encompass a very small number of candidate genes.We thus focused our efforts on the further structural characterization of those two compounds. Purification steps of R13_M320 and R18_M368 led to the isolation of 8 mg, 6 mg, and 4 mg products, respectively. When redissolved at high concentration (in methanol or DMSO) these three compounds harbored a gold-yellow coloration. Q-Exactive Orbitrap MS/MS carried out a forward analysis of the molecular formula. The elemental composition was limited to C, H, N, and O, with the error cutoff set to <3ppm.The molecular formula, C13H15N5O5, and C17H15N5O5 were respectively assigned to m/z 320.0998 [M-H] -and 368.0998 [M-H] -pseudo-molecular ion peaks of R13_M320, R18_M368, respectively. MS and MS/MS/ fragmentation allowed us to uniquely assign the molecular formula of the small anionic fragments and the loss of neutral features.The daughter ion m/z 163 is shared by the two compounds and corresponds to the molecular mass of C6H3N4O2. R13_M320 and R18_M368 both displayed a nitrogencontaining aromatic moiety and were both carboxylated. Additional structural investigations were then performed on these three compounds using a series of NMR techniques, as follows:Ph D. manuscript | Anani Amegan MISSINOU P a g e 169

Figure 6 :

 6 Figure 6: Comparison of 1H NMR and 13C NMR 500 MHz data from experimental chemical shifts (δexp) for R13_M320 and R18_M368 compounds in deuterated methanol (CD3OD) (δ in ppm, J in Hz).

Figure 7 :

 7 Figure 7: NMR-based characterization of the substructure of R13_M320. A/ Characterized fragment B/ Observed HMBC correlations C/ observed NOESY correlations of R13_M320 characterized fragment. The wavy line represents a still not fully resolved poly-nitrogenated aromatic heterocycle (C6H3N4O2).

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 171

Figure 8 :

 8 Figure 8: NMR-based characterization of the substructure of R18_M368. A/ Characterized fragment B/ Observed HMBC correlations C/ Observed NOESY correlations of R18_M368 characterized fragment. The wavy line represents a still not fully resolved poly-nitrogenated aromatic heterocycle (C6H3N4O2).

Figure 9 :

 9 Figure 9: Hypothetical structures of the two compounds R13 (A) and R18 (B). The proposition of a pteridine structure for the poly-nitrogenated aromatic heterocycle is detailed in the discussion.

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 175

Figure 1 :

 1 Figure 1: UPLC-UV chromatogram of a leaf extract (QC).

Figure 2 :

 2 Figure 2: Heatmap showing differences of absorption among 304 accessions of Brassica for eighteen unknown root compounds absorbing at λ330nm. (A) Each row and column respectively represent one accession and one unknown compound detected in the study. (B) Annotations of accession groups per species and cultivars. (C) Boxplots display the variation level of absorbance (AU.g -1 DW) of each unknown compound across accessions.

Figure 3 :

 3 Figure 3: Multivariate analysis of unknown root compounds of B. napus cultivars accessions. (A) Biplot of the unsupervised clustering using PCA model based on unknown root compounds of Brassica varieties (B) Biplot of the supervised clustering using the PLS-DA model based on unknown root compounds of B. napus varieties.

Figure 4 :

 4 Figure 4: Phenotypic variation and Pearson correlation coefficients of unknown Brassica root compounds absorbing at λ330nm. (A) An upper triangular matrix showing Pearson's correlation for 18 UV-absorbing in 304 accessions of Brassica. (B) QTL numbers associated with UV-absorbing compounds content from genetic linkage study.

Figure 5 :

 5 Figure 5: Number of genes identified in each mQTL region. The numbers between the parentheses represent the number of genes. The research of candidate genes was performed on the reference genome of B. napus version 5(Chalhoub et al., 2014).

Figure 6 :

 6 Figure 6: Comparison of 1 H NMR and 13 C NMR 500 MHz data from experimental chemical shifts (δexp) for R13_M320 and R18_M368 compounds in deuterated methanol (CD3OD) (δ in ppm, J in Hz).

Figure 7 :

 7 Figure 7: NMR-based characterization of the substructure of R13_M320. A/ Characterized fragment B/ Observed HMBC correlations C/ observed NOESY correlations of R13_M320 characterized fragment. The wavy line represents a still not fully resolved poly-nitrogenated aromatic heterocycle (C6H3N4O2).

Figure 8 :

 8 Figure 8: NMR-based characterization of the substructure of R18_M368. A/ Characterized fragment B/ Observed HMBC correlations C/ Observed NOESY correlations of R18_M368 characterized fragment Wavy line represents a still not fully resolved poly-nitrogenated aromatic heterocycle (C6H3N4O2).

Figure 9 :

 9 Figure 9: Hypothetical structures of the two compounds R13 (A) and R18 (B). The proposition of a pteridine structure for the poly-nitrogenated aromatic heterocycle is detailed in the discussion.

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 190

B

  . napus responses to phoma infection could help identify localized biochemical regulations that could be induced at the interface between plant tissues and pathogen progression's front. The metabolic responses of two genotypes (the partially resistant Ph D. manuscript | Anani Amegan MISSINOU P a g e 191 'Darmor' and the moderately susceptible 'Bristol') of oilseed rape were analyzed and compared by MALD-MSI.

3 .

 3 Mass spectrometry imaging data processing

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 196

Figure 1 :

 1 Figure 1: Regulation of GLSs induced by Leptosphaeria maculans in the stems of the partially susceptible accession 'Bristol' and the partially resistant accession 'Darmor'. (A) Illustration of the necrotic cavity at stem level at 14dpi in 'Bristol' and 'Darmor' (Image by Anne Levrel). (B) GLS contents in stems (NI=non-inoculated, JN2=infected by L. maculans isolate JN2), at 14-and 28-days post-inoculation (dpi). Yellow = Met-derived aliphatic GLSs. Green = Phe/Try-derived phenylalkyl GLSs (aromatic-). Light salmon = Trp-derived indolic-GLSs. Dark blue= branched and linear alkyl-GLSs. n=3 biological replicates (except 'Darmor' NI and JN2 with n=2). Each replicate is a pool of 6 plants. Stars indicate statistical differences following the student test (<0.05). G32=hexyl-GLS (one of the branched alkyl-GLSs) was not detected in the stems of non-inoculated plants.

Figure 2 :

 2 Figure 2: Untargeted full-scan LC-HRMS analyses of the metabolic responses to Leptosapheria infection in oilseed rape stems in 'Darmor' and 'Bristol'. The two major indolic phytoalexins spirobrassinin and cyclobrassinin are indicated. This preliminary work highlighted the induction of several previously unknown sulfur-containing and pathogen-induced metabolic features (not shown in this figure). Additional work (including further biological replicates) is now required to further document this phenomenon.

3. 2 .

 2 Mass spectrometry imaging reveals the spatial distribution of metabolic responses in stems of B. napus after L. maculans infection 3.2.1. Metabolic responses to L. maculans infection in the two genotypes of B. napus 'Darmor' and 'Bristol'

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 200

Figure 3 :

 3 Figure 3: The common response of resistant and susceptible Brassica napus genotypes to phoma infection. (A) The three steps of the MALDI-MSI data analysis pipeline are implemented in the

  Unfortunately, we have not yet been able to annotate these features. In our future work, MS/MS fragmentation may help to explore the putative chemical structure of those compounds. Ph D. manuscript | Anani Amegan MISSINOU P a g e 202

Figure 4 :

 4 Figure 4: The genotype-specific metabolic response to Leptosphaeria maculans. The images come from a spatial segmentation between the resistant genotype (A) and the susceptible genotype (B). The arrows indicate the inoculation point. The figures represent the number of chemical characteristics resulting from the different comparisons of the metabolic profiles by analyzing the ROC curve with an AUC threshold of 0.75. The top 10 features in each comparison are displayed.

Figure 5 :

 5 Figure 5: Molecular maps of glucosinolates in healthy stems of B. napus (Darmor). Met-derived aliphatic-GLSs: gluconapin, glucobrassicanapin, (epi)progoitrin, gluconasturtiin, glucoalyssin, Trpderived indolic-GLSs: glucobrassicin.

Figure 6 :

 6 Figure 6: Segmentation was carried out individually on each biological replicate per experimental condition. Tissular zones with spectral similarity are coded in the same arbitrary colors within the same section, but not between sections. (A) Susceptible ('Bristol') and (B) resistant ('Darmor'), control at the top and 14dpi after JN2 inoculation at the bottom. Positive mode and negative mode MSI analysis are displayed.

  l'introduction bibliographique de ce manuscrit, avant le début de cette thèse en 2018, la recherche portant sur le métabolisme spécialisé de Brassica napus recélait un vaste territoire inexploré. Dans un contexte où la résistance génétique aux bio-agresseurs constitue un levier majeur des scénarios de transition agro-écologique, il est nécessaire de consolider notre compréhension des mécanismes biologiques impliqués dans les interactions entre le colza et son environnement biotique. Chez cette espèce, il semble aujourd'hui nécessaire d'approfondir les investigations sur la diversité des défenses chimiques constitutives (phytoanticipines), les déterminants génétiques contrôlant leur biosynthèse, et comment la plante mobilise son arsenal de défense chimique (constitutive et induite) en réponses aux contraintes biotiques. C'est dans ce contexte que s'est inscrit mon projet de thèse. IV. A. Discussion et conclusion générale L'objectif de cette thèse était de caractériser le métabolisme spécialisé de B. napus, avec un "fil d'Ariane" à deux sous-objectifs : étudier dans un panel d'accessions la diversité (1) et le contrôle génétique des contenus en phytoanticipines dans les racines et les feuilles, et caractériser la régulation (2) des phytoanticipines et des phytoalexines en réponse à l'infection fongique par L. maculans dans les tiges de B. napus. Au cours de mes recherches, j'ai participé au développement de plusieurs stratégies pour atteindre cet objectif. Dans la première partie de mon travail, nous avons tiré parti d'outils analytiques (spectrométrie de masse et résonnance magnétique nucléaire) Ph D. manuscript | Anani Amegan MISSINOU P a g e 210 performants afin de générer les meilleurs jeux de données possibles. Cette étape, bien qu'étant assez contraignante, est essentielle pour la suite. Certes, la recherche sur le métabolisme spécialisé des plantes est traversée actuellement par une révolution informatique, ce qui offre une grande diversité d'outil permettant, d'extraire automatiquement un grand nombre d'information autour des données métabolomiques. Cependant, en raison d'un certain nombre de contraintes techniques, en particulier la nécessaire exploitation d'un jeu de données pour lequel les données de fragmentation MS2 ont été acquises en basse résolution, et dans un contexte de consolidation de nos capacités à interpréter des données de spectrométrie de masse, nous avons dans un premier temps délibérément privilégié une exploration manuelle des données, en focalisant l'effort sur des catégories particulières de métabolites spécialisés. Cet effort a permis d'annoter 32 composés phénoliques et 36 glucosinolates, dont les schémas de fragmentation ont été proposé dans les données supplémentaires du premier article décrivant la diversité chimique des composés foliaires et racinaires de Brassica.

  ont été habituellement attribuées de manière spécifique aux genres taxonomiques, à savoir la p-hydroxygluconasturtiine chez Arabis soyeri ; l'epiglucobarbarine et la glucobarbarine utilisée pour des affiliations taxonomique des types P et G de Barbarea vulgaris ; la m-hydroxygluconasturtiine commune au genre Arabis et Barbarea ; la 4methoxyglucobrassicine chez Barbarea vulgaris ; l'isopropyl-GLS chez la Cardamine diphylla ; la glucocochlearine chez Cochlearia officinalis ; et 3-methylpentyl-GLS chez Cardamine pratensis. Nous avons montré que B. napus synthétise en plus de ces formes relativement rares de GLSs, un nombre important et stimulant d'isomères d'alkyl-GLSs (2 isomères hydroxy-C4-alkyl-GLSs, 3 isomères de C5-et C6-alkyl-

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 212 GLS (glucocochlearine) ont été rapportées chez Limnanthaceae[START_REF] Agerbirk | Ancient Biosyntheses in an Oil Crop: Glucosinolate Profiles in Limnanthes alba and Its Relatives (Limnanthaceae, Brassicales)[END_REF]. Ces voies de biosynthèse sont considérées comme antérieures à celle des GLS indoliques, et d'après les résultats de mon travail, elles semblent avoir été conservées chez B. napus et chez ancêtres des Brassica.

1 .

 1 issue d'innovation biosynthétique à partir des GLSs ancestraux. En effet, une grande partie des GLSs de B. napus sont issus d'élongation de la chaine R primaire des GLSs contenus dans des familles de plantes basales la phylogénie des Brassicales, à savoir l'homométhionine, l'homophénylamine et l'homotyrosine.Il est admis que la structure de GLS la plus ancienne est la glucotropaeolin et ces dérivés hydroxylés et méthoxylés[START_REF] Ortega | Glucosinolate Survey of Cultivated and Feral Mashua (Tropaeolum tuberosum Ruíz & Pavón ) in the Cuzco Region of Peru[END_REF][START_REF] Edger | Brassicales phylogeny inferred from 72 plastid genes: A reanalysis of the phylogenetic localization of two paleopolyploid events and origin of novel chemical defenses[END_REF]. Bien que le benzyl-GLS et l'hydroxybenzyl-GLS aient été retrouvés chez Sinapis alba, qui est relativement proche du genre Brassica, aucune étude ne rapporte la présence de ces composés chez le colza. Cette dernière semble avoir été perdu ces GLSs en faveur de la gluconasturitine et de ses dérivés hydroxylés (homosinalbine, epiglucobarbarine, glucobarbarine, et m-hydroxygluconasturtiine).Chez Barbarea vulgaris, il existe un polymorphisme en stéréochimie de la 2hydroxylation de la gluconasturtiine (l'epiglucobarbarine et la glucobarbarine), déterminé par la variation allélique sur deux homologues de type FMOGS-OX d'Arabidopsis (SHO : S-HYDROXYLATION) et RHO : R-HYDROXYLATION) qui déterminerait l'accumulation respective des épimères dans le chémotypes G et P de Ph D. manuscript | Anani Amegan MISSINOU P a g e 213 l'espèce en Europe de l'Est(Liu et al., 2019). Très curieusement, les dérivés hydroxylés de GLSs, à l'exception de p/m-hydroxyglucobarbarine et epi/progoitrine, étaient associés à des QTLs localisés sur des chromosomes A03 ou C02. En considérant que le gène CYP81F2 réalisant l'hydroxylation de la glucobrassicine en 1sur C02 chez B. oleracea[START_REF] Sotelo | Identification of metabolic QTLs and candidate genes for glucosinolate synthesis in Brassica oleracea leaves, seeds and flower buds[END_REF], d'une façon spéculative, nous pouvons proposer que ces régions sur les chromosomes A03 et C02 contiendraient des loci codant des enzymes de type FMOGS-OX, un contrôle plus général des oxydations réalisées sur des résidus C-, N-, Sprécurseurs de glucosinolates.IV.A.3. Redondance structurelle dans la biodiversité GLSsNous avons déterminé un grand nombre d'isomères de glucosinolates (hydroxylés, méthoxylés, à chaine R) et des phénoliques (hexosylés et acylés). Ceci suggère, une capacité du colza à co-synthétiser différents composés isomérique hydroxylés, méthoxylés, à chaîne carbonée identique, hexosylés et phénylacylés. Cette cooccurrence de ces formes isomériques peut potentiellement être, d'une part le résultat de rétention des gènes dupliqués impliqués dans la biosynthèse de composés spécialisés chez B. napus[START_REF] Hofberger | Whole Genome and Tandem Duplicate Retention Facilitated Glucosinolate Pathway Diversification in the Mustard Family[END_REF], mais d'autre part, le fruit de séparation des enzymes homologues dans différent compartiments cellulaire, comme cela a été démontré pour les MAMs 37 d'Arabidopsis.37 Les enzymes MAM catalysent la réaction de condensation qui étend la chaîne carbonée dans les précurseurs GSL dérivés d'acides aminés Ph D. manuscript | Anani Amegan MISSINOU P a g e 214 En conclusion, nous avons avancé dans la caractérisation du métabolisme spécialisé du colza, et fourni un premier jalon sur l'impact de la sélection des GLSs graines sur la diversité génétique aux allèles impliqués dans le contrôle génétique de la teneur en GLSs (feuilles/racines), et la caractérisation des réponses métaboliques à l'infection. L'ensemble de mes travaux ouvrent la voie à d'autres thématiques, d'autres thèses potentielles, dans des domaines liés à l'amélioration des plantes et lÉtendre l'inventaire des métabolites spécialisés chez B. napus En plus des GLSs rarement rapportés que nous avons identifiés chez le colza, nous avons repéré après publication, quatre autres glucosinolates, dont deux ont été provisoirement annotés comme étant des isomères de C5-alkyl-GLSs potentiellement équivalent à ceux rapportés chez B. rapa

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 215Certains auteurs ont rapporté 51 GLSs chez Brassica oleraceaL. var. botrytis, dont six dérivés hydroxylés de l'indol-3-ylméthyl-GSLs, trois méthylsulfinylbutyl-GLSs, deux méthylsulfinylpropyl-GLSs, des dérivés sinapoyl, cinnamoyl-, coumaroyl-GLSs entre autres[START_REF] Capriotti | Chromatographic column evaluation for the untargeted profiling of glucosinolates in cauliflower by means of ultra-high performance liquid chromatography coupled to high resolution mass spectrometry[END_REF]. Face à ce nombre croissant de GLSs retrouvés chez B. napus et au fait que Brassica oleracea L. var. botrytis présente d'autres formes inhabituelles de GLS, il se profile que le nombre et la diversité structurelle des GLSs chez B. napus excède au moins les 44 GLSs. De futures optimisations analytiques seront nécessaires pour fournir les preuves de la présence/absence de ces GLSs atypiques chez le colza. En outre, près d'une quarantaine de composés phénoliques détectés n'ont pas été publiés, en raison de leur insuffisante résolution chromatographique qui empêche leur quantification par intégration des pics UV. Certaines d'entre eux ont été provisoirement annotés comme étant des dérivés phénoliques complexés à de l'acide malique, polyhexosylés et polyacylés.De façon très remarquable, certaines études avaient rapporté la présence de la glucotropaeoline chez le chou (Brassica oleracea L. var. gernrnifera)[START_REF] Heaney | Glucosinolates in brassica vegetables. Analysis of 22 varieties of brussels sprout (Brassica oleracea var. gemmifera)[END_REF]. Il serait intéressant de rechercher ce composé dans les variétés anciennes de B. napus (WOSR++).Aussi, il serait avantageux de tester des combinaisons de solvant binaire ou tertiaire, afin d'élargir le prisme du rendement d'extraction et des familles des molécules isolées des matrices cellules, comme cela a été prouvé dans chez d'autre modèles(Silva et al., 2020) et d'optimiser nos conditions analytiques, en testant par exemple les colonnes chromatographiques Kinetex XB-C18 and Kinetex Biphenyl[START_REF] Capriotti | Chromatographic column evaluation for the untargeted profiling of glucosinolates in cauliflower by means of ultra-high performance liquid chromatography coupled to high resolution mass spectrometry[END_REF]. Enfin le fractionnement bio-guidé à partir des plantes infectées permettrait de Ph D. manuscript | Anani Amegan MISSINOU P a g e 216 cibler des fractions biologiquement actives au moyen de tests d'inhibition de croissance des agents pathogènes en culture. L'activité des métabolites R13_M320 et R18_M368 pourrait être testée de cette façon. IV.B.2. Profilage métabolomique non ciblé de B. napus et annotation des métabolites à l'aide de réseaux moléculaires La spectrométrie de masse (MS) couplée à des méthodes de séparation (LC et GC) est couramment appliquée pour le profilage différentiel et quantitatif. Il serait donc judicieux d'appliquer ces méthodes d'analyse utilisant plusieurs plateformes analytiques (LC-MS et GC-MS) sur les échantillons du panel de Brassica. Le défi le plus important de ces approches dites de profilage métabolomique non ciblé est l'efficacité des méthodes de traitement et d'extraction des informations pertinentes.

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 217 approximatives aux spectres de molécules apparentées), la fusion des modes d'ionisation et d'annoter les spectres de fragmentation dans les réseaux moléculaires grâce à plusieurs bases de données et des outils tel que SIRIUS[START_REF] Dührkop | SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information[END_REF], ZODIAC[START_REF] Ludwig | Database-independent molecular formula annotation using Gibbs sampling through ZODIAC[END_REF], MS2LDA[START_REF] Rogers | Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra[END_REF] et de fournir une sortie Cytoscape. Au cours de ma thèse, les échantillons de tige de colza, 14 et 28 jours post-inoculation par L. maculans (JN2), ont été analysés selon les deux modes d'ionisation et une fragmentation systématique a été réalisée sur les ions majoritaires.L'approche mzMine2-GNPS, que je me suis appropriée durant ma thèse, a été initiée sur ces données. Cependant par manque de temps, elle n'est pas présentée dans ce manuscrit.IV.B.3. Affiner la puissance de détection de gènes candidatsLes études d'association à l'échelle du génome (GWAS) ont identifié des associations de plusieurs QTL contenant des polymorphismes mononucléotidiques (SNP) associés aux métabolites spécialisés secondaires de colza. Cependant, la précision de nos analyses GWAS reste à améliorer pour identifier des gènes candidats afin de valider leur implication par l'étude de variants fonctionnels et de caractériser les mécanismes sous-jacents aux QTLs métaboliques. Les intervalles de confiance des QTL correspondent à des régions génomiques incluant de nombreux gènes. Dans nos analyses mGWAS, les pourcentages de variation phénotypique expliquée par les QTLs individuels varient entre 3 et 37%, ce qui correspond plus ou moins forte de la variation génétique de chaque trait. De plus, certains variants SNP peuvent ne pas avoir été capturés dans nos analyses mGWAS, du fait de l'existence d'allèles rares dans le panel colza utilisé. Par exemple, nous n'avons pas détecté de QTL qui soit spécifiquement associé à l'épimérisation 2-hydroxy-3-butenyl-glucosinolate Ph D. manuscript | Anani Amegan MISSINOU P a g e 218 (progoitrine et epiprogoitrine) ni à celle des hydroxyphenylethyl-glucosinolates (epiglucobrabarine et glucobarbarine). Face à ces limites d'identification des associations génétiques, il existe différentes options pour améliorer la puissance et précision de détection des gènes candidats. Premièrement, pour exploiter les variants rares spécifiques à certains cultivars, difficilement détectable par GWAS, il serait intéressant d'analyser la génétique des traits métaboliques par des approches de génétique de liaison dans des populations biparentales ou de génétique d'association dans des populations issues de croisements multiparentaux, comme des populations MAGIC (multiparent advancedgeneration intercross population) (Cavanagh et al. 2008, Holland 2015) en ciblant les parents selon les contrastes visés. Deuxièmement, les données de séquençage du génome entier (WGS) peuvent être utilisées pour densifier en marqueurs certaines régions et mieux capturer les variants rares et les variations structurales. L'obtention des séquences génomiques des accessions du panel Brassica serait sans doute possible dans les années qui viennent, en raison de la chute vertigineuse du coût du séquençage ADN qui a baissé d'un facteur de 1.000.000 ces 15 dernières années.

  Ph D. manuscript | Anani Amegan MISSINOU P a g e 219 CRISPR/cas9, technologie qui peut être mise en oeuvre chez le colza mais qui est parfois difficile en raison de la nature dupliquée du génome du colza. Par ailleurs, les protocoles de transformation génétique actuels ne fonctionnent que pour un nombre restreint de génotypes.

  Malheureusement, l'analyse de leur expression avec les données d'expression transcriptomique du projet Metaphor a révélé qu'un faible nombre était régulé par l'infection par le phoma, à l'exception d'un cluster d'une taille de 80,39 kb. Ce cluster contenait trois gènes biosynthétiques non-homologues, A10p30340.1_BnaDAR (oxydoréductase), A10p30430.1_BnaDAR (CYP71B20), et A10p30490.1_BnaDAR (UDP-glucosyltransférase), régulé à la hausse par l'infection des souches JN2 et NZT4 dans les génotypes 'Darmor-bzh', 'Darmor' et 'Bristol'. Certes ces résultats ne répondent pas à la question de la résistance de 'Darmor/Darmor-bzh' par rapport à 'Bristol', mais fournissent potentiellement des gènes candidats impliqués dans la synthèse de phytoanticipines potentiellement inconnus. Par manque de temps, je n'ai pas investigué les métabolites possiblement produits par ce cluster. Non seulement il Ph D. manuscript | Anani Amegan MISSINOU P a g e 220 serait intéressant de mieux caractériser les variations génomiques sur ces clusters en exploitant les séquences génomiques exploitables, mais aussi, de les analyser avec d'autres jeux d'expression en condition de stress biotique et abiotique. La liaison des informations entre les ensembles de données (génomique, génétique, et métabolomique) est utile, car elle permet l'annotation structurelle et fonctionnelle.L'esprit à l'heure actuelle est d'explorer comment évolue les BGCs dans différentes population[START_REF] Medema | Minimum Information about a Biosynthetic Gene cluster[END_REF][START_REF] Navarro-Muñoz | A computational framework to explore large-scale biosynthetic diversity[END_REF] et de les connecter aux données de fragmentation de la spectrométrie de masse non-ciblée(van der Hooft et al., 2020;[START_REF] Larkan | A supervised fingerprint-based strategy to connect natural product mass spectrometry fragmentation data to their biosynthetic gene clusters[END_REF].

These chemical defenses can be classified according to the control of biosynthesis: constitutive chemical defenses and inducible chemical defenses. I.A.6.1. Constitutive chemical defenses

	During evolution, plants have established a sophisticated chemical arsenal to prevent
	pest attacks. This arsenal encompassed both inorganic and organic chemical
	defenses.
	"Metal hyperaccumulating plants" (e.g., the Brassicaceae family, which accumulates
	cadmium) accumulate inorganic elements from the soil such as silicon, nickel, zinc,
	Ph D. manuscript | Anani Amegan MISSINOU
	P a g e 47

38), amydalin (40))

	Many nitrogen-containing compounds have constitutive antimicrobial activity, like
	gramine alkaloids (31) of Solanaceae, quinolizidine alkaloids (anagyrine) (32) of
	Fabaceae, all benzoxazinoids of Poaceae (Freezman, 1997), breakdown product
	glucosinolates of Brassicales (e.g., neoglucobrassicin (42), epiglucobarbarin (43),
	(epi)progoitrin (44)). Cyanogenic glycosides 16 (e.g., lotaustralin (Ph D. manuscript | Anani Amegan MISSINOU
	P a g e 49

I.A.7. Oilseed rape (B. napus) I.A.7.1. Origin and genomic evolution of oilseed rape

	Oilseed rape (Brassica napus L.) in the genus Brassica is a very complex member of
	the Brassicaceae family that contains many cultivated plants and wild species. The
	cytogenetic relationships between B. napus and their closest relatives were first
	systematically explained more than 80 years ago (Nagaharu U, 1935) (Figure

Identification and Quantification of Glucosinolates and Phenolics in a Large Panel of Brassica napus Highlight Valuable Genetic Resources for Chemical Ecology and Breeding Link for supplementary files https

  Le défi majeur de cette approche est de construire un réseau à partir des mQTLs identifiés et de l'analyser en regard de la diversité structurelle et des voies de 'analyse GWAS a identifié 11 mQTLs contrôlant la teneur en ces composés, en majorité structurellement distincts les uns des autres. Dans cette partie, j'ai co-encadré Identification and Quantification of Glucosinolates and Phenolics in a Large Panel of Brassica napus Highlight Valuable Genetic Resources for Chemical Ecology and Breeding Anani Amegan Missinou, ⊥ Julie Ferreira de Carvalho, ⊥ Nathalie Marnet, Thomas Delhaye, Oumayma Hamzaoui, David Abdel Sayed, Yann Guitton, Lionel Lebreton, Christophe Langrume, Anne Laperche, Régine Delourme, Maria J. Manzanares-Dauleux, Alain Bouchereau, and Antoine Gravot*

	biosynthèse des phytoanticipines. A l'instar du travail initié précédemment au
	laboratoire (Wagner et al., 2019), j'ai construit des réseaux intégrant les associations avec Clément Orione (Ingénieur RMN à la plateforme CRMPO 31 ), le stage de Master
	mQTL-métabolites afin de formaliser l'architecture génétique associée aux variations 2 de Youcef Haddad portant sur la purification et la caractérisation structural des
	qualitatives et quantitatives du phénotype métabolique de B. napus. Nous avons molécules racinaires par raisonnance magnétique nucléaire (RMN) combiné à la
	identifié 105 mQTLs impliqués dans le contrôle des profils phytochimiques racinaires spectrométrie de masse à haute resolution. Cite This: J. Agric. Food Chem. 2022, 70, 5245-5261 Read Online
	et foliaires, soulignant une diversité de modules génétiques contrôlant ACCESS Metrics & More Article Recommendations
	indépendamment les différentes sous-catégories biochimiques.

deuxième article (en préparation J Ferreira de Carvalho*, AA Missinou*, N Marnet, L Lebreton, C Langrume, A Bouchereau, M Manzanares-Dauleux, R Delourme, A Laperche, A Gravot. Genome-wide association studies provide insights into the genetic basis of specialized metabolism and reveal the breeding history of seed glucosinolate content in Brassica napus. For submission to Plant Biotechnology Journal) a pour objectifs : (1) d'identifier des QTLs associés à des variations métaboliques, (2) de proposer des gènes candidats sous-jacents aux QTL détectés pour des études de génomique fonctionnelle, et (3) d'appréhender l'impact de la sélection pour une faible teneur en GLSs aliphatiques dérivés de la méthionine dans les graines de colza sur les GLSs racinaires et foliaires (incluant les GLSs rares des Brassica) et sur les composés phénoliques foliaires. L'objectif à moyen terme est de mettre en relation les QTL métaboliques et les QTL associés à la résistance à des agents pathogènes afin d'établir des hypothèses sur les mécanismes sous-jacents à ces résistances. Pour atteindre ces objectifs, j'ai collaboré avec Julie Ferreira de Carvalho qui a réalisé les analyses de génétique d'association (GWAS) pour identifier les QTLs contrôlant le contenu de ces métabolites (QTL métaboliques ou mQTLs) dans les différents Ph D. manuscript | Anani Amegan MISSINOU P a g e 78 organes. Lors de l'étude de la diversité phytochimique dans un large éventail d'accessions de Brassica, nous avons repéré 18 métabolites racinaires absorbant dans les UV et qu'il n'a pas été possible d'annoter car vraisemblablement absents des bases de données métabolomiques. Parmi ces molécules, deux métabolites de structure inconnue avaient été suggérés par mon laboratoire d'accueil comme étant impliqués dans la résistance à la hernie (Wagner et al., 2019). L'objectif de cette troisième partie, présentée sous forme d'article en préparation (AA Missinou, C Orione, J Ferreira de Carvalho, Y Haddad, N Marnet, P Jéhan, A Laperche, R Delourme, A Bouchereau, MJ Manzanares-Dauleux, A Gravot. Structural and genetic investigation of novel root UVabsorbing compounds reveals major QTLs controlling the content of two pteridine-like amino acid conjugates in Brassica. To be submitted to Phytochemistry) est de caractériser la chimie structurale et le contrôle génétique de ces nouveaux métabolites racinaires. Un effort de purification a conduit à une annotation structurale par RMN concluante pour certaines des molécules. Les résultats préliminaires suggèrent qu'il s'agirait d'une petite famille de composés nouveaux, dont deux ont précédemment été Ph D. manuscript | Anani Amegan MISSINOU P a g e 79

rapporté comme étant associés à la résistance à la hernie

(Wagner et al., 2019)

. LL'ensemble de ces travaux fournit une ressource utile pour l'écologie chimique et l'amélioration des Brassica. Ph D. manuscript | Anani Amegan MISSINOU P a g e 80 Ph D. manuscript | Anani Amegan MISSINOU P a g e 81 Paper I: ://pubs.acs.org/doi/10.1021/acs.jafc.1c08118?goto=supporting-info Ph D. manuscript | Anani Amegan MISSINOU P a g e 82 * sı Supporting Information

ABSTRACT: Glucosinolate (GLS) and phenolic contents in Brassicaceae contribute to biotic and abiotic stress responses. Breeding crop accessions harboring agroecologically relevant metabolic profiles require a characterization of the chemical diversity in Brassica germplasm. This work investigates the diversity of specialized metabolites in 281 accessions of B. napus. First, an LC-HRMS2-based approach allowed the annotation of 32 phenolics and 36 GLSs, revealing 13 branched and linear alkyl-GLSs and 4 isomers of hydroxyphenylalkyl-GLSs, many of which have been rarely reported in Brassica. Then, quantitative UPLC-UV-MS-based profiling was performed in leaves and roots for the whole panel. This revealed striking variations in the content of 1-methylpropyl-GLS (glucocochlearin) and a large variation of tetra-and penta-glucosyl kaempferol derivatives among accessions. It also highlighted two main chemotypes related to sinapoyl-O-hexoside and kaempferol-O-trihexoside contents. By offering an unprecedented overview of the phytochemical diversity in B. napus, this work provides a useful resource for chemical ecology and breeding. KEYWORDS: oilseed rape, specialized metabolism, chemical diversity, BCAA-derived glucosinolates, flavonols, phenylpropanoids, chemotypes

Table 2 .

 2 Identification of Phenylpropanoids a

	a

Table 4 .

 4 Identification of Acylated Flavonoid Hexosides in Leaves of 304 Accessions of Brassica a

	a

Table 5 .

 5 Descriptive Statistics of Major Categories of Glucosinolates and Phenolic Compounds Quantified in Leaves and Roots of Brassica Accessions a Data included 291 accessions of B. napus, 12 accessions of B. rapa, and 11 accessions of B. oleracea. Details for each accession and compound are given in Supporting Tables

a

  #,a , Philippe Duffé a , Christophe Mougel a , Alain Bouchereau ab , Maria Manzanares-Dauleux a , Régine Delourme a , Anne Laperche a , Antoine Gravot * ,a,b a Univ Rennes, Institut Agro, INRAE, IGEPP, 35653, Le Rheu, France

b INRAE, BIA, 35653, Le Rheu, France

Table 1 : Nomenclature and sub-categories of glucosinolates and phenolics used in this work.

 1

Table S2 : Heritabilities for the GLS and PHL compounds in the leaves and roots.

 S2 GLSs annotated with two asterisks (**) were tentatively identified only from daughter anions and accurate parent mass; those with one asterisk (*) were further validated with certified reference plant materials; and those remaining without an asterisk were confirmed with authentic reference compounds.

	Leaf GLS Supplementary GLS compounds	Leaf	SOSR + Root	SOSR -		WOSR -PHL compounds WOSR +	Leaf	QTL
	G1 G2 Compo nent G3 GLS GLS	Glucoiberverin** Glucoiberin Organ Pheno_trait Sinigrin leaves ali_GLS_.GLS leaves ali_GLS_.GLS	Nom_QTL mQA03_22.0 mQA09_4.1	0.675 0.857 Chrom osome nb SNP S* 0.897 A03 1 Bn.A03.p21294836 22 009 685 0.669 PL1 0.873 PL2 Peak SNP Position of peak SNP QTL_start 0.924 PL3 22 001 204 CQA FQA** QTL_end 22 064 3.50E-06 Pvalue Fer-Hex** A09 4 Bn.A09.p2733282 4 101 935 3 305 420 4 564 6.37E-16	SNP Weight -5.816 -10.658	0.758 R² 0.574 0.087 0.772 0.189
	G4 GLS GLS	Glucoerucin leaves ali_GLS_.GLS leaves ind_GLS_.GLS	mQC09_6.8 mQA03_21.1	0.000 C09 3 Bn.C9.p6344887 0.760 A03 1 Bn.A03.p20417630 21 162 949 PL4 6 804 840	Sin-Hex** 6 488 132 6 992 9.38E-07 21 154 400 21 242 3.89E-06	-5.754 3.155	0.091 0.706 0.079
	G5 GLS GLS	Glucoraphanin leaves ind_GLS_.GLS leaves alkyl_GLS_GLS	mQA09_4.1 mQA01_2.9	0.880 A09 3 Bn.A09.p2733282 0.885 A01 1 Bn.A01.p27988223 29 764 089 PL5 4 101 935	Sin-diHex** 3 305 420 4 564 3.54E-10 29 420 126 31 229 3.58E-08	4.645 1.791	0.113 0.802 0.108
	G6 GLS G7 GLS GLS G8 GLS GLS G9 GLS GLS	Gluconapin leaves C3_tot_ali Progoitrin leaves C3_tot_ali leaves C4_tot_ali Epiprogoitrin** leaves C5_tot_ali leaves C5_tot_ali Glucoberteroin** leaves C6_tot_ali leaves C6_tot_ali	mQA08_22.9 mQC07_13.0 mQC01_7.3 mQA07_11.5 mQC01_7.3 mQA07_13.3 mQC04_7.0	0.931 A08 1 Bn.A08.p18750116 23 050 234 0.918 PL6 0.866 0.839 PL7 C07 3 Bn.C7.p10181642 13 721 335 C01 24 Bn.C1.p6868720 7 360 772 0.878 0.863 PL8 A07 1 Bn.A07.p6541352 11 528 722 C01 24 Bn.C1.p6854343 7 334 923 0.579 0.834 PL9 A07 1 Bn.A07.p8334245 13 356 426 C04 1 Bn.C4.p5393354 7 084 250	diFer-diHex** 22 909 753 23 267 4.63E-06 9 984 488 16 394 2.26E-06 diSin-diHex** 7 061 851 7 469 3.72E-11 11 404 433 11 537 3.13E-06 diSin-diHex** 7 061 851 7 469 1.48E-08 13 341 127 13 383 4.19E-06 Fer-Sin-diHex** 6 870 129 7 148 4.54E-06	0.110 0.128 -7.162 -3.912 7.256 0.089 0.095	0.056 0.780 0.061 0.161 0.902 0.085 0.123 0.281 0.055 0.668 0.048
	G10 Glucoalyssin GLS leaves C6_tot_ali GLS leaves C6_tot_ali	mQC07_25.0 mQC09_61.6	0.855 C07 1 Bn.A07.p8096658 24 959 521 0.917 PL10 24 866 759 Fer-Sin-diHex** 25 033 9.62E-07 C09 1 Bn.C9.p51326764 61 689 514 61 555 243 61 871 1.03E-06	0.095 0.098	0.061 0.916 0.063
	G11 Glucobrassicanapin GLS leaves hydroxyalkenyl_tot_ali mQA03_8.3 GLS roots ali_GLS_.GLS mQA06_42.5	0.899 A03 1 Bn.A03.p7793076 0.939 A06 1 Bn.A06.p23776151	PL11 8 126 678 42579204 42 569 236 Fer-Sin-diHex** 7 986 653 8 714 1.05E-07 42 606 2.78E-06	4.118 -3.132	0.106 0.640 0.084
	G12 Gluconapoleiferin** GLS roots ali_GLS_.GLS GLS roots ind_GLS_.GLS Root GLS mQA09_4.1 mQA01_32.1 G13 Glucoesquerellin** GLS roots ind_GLS_.GLS mQA03_1.4 G14 Gluconasturtiin GLS roots ind_GLS_.GLS mQA04_0.3 GLS roots ind_GLS_.GLS mQA04_10.8 G15 p-Hydroxygluconasturtiin* / GLS roots ind_GLS_.GLS mQA05_39.1 GLS roots ind_GLS_.GLS mQC04_28.6	0.873 A09 1 Bn.A09.p1765907 0.946 A01 1 Bn.A01.p28462071 SOSR + 0.398 0.867 A03 3 Bn.A03.p1352996 0.332 0.776 A04 2 Bn.A04.p320972 A04 1 Bn.A04.p7797300 10 811 589 PL12 3543971 32166670 32 131 188 triSin-diHex** 3 517 509 3 559 3.52E-06 32 682 2.88E-07 SOSR -WOSR + WOSR -PL13 Fer-diSin-diHex** 1387520 1 057 128 1 518 9.28E-08 PL14 360 959 267 447 575 5.06E-07 Kae-diHex** 10 806 448 10 828 3.38E-06 PL15 A05 2 Bn.A05.p23143046 39163555 39 137 056 39 326 1.49E-06 Kae-Fer-diHex** C04 1 Bn.C4.p22318210 28653565 21 574 015 29 192 3.42E-07	-3.492 2.855 2.984 -3.284 -3.019 -2.625 4.086	0.084 0.929 0.098 0.105 0.951 0.095 0.083 0.945 0.087 0.100	QTL
	GLS	roots	Homosinalbin* alkyl_GLS_GLS	mQA02_10.7	0.806 A02 1 Bn.A02.p11086855 0.273	10724754	10 715 108	10 734 1.31E-06	-0.263	0.684 0.072
	G16 Epiglucobarbarin* GLS roots alkyl_GLS_GLS GLS roots alkyl_GLS_GLS	mQA09_41.4 mQC02_44.6	0.782 A09 1 Bn.A09.p25747213 0.839 C02 22 Bn.C2.p38175317	PL16 41371883 41 352 833 Kae-triHex** 41 371 5.65E-07 44611642 24 358 921 54 239 4.26E-09	-0.371 -0.266	0.080 0.965 0.059
	G17 Glucobarbarin GLS roots C4_tot_ali GLS roots C5_tot_ali	mQC01_7.3 mQC01_7.3	0.903 C01 25 Bn.C1.p6854343 0.858 C01 25 Bn.C1.p6854343	PL17 7334923 7334923	Kae-triHex** 7 061 851 7 469 5.76E-08 7 061 851 7 469 2.46E-07	-6.405 6.111	0.114 0.865 0.104
	G18 m-Hydroxygluconasturtiin** GLS roots C6_tot_ali mQA04_0.3 GLS roots C6_tot_ali mQA05_35.6	0.551 A04 1 Bn.A04.p324144 0.283 A05 4 Bn.A05.p20319622	PL18 364191 35757678 35 752 192 Kae-Caf-diHex** 267 447 575 4.61E-06 36 087 1.50E-07	-1.075 0.812	0.073 0.727 0.092
	G19 Glucobrassicin GLS roots C6_tot_ali G20 Neoglucobrassicin* GLS roots C6_tot_ali GLS roots C6_tot_ali G21 4-Methoxyglucobrassicin* mQA08_17.9 mQC01_1.4 mQC02_57.2 GLS roots C6_tot_ali mQC07_13.0 GLS roots methylsulfinyl_tot_ali mQA03_22.0	0.771 A08 1 Bn.A08.p13785675 0.612 0.376 0.770 C01 1 Bn.C1.p1471732 C02 3 Bn.C2.p48143863 0.627 0.304 C07 3 Bn.C7.p9955727 A03 1 Bn.A03.p21294836	PL19 17904116 17 825 223 Kae-OHFer-diHex** 17 952 4.83E-06 PL20 1410757 1 406 503 1 438 1.30E-06 Kae-Sin-diHex** 57182578 57 100 829 57 635 1.80E-06 PL21 13038379 9 984 488 16 394 2.08E-08 Kae-OHFer-triHex** 22009685 22 001 204 22 064 2.37E-07	1.003 0.784 0.894 1.240 3.201	0.072 0.924 0.079 0.072 0.680 0.106 0.896 0.100
	G22 4-Hydroxyglucobrassicin** GLS roots methylsulfinyl_tot_ali mQA09_4.1 GLS roots methylsulfinyl_tot_ali mQC03_13.3	0.751 A09 14 Bn.A09.p1989556 0.658 C03 1 Bn.Scaffold01023.p21632 13353482 PL22 3320549 13 351 056 Kae-Fer-triHex** 2 168 403 4 564 1.59E-11 13 479 2.94E-08	4.266 -2.834	0.160 0.873 0.109
	G23 1-Hydroxyglucobrassicin** GLS roots alkenyl_tot_ali mQA03_2.0 GLS roots alkenyl_tot_ali mQA09_4.1	0.934 A03 1 Bn.A03.p2005352 0.855 A09 1 Bn.A09.p1989556	PL23 2084799 3320549	Kae-Sin-triHex** 2 045 223 2 110 2.19E-06 3 305 420 3 451 9.90E-07	1.111 -1.427	0.078 0.740 0.085
	G24 Propyl-GLS* GLS roots hydroxyalkenyl_tot_ali GLS roots hydroxyalkenyl_tot_ali	mQA03_14.6 mQA09_4.1	0.665 A03 5 Bn.A03.p13943992 14 576 370 0.941 PL24 14 531 159 Kae-Fer-tetraHex** 14 619 8.65E-08 A09 4 Bn.A09.p2733282 4101935 2 757 086 4 564 8.23E-08	-2.673 -3.902	0.105 0.587 0.099
	Leaf Phenolics G25 Glucoputranjivin* GLS roots neoglucobrassicin_tot_ind mQC02_21.6 G26 Glucoconringianin* GLS roots GLS22_tot_ind mQC02_57.2 PHL leaves TOT_PPN_PHL mQA08_2.4 G27 Glucocochlearin* PHL leaves TOT_FLA_PHL mQA08_2.4 PHL leaves HQA_PPN mQA06_6.7 G28 Glucoconringiin** PHL leaves HQA_PPN mQC04_63.2 PHL leaves HQA_PPN mQC07_36.3	SOSR + 0.950 44 Bn.C2.p19939091 0.636 C02 0.201 0.988 C02 1 Bn.C2.p48462140 A08 197 Bn.A08.p2897827 0.612 0.969 A08 197 Bn.A08.p3237433 A06 1 Bn.A06.p6182593 0.947 0.925 C04 5 Bn.C4.p51315477 C07 4 Bn.C7.p29949146	SOSR -PL25 21680680 21 460 578 WOSR + Kae-Sin-tetraHex** 22 609 6.99E-07 PL26 57507685 57 100 829 57 635 3.97E-06 Kae-Sin-pentaHex** 2871709 1 588 102 12 927 1.34E-08 PL27 3 231 749 1 588 102 12 927 7.47E-09 Kae-diSin-pentaHex** -3.207 0.022 2.481 -2.526 6 785 465 6 764 993 6 936 5.01E-06 1.278 WOSR -PL28 Quer-triHex** 63 297 495 62 322 712 63 603 9.21E-08 1.521 36 350 384 35 603 274 36 634 4.43E-07 1.827	0.093 0.306 0.046 0.116 0.477 0.120 0.593 0.073 0.100 0.824 0.092	QTL
	G29 Glucosisautricin** PHL leaves HAGE_PPN PHL leaves HAGE_PPN	mQA06_6.7 mQC04_63.2	0.898 A06 1 Bn.A06.p6182593 0.943 C04 5 Bn.C4.p51315477	PL29 6 785 465 63 297 495 62 322 712 Quer-Caf-triHex** 6 764 993 6 936 5.01E-06 63 603 9.21E-08	-1.278 -1.521	0.073 0.857 0.100
	G30 Pentyl-GLS PHL leaves HAGE_PPN PHL leaves PPN_monoA_PPN	mQC07_36.3 mQC08_33.0	0.440 C07 4 Bn.C7.p29949146 0.775 C08 5 Bn.C8.p33518339	PL30 36 350 384 35 603 274 Quer-OHFer-triHex** 36 634 4.43E-07 33 006 364 32 926 325 33 033 9.52E-08	-1.827 -2.385	0.092 0.713 0.104
	G31 3-methylpentyl-GLS * PHL leaves PPN_diAc_PPN mQA09_46.1 G32 Hexyl-GLS isomer I** PHL leaves PPN_diAc_PPN mQC08_33.0 PHL leaves PPN_triAc_PPN mQC01_28.7 PHL leaves FLA_monoAc_FLA mQA08_2.4 G33 Hexyl-GLS isomer II** PHL leaves KAEM_FLA mQA02_10.7	0.551 A09 2 Bn.A09.p30270747 46 131 663 0.831 PL31 45 983 582 Quer-diSin-tetraHex** 46 140 4.73E-06 -1.798 0.317 0.890 PL32 C08 20 Bn.C8.p33518339 33 006 364 32 863 135 33 033 2.23E-08 2.521 Iso-triHex** A01 2 Bn.C1.p40541584 28 666 611 28 665 028 28 800 2.24E-12 0.881 A08 322 Bn.A08.p7260514 10 206 323 1 588 102 15 397 6.70E-15 3.578 0.318 0.749 A02 2 Bn.A02.p10869120 10 487 005 10 388 981 10 851 2.64E-07 2.440	0.076 0.708 0.114 0.162 0.729 0.205 0.098
	G34 Heptyl-GLS isomer I** PHL leaves KAEM_FLA mQA10_10.0 PHL leaves QUER_FLA mQA10_10.0	0.346 A10 1 Bn.A10.p5727780 0.859 A10 10 Bn.A10.p6120400 10 025 910 9 637 435		8 720 536 8 627 463	9 682 7.06E-07 10 374 1.38E-11	-1.838 1.957	0.088 0.152
	G35 Heptyl-GLS isomer II** PHL leaves QUER_FLA mQC03_7.8 PHL leaves ISOR_FLA mQC03_7.8	0.244 C03 18 Bn.C3.p7333568 0.939 C03 2 Bn.C3.p7781513	7 903 252 8 430 690		7 223 143 8 427 090	8 800 7.25E-07 8 800 2.23E-06	1.471 -1.072	0.086 0.078
	G36 Heptyl-GLS isomer III** PHL leaves ISOR_FLA mQC07_38.5	0.654 C07 4 Bn.C7.p32304272 0.831	38 494 702	36 959 414	38 623 1.73E-08	-1.509	0.110
						3.7	0.2 -7.8	3.4	1.4 -5.9	4.2	0.4 -9.5	4.2	1.6 -8
				% Kaempferol / Flavonols 81.3 62.8 -97.1 81.0 66 -91.6	78.7	68.9 -90.8	80.7	70 -88.5 A02_10.7 A10_10.0
				% Quercetin / Flavonols 13.6	2 -28.1	13.1	7.2 -22.2	12.3	3.9 -19.2	11.4	5.9 -21.2 A10_10.0 C03_7.8
				% Isorhamnetin / Flavonols	5.1	0.4 -19.8	5.9	1 -15.9	9.0	3.2 -14.6	7.9	3.7 -13.7 C07_38.5 C03_7.8
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Ph D. manuscript | Anani Amegan MISSINOU P a g e 138 Ph D. manuscript | Anani Amegan MISSINOU P a g e 139

  Table S1c (coming soon in the published article), the distribution of the mean absorbance values is displayed for each compound, and 5% lowest or highest mean values are shown. Both cultivar-

		Unknown root compounds absorbing at λ330nm (AU.g-1 DW)
	[M-H]-MS1 (m/z)	B. napus	B. rapa	B. oleracea
	ID	Exp.	mean (% )	min -max	mean (% )	min -max	mean (% )	min -max
	R01_M315	315.071	124.9 (2.7)	0 -268	95.1 (1.8)	0 -264	122.6 (2.9)	67 -173
	R02_M431	431.117	366.2 (7.9)	80 -1396	1096.8 (20.4)	126 -3857	171.6 (4.1)	97 -397
	R03_M434	434.207	623.4 (13.5)	136 -1594	808.5 (15)	152 -2090	155.7 (3.7)	72 -286
	R04_M385	385.113	258.6 (5.6)	0 -976	159.4 (3)	0 -341	60.7 (1.4)	0 -136
	R05_M434	434.207	155.1 (3.4)	0 -668	54.3 (1)	0 -85	349.2 (8.3)	113 -525
	R06_M479	479.041	303 (6.5)	120 -721	473.2 (8.8)	83 -727	209.4 (5)	144 -410
	R07_M551	551.175	543.2 (11.7)	83 -1303	162.6 (3)	0 -546	923.8 (21.9)	679 -1562
	R08_M681	681.237	164.1 (3.5)	0 -489	106.8 (2)	0 -191	105.2 (2.5)	0 -191
	R09_M385	385.113	185.9 (4)	74 -419	204.2 (3.8)	110 -313	225.3 (5.3)	62 -539
	R10_M565	565.191	105.7 (2.3)	0 -372	138.9 (2.6)	88 -256	91.2 (2.2)	0 -214
	R11_M523	523.144	100.8 (2.2)	0 -319	135.6 (2.5)	24 -304	57.2 (1.4)	0 -127
	R12_MNA	NA	364 (7.9)	181 -855	337.6 (6.3)	208 -574	380.4 (9)	279 -491
	R13_M320	320.098	222.9 (4.8)	0 -652	215.8 (4)	65 -469	223.2 (5.3)	85 -439
	R14_MNA	NA	525 (11.3)	141 -892	864.7 (16.1)	275 -5840	532.7 (12.6)	395 -687
	R15_M380	380.079	83.1 (1.8)	0 -232	74.2 (1.4)	0 -157	98 (2.3)	76 -135
	R16_M493	493.115	173.9 (3.8)	59 -630	161.4 (3)	93 -310	233.9 (5.5)	97 -460
	R17_MNA	NA	118.5 (2.6)	0 -323	116.1 (2.2)	75 -165	85.1 (2)	56 -112
	R18_M368	368.099	208 (4.5)	0 -1192	169.9 (3.2)	70 -304	200.8 (4.8)	0 -673
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Table 3 :

 3 Genome-wide association study of UVλ330-absorbing compound contents in B. napus roots.

Table S3a

 S3a

	mQTL name	Metabolic Trait	Chrs	SNP Marker	R 2 (%)
	mQA06_40.0	R01_M315	A06	Bn.A06.p21800812	0.12
	mQC01_34.4	R02_M431	C01	Bn.C1.p29015489	0.20
	mQA03_28.6	R03_M434	A03	Bn.A03.p27377892	0.21
	mQA06_37.7	R03_M434	A06	Bn.A06.p17175388	0.10
	mQC07_52.2	R03_M434	C07	Bn.C7.p45129145	0.21
	mQC07_52.2	R05_M434	C07	Bn.C7.p45128577	0.25
	mQC03_13.6	R07_M551	C03	Bn.C3.p18789565	0.11
	mQC05_39.2	R07_M551	C05	Bn.C5.p44425675	0.11
	mQC03_22.2	R07_M551	C03	Bn.C3.p20525188	0.31
	mQA09_15.9	R08_M681	A09	Bn.A09.p14783306	0.12
	mQA07_23.3	R11_M523	A07	Bn.A07.p17017277	0.11
	mQC07_37.3	R12_MNA	C07	Bn.C7.p31107417	0.10
	mQA04_4.7	R13_M320	A04	Bn.A04.p4325390	0.10
	mQA04_9.36	R13_M320	A04	Bn.A04.p6588935	0.24
	mQA04_9.9	R13_M320	A04	Bn.A04.p7066595	0.14
	mQC04_46.3	R13_M320	A04	Bn.A04.p7044446	0.11
	mQA09_15.9	R16_M493	A09	Bn.A09.p14751809	0.14
	mQC05_32.6	R16_M493	C05	Bn.C5.p22057936	0.10
	mQA01_12.6	R18_M368	A01	Bn.A01.p12544054	0.11
	mQA04_9.36	R18_M368	A04	Bn.A04.p6588935	0.15
				, coming soon in the published
	article). Interestingly, R13_M320/R18_M368 and R08_M681/ R16_M493 were already
	shown to display common structural and profile properties, such as fragmentation
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Table 3 :

 3 Genome-wide association study of UVλ330-absorbing compound contents in B. napus roots.

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	P a g e 181

2.1. Chemicals HPLC

  -grade acetonitrile, methanol, and formic acid were from Carlo Erba. Authentic glucosinolate standards (Supporting TableS2) were acquired from PHYTOPLAN Diehm & und Neuberger GmbH. Chemical structures were drawn usingMarvinSketch 20.21 (ChemAxon Ltd.).

Titre : Métabolisme spécialisé chez Brassica napus : Caractérisation de la diversité phytochimique, de ses déterminants génétiques et de sa régulation par l'infection d'un agent pathogène Mots clés

  : colza, métabolites spécialisées, diversité, mGWAS, agent pathogène, métabolomique Le métabolisme spécialisé joue un rôle essentiel dans les interactions plante-environnement. Sa caractérisation chez les plantes cultivées représente un enjeu scientifique important. Au cours de ma thèse, j'ai travaillé à la caractérisation du métabolisme spécialisé et de ses déterminants génétiques chez Brassica napus, et j'ai étudié sa régulation en réponse à l'infection par Leptosphaeria maculans, agent causal du phoma. J'ai contribué au développement d'une méthode de profilage métabolique ciblé et identifié 36 glucosinolates (GLSs) foliaires/racinaires, 32 composés phénoliques (PHLs) foliaires et 18 composés racinaires non documentés jusqu'à présent. La quantification des ces SMs dans 304 accessions de Brassica a permis de révéler des contrastes

	phytochimiques importants au sein du panel.
	L'analyse	GWAS	de	ces	variations
	phytochimiques a identifié 104 locus (QTLs).

jamais délaissé à mon propre sort ne serait-ce que le temps d'un clin d'oeil, et m'a octroyé la force, le courage et la patience d'accomplir ce modeste travail. Fruit d'un travail de recherche triennale et demi, ce manuscrit résulte d'un concours d'efforts solidaires de plusieurs personnes envers qui je suis reconnaissant et que je ne pourrai tous citer. En première ligne, Antoine GRAVOT et Maria MANZANARES-DAULEUX m'ont fait vivre plus qu'une direction de thèse, comme si un directeur de thèse pouvait aussi adopter son doctorant. Vous avez été à l'écoute de mes questions et intéressés par l'avancée de mes travaux. Votre capacité d'analyse et votre enthousiasme m'ont montré que le monde de la recherche pouvait être un univers passionnant. Les nombreuses discussions que nous avons eues ainsi que vos encouragements et conseils ont, d'une part guidé mes pas et donné un ton initiatique à ces années de recherche et d'autre part sont pour beaucoup dans le résultat final de ce travail. Veuillez trouver ici, l'expression de mes respectueux hommages. En seconde ligne, ma profonde gratitude va à Régine DELOURME, Anne-Marie CHÊVRE, Anne LAPERCHE et Alain BOUCHEREAU, pour leurs accueils chaleureux, leurs conseils avisés, leurs franchises, leurs corrections si éclairantes. Mention spéciale à Régine D., pour sa protection maternelle, qu'elle en soit aussi remerciée pour sa gentillesse, sa disponibilité permanente et pour ses nombreux encouragements et aussi à Alain B. pour ses implications conséquentes qui ont permis de rendre les différentes collaborations plus agréables et d'enrichir les travaux présentés dans ce manuscrit et pour les opportunités qu'il m'a offerte de faire connaître mes travaux en m'encourageant à participer aux conférences. En troisième ligne, je remercie grandement Nathalie MARNET pour toute ton aide. Je suis ravi d'avoir travaillé en sa compagnie car outre son appui scientifique et les nombreux conseils qu'elle m'a prodigué, non seulement elle m'a initié à la théorie et pratique en spectrométrie de masse en début de ma thèse, mais elle m'a aussi inculqué une rigueur et précision dans l'interprétation des spectres de masse. Je remercie Thomas DELHAYE pour son soutien indéfectible, nos discussions techniques autour des spectres de fragmentation, son regard différent et plus pragmatique en tant qu'expert du domaine et ces commentaires très enrichissants. Merci également à Clément ORIONE, Philippe JÉHAN, et Régis LAVIGNE pour leur participation scientifique ainsi que le temps qu'ils ont consacré à ma recherche, remerciements auxquels j'associe Sylvain CHEREAU pour sa bonne humeur permanente et pour son aide, en particulier sur la fin de la thèse. Tous répondirent avec calme, patience enthousiasme et sympathie aux nombreuses questions dont je les accablais. Ce fut un réel plaisir de travailler avec vous et merci encore pour vos contributions analytiques.

Tannins contain three or more phenol subunits subdivided into tannins and their polymers, hydrolyzable or non-hydrolyzable.

Hemibiotrophic pathogens keep their host alive while establishing themselves in the host tissue, absorbing nutrients with a brief biotrophic-like phase before having a necrotrphic phase.

An obligate heterothallic fungus produces ascospores only if mycelia from strains with opposite sexual signs (mating types) occur on the same plant.

Sporulation is the phenomenon of differentiation which leads from the vegetative form to the spore (form of resistance).

Pseudothecia arise from the encounter between two strains with opposite sexual signs.

BCAT: branched-chain aminotransferase

La plateforme MELISA (MEtabolomics LIpidomics Steroidomics Analysis) du Laboratoire d'études des résidus et contaminants dans les aliments (LABERCA) est membre de la composante "Analyses structurale et métabolomique" (Corsaire) du réseau Biogenouest.

https://doi.org/10.1021/acs.jafc.1c08118 J. Agric. Food Chem. 2022, 70, 5245-5261 Downloaded via INRAE on February 25, 2023 at 13:28:15 (UTC).See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

https://doi.org/10.1021/acs.jafc.1c08118 J. Agric. Food Chem. 2022,[START_REF] Mithen | Glucosinolate biochemical diversity and innovation in the Brassicales[END_REF][5245][5246][5247][5248][5249][5250][5251][5252][5253][5254][5255][5256][5257][5258][5259][5260][5261]

Remerciements

Toute la louange revient à Allah, le Tout Puissant qui améliore ma situation en tout point et ne m'a

Funding

The salaries of A.A.M. and J.F.d.C. were provided by INRAE and Reǵion Bretagne. Operating funding was supported by INRAE, Agrocampus Ouest, UniversitéRennes 1, and PROMOSOL. Salaries of O.H. and D.A.S. were provided by PROMOSOL (Project DESCRIBE).

Funding sources

The salaries of A.A.M. and J.F.C. were provided by INRAE and Région Bretagne.

Operating funding was supported by INRAE, Institut Agro, Université Rennes 1, and

Author Contributions

⊥ Anani Amegan Missinou and Julie Ferreira de Carvalho equally contributed. M.J.M.-D., A.B., and A.G. obtained supporting funding. A.L., R.D., M.J.M.-D., L.L., C.L., and A.G. defined the Brassica panel and the sampling experimental design. A.A.M., N.M., O.H., Y.G., T.D., and A.G. worked on the extensive research and identification of glucosinolates and phenolics, in a series of pooled samples from Brassica accessions, using high-resolution MS/MS data. A.A.M., N.M., O.H., and D.A.S. have set up the UPLC-MS method for quantitative glucosinolate and phenolic profiling and then did a chromatographic analysis and peak integrations to generate quantitative data. A.A.M. and J.F.d.C. worked on the statistical analysis of data. A.A.M., J.F.d.C., and A.G. wrote the manuscript.

Notes

The authors declare no competing financial interest.

■ ACKNOWLEDGMENTS

The authors acknowledge the two facilities P2M2 and MELISA from the CORSAIRE metabolomic and fluxomic platform of Biogenouest. The greenhouse experimental team of IGEPP is acknowledged for contributing to the experiments in the phytotron. The authors would like to thank the BrACySol Biological Resource Center (INRAE Ploudaniel, France) for providing seeds from SOSR accessions, breeder companies from the PROMOSOL Association for providing seeds from elite WOSR accessions, and Professor Rod Sowndon for providing the seeds of rutabaga and the WFR genotypes. Many people from IGEPP have also been mobilized as technical support during the 3 weeks of the leaf and root sampling stage. May they all be here sincerely thanked. We also thank the reviewers for their constructive corrections and comments which helped us to improve the quality of this manuscript.

■ ABBREVIATIONS USED

AQAs, acyl-quinic acids; BCAAs, branched-chain amino acids; Caf, caffeoyl; DW, dry weight; Fer, feruloyl; GLS, glucosinolate; Hex, hexoside; HAGE, hydroxycinnamic acid hexoside esters; HPLC-HRMS2, liquid chromatography coupled to high-resolution tandem mass spectrometry; Isor, isorhamnetin; Kaem, kaempferol; SGlu, thioglucose; Sin, sinapoyl; SORS, spring oilseed rape; OH-Fer, hydroxyferuloyl; PCA, principal component analysis; Quer, quercetin; UPLC-UV-MS, ultrahigh-performance chromatography with ultraviolet detector coupled in-line to a triple quadrupole detector mass spectrometry; WOSR, winter oilseed rape P a g e 126 Supplementary Table S1 % Aliphatic-GLS / Total GLS 85. 5 57.5 -96.8 46.1 10.5 -92.5 % C4 / Aliphatic-GLS 46.5 21.7 -98.4 39.9 24.5 -77.5 44.9 30.4 -79.9 45.8 31.7 -66 C01_7.3 % C5 / Aliphatic-GLS 53. 3 1.4 -78.3 59.4 21.5 -75.3 54.9 19.9 -69.6 54.0 33.8 -67.8 C01_7.3 A07_11.5 % C6 / Aliphatic-GLS 0.0 0 -0.4 0.3 0 -2.9 0.0 0 -0. % Gluconasturtiin / Phenylalkyl-GLS 99.8 99.7 -99.9 99.8 99.7 -99.9 99.8 99.7 -99.9 99.8 98.9 -99.9 C02_57.2 % Epiglucobarbarin / Phenylalkyl-GLS 0.0 0 -0 0.0 0 -0.2 0.0 0 -0 0.0 0 -0 A03_14.6 A09_4.1 % Neoglucobrassicin / Indolic-GLS 42.5 24.9 -62.1 39.9

P a g e 128

Supplementary Table S3a: QTL identified for seed total GLS, total GLS, and total Aliphatic GLS in the leaves and for individual leaf GLS compounds.

The number of significant SNP per mQTL, the position of the mQTL, and the peak SNP on the chromosome of the DarmorV10 reference sequence are indicated as well as the confidence interval of the mQTL, the p-value, the minor allele effect, and the R² of the peak SNP, The number of significant SNP per mQTL, the position of the mQTL, and the peak SNP on the chromosome of the DarmorV10 reference sequence are indicated as well as the confidence interval of the mQTL, the p-value, the minor allele effect, and the R² of the peak SNP, Supplementary Table S3c: QTL identified for total PHL, subcategories in the leaves, and for individual leaf PHL compounds.

The number of significant SNP per mQTL, the position of the mQTL, and the peak SNP on the chromosome of the DarmorV10 reference sequence are indicated as well as the confidence interval of the mQTL, the p-value, the minor allele effect, and the R² of the peak SNP, The number of significant SNP per mQTL, the position of the mQTL, and the peak SNP on the chromosome of the DarmorV10 reference sequence are indicated as well as the confidence interval of the mQTL, the p-value, the minor allele effect, and the R² of the peak SNP, Gao threshold (Gao, Starmer, & Martin, 2008) calculated using the Bonferroni multitest at 5% and 10%, respectively, to adjust the threshold of the genome-wide significance p-value.

List of supporting Figures

Supporting Figure S1: Root UV-absorbing compounds content in a panel of 304 Brassica accessions. S1b: UV-absorbance measurement of unknown compounds in each biological replicate AU.g -1 DW (arbitrary unit of UV-absorbing compounds content fitting with 1/x weighting). S1c: Mean of UV-absorbing root unknown compounds, min, max, percentile 5, and percentile 95. S1d: Selection of accessions belonging to percentile 5 and percentile 95 for each UV-absorbing root unknown compound (arbitrary unit peak area per DW).

Supporting Figure S2: Frequency distribution histograms of eighteen unknown root chemical traits UV-absorbing (λ330nm) in 250 accessions of Brassica napus. Each bar represents the mean of absorbance for one variety, from 3 independent biological replicates. The units of absorbance are absorbance units per gram of dry weight (AU.g-1 DW).

Supporting Figure S3: Manhattan plot of genome-wide association analysis of root UV-absorbing compounds content. Homoeologous chromosomes of the A and C subgenomes of the allopolyploid Brassica napus are represented in blue and red blocks, respectively. The horizontal lines represent the Gao threshold (Gao, Starmer, & Martin, 2008) calculated using the Bonferroni multitest at 5% and 10%, respectively, to adjust the threshold of the genome-wide significance p-value.

List of tables